农业遥感研究应用进展与展望  

Progress and perspectives on agricultural remote sensing research and applications in China

作　　者：陈仲新[1] 任建强[1] 唐华俊[1] 史云[1] 冷佩[1] 刘佳[1] 王利民[1] 吴文斌[1] 姚艳敏[1] 哈斯图亚[1] 

机构地区：[1]中国农业科学院农业资源与农业区划研究所农业部农业信息技术重点实验室,北京100081

出　　处：《遥感学报》2016年第5期748-767,共20页NATIONAL REMOTE SENSING BULLETIN

基　　金：引进国际先进农业科学技术计划(948计划)(编号:2016-X38);国家自然科学基金(编号:41371396)~~

摘　　要：得益于中国自主遥感卫星、无人机遥感和物联网等技术的发展,中国农业遥感研究与应用在过去20年取得了显著进步,中国农业遥感信息获取呈现出天地网一体化的趋势;农业定量遥感在关键参数遥感反演技术方法与应用方面取得进展;作物面积、长势、产量、灾害遥感监测的理论与技术方法取得突破,农业遥感技术应用领域不断拓展。本文从农业遥感信息获取、农业定量遥感、农业灾害遥感、作物遥感识别与制图、作物长势遥感监测与产量预测、农业土地资源遥感等方面对中国农业遥感科研与应用进行了总结综述。This paper represents a literature review on the progress in the field of research and applications of agricultural remote sensing in the past 20 years in China. In remote sensing information retrieval, the space-ground-network integrated technical system has emerged be- cause of the rapid development of Earth observation satellites, the booming of unmanned aerial vehicles, as well as the extensive and intens- ive application of wireless sensor networks and the Internet of Things in China. In quantitative remote sensing, various agricultural paramet- ers, including LAI, soil moisture, and crop nutrients have been inverted from remote sensing data via statistical and/or mechanical models. In crop acreage estimation and crop mapping by remote sensing, considerable progress in algorithms and operational system development has been made in the past 20 years in China. In crop growth monitoring and yield estimation/prediction, quantitative remote sensing data products as well as various remote sensing indexes have been used with in-situ data. Various empirical models have also been investigated. Remote sensing data assimilation with crop growth models is a prevailing issue in this research field. For agricultural disaster monitoring and assessment with remote sensing, drought, flood, pests, plant disease, and so on have been studied with different types of remote sensing data and quantitative data products with various models. Some of these research outcomes and systems have been operational. In remote sensing for agricultural land resources, the research foci is shifting from land resources quantity research to spatial patterns and their dynam- ics, as well as to specific elements of agricultural lands, e.g., facility agriculture land and plastic-mulching cropland. The classification meth- ods are more diverse, and novel methods, including object-oriented methods, machine learning methods, knowledge-based algorithms, and so on, are investigated. In the past 20 years, significant progress has been made in the research

关 键 词：农业 遥感 进展 展望 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]