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Spatially explicit measurement of Above Ground Biomass (AGB) is crucial for the quantification of forest carbon stock and fluxes. To achieve this, an integration of Optical and Synthetic Aperture Radar (SAR) satellite datasets could provide an accurate estimation of forest biomass. This will also help in removing the uncertainties associated with the single sensor-based estimation approaches. Therefore, the present study attempts to integrate Sentinel-2 optical data with Sentinel-1 SAR dataset to estimate AGB in the Shoolpaneshwar Wildlife Sanctuary (SWS), Gujarat, India. In this study, two non-parametric machine learning algorithms viz Support Vector Machines (SVMs) with different kernel functions—linear, sigmoidal, radial and polynomial and Random Forest (RF) were employed for the prediction of AGB using different combinations of VV, VH, Normalized Difference Vegetation Index (NDVI) and Incidence Angle (IA). Ground based AGB was estimated through allometric equation at 35 sampling sites with the help of tree height and Diameter at Breast's Height (DBH). Standalone collinearity analysis among different parameters resulted in poor correlation of AGB with VH (r = 0.05) and IA (r = 0.015), whereas a significantly good correlation with NDVI (r = 0.80) and VV (r = 0.74) were observed. Inclusion of NDVI with VV and VH together also resulted in a better correlation (r = 0.85) than other combinations. The SVM with linear kernel utilizing parametric the combinations of VV + VH + NDVI and VV + VH + NDVI + IA were found to be best performing on the basis of evaluation metrics. The outcome of this study highlighted the significance of machine learning techniques and synergistic use of different remote sensing data for an improved AGB quantification in tropical forests. [ABSTRACT FROM AUTHOR]

Coal mines are the major source of energy in industries and are important indicators of the economic growth of a country. Excessive withdrawal of coal from underground coal mines without stowing leads to surface deformation. In this study, Synthetic Aperture Radar Technology has been used to identify the surface deformation in the Korba Coal Mines of India. Korba coal mines are major coal-producing mines in India that come under South Eastern Coalfields Limited (SECL). It covers three underground mines. Depillaring has been done through the caving method, which may lead to the deformation of the area and its surroundings. Deformation may have devastating consequences if overlooked. So, it requires continuous monitoring of the area. Space-based SAR interferometry is the most preferred technique to monitor any mining area over a period of time. In this technique, known as the DInSAR technique, a deformation map can be generated from images of the same area acquired over different points of time. In the present study, images of the month of February of the years 2015, 2016, 2017, and 2019 have been successfully utilized for DInSAR analysis over the Rajgamar area. The Interferogram allows analysis of an entire mine site including pits and their surrounding area. High precision monitoring over wide coverage enables to bring out accurate deformation results due to the presence of coherent targets and monitoring risk across the study area. Maps generated from data were scrutinized and interpreted. Consequentially, 2015–2016 shows greater deformation than the other two corresponding maps generated 2015–2017 and 2015–2019 data. Results were validated through ground observations. Overall the area of the Rajgamar coal mine is getting deformed at a slow rate. • Rajgamar coalmine is an underground mine which area due to excavation of coal. • The DInSAR technique helps to predict the Deformation with low cost and time. • It helps to identify the affected area with the help of less no. of images with suitable parameters. • This helps to predict the most hazardous zones in the area and helps in planning and management of identical area. [ABSTRACT FROM AUTHOR]

Glacier velocity is one of the important parameters to know about glacier dynamics, its mass and health. Understanding glacier velocity also assists in the analysis of ice thickness, ice flux and mass balance. Furthermore, basin/sub-basin wise studies are helpful to understand the climate change over that region instead of monitoring individual glaciers. In the current study, the spatial distribution of glacier velocity is generated for the entire Chandra and Bhaga sub-basins, in the Lahaul-Spiti district of Himachal Pradesh, India, using Advanced Land Observing Satellite-2/Phased Array type L-band Synthetic Aperture Radar-2 (ALOS-2/PALSAR-2) differential interferometry pair images with a 14-days temporal gap. The glaciers in Chandra sub-basin are found to have a high flow rate as compared to the glaciers in Bhaga sub-basin. Local slope and ice thickness, which decrease towards the terminus in general, control the movement of valley glaciers, and lower movement rate is observed for most of glaciers towards the terminus/frontal area. However, a few glaciers of Bhaga sub-basin demonstrate an accelerated movement in their frontal areas. This irregular behaviour is also studied in this work and it is discovered that terrain slope and influx of melting water from adjacent glaciers are the major causes for such behaviour of these glaciers. They are, therefore, prone to accelerated mass loss compared to other glaciers in the sub-basin. Another key finding of the anomalous glacier dynamics study is the disintegrating behaviour of glaciers, which is also identified by interpreting the responses of physical scattering mechanisms retrieved from glaciers using fully polarimetric ALOS-2/PALSAR-2. Warming temperatures are expected to cause glacier retreat and separation of tributary glaciers from the main glacier body. Melt water from tributary glaciers can further accelerate glacier flow and ice melt in lower part of glacier trunk. This can lead to formation of dead ice zones and disintegration of Himalayan glaciers, which are supported by numerous tributary glaciers. Therefore, we expect that the loss in glacier area due to warming will be larger than the present prediction, where mass loss is considered from conventional way. • DInSAR glacier velocity spatial distribution is generated for Chandra and Bhaga basins, Himalaya. • Anomalous glacier dynamics information is discovered using DInSAR. • Influx of melting water from adjacent glaciers is major cause for anomalous dynamics of glaciers. • Disintegrating behaviour in glaciers is also observed due to influx of melting water. • Melt water from tributary glaciers accelerates glacier flow and bottom ice melt of glacier trunk. [ABSTRACT FROM AUTHOR]