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@inproceedings{bib_Eval_2025, AUTHOR = {KV, Suresh Babu and Pillutla, Rama Chandra Prasad }, TITLE = {Evaluation of Forest Fire Susceptibility in Mizoram State utilizing Analytical Hierarchy Processes and Frequency Ratios.}, BOOKTITLE = {Forest Fire and Climate Change}. YEAR = {2025}}

The forest cover in Mizoram State is essential for the region’s socio-economic development and environmental sustainability. This state features abundant natural resources and diverse biodiversity, predominantly harbored within its forests. However, forest fires pose a significant risk, especially during dry seasons. Factors such as human activities, weather conditions, and traditional bamboo and Jhum cultivation practices contribute to the occurrence of forest fires in Mizoram. It’s crucial to map forest fire susceptibility to manage this risk effectively. This proactive approach enables better fire management, reduces risks, and facilitates informed decision-making. By identifying areas vulnerable to wildfires, it’s possible to promote sustainable land use practices, preserve ecosystems, and safeguard people and property. Statistical techniques such as frequency ratio (FR) and analytic hierarchy process (AHP) are used to generate the fire susceptibility maps for Mizoram based on satellite datasets. The MODIS Terra and Aqua active fire points (MCD14) are the basis, divided into training and testing datasets. AHP and FR techniques establish relationships between the training dataset and fourteen key factors, including slope, aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), Normalized Multiband Drought Index (NMDI), rainfall, temperature, wind speed, and proximity to settlements and roads. Various datasets such as MODIS Terra (surface reflectance, land surface temperature, vegetation indices), SRTM Digital Elevation Model, ERA-5, and CHRS are utilized in this study. The accuracy of the susceptibility maps generated by FR and AHP is validated against active fire test datasets, ensuring reliability in predicting fire-prone areas.

@inproceedings{bib_Isla_2025, AUTHOR = {Sulaiman, Firose and Pillutla, Rama Chandra Prasad }, TITLE = {Island lens approach to historical landscape characterization of the Nicobar Islands using remote sensing}, BOOKTITLE = {GeoJournal}. YEAR = {2025}}

Landscapes are shaped by both natural and cultural factors, influencing their management. In the Andaman and Nicobar Islands, rapid land-use changes from tsunamis and human activities threaten both ecological integrity and local communities. While the Andaman Islands have been extensively studied, research on the Nicobar Islands remains limited, prompting this investigation of historical land-use and land-cover changes using geospatial data. Multi-temporal satellite imagery revealed significant changes across selected Nicobar Islands. Trinket Island, heavily impacted by the 2004 tsunami, experienced considerable forest loss, mudflat formation, and fluctuations in grassland and water body areas. Katchal Island saw major forest declines from the tsunami and human activity, with partial recovery hindered by ongoing seawater intrusion and erosion. Camorta Island experienced reduced forest and grassland areas post-tsunami, followed by gradual forest recovery and water body expansion. Nancowry Island, though minimally affected initially, later faced significant forest loss due to seawater intrusion, followed by recovery and settlement growth. Car Nicobar Island suffered severe forest loss from the tsunami but has seen partial vegetation recovery alongside settlement expansion. Additionally, the Nicobar Islands' tropical grasslands, crucial for biodiversity and local livelihoods, are under threat from environmental changes and proposed oil palm plantations, which could lead to further ecological disruption and cultural impacts.

@inproceedings{bib_AI-E_2025, AUTHOR = {Vinayaka, and Pillutla, Rama Chandra Prasad }, TITLE = {AI-Enhanced Remote Sensing for Precise Evaluation of Salinity, Water Stress, and Nitrogen Levels in Sugarcane Cultivation: A Comprehensive Review.}, BOOKTITLE = {Frontiers in Agronomy}. YEAR = {2025}}

Sugarcane is a vital cash crop with substantial significance in both global sugar production and the biofuel industry. However, its sustainable cultivation faces persistent challenges from environmental stressors, particularly salinity and water scarcity. In recent years, the integration of artificial intelligence (AI) and remote sensing (RS) technologies has proven to be a transformative approach for detecting and evaluating these stress conditions, offering critical insights for advancing precision agriculture (PA). This review explores the utilization of satellite imagery and sensor-based data including RGB, multispectral, hyperspectral imaging, and unmanned aerial vehicles (UAVs) to monitor stress-related parameters in sugarcane farming. It emphasizes key indices used to assess water stress, generate salinity stress maps, and estimate nitrogen levels, demonstrating their role in equipping farmers with actionable information to optimize irrigation and nutrient management strategies. These innovations significantly enhance crop productivity while promoting environmental sustainability. The review sets out three core objectives: (i) to evaluate the contribution of AI and RS in assessing water stress in sugarcane cultivation, (ii) to examine methods for mapping salinity stress using RS and AI tools, and (iii) to highlight the relevance of spectral indices in tracking nitrogen status in sugarcane crops. Drawing upon reputable bibliographic sources such as Google Scholar, Scopus, ResearchGate, and Web of Science, along with current literature on AI and RS applications in sugarcane stress assessment, the review consolidates detailed information on advanced sensors and UAV technologies. It also introduces novel deep learning models and sensor platforms that have received limited attention in prior studies. In conclusion, the review affirms that AI-driven remote sensing is a highly effective approach for monitoring and managing critical stress factors in sugarcane production. It not only contributes to enhanced yield and crop quality but also delivers significant socio-economic and environmental benefits, marking a major step forward in achieving sustainable and efficient sugarcane cultivation.

@inproceedings{bib_Anal_2025, AUTHOR = {Xiao, Shu-Mei and Pillutla, Rama Chandra Prasad }, TITLE = {Analogous Environments Across the Tropics Have Similar Levels of Tree Species Alpha Diversity}, BOOKTITLE = {National Science Review}. YEAR = {2025}}

Different regions of the tropics vary in overall tree species diversity, with the tropical Americas exhibiting strikingly higher regional tree species richness than Africa and Southeast Asia. We investigated whether these differences also occur at the local scale, and whether the environmental conditions associated with tree species richness are consistent across tropical regions despite highly dissimilar species pools. A spatial random forest (RF) model was trained using a network of 429 one-hectare plots across the tropics, together with 24 environmental variables, to predict plot-level tree α diversity. A combination of climatic, soil and topographical variables explained around 86% of variation in richness. Despite differences in regional species pools and potentially disruptive effects of different geological, climatic and evolutionary histories, the relationship between environmental variables and local scale tree species richness is closely similar across different continents. Our findings imply a pervasive role of niche-based mechanisms in structuring local tree species richness, regardless of regional species assemblages. This pantropical convergence in the richness-environment relationship poses a challenge for ecology to explain.

@inproceedings{bib_Comp_2025, AUTHOR = {D, Sowjanya and Pillutla, Rama Chandra Prasad }, TITLE = {Comparative evaluation of machine learning algorithms for Coringa Mangroves mapping with satellite imagery and spectral indicesComparative evaluation of machine learning algorithms for Coringa Mangroves mapping with satellite imagery and spectral indices}, BOOKTITLE = {Journal of Earth System Science}. YEAR = {2025}}

This research utilises the capabilities of Google Earth Engine, a cloud-based computing platform, to conduct a comprehensive spatiotemporal assessment of the Coringa mangrove. Situated within the Coringa Wildlife Sanctuary in Andhra Pradesh, India, this mangrove – the country's second largest – is evaluated across various timeframes: 1999, 2002, 2007, 2013, 2017, and 2022. ML algorithms – Random Forest and Support Vector Machine with an RBF kernel – are employed. These algorithms analyze band composites derived from Landsat-7 ETM+ (1999, 2002, 2007), Landsat-8 (2013, 2017), and Sentinel-2 MSI (2022) satellite images. This analysis incorporates key spectral indices and utilises two spectral index thresholds for mangrove classification: one derived from established literature that identifies common thresholds at which mangroves typically occur (standard threshold), and the other is a customised threshold obtained from individual spectral index maps, tailored specifically to delineate mangrove areas in the study area (customized threshold). The results show that RF, particularly with the CT, outperforms all other methods, including RF with the ST and SVM with both thresholds, in terms of training and testing accuracy. These findings affirm the effectiveness of RF with the CT approach in accurately differentiating mangrove areas, emphasizing the critical role of threshold selection in enhancing the accuracy and competence of classification methods for mapping mangrove ecosystems.

