Satya P.S. Kushwaha

Bio: Satya P.S. Kushwaha is an academic researcher from Indian Institute of Remote Sensing. The author has contributed to research in topics: Biodiversity & Endemism. The author has an hindex of 10, co-authored 14 publications receiving 356 citations.

Neural network-based modelling for forest biomass assessment

Abstract: Forest biomass is an important parameter for assessing the status of forest ecosystems. In the present study, forest biomass was assessed by integrating remotely-sensed satellite data and field inventory data using an artificial neural network (ANN) technique in Barkot forest, Uttarakhand, India. Spectral and texture variables were derived from Resourcesat-1 (RS1) LISS-III (Linear Imaging Self-Scanning Sensor) data of April 24, 2013. ANN was used for finding the relation of spectral and texture variables to field-measured biomass. The top 10 variables, namely shortwave infrared (SWIR) band reflectance, near infrared (NIR) band reflectance, normalized difference vegetation index (NDVI), difference vegetation index (DVI), green band contrast, green band variance, SWIR band contrast, NIR band dissimilarity, SWIR band second angular moment, and red band mean, were selected for generating a multiple linear regression model to predict the biomass. The predicted biomass showed a good relationship (R2 = 0...

An analysis of altitudinal behavior of tree species in Subansiri district, Eastern Himalaya

Abstract: Plant species diversity and endemism demonstrate a definite trend along altitude. We analyzed the (i) pattern of tree diversity and its endemic subset (ii) frequency distribution of altitudinal range and (iii) upper & lower distributional limits of each tree species along altitudinal gradients in eastern Himalaya. The study was conducted in Subansiri district of Arunachal Pradesh. Data on the tree species (cbh ≥ 15 cm) were gathered every 200 m steps between 200 m and 2200 m gradients. Tree diversity demonstrated a greater variation along the gradients. A total of 336 species (of which 26 are endemic) were recorded belonging to 185 genera and 78 families. The alpha diversity demonstrated a decreasing pattern with two maxima (i.e., elevational peaks) along the gradients; one in 601–1000 m and the other in 1601–1800 m, corresponding to transition zones between tropical-subtropical and subtropical-temperate forests. Pattern diversity revealed a narrow range along the gradients. Frequency of altitudinal range was distributed between 1 and 41. Only one species (Altingia excelsa) showed widest amplitude, occurring over the entire range. Highest level of species turnover was found in 400–600 m step at lower elevational limit whereas for upper elevational limit, the highest turn over was recorded between 800 and 1000 m. Tree diversity decreased and its endemic subset increased along the gradients. Two maximas in tree diversity pattern correspond to forest transition zones with subtropical-temperate transition is narrower than tropical-subtropical. The pattern observed here could be attributed to varied microclimates or environmental heterogeneity. If altitudinal amplitude of a species is considered as an aspect of its niche breadth, it is clear from these results that niche breadth in these organisms is in fact independent of the diversity of the assemblage in which they occur. This analysis calls for detailed floristic studies to determine the breadth of changes between adjacent forest types and details of local species richness in high diversity areas.

High plant endemism in an Indian hotspot - eastern Himalaya

Abstract: A preliminary investigation in the Subansiri area of the eastern Himalaya recorded high plant endemism. As a regular exercise of field sampling of various forest types to map the biorich areas, the number of species observed was evaluated to analyze their endemic status in one of the important hotspot regions of the world. The total number of individuals, species, genera and families observed were recorded in various natural and semi-natural forest types. A total of 122 plots sampled randomly in various forest types recorded 764 plant species, of which 59 were found to be endemic. The overall species endemism is observed to be 13 per ha. These 59 species belong to 27 families and 46 genera. Fifty percent of species were from just five families, Rubiaceae, Lauraceae, Acanthaceae, Magnoliaceae and Rosaceae. Stem size class distribution of the most abundantly found endemic tree species in three primary forest types indicated a quantitative status. This study envisages the status of plant endemism carried out following a proportional stratified random sampling method for various classified vegetation cover types using satellite remote sensing data. Many primitive genera and families were recorded which are indicative of long evolutionary age and affinities of the area with respect to species endemism.

Remote Sensing And Image Interpretation

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Polarimetric SAR interferometry

Abstract: In this paper, we examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. We first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, we show how polarimetric basis transformations can be introduced into SAR interferometry and applied to form interferograms between all possible linear combinations of polarization states. This allows us to reveal the strong polarization dependency of the interferometric coherence. We then solve the coherence optimization problem involving maximization of interferometric coherence and formulate a new coherent decomposition for polarimetric SAR interferometry that allows the separation of the effective phase centers of different scattering mechanisms. A simplified stochastic scattering model for an elevated forest canopy is introduced to demonstrate the effectiveness of the proposed algorithms. In this way, we demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. We investigate the potential of polarimetric SAR interferometry using results from the evaluation of fully polarimetric interferometric shuttle imaging radar (SIR)-C/X-SAR data collected during October 8-9, 1994, over the SE Baikal Lake Selenga delta region of Buriatia, Southeast Siberia, Russia.

Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review

Abstract: Carbon exists as carbon dioxide in the atmosphere and constitutes about 0.04% of the atmosphere. In the recent past, it has gained a lot of attention as a greenhouse gas, as it has potential to influence the climate pattern of the world. Anthropogenic activities like industrialisation, deforestation, forest degradation and burning of fossil fuel, has caused an increase in the level of carbon in the atmosphere and disrupted the global carbon cycle. However, nature has its own mechanism of sequestering and storing the carbon in its “reservoirs” or “sinks’’. Forest plays an important role in the global carbon cycle as carbon sinks of the terrestrial ecosystem. The carbon sequestered or stored on the forest trees are mostly referred to as the biomass of the tree or forest. The Intergovernmental Panel on Climate Change identified five carbon pools of the terrestrial ecosystem involving biomass, namely the aboveground biomass, below-ground biomass, litter, woody debris and soil organic matter. Among all the carbon pools, the above-ground biomass constitutes the major portion of the carbon pool. Estimating the amount of forest biomass is very crucial for monitoring and estimating the amount of carbon that is lost or emitted during deforestation, and it will also give us an idea of the forest’s potential to sequester and store carbon in the forest ecosystem. Estimations of forest carbon stocks are based upon the estimation of forest biomass. Forest’s carbon stocks are generally not measured directly; however, many authors assume the carbon concentration of tree parts to be 50% or 45% of the dry biomass. This paper, aims to review and summarise the various methods and studies that were carried out to estimate the above-ground biomass of the forest.