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基于关键期HJ卫星数据提取无棣县作物种植面积
引用本文:刘庆生,黄翀,刘高焕,柴思跃,褚琳,荆鑫.基于关键期HJ卫星数据提取无棣县作物种植面积[J].中国农学通报,2014,30(26):284-290.
作者姓名:刘庆生  黄翀  刘高焕  柴思跃  褚琳  荆鑫
作者单位:1. 中国科学院地理科学与资源研究所2. 西南林业大学
基金项目:国家科技支撑计划项目;国家自然科学基金项目;国家自然科学基金项目
摘    要:探讨利用作物关键生育期HJ卫星遥感数据,进行区域主要作物种植面积快速监测的可行性,旨在建立一种方便快捷的作物种植面积提取技术。以山东省无棣县为研究区,根据该县作物栽培技术月历为参考选择关键期HJ星遥感数据,通过EVI指数时序数据分析,采用支持向量机(SVM)方法进行了该县主要作物种植空间分布信息提取。结果表明:关键期HJ星EVI指数数据结合SVM方法,能较为准确地获取该县冬小麦、玉米和棉花的种植面积,总体的面积总量精度超过93%,空间分布精度大于75%;利用关键期影像大大减少了数据处理量,便于可视化感兴趣区的选择,仅利用SVM方法就获得了满足精度要求的作物面积提取结果,大大简化了操作流程,为其他区域利用HJ卫星数据提取作物种植面积提供了参考。

关 键 词:增强性植被指数(EVI)
收稿时间:2013/12/19 0:00:00
修稿时间:2014/1/24 0:00:00

Planting Area Extraction of A Crop Key Growth Period in Wudi County Based on HJ Satellite Data
Abstract:To explore the feasibility of quickly extracting planting area using HJ satellite CCD data acquired at the main crop key growth periods, a quick and easy crop planting area extraction method was presented. The author took Wudi County of Shandong Province as a study area, 3 HJ remote sensing images acquired at the main crop key growth periods were selected based on the main crop cultivation technique calendar. Through the EVI time-series data analysis and regions of interesting (ROI) creations, the support vector machine (SVM) was used for extracting the main crop planting area. The results showed that: the EVI data of the crop key growth periods in combination with the SVM method could more accurately estimate the winter wheat, corn and cotton planting area of Wudi County, and overall accuracy of total planting area extraction and spatial distribution location was more than 93% and 75% respectively. Through using the remote sensing data acquired at a crop key growth period, time and labor for remote sensing data processing was reduced greatly, and it was easy to visualize the choice of ROI. Only used SVM could guarantee the regional crop planting area extraction accuracy, which greatly simplified the operation process and provided a reference for other regions to use HJ satellite data to extract crop planting area.
Keywords:enhancement vegetation index (EVI)
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