基于Landsat 8 OLI遙感影像的沈陽(yáng)市水稻種植面積提取方法
[Abstract]:In order to study the feasibility of remote sensing data and extraction methods in estimating rice planting area, the rice growth in Shenyang from June to September 2015 was monitored by using Landsat 8 OLI image as data source and ENVI5.1 software platform. Finally, the planting area was extracted. According to the field survey samples, by analyzing the spectral characteristic curve of the local objects, normalized vegetation index mean value characteristics and the imaging characteristics of remote sensing images, the pseudo-color synthesis of the images was determined by using band 6, band 5 and band 2. For the synthesized images, three groups of comparative experiments of the number of different sample points were designed in different periods. The number of samples was 100150200, and the sampling points of rice were determined by using mixed pixel method. The separability of each sample is tested by transform dispersion and J-M distance. Support vector machine (SVM) is used to classify each sample. Finally, Majority/Minority analysis method is used to classify and post-process the extracted results. Different models of rice area extraction were established. The results showed that the extraction results of 200 samples were all accurate in June, July and September. The extraction areas were 1 032.044 8 / 1 201.125 9 and 1 180.685 5 km2, respectively. The results were evaluated with reference to Shenyang Statistical Yearbook 2015. The accuracy is 94.7389. 75% and 92. 62% respectively. The experiment shows that the Landsat 8OLI remote sensing data can accurately extract the planting area of rice in Shenyang and lay a foundation for the comprehensive monitoring of rice planting with multi-source data.
【作者單位】: 沈陽(yáng)農(nóng)業(yè)大學(xué)信息與電氣工程學(xué)院;遼寧省農(nóng)業(yè)信息化工程技術(shù)中心;
【基金】:國(guó)家重點(diǎn)研發(fā)計(jì)劃(2016YFD020060307)
【分類號(hào)】:S127;S511
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