@inproceedings{bib_Anal_2024, AUTHOR = {Chakraborty, S. and Pillutla, Rama Chandra Prasad }, TITLE = {Analysing the temporal land use and land cover transformations in Baratang Group Islands of Andaman and Nicobar}, BOOKTITLE = {Geography and Natural Resources}. YEAR = {2024}}

A number of anthropogenic and natural disasters that have impacted the fragile ecosystems of the Baratang group of islands in the Andaman and Nicobar archipelago, resulting in the degradation and depletion of their natural environment and biodiversity, have been identified. It is found that, in the early 20th century, the resources of the archipelago, especially Baratang Island, were exploited for infrastructure and plantations, resulting in a decrease in forest cover and an increase in anthropogenically transformed landscapes. However, the most recent available information on land use (LU) and land cover is only from 2013. This study aims to understand the dynamics of LU and land cover change in the Baratang Island group using multitemporal satellite data for 1976, 1993, 2004, 2014, and 2023. Using visual interpretation techniques, spatial and temporal change maps were created to represent the different LU and land cover features in the study area. An analysis of these maps revealed an interesting trend: there is an increase in forest area with a simultaneous decrease in settlements and agricultural land, which contradicts the findings of previous studies. This work has identified several factors contributing to this trend, namely natural regeneration, a reduction in logging and human activities, government policies and laws, and the implementation of conservation measures by the forest department. However, the evidence on mangrove decline attributed to both human activities and natural disasters is consistent with the results of other studies. This study emphasizes the importance of regularly monitoring the island’s landscape dynamics to understand changes in LU and land cover and to take appropriate conservation measures.

@inproceedings{bib_Wind_2024, AUTHOR = {Ferry, Slik and Pillutla, Rama Chandra Prasad }, TITLE = {Wind dispersed tree species have greater maximum height.}, BOOKTITLE = {Global Ecology and Biogeography}. YEAR = {2024}}

Aim We test the hypothesis that wind dispersal is more common among emergent tree species given that being tall increases the likelihood of effective seed dispersal. Location Americas, Africa and the Asia-Pacific. Time period 1970–2020. Major taxa studied Gymnosperms and Angiosperms. Methods We used a dataset consisting of tree inventories from 2821 plots across three biogeographic regions (Americas, Africa and Asia-Pacific), including dry and wet forests, to determine the maximum height and dispersal strategy of 5314 tree species. A web search was used to determine whether species were wind-dispersed. We compared differences in tree species maximum height between biogeographic regions and examined the relationship between species maximum height and wind dispersal using logistic regression. We also tested whether emergent tree species, that is species with at least one individual taller than the 95% height percentile in one or more plots, were disproportionally wind dispersed in dry and wet forests within each biogeographic region. Results Our dataset provides maximum height values for 5314 tree species, of which more than half (2914) had no record of this trait in existing global databases. We found that, on average, tree species in the Americas have lower maximum heights compared to those in Africa and the Asia Pacific. The probability of wind dispersal increased significantly with tree species maximum height and was significantly higher among emergent than non-emergent tree species in both dry and wet forests in all three biogeographic regions. Main conclusion Wind dispersal is more prevalent in tall, emergent tree species than in non-emergent species and may thus be an important factor in the evolution of tree species maximum height. By providing the most comprehensive dataset so far of tree species maximum height and wind dispersal strategies, this study paves the way for advancing our understanding of the eco-evolutionary drivers of tree size.

@inproceedings{bib_Geos_2024, AUTHOR = {Nandakrishnan, and Pillutla, Rama Chandra Prasad }, TITLE = {Geoscape characterization of Ashtamudi, Sasthamkotta, and Vembanad Ramsar sites in Kerala, India}, BOOKTITLE = {Water Resources}. YEAR = {2024}}

Wetlands, which serve as transitional zones between terrestrial and aquatic environments, play a crucial role in providing diverse ecosystem services for the sustenance of wildlife and mankind. Unfortunately, these delicate systems have experienced illicit human interventions in recent times, resulting in degradation and deterioration. Despite being designated as protected areas, wetlands are being exploited beyond their ecological capacity, posing a threat to their sustainability and potential existence in the near future. The present study aims to analyse the historical spatial changes in three wetlands located in Kerala, India, both before and after their declaration as Ramsar sites. Ashtamudi Lake, Sasthamkotta Lake, and Vembanad Lake were the focus areas, and the study employed multi-temporal satellite data sets from 1988 to 2023 to generate land use and land cover maps. The objective was to assess the ecological transitions, particularly the expansion of urbanization and subsequent reclamation of wetlands. By analysing the changes in aerial extent of each land cover class within the study area, the study identified spatio-temporal transitions and modifications occurring in and around the Ramsar sites. A comparison of the thematic maps from 1988 to 2023 revealed a significant increase in built-up areas and a noticeable reduction in vegetation, agriculture, and water bodies, both in terms of extent and quality. The study identified various socio-economic drivers that are responsible for these changes and emphasized the urgent need for regular monitoring and management of these wetland ecosystems. It stresses the importance of treating wetland conservation as a priority.

@inproceedings{bib_AI-E_2024, AUTHOR = {Vinayaka, and Pillutla, Rama Chandra Prasad }, TITLE = {AI-Enhanced Remote Sensing Applications in Indian Sugarcane Research: A Comprehensive Review}, BOOKTITLE = {Sugar Tech}. YEAR = {2024}}

Sugarcane holds a critical position in global agriculture, serving as a basis for the sugar and bioenergy sectors. The integration of remote sensing technologies and sophisticated machine learning approaches and related models has revolutionized sugarcane research. These tools ofer efcient, noninvasive, and large-scale assessment methods. This review highlights the utilization of satellite imagery and sensor data, encompassing RGB, multispectral, hyperspectral, and unmanned aerial vehicles (UAVs) in sugarcane agriculture. It addresses crop identifcation, pest and disease management, yield and acreage estimation, modeling, phenotypic measurement, and their impact on empowering farmers with insights for optimal irrigation, fertilizer application, and overall crop management. These advancements signifcantly increase productivity and foster environmental sustainability. The review had dual aims: (1) consolidate RS data applications in India’s sugarcane research and development, and (2) examine the pros and cons of RS and AI methods in sugarcane farming. The review employed prominent bibliographic databases—google scholar, scopus, researchgate, and web of science—along with pertinent research articles on RS and AI applications in sugarcane, and comprehensive data on sensors and UAVs retrieved from these databases. The study concludes that AI-driven crop RS stands as an efective method for monitoring and managing sugarcane, contributing signifcantly to improving yield and quality, while simultaneously ofering substantial benefts in social, economic, and environmental realms. However, challenges in the sugar industry, such as adapting technology, high initial costs, climate impact, communication, policy, and regulation, must be addressed.

