The retrieval and monitoring of vegetation parameters from COSMO-SkyMed images

E. Santi, G. Fontanelli, F. Montomoli, M. Brogioni, G. Macelloni, S. Paloscia, S. Pettinato, P. Pampaloni
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引用次数: 15

Abstract

The capability of COSMO-SkyMed in estimating vegetation biomass has been investigated in this paper. SAR data from COSMO-SkyMed were collected on two agricultural areas in Italy in 2010 at different dates during the vegetation cycle. The performances of X-band data have been compared with accurate ground truth measurements of soil and vegetation carried out simultaneously to satellite passes. Experimental data have been compared with model simulations obtained with a discrete element radiative transfer model. Moreover, an inversion algorithm, based on an Artificial Neural Network and trained by using AIEM and the radiative transfer model, has been applied to retrieve the plant water content of wheat and sunflower crops and to generate the corresponding plant water content maps.
COSMO-SkyMed影像中植被参数的检索与监测
本文对COSMO-SkyMed估算植被生物量的能力进行了研究。COSMO-SkyMed的SAR数据是在2010年意大利两个农业区植被周期的不同日期收集的。将x波段数据的性能与卫星通道同步进行的土壤和植被的精确地面真值测量进行了比较。实验数据与离散元辐射传递模型的模拟结果进行了比较。利用AIEM和辐射传输模型训练的基于人工神经网络的反演算法,检索小麦和向日葵作物的植株含水量,生成相应的植株含水量图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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