Research Papers
Spatial variation of biochar production potential from surplus crop residues in India
Datta Arindam , Dutta Sutapa , Sharma Shivani , Rahman Md.Hafizur
| 2025
India faces environmental issues due to large-scale seasonal in situ burning of crop residues, leading to air pollution and nutrient loss. Biochar application can increase soil carbon content, moisture, and nutrient content while reducing air pollution. India produces 156 Mt. of annual in situ surplus crop residues from ten major crops, with the highest potential for rice residue biomass in Sangrur, Punjab. Biochar could reduce greenhouse gas emissions by 405 Tg annually and its application to soil could sequester 7.5 Tg of carbon.
GIS and ML-Driven Insights into Forest Vulnerability and Climate Hotspots in Assam, India
Ghosh Sayanta , Warman Aakash , Chauhan Pranjul , Soni Aniruddh , and Sharma Jitendra Vir
| 2025
This study assesses the impact of regional climate variability on forest vulnerability in Assam using a GIS and Machine Learning (ML)-based approach. A grid-based Forest Vulnerability Index (FVI) was developed using eight key indicators, and climate change hotspots were mapped using temperature and precipitation anomalies. The results revealed that 87 forested grids are highly vulnerable, with significant overlaps between climate hotspots and biodiversity risk zones.
Remote Sensing and Machine Learning-based assessment of Forest Biomass Changes in Pench Tiger Reserve, Maharashtra, India
Ghosh, S., Zaidi, A., Chauhan, P., Soni, A., & Vir Sharma, J. V
| 2024
This study evaluates spatio-temporal variations in forest biomass in the Pench Tiger Reserve, Maharashtra, India, using a combination of remote sensing, field-based observations, and machine learning approaches. Fractional Vegetation Cover (FVC) layers were generated using the Linear Spectral Unmixing (LSU) Algorithm applied to multi-temporal LANDSAT data (2001-2022). A Linear Regression Model (LRM) was developed to estimate forest biomass across three forest strata: Very Dense Forest (VDF), Moderate Dense Forest (MDF), and Open Forest (OF), based on field sampling plots.
Technical note on steps in baseline quantification for ARR carbon finance projects using remote sensing and GIS.
Ghosh Sayanta, Sharma Jitendra Vir
| 2024
This technical note outlines a systematic approach to baseline quantification for ARR (Afforestation, Reforestation, and Revegetation) carbon finance projects using advanced remote sensing (RS) and GIS methodologies. This approach particularly addresses India's fragmented landscapes, aiming to integrate small and marginal farmers into carbon finance markets, thus enhancing agroforestry potential and providing additional income generation.
Advancing India’s Agroforestry Potential: Leveraging Technology and Community Approaches for Sustainable Development
Ghosh Sayanta, Sharma Jitendra Vir
| 2024
Agroforestry, a sustainable land management practice integrating trees with crops and livestock, holds immense potential for climate change mitigation and enhancing rural livelihoods in India. This article explores the synergy between advanced Remote Sensing (RS) technologies, such as vegetation indices like NDVI, and participatory approaches involving Farmer Producer Organizations (FPOs), cooperatives, and other farmer collectives.
Assessing forest biomass changes in Pench Tiger Reserve, Maharashtra, India with remote sensing and machine learning approaches
Ghosh, Sayanta, Zaidi, A., Chauhan, P., Soni, A., & Sharma, J. V.
| 2024
This study explores the use of remote sensing and machine learning approaches to monitor forest biomass changes in the Pench Tiger Reserve, Maharashtra, India. It integrates Earth observation data and advanced computational models to assess biomass dynamics, providing critical insights into forest management and conservation efforts. The research underscores the potential of geospatial technologies in supporting sustainable practices, biodiversity conservation, and carbon sequestration initiatives, aligning with India's commitments to environmental sustainability.
Turning trash into treasure: conversion of agroresidue rice straw into carboxymethylcellulose biopolymer
Kaur Prabhpreet , Bohidar Himadri B., Williams Richard , Pfeffer Frederick M. , Agrawal Ruchi
| 2024
In the present study, rice straw-derived cellulose was converted into carboxymethylcellulose (CMC) using alkalization followed by an etherification reaction. The synthesis conditions for this chemical modification were optimized such that CMC with a high degree of substitution (1.02) was obtained. Infrared spectra of the synthesized CMC clearly showed an increased intensity of the C═O bond at 1600cm−1, confirming successful carboxymethylation.
Challenges and Opportunities for Sustainable Diets in India: A Systems Strengthening Perspective
Anand Manish, Sehgal Meena, Gupta Vidhu
| 2023
India is currently in a totally different arena since the Green Revolution era with formidable challenges of nutritional security and sustainability of production systems. To enable a diagnostic analysis of India’s food and land use systems and towards identifying the issues and prospects of the concept of sustainable diets in the Indian context, the book chapter analyses the determinants of sustainable diets from a sustainability and public health perspective.
Reconciling Value Trade-Offs in Advancing Sustainable Development Goals: Risks and Opportunities
Anand Manish, Yerramsetti Srinivas
| 2024
This chapter discusses the centrality of sustainability as a meta-concept shaped by everyday negotiation of the trade-offs between various public values. It uses the political, legal, organizational, and market public values frames to articulate sustainable development as an effort at public value creation.
Enhancing baseline quantification and eligibility assessment for ARR carbon finance projects through remote sensing and GIS
Ghosh Sayanta, Sharma Jitendra Vir
| 2024
Accurate baseline quantification and eligibility assessment are critical in ARR (Afforestation, Reforestation, and Revegetation) carbon finance projects to ensure reliable carbon sequestration outcomes. Leveraging remote sensing (RS) and GIS-based analyses, this approach establishes the eligibility of land for ARR projects, setting baselines for carbon stock assessment and monitoring through time.