基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法  

Cropland Information Extraction Method of Landsat 8 OLI Images Based on Multi-seasonal Fractal Features

作　　者：孟凤 朱庆伟[1] 董士伟[2,3] 刘玉 张欣欣[2,3] 潘瑜春 MENG Feng;ZHU Qingwei;DONG Shiwei;LIU Yu;ZHANG Xinxin;PANYuchun(College of Geomatics,Xian University of Science and Technology,Xi'an 710054,China;Research Center of Information Technology,Bejing Academy of Agriculture and Forestry Sciences,Bejing 100097,China;National Engineering Research Center for Information Technology in Agriculture,Beijing 100097,China)

机构地区：[1]西安科技大学测绘科学与技术学院,西安710054 [2]北京市农林科学院信息技术研究中心,北京100097 [3]国家农业信息化工程技术研究中心,北京100097

出　　处：《农业机械学报》2024年第6期168-177,共10页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2021YFD1500203)。

摘　　要：利用遥感技术快速准确地提取耕地信息是耕地保护的关键环节。以山东省商河县为例,提出了一种基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法。首先采用毯子覆盖法计算多季相遥感影像每个像元的上分形信号和下分形信号,对比分析耕地和其他土地利用类型的分形特征,选取上分形信号的第3尺度作为特征尺度,提取商河县耕地空间分布特征;其次采用同时期的土地利用矢量数据、Esri land cover数据和统计数据进行耕地信息提取精度评价;最后分别设置多季相分形提取与单季相分形提取、现有土地利用数据产品的对比实验,并基于点位匹配度和面积匹配度进行评价。结果表明:多季相数据更能反映农作物生长的复杂性,有助于提高耕地信息的提取精度;不同土地利用类型在不同分形尺度的信号值各不相同,分形特征可以在不同尺度上清晰地刻画出不同土地利用类型的分异性;基于矢量数据和Esri land cover数据评价的多季相分形特征耕地提取点位匹配度为87.13%和89.83%,面积匹配度为99.73%和97.91%,均比单季相分形提取结果精度高;综合考虑点位匹配度、面积匹配度和空间分布特征,研发方法能有效区分耕地和其他土地利用类型,提取结果更优,且与统计数据有更高的一致性。该方法可准确提取耕地信息,为耕地的动态监测和损害评估提供技术支撑。The rapid and accurate extraction on cropland information by using remote sensing technology is a key aspect of cropland protection.Taking Shanghe County of Shandong Province as an example,a cropland information extraction method of Landsat 8 OLI images based on multi-seasonal fractal features was proposed.Firstly,the upper fractal signal and lower fractal signal of each pixel of multi-seasonal remote sensing images were calculated by using a blanket covering method,and the fractal characteristics of cropland and other land use types were compared and analyzed.The third scale of the upper fractal signal was selected as the feature scale to extract the spatial distribution of cropland in Shanghe County.Secondly,the land use vector data,Esri land cover data and statistics at the same period were used to evaluate the extraction accuracy of cropland information.Finally,comparative experiments between multi-seasonal fractal extraction with the single season fractal extraction and the existing land use data products were set up to evaluate the accuracies based on the point matching degree and area matching degree,respectively.The results showed that the multi-seasonal data can better reflect the complexity of crop growth and improve the extraction accuracy of cropland information.Different land use types had different signal values at different fractal scales,and their fractal features can clearly depict the differentiations among them at different scales.The evaluated point matching degree and area matching degree of cropland extraction results by using multi-seasonal fractal features based on the land use vector data and Esri land cover data were 87.13%and 89.83%,99.73%and 97.91%,respectively,which were higher than that of single season fractal extraction.Considering the point matching degree,area matching degree and spatial distribution characteristics,the research method could effectively distinguish cropland and other land use types,which had much better extraction results and a higher consistency with the statist

关 键 词：耕地信息提取 多季相 遥感影像 分形特征 毯子覆盖法 Landsat 8 OLI 

分 类 号：S127[农业科学—农业基础科学]