基于MODIS和天地图遥感数据的区域作物秸秆产量估算方法

乡镇是秸秆焚烧最直接责任主体,开展镇（乡）区域农作物秸秆产生量估算方法研究,可为镇（乡）区域秸秆资源规划和收储设施选址提供有效方法。该文以泗洪县车门乡为试验,研究利用MODIS卫星遥感影像时间序列数据和天地图免费遥感影像数据,建立区域秸秆资源量及其空间分布的估算方法。根据天地图选取样本田块,通过网站获取MODIS-EVI时间序列数据,确定作物类型-EVI参数判别准则;选取图像识别样本田块,以图像参数为判别变量做判别分析,确定作物类型-图像参数判别准则。基于以上方法,完成全乡秸秆资源面积和秸秆产生量估算。水稻秸秆资源量1.77万t,可收集水稻秸秆资源量1.27万t,小麦秸秆资源量2.78万t,可...

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Published in农业工程学报 Vol. 31; no. 19; pp. 177 - 182
Main Author 王雪 常志州 张恒敢 王效华
Format Journal Article
LanguageChinese
Published 南京农业大学工学院,南京,210031%江苏省农业科学院农业资源与环境研究所,南京,210014 2015
Subjects
MODIS-EVI
估算
判别分析
地块数据
天地图
秸秆
遥感
calculation
秸秆
parcel data
discriminant analysis
判别分析
MODIS-EVI
remote sensing
遥感
straw
估算
天地图
地块数据
world map
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2015.19.024

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Summary:乡镇是秸秆焚烧最直接责任主体,开展镇（乡）区域农作物秸秆产生量估算方法研究,可为镇（乡）区域秸秆资源规划和收储设施选址提供有效方法。该文以泗洪县车门乡为试验,研究利用MODIS卫星遥感影像时间序列数据和天地图免费遥感影像数据,建立区域秸秆资源量及其空间分布的估算方法。根据天地图选取样本田块,通过网站获取MODIS-EVI时间序列数据,确定作物类型-EVI参数判别准则;选取图像识别样本田块,以图像参数为判别变量做判别分析,确定作物类型-图像参数判别准则。基于以上方法,完成全乡秸秆资源面积和秸秆产生量估算。水稻秸秆资源量1.77万t,可收集水稻秸秆资源量1.27万t,小麦秸秆资源量2.78万t,可收集小麦秸秆资源量为1.51万t;通过实际调研得知,该地水稻秸秆实际资源发生量约为1.82万t,小麦秸秆实际资源发生量约为2.75万t,估算数据和实际数据的误差仅为2.7%和1.1%,证明了该方法可以较准确的估算实际值,而且方便易用,节约成本。
Bibliography:11-2047/S
Wang Xue, Chang Zhizhou, Zhang Henggan, Wang Xiaohua （1. College of Engineering, Nanjing Agricultural University, Nanjing 210031, China; 2. Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing 21 O014, China）
straw; remote sensing; calculation; parcel data; MODIS-EVI; world map; discriminant analysis
Township is the main direct part of duty for straw burning. It is very important for an effective method to estimate the total amount of straws in small-scale region, such as Chinese townships. Research of township regional estimation methods for crop straw production would provides an effective approach for the township straw resources＇ planning and storage facilities location. This study aims to estimate straw production and their spatial distribution by using MODIS time series data and free world map image data in Chemen experimental site of Sihong County. The estimation process included three steps. Firstly, an uniformly distributed and relatively large
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2015.19.024