Professor
Centre for Ocean, River, Atmosphere and Land Sciences (CORAL)
+91-3222-281802
The significant research contributions of Mukunda Dev Behera have been centered on advancing the quantitative understanding of terrestrial ecosystems using integrative geospatial and ecological approaches. His work has substantially improved methodologies for estimating aboveground biomass and carbon stocks by combining field observations with satellite-based datasets such as LiDAR and multispectral imagery. By developing robust models that integrate climatic, spectral, and edaphic variables, he has reduced uncertainties in biomass estimation and enabled more reliable carbon accounting across heterogeneous landscapes. These contributions hold particular importance for climate mitigation frameworks, including REDD+ and national greenhouse gas inventories.
A major contribution of his research lies in linking ecosystem productivity and phenology with climate variability. Through the use of remote sensing indices and machine learning techniques, he has enhanced the monitoring of vegetation dynamics, crop productivity, and forest health across seasonal and interannual scales. His work has demonstrated how local climatic drivers often exert stronger control over ecosystem processes than large-scale teleconnections, offering nuanced insights into region-specific climate–ecosystem interactions. This has significant implications for improving predictive models under changing monsoon regimes and extreme climatic events.
He has also contributed extensively to biodiversity assessment and conservation planning by applying species distribution models and landscape-level analyses. His studies have identified potential shifts in species habitats and ecosystem resilience under future climate scenarios, thereby informing conservation prioritization and adaptive management strategies. The integration of spatial ecology with policy-relevant modelling has strengthened evidence-based decision-making in vulnerable ecosystems.
Overall, his research delivers a broader message: that scalable, data-driven Earth observation frameworks are essential for managing ecosystems in an era of rapid environmental change. By bridging science, technology, and policy, his contributions support sustainable land management, climate resilience, and biodiversity conservation at regional to global scales.
Area of Research: Carbon Studies using Satellite Data
Area of Research: Geoinformation of Forest Resources
Area of Research: Modeling in Forest CO2 Sequestration
Area of Research: Geoinformation of Forest
Area of Research: Geoinformation of Natural Disaster
Area of Research: Understanding role of Vegetation in modulating Precipitation
Area of Research: Remote Sensing of Forest Hydrology
Area of Research: Plant flammability for forest fire management
Area of Research: SAR for Vegetation Studies
Area of Research: Dynamic Vegetation Model
Area of Research: LiDAR Remote Sensing of Forest
Area of Research: Forest functioning and AI
Area of Research: Modelling in remote Sensing
Thesis Title: Landscape Transience in Himalayan Syntaxial Catchments: Drainage Reorganization, Extreme Event Responses, and Numerical Modelling
Area of Research: Vegetation Carbon
Thesis Title: Modeling Forest Aboveground Biomass and Phenology Using Field Measurements, Satellite Remote Sensing and Pheno-Meteorological Observations
Area of Research: Remote Sensing and Forest Carbon Modeling
Thesis Title: Analysis of Plant Diversity and Endemism Distribution in Biodiversity Hotspots in India
Area of Research: Structural Characterization of Rubber Plantation
Thesis Title: Assessing Distribution Potential of Hevea brasiliensis Using Ecological Niche Modelling Approach
Area of Research: Forest Carbon Dynamics Modeling
Thesis Title: Ensemble Modelling of Plant Diversity in Biogeographic Regions of India
Area of Research: Forest Resilience and Vulnerability in changing climate
Thesis Title: Modelling Forest Cover Resilience using Geo-Spatial Approach
Area of Research: Automatic Feature Extraction of Crop Fields using high resolution Satellite Data
Thesis Title: Agroforestry Interventions for Improved Crop Management using Geospatial Technology
Area of Research: Spatial Statistics and Water-Energy Relationships
Thesis Title: Environmental Determinants of Plant Richness in Indian Himalaya
Area of Research: Remote Sensing and Modelling
Thesis Title: Tropical Ocean Teleconnections with Gross Primary Productivity of Monsoon-Asia with Emphasis over India
Area of Research: Landscape Analysis and Modeling
Thesis Title: Characterising Land Degradation in the Indian Ganga River Basin using Geoinformatics
Area of Research: Hyperspectral Remote Sensing and Mangrove Chlorophyll Estimation
Thesis Title: Estimation of Leaf Area Index and Chlorophyll Concentration using Earth Observation Data and Machine Learning in a Mangrove Forest
Area of Research: FACE Carbon Analysis
Thesis Title: Biomass, Net Primary Productivity and Community Analysis in an Indian Tropical Deciduous Forest
Area of Research: Vegetation Carbon Sequestration through multi-sensor data merging
Thesis Title: Above ground Biomass Estimation in Tropical Forests using Multi-Sensor Data Synergy
Area of Research: Spatial Biodiversity
Thesis Title: Congruence between Plant Dispersal and Diversity with Environmental Heterogeneity
Area of Research: Machine Learning in Remote Sensing
Thesis Title: Development of Multi-Modal and Scalable Deep Learning Framework for Species Level Mapping and Monitoring of Horticulture Plantations from UAV and Satellite Imagery
Area of Research: Data Analytics
Thesis Title: Forest Fire Modelling using Geospatial Technique
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