@inproceedings{bib_Asse_2024, AUTHOR = {Prasad, Anagha and Pillutla, Rama Chandra Prasad and Rao, N. Srinivasa }, TITLE = {Assessing the water quality dynamics in the coastal waters of Kollam (Kerala, India) using Sentinel images}, BOOKTITLE = {Anthropocene Coast}. YEAR = {2024}}

Coastal waters are complex, dynamic, and sensitive, and any change in the system impacts the marine environment and life. Coastal water quality has been decreasing due to the incursion of anthropogenic derived waste and toxins into the ocean. This study investigates water quality along the Kollam coast of Kerala State, India, using Sentinel-2 Multispectral Imager (MSI) data for the period of 2019–2022. Four key water quality parameters, chlorophyll (Chl-a), total suspended matter (TSM), turbidity, and coloured dissolved organic matter (CDOM), were analysed for seasonal variations and driving factors. The study highlights the potential of web-based platforms like Google Earth Engine for facilitating large-scale water quality assessments. The results reveal a distinct seasonal pattern in all parameters, primarily influenced by monsoonal riverine discharge and anthropogenic activities as contributing factors to water quality degradation. Overall, the study emphasises the need for comprehensive monitoring and management strate- gies to ensure the long-term sustainability of the coastal ecosystem.

@inproceedings{bib_Eval_2024, AUTHOR = {Reddy, Shashank and Pillutla, Ramachandra Prasad }, TITLE = {Evaluating the effects of natural disasters, human influence, and government development policies on the landscape dynamics of Little Andaman, India.}, BOOKTITLE = {Journal of Coastal Conservation}. YEAR = {2024}}

@inproceedings{bib_Anal_2024, AUTHOR = {Mustafa, Mahammad and Pillutla, Ramachandra Prasad }, TITLE = {Analysing the fragile islandscape of Ritchie’s Archipelago: understanding land use changes, biodiversity loss, and tourism impacts on both the ecosystem and islanders}, BOOKTITLE = {GeoJournal}. YEAR = {2024}}

@inproceedings{bib_Asse_2024, AUTHOR = {Portal, Vaishali and Pillutla, Ramachandra Prasad }, TITLE = {Assessment of Water Quality Parameters in the Hooghly Estuary, India, using Sentinel-3 and Global Biogeochemical Analysis and Forecasts Products}, BOOKTITLE = {An International Journal of Marine Sciences}. YEAR = {2024}}

@inproceedings{bib_Phyt_2023, AUTHOR = {Pillutla, Rama Chandra Prasad and Karamchandani, Gunjan and Karpe, Neal and Manjunaath, }, TITLE = {Phytosociology Analysis Tool}, BOOKTITLE = {Nelumbo}. YEAR = {2023}}

Researchers quantify vegetation characteristics using phytosociology studies. The data collected from vegetation surveys, such as tree girth and height measurements, are used to calculate various phytosociological attributes like frequency, density, basal cover, important value index, etc. In general, they are calculated using an Excel spreadsheet and a lengthy mathematical process. There are a few open-source or free software available to compute some of these parameters. However, they are not user friendly for most researchers. Also, these software primarily doesn’t compute basic phytosociological attributes. In view of these constraints and to ease researchers work, we have developed a simple tool, “PAT” Phytosociology Analysis Tool,” that computes the maximum attributes from the field collected vegetation data. The PAT GUI is simple. PAT computes results using standard formulas after users upload a csv file in the required format. Users can download the table's results and figures in PNG format.

@inproceedings{bib_Corr_2023, AUTHOR = {Bhagat, Shubham and Pillutla, Ramachandra Prasad }, TITLE = {Correction: Assessing the impact of spatio-temporal land use and land cover changes on land surface temperature, with a major emphasis on mining activities in the state of Chhattisgarh, India.}, BOOKTITLE = {Spatial Information Research}. YEAR = {2023}}

@inproceedings{bib_Asse_2023, AUTHOR = {Bhagat, Shubham and Pillutla, Ramachandra Prasad }, TITLE = {Assessing the impact of spatio-temporal land use and land cover changes on land surface temperature, with a major emphasis on mining activities in the state of Chhattisgarh, India}, BOOKTITLE = {Spatial Information Research}. YEAR = {2023}}

The global impact of coal mining and associated activities on land use/land cover (LULC) changes is significant. This study used Landsat satellite images from 1990 to 2020 to assess LULC changes and their impact on land surface temperature (LST) in four districts of Chhattisgarh state, India. Over three decades, Korba and Raigarh districts saw expansion in coal mines, built-up areas, and water bodies, while forest areas diminished by 711.3 km2 and 212.87 km2, respectively. Koriya district saw coal mine expansion of 5.68 km2 (1990–2010), later declining to 2.85 km2, alongside growth in built-up regions, and forest cover reduction by 251.31 km2 in 2020. Surguja district experienced coal mine and built-up area expansion (1990–2020), with initial forest decline of 160.21 km2 in 2010 followed by recovery in 2020. LST was determined using the Mono-window algorithm. LST increased during winter and summer, with the most significant rise in summer. Vegetation-rich regions had lower LST, while coal mines had the highest temperatures. There was a positive relationship between mining land patch size and patch temperatures. This study underscores the need for vegetation restoration in mining areas, particularly abandoned sites, and sustainable mining practices to mitigate coal mining's warming effects.

@inproceedings{bib_Edit_2023, AUTHOR = {Goparaju, Laxmi and Pillutla, Ramachandra Prasad and KV, Suresh Babu and Tecimen, Hüseyin Bariş }, TITLE = {Editorial: Forest fire emissions and their impact on global climate change}, BOOKTITLE = {Frontiers in Forests and Global Change}. YEAR = {2023}}

The ever-increasing problem of forest fire risks has intrigued researchers globally to find a mechanism that can provide an early warning of forest fire incidents as well as assess the extent of spatial-temporal damage caused by them. Further information and data on its impacts would help in mitigating the disaster through advanced planning and management. The effects of forest fire have been known for a long time, but due to limited data, mitigation measures were always hampered. With the advancement of technology in the recent past with respect to high-resolution satellite data, a programming interface, and the development of mobile applications to a certain extent, it is now possible to predict forest fires and to study the impacts at local, regional, and global levels. Several open satellite data sets available from NASA, NOAA, and COPERNICUS have facilitated the quantification of various variables in near real time. Further the easy access to open-source data facilitated in the development of user-friendly web interfaces and APPS to continuously monitor the spatio-temporal changes caused as a result of forest fires on the ecosystem and on climate.

@inproceedings{bib_Asse_2023, AUTHOR = {Goparaju, Laxmi and Pillutla, Ramachandra Prasad and Babu, Suresh }, TITLE = {Assessment of forest fire emissions in Uttarakhand State, India, using Open Geospatial data and Google Earth Engine}, BOOKTITLE = {Environmental Science and Pollution Research}. YEAR = {2023}}

In the recent past, forest fires have increased due to the changing climate pattern. It is necessary to analyse and quantify various gaseous emissions so as to mitigate their harmful effects on air pollution. Satellite remote sensing data provides an opportunity to study the greenhouse gases in the atmosphere. The multispectral sensor of the Tropospheric Monitoring Instrument (Sentinel-5) is capable of recording the reflectance of wavelengths vital for measuring the atmospheric concentrations of methane, formaldehyde, aerosol, carbon monoxide, etc., at a spatial resolution of 0.01°. The present study utilized the Google Earth Engine (GEE) platform to study the emissions caused by forest fires in four districts of Uttarakhand State of India, which witnessed unprecedented fires in April-May 2021. All the datasets were ingested in GEE, which has the capability to analyse large datasets without the need to download them. The pre-fire period chosen was September 2020; the fire period was February-May 2021, and the post-fire period was June 2021. The variables chosen were aerosol absorbing index (AAI), carbon monoxide (CO) and nitrogen dioxide (NO2). The climate parameter temperature (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) and precipitation (from Climate Hazards Group InfraRed Precipitation (CHIRPS) Pentad) were also studied for the period mentioned. The results indicate a different trend for emissions in each district. For AAI, maximum emissions were noted in district Nainital

@inproceedings{bib_Mode_2023, AUTHOR = {SRINIVAS, MARIMGANTI and Pillutla, Ramachandra Prasad }, TITLE = {Modeling Uncertainty Quantification of NDVI of Agricultural Fields through Bayesian Linear Regression in Time Series Prediction}, BOOKTITLE = {Journal of Environmental Informatics Letters}. YEAR = {2023}}

