Stefano TEBALDINI et al. |《测绘学报（英文版）》（JGGS）精选论文

Title l 题目

Progresses on SAR Remote Sensing of Tropical Forests: Forest Biomass Retrieval and Analysis of Changing Weather Conditions

Citation l 引文格式

Stefano TEBALDINI,Xinwei YANG,Yu BAI,Mauro Mariotti D’ALESSANDRO,Mingsheng LIAO,Wen YANG. Progresses on SAR Remote Sensing of Tropical Forests: Forest Biomass Retrieval and Analysis of Changing Weather Conditions[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(1): 88-93.DOI: 10.11947/ j.JGGS.2021.0111.

Abstract l 摘要

This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation (ID: 32278), sub-project Multi-baseline SAR Processing for 3D/4D Reconstruction (ID: 32278_2). The work here reported focuses on two important aspects of SAR remote sensing of tropical forests, namely the retrieval of forest biomass and the assessment of effects due to changing weather conditions. Recent studies have shown that by using SAR tomography the backscattered power at 30m layer above the ground is linearly correlated to the forest Above Ground Biomass (AGB). However, the two parameters that determine this linear relationship might vary for different tropical forest sites. For purpose of solving this problem, we investigate the possibility of using LiDAR derived AGB to help training the two parameters. Experimental results obtained by processing data from the TropiSAR campaign support the feasibility of the proposed concept. This analysis is complemented by an assessment of the impact of changing weather conditions on tomographic imaging, for which we simulate BIOMASS repeat pass tomography using ground-based TropiSCAT data with a revisit time of 3 days and rainy days included. The resulting backscattered power variation at 30m is within 1.5dB. For this forest site, this error is translated into an AGB error of about 50~80t/hm2, which is 20% or less of forest AGB.

Key words l 关键词

tropical forest; biomass; SAR tomography; LiDAR; temporal decorrelation

Authors l 作者

Stefano TEBALDINI, Xinwei YANG, Yu BAI, Mauro Mariotti D’ALESSANDRO, Mingsheng LIAO, Wen YANG. 

Full Paper | 全文如下

本文选自JGGS 2021,Volume 4,Issue 1, P88-93。本期审图号（Map Approval Number）：GS（2021）1071。点击阅读原文即可下载。

请登录《测绘学报（英文版）》（JGGS）官网http://jggs.sinomaps.com 查看更多精选论文

初审：段鹏丽

复审：宋启凡
终审：金   君