POLINSAR COHERENCE-BASED REGRESSION ANALYSIS OF FOREST BIOMASS USING RADARSAT-2 DATASETS

被引:2
|
作者
Singh, Jenia [1 ]
Kumar, Shashi [1 ]
Kushwaha, S. P. S. [1 ]
机构
[1] ISRO, Indian Inst Remote Sensing, Dehra Dun 248001, Uttar Pradesh, India
来源
关键词
Backscatter; Complex coherence; Forest biomass; Polarimetric Interferometric SAR (POLINSAR); SAR; VOLUME;
D O I
10.5194/isprsarchives-XL-8-631-2014
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Forests play a pivotal role in synchronizing earth's carbon cycle by absorbing carbon from the atmosphere and storing it in the form of biomass. Researchers today are trying to understand the climatic variations, especially those occurring due to destruction of forest and its corresponding biomass loss. Hence, quantification of various forest parameters such as biomass is imperative for evaluating the carbon. The objective of this research was to exploit the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) technique for analysing the relationship between complex coherence and field-estimated aboveground biomass. Association between the backscatter and the aboveground biomass was also established in the process. To serve our objective, Radarsat-2 interferometric pair dated 4th March, 2013(master image) and 28th March, 2013 (slave image) were procured for the Barkot Reserve Forest region of Dehradun, India. Field sampling was done for 30 plots (31.62m x 31.62m) and stem diameter and tree height were measured in each plot. The study emphasized on the application of POLINSAR coherence instead of using conventional method of relying on backscatter values for retrieving forest biomass. Coherence matrices were utilized for generating complex coherence values for different polarization channels and were regressed against field estimated aboveground biomass. Results indicated a negative linear relationship between complex coherence and aboveground biomass with the cross - polarized coherence showing the highest R-2 value of 0.71. Further, the backscatter mechanism when studied with respect to aboveground biomass indicated a positive linear relationship between backscatter values and field estimated aboveground biomass with R-2 value of 0.45 and 0.61 for slave and master image respectively. The results suggest that PolInSAR technique, in combination with different modelling approaches, can be adopted for estimating forest biomass.
引用
收藏
页码:631 / 635
页数:5
相关论文
共 50 条
  • [1] RADARSAT-2 POLINSAR COHERENCE OPTIMIZATION FOR AGRICULTURE CROP CHANGE DETECTION
    Li, Yifeng
    Liu, Ting
    Lampropoulos, George
    McNairn, Heather
    Shang, Jiali
    Touzi, Ridha
    [J]. 2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014,
  • [2] Machine learning based urban land cover classification using PolInSAR data: a study with ALOS-2 and RADARSAT-2 datasets
    Luvkesh Attri
    Shashi Kumar
    Sandeep Maithani
    [J]. Discover Geoscience, 2 (1):
  • [3] Multibaseline PolInSAR Using RADARSAT-2 Quad-Pol Data: Improvements in Interferometric Phase Analysis
    Alipour, Samira
    Tiampo, Kristy F.
    Samsonov, Sergey
    Gonzalez, Pablo J.
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2013, 10 (06) : 1280 - 1284
  • [4] Tropical Peatland Forest Biomass Estimation Using Polarimetric Parameters Extracted from RadarSAT-2 Images
    Waqar, Mirza Muhammad
    Sukmawati, Rahmi
    Ji, Yaqi
    Sumantyo, Josaphat Tetuko Sri
    [J]. LAND, 2020, 9 (06)
  • [5] EIGEN DECOMPOSITION PARAMETER BASED FOREST MAPPING USING RADARSAT-2 POLSAR DATA
    Li, Yang
    Hong, Wen
    Cao, Fang
    Chen, Erxue
    Goodenough, David G.
    Chen, Hao
    Wang, Peng
    Richardson, Ashlin
    [J]. 2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 4784 - 4787
  • [6] WETLAND VEGETATION BIOMASS INVERSION USING POLARIMETRIC RADARSAT-2 DATA
    Shen, Guozhuang
    Liao, Jingjuan
    Guo, Huadong
    Liu, Ju
    Zhang, Lu
    Chen, Jie
    [J]. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 750 - 753
  • [7] AUTOMATED DETECTION OF FOREST DISTURBANCES USING MULTITEMPORAL RADARSAT-2 DATA
    Staples, Gordon
    van der Kooij, Marco
    Goodenough, David
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 5331 - 5333
  • [8] Forest inventory applications using optical and RADARSAT-2 images in Mexico
    Fernandez-Ordonez, Yolanda
    Soria-Ruiz, Jesus
    Woodhouse, Iain H.
    [J]. IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 4350 - +
  • [9] Estimating Paddy Rice Biomass Using Radarsat-2 Data Based on Artificial Neural Network
    Jing Zhuo-xin
    Wang Ke-jing
    Zhang Yuan
    [J]. PROCEEDINGS OF THE 2013 THE INTERNATIONAL CONFERENCE ON REMOTE SENSING, ENVIRONMENT AND TRANSPORTATION ENGINEERING (RSETE 2013), 2013, 31 : 423 - 426
  • [10] WETLAND WATER SEGMENTATION USING MULTI-ANGLE AND POLARIMETRIC RADARSAT-2 DATASETS
    Allain-Bailhache, S.
    Marechal, C.
    Pottier, E.
    [J]. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 4915 - 4917