Modeling Uncertainty Quantification of NDVI of Agricultural Fields through Bayesian Linear Regression in Time Series Prediction

@inproceedings{bib_Unde_2022, AUTHOR = {Thekkan, Akhil Francis and George, Anjaly and Pillutla, Ramachandra Prasad and Joseph, Shijo }, TITLE = {Understanding Blue-Green Infrastructure Through Spatial Maps: Contribution of Remote Sensing and GIS Technology}, BOOKTITLE = {Blue-Green Infrastructure Across Asian Countries}. YEAR = {2022}}

Understanding the spatiotemporal distribution of blue-green infrastructures in urban environment is a critical element in the landscape-level planning. Asian cities, which are rapidly undergoing transformational changes in its land cover, predominantly feature urban signatures at the expenses of natural ecosystems. The rapid urbanization in conjunction with mega developmental projects and industrialization requires sophisticated analytical tools in the synoptic assessments and impact measurements. Remote sensing together with geographical information system (GIS) and Global Positioning Systems (GPS) plays an important role in developing the spatial maps and assessing the dynamics of land cover in the urban environment. This chapter reviews various remote sensing instruments available to characterize vegetation and water in complex urban environments. The progress with respect to diverse instruments such as panchromatic, multispectral, hyperspectral, radar, and LiDAR in mapping the blue-green infrastructures is reviewed in this chapter. The chapter helps in understanding the diverse initiatives and instruments in mapping the extent and quality of blue-green infrastructures which are vital for the spatial planning of urban landscapes.

@inproceedings{bib_Asse_2022, AUTHOR = {Vasanthawada, S. R. S. and Puppala, H. and Pillutla, Ramachandra Prasad }, TITLE = {Assessing impact of land-use changes on land surface temperature and modelling future scenarios of Surat, India}, BOOKTITLE = {International Journal of Environmental Science and Technology}. YEAR = {2022}}

Understanding the nexus between land use land cover (LULC) and land surface temperature (LST) of a rapidly growing city may help planners mitigate the effects of uncontrolled urbanization on the micro- and macro-environment. The primary focus of the study is to monitor the transient LULC of Surat, one of the rapidly growing cities in India. To comprehend the urban dynamics, the study analyses the tri-decadal LULC of Surat using temporal Landsat imagery corresponding to 1990, 2001, 2009, and 2020. Besides classification of satellite data to derive LULC using the maximum likelihood algorithm, emphasis has been given to evaluate the normalized difference vegetation index and normalized difference built-up index, which help in differentiating vegetation and built-up from other land-use types. In addition, the LST of Surat is computed, and zonal analysis is performed to examine its association with LULC. Results show that the built-up area of Surat increased by 3.22 times during the considered time, while the aerial extent of vegetation decreased by 1.58 times. Future land-use dynamics are predicted using the Markov model. Findings revealed that the built-up area is expected to increase by 20% between 2020 and 2030, while the vegetation area is likely to decrease by 13%. The developed model attained an accuracy of 52.08%, which is in agreement with the past studies. The findings of this study help urban planners and stakeholders to devise effective policies that can mitigate the

@inproceedings{bib_Mode_2022, AUTHOR = {VANI, M and Pillutla, Ramachandra Prasad }, TITLE = {Modelling urban expansion of a south-east Asian city, India: comparison between SLEUTH and a hybrid CA model}, BOOKTITLE = {Modeling Earth Systems and Environment}. YEAR = {2022}}

Accurate identification of the dominant driving factors in the expansion of a city is essential for cellular automata (CA)-based urban expansion modelling. The current study aimed at analyzing the drivers of change for Vijayawada city, a tier-II developing city in south-east Asia, India and then applies them to model the future scenario of the city in a CA-based environment. Furthermore, the study also aims at comparing the efficiency of the renowned CA-based urban growth model, SLEUTH (Slope, Land use, Exclusion, Urban extent, Transportation, Hill shade), and a self-designed CA-based hybrid model developed in combination with genetic algorithm (GA) for developing future scenario of the city. The models were built, calibrated, and validated for the city using land use maps derived from temporal Landsat satellite images. Analysis of the statistical significance of the driving factors shows that the terrain and …

@inproceedings{bib_Semi_2021, AUTHOR = {Salghuna, N.N. and Pillutla, Ramachandra Prasad and Nidamanuri, Rama Rao }, TITLE = {Semi-empirical model for upscaling leaf spectra (SEMULS): a novel approach for modeling canopy spectra from in situ leaf reflectance spectra}, BOOKTITLE = {Geocarto International}. YEAR = {2021}}

The use of in situ hyperspectral reflectance and bio-physical measurements has been increasing in forestry. Due to limited physical accessibility in a forest environment, most of the reflectance measurements of trees are acquired at a leaf or bunch of leaves level. A few radiative transfer models are available for upscaling leaf spectra to canopy level. While these models are sophisticated, they retrieve canopy spectra based on certain assumptions. We propose ‘semi-empirical model for upscaling leaf spectra (SEMULS)’ which upscales in situ leaf spectra to canopy level based on the relationship between leaf spectra and its bio-physical parameters. The performance of the model has been quantitatively validated by comparing the upscaled canopy spectra with spectra from – CHRIS hyperspectral imagery acquired concurrently and from the PROSAIL model. Results indicate that the SEMULS retrievals are …

@inproceedings{bib_Asse_2020, AUTHOR = {VANI, M and Pillutla, Ramachandra Prasad }, TITLE = {Assessment of spatio-temporal changes in land use and land cover, urban sprawl, and land surface temperature in and around Vijayawada city, India}, BOOKTITLE = {Environment, Development and Sustainability}. YEAR = {2020}}

The urban agglomeration is the unplanned growth of a city into its surrounding peri/rural areas causing unsustainable exploitation of natural resources. This leads to an increase in the land surface temperature that in turn results in climatic issues ranging from local to global scales. In the current study, an attempt has been made to map the urban growth and its associated land surface temperature variations in and around Vijayawada city of Andhra Pradesh state, India. Temporal Landsat satellite images from 4 years, viz. 1990, 2000, 2010, and 2018, were used to generate land use/land cover maps with four major classes such as built-up, vegetation, water body, and others. Change detection and transition of the natural land cover to man-made land use were statistically computed for the study area. Sprawl analysis of the city was carried out by generating multiple buffer rings over the study region to evaluate …

@inproceedings{bib_DISC_2019, AUTHOR = {Salguna, N N and Pillutla, Ramachandra Prasad and N, Rama Rao }, TITLE = {DISCRIMINATION OF TREE SPECIES BASED ON THEIR SPECTRA COLLECTED AT SPATIO-TEMPORAL SCALE IN THE FOREST OF ARAKU, EASTERN GHATS, INDIA}, BOOKTITLE = {Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing}. YEAR = {2019}}

In the field of hyperspectral remote sensing, the spectral data is derived from hyperspectral images and are matched with the spectral library. Till date there are no studies that have matched with the hand–held spectrum collected by spectroradiometer at temporal scale. Creating a spectral library for the same species at various regions is a challenge, as acquiring spectrum at temporal sets are practically difficult and expensive. The absorption features are the unique key print for the identification of the two different samples of same species and also helps to discriminate two different species. The intensity and position of strong absorption region helps to match the spectrum accurately. In the current study probability based matching technique is used where the dips of a species of a season is matched to the other within a predefined abundance window. This study helps to know the seasonal changes of the tree due to its environmental factors, stress and deficiency.

