Browsing by Author "Sujoy Mudi"

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Assessment of tropical cyclone amphan affected inundation areas using sentinel-1 satellite data
(Springer, 2022) Mukunda Dev Behera; Jaya Prakash; Somnath Paramanik; Sujoy Mudi; Jadunandan Dash; Roma Varghese; Partha Sarathi Roy; P.C. Abhilash; Anil Kumar Gupta; Prashant Kumar Srivastava
Tropical cyclones as natural disturbances, influence ecosystem structure, function and dynamics at the global scale. This study assesses the inundation due to the super cyclone Amphan in coastal districts of eastern India by leveraging the computational power of Google Earth Engine (GEE) and the availability of high resolution Sentinel-1 Synthetic Aperture Radar (SAR) data. A cloud-based image processing framework was developed and implemented in GEE for classification using Random Forest algorithm. The inundation areas due to storm surge owing to cyclone Amphan, were mapped and further categorised to different land use and land cover classes based on an existing land cover map. Sentinel-1 images were useful in post-cyclone studies for the change detection analysis due to its higher temporal resolution and cloud penetration ability. The study found that the majority of agricultural and agricultural fallow lands were inundated in the coastal districts. The availability of open-source cloud-based data processing platforms provides cost effective way to rapidly gather accurate geospatial information. Such information could be useful for emergency response planning and post-event disaster management including relief, rescue and rehabilitation measures; and crop yield loss assessment. Cyclone and Land Use and Land Cover (LULC) change can have significant impacts on the human population and if both coexist, the consequences for people and the surrounding environment may be severe. © 2021, International Society for Tropical Ecology.
Shifting cultivation induced burn area dynamics using ensemble approach in Northeast India
(Elsevier B.V., 2022) Pulakesh Das; Mukunda Dev Behera; Saroj Kanta Barik; Sujoy Mudi; Buddolla Jagadish; Swarup Sarkar; Santa Ram Joshi; Dibyendu Adhikari; Soumit Kumar Behera; Kiranmay Sarma; Prashant Kumar Srivastava; Puneet Singh Chauhan
Identifying shifting cultivation areas and assessing their spatio-temporal dynamics are essential in framing climate-adaptive policies for efficient forest management and agriculture practices for the benefit of people. The current study attempts to develop an alternative approach to classify the shifting cultivation areas using an ensemble technique, integrating multiple spectral indices in three states of northeast India (NEI), such as Assam, Manipur, and Meghalaya. The adopted approach integrates green cover and leaf water content changes during shifting cultivation land preparation in Landsat imagery. The deforested burned area patches were identified based on threshold values using Landsat data-derived indices on vegetation, burned area and leaf water, and digital elevation model (DEM). The ensemble approach provided shifting cultivation maps with good overall accuracy (> 83%). The maximum shifting cultivation area was observed in Assam (126.87 km2), followed by Meghalaya (51.53 km2) and Manipur (46.04 km2) in 2016. The normalized difference vegetation index (NDVI) and NDVI difference performed better than other vegetation indices. The ensemble approach can be applied in other regions with minor modifications in threshold values, thus having the potential for accounting to shifting cultivation dynamics on an operational basis. Future research may include blending local traditional knowledge and modern scientific solutions for improved forest and land resources planning for the benefit of inhabitants and the mountain environment under the climate change scenarios. © 2021