Forest biomass monitoring with GNSS-R: Theoretical simulations

被引:106
作者
Ferrazzoli, P. [1 ]
Guerriero, L. [1 ]
Pierdicca, N. [2 ]
Rahmoune, R. [1 ]
机构
[1] Univ Roma Tor Vergata, Dipartimento Informat Sistemi & Produz, I-00133 Rome, Italy
[2] Univ Roma La Sapienza, Dipartimento Ingn Elettron, I-00184 Rome, Italy
关键词
Electromagnetic models; Bistatic scattering; Vegetation; Soil moisture; GPS SIGNALS; SCATTERING; MODEL; TREE; EMISSION; LAYER; OCEAN;
D O I
10.1016/j.asr.2010.04.025
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
GNSS-Reflectometry (GNSS-R) is a remote sensing technique which performs bistatic measurements of the earth surface scattering. This paper presents some theoretical simulations of the specular scattering coefficient of a forested area, with the aim of demonstrating the potentiality of GNSS-R in monitoring forest biomass. The study is performed by means of an electromagnetic model developed in the past years and tested over several vegetation covered sites in its active and passive version. Here, after showing a comparison between model results and measurements over a forest site in the monostatic configuration, and after summarizing other previous validations, the extension to the specular configuration, typical of GNSS-R systems, will be presented. Namely, simulations are carried out at circular polarization and a sensitivity analysis of the received power in the specular configuration to some soil and forest parameters is shown. In the GNSS-R configuration, the theoretical response of vegetation shows a decreasing trend with increasing biomass, due to the increasing attenuation by the plant canopy which reduces the coherent scattering from the soil. The latter, however, remains higher than incoherent scattering even when forest biomass is large, especially at RL polarization and low incidence angle. Consequently the magnitude of the received power is sensitive to the forest biomass without exhibiting the typical saturation of radar backscattering measurements, and it may thus allow biomass retrieval. (C) 2010 COSPAR. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1823 / 1832
页数:10
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