@inproceedings{bib_Stru_2019, AUTHOR = {Pillutla, Ramachandra Prasad and Kumari, Jasti Asha }, TITLE = {Structure, composition and diversity of trees within the dry evergreen reserve forest of Kondapalli (Eastern Ghats, southern India)}, BOOKTITLE = {Biodiversity Research and Conservation}. YEAR = {2019}}

he dry evergreen forest of Kondapalli (Andhra Pradesh state, India) is declared as a forest reserve, but, despite of this, it is subjected to degradation resulting in loss of biodiversity. Thus, the current study was carried out to investigate the tree diversity of Kondapalli forest. A total of 566 ±16 trees (≥10 cm) representing 46±8 species from 40 genera and 21 families were recorded from the 0.36 ha area of Kondapalli forest. Mimosaceae was the most species rich family, while Rutaceae was the most abundant family. Atalantia monophylla was most frequent and abundant species and, with respect to basal area, Melia azedarach and Syzygium cumini were the dominant taxa. The recorded stem density was 1572 stems ha−1 and the mean forest basal area was 47.17 m2 ha−1. The results of cluster analysis revealed that Atalantia monophylla, characterised by a high ecological amplitude, had a wide distribution and was associated with species forming different communities. The study showed that Kondapalli forest is characterised by a fairly high species richness, which provides the baseline data on the floristic structure and diversity of this forest for better management and conservation.

@inproceedings{bib_Semi_2019, AUTHOR = {Salguna, N N and Pillutla, Ramachandra Prasad and Nidamanur, Rama Rao }, TITLE = {Semi-empirical model for upscaling leaf spectra (SEMULS): a novel approach for modeling canopy spectra from in situ leaf reflectance spectra}, BOOKTITLE = {Geocarto International}. YEAR = {2019}}

The use of in situ hyperspectral reflectance and bio-physical measurements has been increasing in forestry. Due to limited physical accessibility in a forest environment, most of the reflectance measurements of trees are acquired at a leaf or bunch of leaves level. A few radiative transfer models are available for upscaling leaf spectra to canopy level. While these models are sophisticated, they retrieve canopy spectra based on certain assumptions. We propose ‘semi-empirical model for upscaling leaf spectra (SEMULS)’ which upscales in situ leaf spectra to canopy level based on the relationship between leaf spectra and its bio-physical parameters. The performance of the model has been quantitatively validated by comparing the upscaled canopy spectra with spectra from – CHRIS hyperspectral imagery acquired concurrently and from the PROSAIL model. Results indicate that the SEMULS retrievals are …

@inproceedings{bib_Pred_2018, AUTHOR = {REDDY, DEVIREDDY SUSHMA and Pillutla, Ramachandra Prasad }, TITLE = {Prediction of vegetation dynamics using NDVI time series data and LSTM}, BOOKTITLE = {Modeling Earth Systems and Environment}. YEAR = {2018}}

Understanding and analyzing the changes in vegetation cover is very important in several aspects including climatic changes, water budget, ecological balance and specially to undertake necessary conservation measures. The concept of neural network has gained much significance in the analysis of vegetation dynamics using remote sensing satellite data. In the current study an attempt has been made to predict the vegetation dynamics using MODIS NDVI time series data sets and long short term memory network, an advanced technique adapted from the artificial neural network. The dataset of 861 NDVI images from January 2000 to June 2016 is used for making the time series. The data is segregated into three sets which comprises of training set (70%), validation set (20%), and testing set (10%). To check the reliability of the experiment we have finalised two different regions after extensive research for investigation. These include different terrains in the Great Nicobar Islands, one region along the coast where vegetation has severe ecological damage due to 2004 Indian Ocean tsunami and the other, an interior region which remained imperturbable during the tsunami. Long short term memory network, an advanced neural network is trained with these NDVI values for both the regions separately to predict the future vegetation dynamics. To measure the accuracy of the LSTM network, root mean square error is calculated. The resulting plots from both the experiments indicate that the long short-term memory neural network follows the series in addition to coinciding with the required time series. Also, an unanticipated change in the trend of the NDVI series were well adapted by the network and was able to predict the future NDVI values with good accuracy maintaining RMSE less than 0.03 without providing any supplementary data. By adopting the prescribed method in the paper, anticipation of vegetation changes can be done accurately much ahead of time and take proactive measures accordingly to safeguard and improve the vegetation in any area.

@inproceedings{bib_Geos_2018, AUTHOR = {M.Vani, and Pillutla, Ramachandra Prasad }, TITLE = {Geospatial Assessment of Spatio-Temporal Changes in Mangrove Vegetation of Pichavaram Region, Tamil Nadu, India}, BOOKTITLE = {Journal of Earth Science and climate change}. YEAR = {2018}}

The present work is a multi-temporal satellite based spatial dynamic study of an important coastal habitat, the Pichavaram mangrove ecosystem, over a period of 15 years. The study discusses the importance and the status of mangroves on both global and regional scales. Maximum likelihood estimate method of supervised classification technique has been used to classify the land use-land cover changes in the Pichavaram Reserve Forest, Killai Reserve Forest and Pichavaram Extension. The status of the classes has been monitored using Landsat ETM+ of 2000, 2006, 2011, and OLI of 2016 satellite imageries. The total area of the Pichavaram mangrove showed a net increase of approximately 11.41% of the total study area within a span of 15 years (2000–2016)

@inproceedings{bib_Asse_2018, AUTHOR = {Kumari, J Asha and Pillutla, Ramachandra Prasad }, TITLE = {Assessing the Allelopathy and Autotoxicity Effects of Parthenium hysterophorus L., Senna uniflora (Mill.) H.S. Irwin and Barneby and Hyptis suaveolens (L.) Poit}, BOOKTITLE = {Russian Journal of Biological Invasions}. YEAR = {2018}}

Abstract In the current study laboratory experiments were conducted to elucidate the allelopathic and autotoxic effects of Parthenium hysterophorus, Senna uniflora and Hyptis suaveolens. The seed germination experiments were conducted using the leachates obtained from different organs of the three species. Ten grams, each of the plant materials were homogenized in 100 mL of quartz-distilled water for 24 hours, filtered and used as a stock solution of 100% concentration. From the stock solution, 25, 50 and 75% concentrations were prepared by diluting with quartz-distilled water. Three replicates with 30 seeds each for each plant species were maintained. Observations were made at regular intervals of 24 hours. The emergence of radicle was taken as the indicator of germination. Germination, root and shoot elongation was monitored for eight days. The study revealed inhibition of germination …

@inproceedings{bib_Asse_2018, AUTHOR = {Salguna, N N and Pillutla, Ramachandra Prasad and Kumari, J. Asha }, TITLE = {Assessing the impact of land use and land cover changes on the remnant patches of Kondapalli reserve forest of the Eastern Ghats, Andhra Pradesh, India}, BOOKTITLE = {The Egyptian Journal of Remote Sensing and Space Science}. YEAR = {2018}}

The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropogenic interference, despite its status as reserve forest. The present research focuses on assessing the land use and land cover changes in and around KRF using temporal satellite data. It is evident from the current study that there has been a considerable decrease in the forest cover from 1990 to 2015; as seen from 2017 data, huge urban expansions and development activities were observed around KRF. This increase is linked to the growth in population, thereby consuming land available for their basic needs. To assess the rate of urban expansion around the forest, Land consumption rate and Land absorption coefficient were computed. The result of this analysis showed a rapid growth in built-up land between 1990 and 2017 while the periods between 1990 and 2015 witnessed a reduction in the forest class. Further

@inproceedings{bib_Fill_2017, AUTHOR = {Srinivas, M. and Pillutla, Ramachandra Prasad }, TITLE = {Filling the data gaps in Landsat 7 Images using Texture Analysis}, BOOKTITLE = {Asian Conference on Remote Sensing}. YEAR = {2017}}

Missing data in satellite images is a known phenomenon in remote sensing. There are various reasons for these gaps in satellite images e.g. shadowed area for SAR data sets, cloud coverage for optical imagery and instrument errors such as Scan Line Corrector(SLC-off) failure. The Scan Line Corrector (SLC) of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed permanently causing around 23% of pixels not scanned in each scene and this failure has seriously limited the scientific applications of ETM+ data. Reconstructing the gap regions is an important issue in remote sensing. To address this issue, we have proposed an idea to find the homogeneous and heterogeneous regions of ETM+ image using Morphological operations and replace the unscanned pixel value by Neighborhood similar pixel threshold based Local Binary Pattern value. We have applied padding approach with additional rows and columns for unscanned mixels at borders to replace with the corresponding NLBP value. It is observed that our results are promising to fill the data gaps in both homogeneous and heterogeneous regions.

