Forest Characterization Using C-band SAR Data—Initial Results of EOS-04 Data

被引:0
|
作者
Jayant Singhal
Tanumi Kumar
Rakesh Fararoda
Prabir Kumar Das
Rakesh Paliwal
Sudhakar Reddy Chintala
Gopalakrishnan Rajashekar
机构
[1] Indian Space Research Organisation,Regional Remote Sensing Centre – North, National Remote Sensing Centre
[2] Antariksh Bhavan,Regional Remote Sensing Centre – East, National Remote Sensing Centre
[3] Indian Space Research Organisation,Regional Remote Sensing Centre – West, National Remote Sensing Centre
[4] Indian Space Research Organisation,Forestry and Ecology Group, Remote Sensing Applications Area, National Remote Sensing Centre
[5] Indian Space Research Organisation,undefined
关键词
EOS-04; C-band; SAR; Phenology; Biomass; Mangroves;
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学科分类号
摘要
In satellite remote sensing, C-band synthetic aperture radar (SAR) sensors with the frequency of about 5.4 GHz and wavelength of about 5.5 cm interact heavily with the leaves, twigs and small stems. Hence, it is ideal for monitoring vegetation phenology, stratification of canopy closure/openness and biomass assessment of low- to medium-aboveground-biomass (AGB) density regions. Earth Observation Satellite-04 (EOS-04) is a C-band SAR mission from the Indian Space Research Organisation launched on 14 February 2022. This study presents the applications of EOS-04 data in forest phenological studies and biomass estimation in different vegetation conditions. Multi-temporal EOS-04 data were used to track the land surface phenology of tropical dry deciduous forests of Betul, Madhya Pradesh, which is mostly dominated by Tectona grandis. Phenological metrics were also derived from the tracked land surface phenology. For the mangrove forests of Sundarbans delta for two islands, namely Lothian and Dhanchi characterization in terms of canopy density and homogeneity/heterogeneity was carried out and AGB was estimated. The AGB values ranged from 29 to 241 Mg/ha, and the validation root mean square error (RMSE) was calculated to be 34 Mg/ha. EOS04 data were also used in combination with L-band ALOS PALSAR data for the forest biomass estimation in the part of Central India. Synergistic utilization of C- and L-band improves upon the individual models in terms of R2 and RMSE. L-band HV backscatter estimates AGB with a correlation coefficient of 0.49 which improved to 0.57 with the inclusion of C-band and estimates AGB with RMSE of 29 Mg/ha. This study successfully demonstrated the usability of EOS-04 for tracking land surface phenology and deriving phenological metrics from it, for the characterization of mangrove forests and it AGB estimation and for AGB estimation of forests in low-biomass regions.
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页码:787 / 800
页数:13
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