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利用MODIS遥感数据监测冬小麦种植面积
引用本文:许文波,张国平,范锦龙,钱永兰.利用MODIS遥感数据监测冬小麦种植面积[J].农业工程学报,2007,23(12):144-149.
作者姓名:许文波  张国平  范锦龙  钱永兰
作者单位:1. 电子科技大学地表空间信息技术研究所,成都,610054
2. 中国气象局国家气象中心,北京,100081
3. 中国气象局国家卫星气象中心,北京,100081
基金项目:国家自然科学基金面上项目
摘    要:冬小麦是中国最主要的粮食作物之一,利用遥感技术进行冬小麦种植面积监测是粮食安全的核心内容之一。美国1999年发射的TERRA卫星上携带的中分辨率成像光谱仪(MODIs)具有独特的光谱、时相和空间分辨率,为大范围的冬小麦种植面积监测提供了可靠的数据源。但中国耕地破碎,即使是250m分辨率的MODIS数据,采用传统的信息提取方法依然无法取得高的精度。因此结合多源遥感数据和GIS数据,建立了基于TERRA/MODIS数据的冬小麦种植面积遥感监测体系结构。首先利用IKONOS米级高分辨率遥感影像提取试验样区的地块图,用以指导野外采样工作;其次,在采样工作基础上,利用LANDSAT进行区域冬小麦种植面积提取;最后利用2002年TERRA/MODIS时间序列数据的混合像元线性分解模型进行河南省冬小麦种植面积的遥感监测,监测结果与国家统计数据相比,相对误差为5.25%,精度能满足农情监测的需要。研究结果为中国冬小麦种植面积遥感监测提供了一种业务化工作方法。

关 键 词:冬小麦  种植面积  遥感监测  时间序列  混合像元  线性分解
文章编号:1002-6819(2007)12-0144-06
收稿时间:2006-07-17
修稿时间:2006-10-30

Remote sensing monitoring of winter wheat areas using MODIS data
Xu Wenbo,Zhang Guoping,Fan Jinlong and Qian Yonglan.Remote sensing monitoring of winter wheat areas using MODIS data[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(12):144-149.
Authors:Xu Wenbo  Zhang Guoping  Fan Jinlong and Qian Yonglan
Institution:Institute of Geo-Spatial Information Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China;National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China;Institute of Geo-Spatial Information Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China;National Meteorological Center, China Meteorological Administration, Beijing 100081, China
Abstract:Winter wheat is one of main food crops in China. Its planting acreage monitoring is basic information for wise management of plant natural resources. The Moderate Resolution Imaging Spectroradiometer(MODIS) is one detector board on Terra's (EOS-AM1), which was lunched on December 18, 1999 by NASA. It offers a unique combination of spectral, temporal, and spatial resolution compared with previous global sensors, making it a good candidate for large-scale winter wheat planting area monitoring. However, because of subpixel heterogeneity, the application of traditional hard classification approaches to MODIS data may result in significant errors in planting area estimation. The authors developed and tested a linear unmixing approach with MODIS data that estimates subpixel fractions of crop area based on the temporal signature of reflectance throughout the growing season. This method is based on multi-source data. First, the authors use IKONOS data classification result to instruct field work. Second, high accuracy classification results can be obtained in research areas from LANDSAT data. Finally, based on time-series data of TERRA /MODIS surface reflectance daily L2G global 250 m sin grid v004, using linear decomposition of mixed pixels for monitoring winter wheat planting area in Henan Province of China. Comparing with national statistic data, the relative error of wheat planting area is 5.25% in Henan Province in 2002. The accuracy of result can meet the requirements of agricultural monitoring. This research provides an operational approach for remote sensing monitoring of winter wheat acreage in China.
Keywords:MODIS
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