@inproceedings{bib_Asse_2017, AUTHOR = {KUKKALA, V SURESH BABU and Vanama, Venkata Sai Krishna and Roy, Arijit and Pillutla, Ramachandra Prasad }, TITLE = {Assessment of forest fire danger using automatic weather stations and MODIS TERRA satellite datasets for the state Madhya Pradesh, India}, BOOKTITLE = {International Conference on Advances in Computing, Communications and Informatics}. YEAR = {2017}}

Forest fires are the most frequently occurred phenomenon during summer seasons in the state Madhya Pradesh. Monitoring and assessment of forest fires are the crucial steps in effective forest fire management. Forest fire danger estimation helps the disaster management authorities to take necessary mitigation measures for minimizing the losses and to evacuate the local people. Fire danger rating systems predict the fire danger based on the meteorological station parameters and ground datasets. McArthur Forest Fire Danger Index (FFDI) is the most popularly used fire danger rating systems using in the country Australia. This index requires large amount of ground datasets for the computation of drought parameter. In India, it is very difficult to compute the drought parameter due to the unavailability of instruments and man power. In the present research, McArthur Fire Danger Index was modified by inducing Normalized multiband drought index (NMDI) that was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA surface reflectance product MOD09GA as a substitute for fuel availability parameter. To test the robustness of modified FFDI, the research was carried out on Madhya Pradesh state for the assessment of forest fire danger. The results obtained from

@inproceedings{bib_AUTO_2016, AUTHOR = {REDDY, D SUSHMA and AGRAWAL, MAYANK and Pillutla, Ramachandra Prasad }, TITLE = {AUTOMATIC EXTRACTION OF MANGROVE VEGETATION FROM OPTICAL SATELLITE DATA}, BOOKTITLE = {INTERNATIONAL SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING}. YEAR = {2016}}

Mangrove, the intertidal halophytic vegetation, are one of the most significant and diverse ecosystem in the world. They protect the coast from sea erosion and other natural disasters like tsunami and cyclone. In view of their increased destruction and degradation in the current scenario, mapping of this vegetation is at priority. Globally researchers mapped mangrove vegetation using visual interpretation method or digital classification approaches or a combination of both (hybrid) approaches using varied spatial and spectral data sets. In the recent past techniques have been developed to extract these coastal vegetation automatically using varied algorithms. In the current study we tried to delineate mangrove vegetation using LISS III and Landsat 8 data sets for selected locations of Andaman and Nicobar islands. Towards this we made an attempt to use segmentation method, that characterize the mangrove vegetation based on their tone and the texture and the pixel based classification method, where the mangroves are identified based on their pixel values. The results obtained from the both approaches are validated using maps available for the region selected and obtained better accuracy with respect to their delineation. The main focus of this paper is simplicity of the methods and the availability of the data on which these methods are applied as these data (Landsat) are readily available for many regions. Our methods are very flexible and can be applied on any region.

@inproceedings{bib_Auto_2015, AUTHOR = {MISHRA, KSHITIJ and Pillutla, Ramachandra Prasad }, TITLE = {Automatic Extraction of Water Bodies fromLandsat Imagery Using Perceptron Model}, BOOKTITLE = {Journal of Computational Environmental Sciences}. YEAR = {2015}}

Extraction of water bodies from satellite imagery has been widely explored in the recent past. Several approaches have been developed to delineate water bodies from different satellite imagery varying in spatial, spectral, and temporal characteristics. The current study puts forward an automatic approach to extract the water body from a Landsat satellite imagery using a perceptron model. Perceptron involves classification based on a linear predictor function that merges few characteristic properties of the object commonly known as feature vectors. The feature vectors, combined with the weights, sum up to provide an input to the output function which is a binary hard limit function. The feature vector in this study is a set of characteristic properties shown by a pixelof the water body. Low reflectance of water in SWIR band, comparison of reflectance in different bands, and a modified normalized difference water index are used as descriptors. The normalized difference water index is modified to enhance its reach over shallowregions. For this study a threshold value of 2 has been proved as best among the three possible threshold values. The proposed method accurately and quickly discriminated water from other land cover features.

@inproceedings{bib_Esti_2015, AUTHOR = {Pillutla, Ramachandra Prasad and Lakshmi, P. Mamtha }, TITLE = {Estimation of biomass density and carbon storage in the forests of Andhra Pradesh, India, with emphasis on their deforestation and degradation conditions}, BOOKTITLE = {European Journal of Ecology}. YEAR = {2015}}

The current study evaluates the growing stock, biomass and carbon content of Andhra Pradesh state’s forest (India) along with its current status of forest degradation and loss. For this purpose, the study used the growing stock data collected by state forest department in 2010 for the calculation of biomass and carbon storage using the standard conversion and expansion factors given by IPCC. The analysis shows low biomass and carbon values for the state’s forest in comparison to the mean values recorded in different studies made for Andhra Pradesh. It is also observed to be lower when compared with the average carbon and biomass for Indian forests. Overall, the analysis showed degradation and loss of forest in the state, coupled with reduction in biomass and carbon sink.

@inproceedings{bib_DEVE_2015, AUTHOR = {CHHAJER, VAIDEHI and PRABHAKAR, SUMATI and Pillutla, Ramachandra Prasad }, TITLE = {DEVELOPMENT OF INDEX TO ASSESS DROUGHT CONDITIONS USING GEOSPATIAL DATA A CASE STUDY OF JAISALMER DISTRICT, RAJASTHAN, INDIA}, BOOKTITLE = {Geoinformatica Polonica}. YEAR = {2015}}

The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However fl ood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006−2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation defi cit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-defi cit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modifi ed Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifi cally for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

@inproceedings{bib_Dete_2015, AUTHOR = {CHATURVEDI, RAJESH and Pillutla, Ramachandra Prasad }, TITLE = {Determining species expansion and extinction possibilities using probabilistic and graphical models}, BOOKTITLE = {Ekológia (Bratislava)}. YEAR = {2015}}

Survival of plant species is governed by a number of functions. The participation of each function in species survival and the impact of the contrary behaviour of the species vary from function to function. The probability of extinction of species varies in all such scenarios and has to be calculated separately. Secondly, species follow different patterns of dispersal and localisation at different stages of occupancy state of the site, therefore, the scenarios of competition for resources with climatic shifts leading to deterioration and loss of biodiversity resulting in extinction needs to be studied. Furthermore, most possible deviations of species from climax community states needs to be calculated before species become extinct due to sudden environmental disruption. Globally, various types of anthropogenic disturbances threaten the diversity of biological systems. The impact of these anthropogenic activities needs to be analysed to identify extinction patterns with respect to these activities. All the analyses mentioned above have been tried to be achieved through probabilistic or graphical models in this study

@inproceedings{bib_CLIM_2015, AUTHOR = {Pillutla, Ramachandra Prasad }, TITLE = {CLIMATE CHANGE RESEARCH – WHAT DO WE NEED REALLY?}, BOOKTITLE = {Papers on Global Change}. YEAR = {2015}}

This research note focuses on the current climate change research scenario and discusses primarily what is required in the present global climate change conditions. Most of the climate change research and models predict adverse future conditions that have to be faced by humanity, with less emphasis on mitigation measures. Moreover, research ends as reports on the shelves of scientists and researchers and as publications in journals. At this juncture the major focus should be on research that helps in reducing the impact rather than on analysing future scenarios of climate change using different models. The article raises several questions and suggestions regards climate change research and lays emphasis on what we really need from climate change researchers.

