A simple model for the estimation of biomass density of regenerating tropical forest using JERS-1 SAR and its application to Amazon region image mosaics

遥感信息 Pub Date : 1997-08-03 DOI:10.1109/IGARSS.1997.609076

A. Luckman, J. Baker

引用次数: 0

Abstract

Regenerating tropical forests are important to the regional carbon balance because they represent areas of high carbon flux from the atmosphere to the land. These forests are complex in species distribution and structure so generalised models of radar backscatter are difficult to develop. However, empirical studies suggest a sensitivity of L-band SAR to the biomass density in these forests which may be employed to map and measure their growth. This paper investigates a simple empirical model representing the response of the JERS-1 SAR to the biomass density of regenerating forest in Brazil. This model was verified using independent data sources and employed to map biomass density over large regions of Amazonia from large scale JERS-1 image mosaics provided by NASDA.

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基于JERS-1 SAR估算热带再生林生物量密度的简单模型及其在亚马逊地区图像拼接中的应用

热带森林的再生对区域碳平衡很重要，因为它们代表了从大气到陆地的高碳通量地区。这些森林在物种分布和结构上都很复杂，因此很难建立雷达后向散射的一般模型。然而，经验研究表明，l波段SAR对这些森林的生物量密度具有敏感性，可用于绘制和测量其生长情况。本文研究了一个代表JERS-1 SAR对巴西再生林生物量密度响应的简单经验模型。利用独立数据源验证了该模型，并利用NASDA提供的JERS-1大比比尺图像拼接图绘制了亚马逊大区域的生物量密度。

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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来源期刊

遥感信息

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3984

期刊介绍： Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively. Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on. Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.