摘要: |
[目的]及时准确获取农作物种植结构信息,对农作物种植结构调整具有重要意义。[方法]文章以多期GF-1卫星PMS影像为主要数据源,通过分层分类方法成功提取了朱仙镇一个种植年内秋播蔬菜、冬小麦、春花生、早熟西瓜、夏玉米、夏花生等农作物,并通过叠加分析得到朱仙镇的农作物种植模式。[结果]朱仙镇有10种种植模式,以一年两熟的冬小麦-夏玉米为主要倒茬模式,占比49.7%,其他9种种植模式所占比例之和接近50%; 从整体景观的角度对朱仙镇的主要作物种植模式进行衡量,斑块丰富度PR达到9.0,香农多样性指数SHDI达到1.483 6,说明朱仙镇种植模式多样,有利于多元农业种植结构发展; 分层分类的方法能够延续最优提取结果的精度,各类作物提取精度均达到了80%以上。[结论]PMS影像的高分辨率能够清晰的表达地块边界,一定程度上呈现了非大宗作物的空间分布,GF-1卫星PMS为多尺度的农业监测提供了更多的选择。 |
关键词: GF-1 种植结构 遥感 多时相 层次分类 种植结构 |
DOI:10.7621/cjarrp.1005-9121.20170909 |
分类号:S127 |
基金项目:河南省科技攻关重点项目“基于‘互联网+’的农情遥感监测与服务研究”(172102110090); 国家自然科学基金项目“利用遥感与高光谱技术进行土壤有机碳的制图与不确定性研究”(41601213);河南省农业科学院自主创新专项基金“基于多源遥感的河南省小麦面积提取研究”(2017ZC60) |
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CROP PLANTING STRUCTURE EXTRACTION BASED ON MULTI-TEMPORAL GF-1 PMS REMOTE SENSING IMAGES |
Li Bing1,2, Liang Yanhua3, Li Dandan4, He Jia5, Guo Yan5, Wang Laigang5
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1. Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China;2. Zhengzhou Shuqing Medical College, Zhengzhou 450000, China;3.Zhengzhou Shuqing Medical College, Zhengzhou 450000, China;4.Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;5.Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
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Abstract: |
Timely and accurately obtaining crop planting structure is crucial for crop planting structure adjustment. This paper used Multi-temporal GF-1 PMS images to extract crop planting structure, interpreted winter wheat, spring peanut, early-maturing watermelon, summer corn, summer peanut by the hierarchical classification method, and analyzed crop planting patterns by overlay analysis in Zhuxian township during a vegetable planting year. The results showed that (1) There were 10 kinds of planting patterns in Zhuxian town, of which winter wheat summer maize was a major crop model, accounting for 49.7%. (2)The patch richness of PR reached 9, the Shannon diversity index SHDI reached 1.483 6, which indicated that the town planting pattern was multiple variety agricultural planting structure.(3) The hierarchical classification method can improve the extract accuracy of each crop, which can reach more than 80%. PMS high resolution image can clearly define express parcel boundaries and show the spatial distribution of the non staple crops. GF-1 PMS provided more choices on multiple scales of agricultural monitoring. |
Key words: GF-1 planting structure remote sensing multi-temporal hierarchical classification |