@inproceedings{bib_Inte_2014, AUTHOR = {Singh, Raghvendra and Pillutla, Ramachandra Prasad }, TITLE = {Interpolation of data gaps of SLC-off Landsat ETM+ images using algorithm based on the differential operators}, BOOKTITLE = {Journal of Applied Computer Science Methods}. YEAR = {2014}}

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in May 2003, and this abnormal functioning of SLC resulted in about 22% of the pixels per scene without being scanned. By filling the un-scanned gap by a good technique will help in more use of ETM+ data for many scientific applications. While there have been a number of approaches developed to fill in the data gaps in ETM+ imagery, each method has shortcomings, especially they require SLC-on (images acquired before SLC-off anomaly) imagery for the same location to fill the gaps in SLC-off (images acquired after SLC anomaly) image. To overcome such shortcomings this study proposes an alternative interpolation method based on the partial derivative. This case study shows that this technique is very much useful to interpolate the missing pixel values in the SLC-off ETM+ data.

@inproceedings{bib_Unde_2014, AUTHOR = {Pillutla, Ramachandra Prasad and Kumari, Jasti Asha }, TITLE = {Understanding the changing lake dynamics and its sustainable management practices-A case study from Krishna District, Andhra Pradesh, India.}, BOOKTITLE = {Sustainable Environment Research}. YEAR = {2014}}

The deterioration and loss of water bodies like lakes due to anthropogenic activities, are at the same pace at which forests are degraded. Lakes and ponds play a major role in the global cycle (carbon, water, etc.). They act as the basic units of hydrological systems to better understand the biogeochemical processes that take place within these aquatic systems and further for their management plans. As an initiative of managing resources at the unit level (lake) in the current study, we tried to understand the history and ecological dynamics of" Brahmayyalingam Cheruvu", a lake located in the peri-urban areas of the rapidly expanding Vijayawada city, Andhra Pradesh State, India. The study is based on field inventories, local surveys and satellite data, both current and past. Use of satellite images aided in capturing the changing spatiao-temporal lake dynamics due to climatic variations and government policy. The …

@inproceedings{bib_Is_c_2014, AUTHOR = {Pillutla, Ramachandra Prasad and Sundara, Rajan Krishnan }, TITLE = {Is current forest landscape research approaches providing the right insights? Observations from India context}, BOOKTITLE = {Ecological Questions}. YEAR = {2014}}

One of the major challenges in the current scenario for ecological conservation is to quantify the forest landscape in its spatio-temporal domain and understand further implications of those. While the detailed study of the forest ecosystems may provide insights into biodiversity, carrying capacity and productive nature, most of the studies are restricted to single time/event inventory and focused on assessment of tree diversity patterns. Through the adoption of geospatial technologies like remote sensing and Geographical Information System (GIS), though forest monitoring has been possible, the linkages to the biodiversity distribution and its patterns are still at an empirical level, thus supporting broad measures of protection and preservation without accounting for the local/regional variability.

@inproceedings{bib_Appl_2013, AUTHOR = {CHATURVEDI, ANUBHAV and Pillutla, Ramachandra Prasad }, TITLE = {Application of fractal geometry in determining optimal quadrat size for vegetation sampling}, BOOKTITLE = {Current Science}. YEAR = {2013}}

Geometry in ecological patterns of landscape and vegetation is not truly fractal, and varies across a range of scales, whereas fractal geometry provides tools for predicting and describing ecological patterns. In this study, fractal analysis is used to assess presence of pseudo random quadrats or spatial dependence which hamper generality and performance of classical inferential statistics. Fractal dimension (FD) as a function of scale is used to determine quadrat size which eliminates spatial dependence. The semivariograms are plotted with fractograms to correlate structures of spatial dependence of the properties studied. The use of FD as a degree of spatial dependence of variables is the basis of applications of fractals.

@inproceedings{bib_Spat_2013, AUTHOR = {CHATURVEDI, RAJESH and Mishra, Kshitij and Pillutla, Ramachandra Prasad and Sundara, Rajan Krishnan }, TITLE = {Spatial Analysis of Indian Railways}, BOOKTITLE = {India Geospatial Forum}. YEAR = {2013}}

: Railway is the largest undertaking in the country. A retrospective study of prevailing conditions is necessary to assimilate the progress of the sector and how far have the changes introduced in previous few years been successful. The paper examines how the proposed changes in the Indian railways have changed the face of it through rigorous spatial analysis in diversified fields. A balanced analysis of shortcomings as well as achievements has been tried to be achieved through this paper for few selected regions of India.Each year there has to be more emphasis on enhancing the services provided. The rail budgets play a vital role and are responsible for taking care of it. The numerous promises made in terms of introduction of trains, electrification of routes, gauge conversion, doubling and increasing frequency of trains are made every year, in order to keep track of fulfillment of those decisions the spatial analysis is conducted rigorously. Railway has also witnessed a number of disasters in past few years; the spatial analysis conducted brings out few major reasons of those. A section of study also covers the topographic conditions in the state of Jammu and Kashmir that have not allowed the progress of railways in these regions.

@inproceedings{bib_Huma_2012, AUTHOR = {Pillutla, Ramachandra Prasad and Kumari, J. Asha and Mathew, Manju and Thomas, Rosina }, TITLE = {Human-Bird Conflicts and Management Issues: A Case Study of Birds at Uppalapadu Lake, Andhra Pradesh, India}, BOOKTITLE = {International Journal of Zoology}. YEAR = {2012}}

The current research focused on the issues related to human-bird conflicts and subsequent alternatives adopted by the migratory birds at Uppalapadu Lake (India). The study collates the information from field observations and literature surveys and draws conclusions based on the observation data. The study highlights the ways the local community, Forest Department, activist groups and other organizations participate in protecting the birds from harm. It also focuses on some of the management initiatives taken by the Forest Department that are helping the birds during their breeding periods. Overall, the research identifies the ecological importance of the lake with respect to birds and stresses the need for its protection and further expansion.

@inproceedings{bib_Comm_2012, AUTHOR = {Pillutla, Ramachandra Prasad and C.B.S.Dutt, }, TITLE = {Community Classification and Species Assemblage Limit within the Forests of North Andaman Islands, India}, BOOKTITLE = {Tree and Forestry Science and Biotechnology}. YEAR = {2012}}

In the present study, three large ecological plots of 3 ha each were surveyed in 3 different forest types of North Andaman Islands. Each 3-ha plot (30 sub-plots of 0.1 ha each) was classified into different classes based on site quality as either excellent, good, moderate or poor using an index developed by utilizing vegetation parameters such as species richness, diversity, density, among others. Analysis revealed most of the area to be under the good category in three forest communities, indicating that forests of North Andaman are potential sites of species richness and diversity. The “general limit of species assemblage” with respect to higher angiosperm taxa in North Andaman was observed based on two independent approaches of sampling: stratified random plots and the large area ecological plots. The general limit of species assemblage was in the range of 14-33 species. The present analysis provides a base …

@inproceedings{bib_Tsun_2012, AUTHOR = {Pillutla, Ramachandra Prasad and Lakshmi, P Mamtha and Sundara, Rajan Krishnan and , Vijaya Bhole and Dutt, C. B. S. }, TITLE = {Tsunami and tropical island ecosystems: a meta-analysis of studies in Andaman and Nicobar Islands}, BOOKTITLE = {Biodiversity and Conservation}. YEAR = {2012}}

