DETECTION OF FOREST DISTURBANCE USING TANDEM-X POL-INSAR COHERENCE

This current study shows the potential of TanDEM-X pol-InSAR coherence to identify progressive selective logging of Teak plantation in Uttarakhand, India. Pol-InSAR data were acquired over four months with 11 days interval with perpendicular baseline varying from 111 to 689 m. Progressive selective logging of mature teak plantation from January to February was analyzed using time-series pol-InSAR coherences. The results shows the baseline selection critical for forest change studies. TanDEM-X derived pol-InSAR coherence would enable us to detect the change in forest structure with high reliability

3-D STRUCTURE OF INDIAN FORESTS – PERSPECTIVES FROM EXPERIMENTS ON THE FIRST FULLY-POLARIMETRIC TANDEM-X TOMOGRAMS

This paper provides a first hand view of the 3-D structure of the forests when viewed by X-band SAR data. Tomograms are generated using multi-polarimetric space-borne TerraSAR-X/TanDEM-X acquisitions and analysed over a multi-species forest range. The paper analysed these generated tomograms and puts forth-interesting observations of these unique forest species. The high- and low-canopy density plantations provide unique tomograms and vertical structure profiles where the effect of varying extinction is observed in X-band. Further, the scattering powers are shown relative to their backscatter powers. In-depth analysis in currently underway and would be reported in future

Potential of Space-Borne PolInSAR for Forest Canopy Height Estimation Over India-A Case Study Using Fully Polarimetric L-, C-, and X-Band SAR Data

This paper aims to demonstrate the potential of space-borne datasets for forest height estimation over Indian tropical forests. Fully polarimetric space-borne SAR interferometry (PolInSAR) data is acquired at the L-, C-, and X-band frequencies. The X-band data are acquired in two modes-single pass and repeat pass. The datasets are compensated for decorrelation due to SNR and varying spatial baselines. The remaining major decorrelation is the volumetric decorrelation, which is modeled using random volume over ground model to estimate the PolInSAR height for all the three frequencies. The modified Three-stage inversion algorithm is utilized for forest stand height estimation. The effect of forest biomass on height inversion accuracy is assessed. Furthermore, a first-order estimate of the absolute temporal decorrelation is demonstrated for the repeat-pass space-borne PolInSAR datasets. Extensive field validation campaigns are carried out in the tropical forest ranges. The forest height is inverted using data at all the three frequencies and validated with field measured values. The zero-temporal baseline bistatic TerraSAR-X/TanDEM-X and the L-band ALOS-2/PALSAR-2 result in a good height inversion with r(2) and RMSE of 0.77 and 1.86 m (X-band) and 0.75 and 1.94 m (L-band), respectively. Furthermore, a comparison of estimated height of ALOS-2/PALSAR-2, TerraSAR-X, and RadarSAT-2 has been done with respect to the estimated height of TerraSAR-X/TanDEM-X. It is observed that RMSEof height inversion with respect to TerraSAR-X/TanDEM-X height is found to be 5.4 m, 7.6 m, and 12.8mfor ALOS-2/PALSAR2, RadarSAT-2, and TerraSAR-X, respectively

First demonstration of space-borne Tomosar using Terrasar-x/Tandem-x Full-polarimetric acquisitions

International audienceTomoSAR provides 3D information of complex targets such as forests. Space-borne SAR data utility for TomoSAR analysis is limited due to temporal decorrelation. A novel technique is introduced which utilizes multiple TanDEM-X data sets to generate accurate tomograms. The technique is demonstrated using multiple space-borne SAR acquisitions over Indian tropical forest. Cross-validation with PolInSAR estimation forest height and field height shows high accuracy of generated tomograms. Fully polarimetric space-borne X-band SAR data shows surprising capability to extract 3D scattering information of forested regions. © 2017 IEEE

Identification of forest cutting in managed forest of Haldwani, India using ALOS-2/PALSAR-2 SAR data

Large-scale forest clear-cut identification is one of the major application of remote sensing techniques. ALOS-2/PALSAR-2 is the latest SAR satellite providing multi-polarized L-band SAR data. With increasing deforestation, it is important to assess the potential of SAR data for identifying clear-cuts in forest regions. In this research work, multi-temporal ALOS-2/PALSAR-2 SAR data and supplementary Landsat-8 optical data sets are acquired over Indian tropical forest, and SAR parameters are analysed over a progressively clear-cut Teak plantation. Sensitivity of the SAR parameters to progressive clear-cuts is estimated and found that the cross polarized backscatter sigma HV0 and entropy parameter H are most sensitive to both partial and complete clear-cut in forest compartments. An entropy thresholding based classification is carried out to identify clear-cut regions with a good accuracy. The study highlights the utility of SAR parameters to monitor forest clear-cuts for better forest management. (C) 2018 Elsevier Ltd. All rights reserved