Tropical islands are special and sensitive ecosystems which are subjected to various disturbances imposed by human activities and natural disasters. A detailed study about the changing landscape scenarios of these fragile island systems induced by various driving factors could be used for setting up measurements in support of conservation and sustainable development projects. The current research is a meta-analysis of the studies carried out in Andaman and Nicobar islands which analyzed the impact of tsunami of 2004 using geospatial tools. Based on the analysis, it was observed that the Nicobar islands were more affected compared to the Andaman islands. The majority of the researchers used pre- and post-tsunami satellite imagery and adopted visual interpretation method to delineate the changed classes. The study infers uplift of land in Andaman (exposing) and subsidence in Nicobar islands …

@inproceedings{bib_Ecol_2011, AUTHOR = {Pillutla, Ramachandra Prasad }, TITLE = {Ecological analysis of Dipterocarpaceae of North Andaman Forest, India.}, BOOKTITLE = {Journal of plant development}. YEAR = {2011}}

Dipterocarpaceae is one of the important timber families of Andaman Islands whose members were largely exploited for their timber in the past. The current study discusses in detail about the family Dipterocarpaceae of North Andaman forest with reference to its species composition, population structure and other ecological entities. Data was analyzed using various ecological and statistical methods. Dipterocarps were encountered in 97 plots, occupying 80% of the sampled area with 68 stems ha-1 and basal area of 8.2 m2 ha-1. Dipterocarpaceae ranked 3rd with reference to stem density (11%) and 1st with respect to basal area (18%). The family showed five species viz., Dipterocarpus alatus, D. costatus, D. gracilis, D. grandiflorus and Hopea odorata compounded from two genera–

@inproceedings{bib_Tsun_2011, AUTHOR = {Pillutla, Ramachandra Prasad and , P. M. Lakshmi and Sundara, Rajan Krishnan and Bhole, Vijaya and S., Dutt C. B. }, TITLE = {Tsunami and tropical island ecosystems: a meta-analysis of studies in Andaman and Nicobar Islands}, BOOKTITLE = {Biodiversity and Conservation}. YEAR = {2011}}

t Tropical islands are special and sensitive ecosystems which are subjected to various disturbances imposed by human activities and natural disasters. A detailed study about the changing landscape scenarios of these fragile island systems induced by various driving factors could be used for setting up measurements in support of conservation and sustainable development projects. The current research is a meta-analysis of the studies carried out in Andaman and Nicobar islands which analyzed the impact of tsunami of 2004 using geospatial tools. Based on the analysis, it was observed that the Nicobar islands were more affected compared to the Andaman islands. The majority of the researchers used preand post-tsunami satellite imagery and adopted visual interpretation method to delineate the changed classes. The study infers uplift of land in Andaman (exposing) and subsidence in Nicobar islands (inundation) with severe damage to the coastal elements like mangroves, coral reefs, plantations and in few cases interior forest. The analysis showed there were no records of the damage for some small islands. Finally, it is concluded that utility of microwave satellite data for change analysis will prove better in regions like Andaman and Nicobar where it is difficult to get cloud free optical data because of the high monsoon periods in these islands. It is also suggested that future work utilizing suitable temporal satellite imagery should focus on the extent of recovery of vegetation and other coastal elements which suffer the impact of disaster.

@inproceedings{bib_A_co_2010, AUTHOR = {Pillutla, Ramachandra Prasad and Sundara, Rajan Krishnan and Dutt, C. B. S. and S.., Roy P. }, TITLE = {A conceptual framework to analyse the land-use/ land-cover changes and its impact on phytodiversity: a case study of North Andaman Islands, India}, BOOKTITLE = {Biodiversity and Conservation}. YEAR = {2010}}

Phytodiversity is affected both by natural and anthropogenic factors and in Island ecosystems these impacts can devastate or reduce diversity, if the native vegetation is lost. In addition to rich species richness and diversity, Island systems are the sites of high endemism and any threat to these ecosystems will consequently lead to loss and extinction of species. To understand the dynamics including feedbacks of these changes in phytodiversity of North Andaman Islands, a conceptual framework is proposed which focuses on understanding the land-use and land-cover changes and its impact with phytodiversity. In considering land-use and land-cover changes this work highlights the direct and indirect drivers of changes—socio-economic, biophysical and climatic factors. Migration of population, their socio economic needs and government policies were identified as major driving forces threatening the phytodiversity of these Islands. Apart from human beings, natural disasters like tsunami and introduced herbivorous animals like elephants also contributed to forest destruction in these Islands. The integrated analysis based on such framework will provide insights for holistic resource management including ecological conservation.

@inproceedings{bib_IS_R_2009, AUTHOR = {Pillutla, Ramachandra Prasad and Sundara, Rajan Krishnan and , Vijaya Bhole and Dutt, C.B.S. }, TITLE = {IS RAPID URBANIZATION LEADING TO LOSS OF WATER BODIES?}, BOOKTITLE = {Journal of Spatial Science}. YEAR = {2009}}

Water bodies, the aquatic systems on land, are one of the important store houses for variety of wildlife as well as nesting and breeding sites for different kind of avifauna. Currently these water bodies are under tremendous human pressure due to rapid urbanization. The lakes and reservoirs, across the country, are in varying degrees of environmental degradation due to various anthropogenic activities. In this context a study was carried out in and around the city, covering an area of about 7800 km2 to identify the impact of expanding urbanization process on water bodies of the Hyderabad city using 1989 and 2001 satellite data. The results of the study showed reduction in water bodies both in the area (19%) as well as in number. A negative change was observed in the status of water bodies towards NE and NW directions of the city. Most of the water bodies either were encroached by urban expansion or reduced in size due to eutrophication process. The expanding IT sector and developments in real estate, acted as major driving forces that converted agricultural lands into residential plots and there by exerting pressure on the nearby water bodies. The change study here provides us with vital clues towards understanding the change in water bodies’ vis-à-vis the urban needs, economic growth, and its location characteristics within a rapidly urbanization region.

@inproceedings{bib_Asse_2009, AUTHOR = {Pillutla, Ramachandra Prasad and REDDY.c, SUDHAKAR and Sundara, Rajan Krishnan and K.S., and Raza, and Dutt, and C.B.S, }, TITLE = {Assessment of tsunami and anthropogenic impacts on the forest of the North Andaman Islands, India}, BOOKTITLE = {International Journal of Remote Sensing}. YEAR = {2009}}

Forests are depleted drastically at higher rates to cope up the needs of increasing population. The present study was carried out to assess the impact of anthropogenic and natural disturbances (tsunami) on the vegetation of North Andaman islands using three different satellite images of different time period by visual image interpretation technique. A higher proportion of land cover and vegetation converted into agriculture, settlement, sand and water. Assessment of overall forest change from 1976 to 2005 is 117 Km 2 , with forest loss at the rate of 3.8 Km 2 / year. Simulation study for future forest scenario predicted an increase in agriculture / settlement area to be 196, 296, 392 and 492 Km 2 for the next 25, 50, 75 and 100 years, coupled with the conversion of forest areas of 131, 227, 320 and 427 Km 2 . Finally by the end of 100 years the estimated forest area of 1271 Km 2 (1999 data) reduces to 846 Km 2 if proper conservative actions are not taken.

@inproceedings{bib_Asse_2008, AUTHOR = {Pillutla, Ramachandra Prasad and Nagabhatla, Nidhi and Reddy, C. S. and Gupta, Stutee and Sundara, Rajan Krishnan and Raza, S. H. and .Dutt, C.B.S }, TITLE = {Assessing forest canopy closure in a geospatial medium to address management concerns for tropical islands—Southeast Asia}, BOOKTITLE = {Environmental Monitoring and Assessment}. YEAR = {2008}}

The present study outlines an approach to classify forest density and to estimate canopy closure of the forest of the Andaman and Nicobar archipelago. The vector layers generated for the study area using satellite data was validated with the field knowledge of the surveyed ground control points. The methodology adopted in this present analysis is three-tiered. First, the density stratification into five zones using visual

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