地块破碎度对软硬变化检测法识别冬小麦分布精度的影响

软硬变化检测作物识别（soft and hard change detection,SHCD）是一种新型的作物识别方法。该研究针对不同耕地地块破碎程度的农业景观地区进行SHCD冬小麦识别,分析地块破碎程度对SHCD冬小麦识别精度的影响。试验结果表明,在种植地块破碎试验区,SHCD的RMSE对分辨率不敏感,均小于0.15,bias也比较小,R2随着检测窗口的增加,相关性逐步升高,达到98%以上。在种植地块规整试验地区,亦能够得到相同试验结论。SHCD方法综合了硬变化（hard change detection,HCD）和软变化（soft change detection,SCD）各自的优势,能够...

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Bibliographic Details
Published in农业工程学报 Vol. 32; no. 10; pp. 164 - 171
Main Author 朱爽 张锦水
Format Journal Article
LanguageChinese
Published 北京工业职业技术学院,北京100042 2016
北京师范大学资源学院,北京100875
北京师范大学资源学院,北京100875%北京师范大学地表过程与资源生态国家重点实验室,北京100875
Subjects
作物
冬小麦
支撑向量机
软硬变化检测
遥感
support vector machines
软硬变化检测
作物
remote sensing
支撑向量机
遥感
crops
winter wheat
冬小麦
soft and hard change detection method(SHCD)
Online AccessGet full text
ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2016.10.023

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Summary:软硬变化检测作物识别（soft and hard change detection,SHCD）是一种新型的作物识别方法。该研究针对不同耕地地块破碎程度的农业景观地区进行SHCD冬小麦识别,分析地块破碎程度对SHCD冬小麦识别精度的影响。试验结果表明,在种植地块破碎试验区,SHCD的RMSE对分辨率不敏感,均小于0.15,bias也比较小,R2随着检测窗口的增加,相关性逐步升高,达到98%以上。在种植地块规整试验地区,亦能够得到相同试验结论。SHCD方法综合了硬变化（hard change detection,HCD）和软变化（soft change detection,SCD）各自的优势,能够达到稳定且较高的识别精度,不受影像分辨率的影响;有效地解决了SCD在硬变化区（纯净像元）受到光谱不稳定性和HCD在软变化区（混合像元）识别为＂0-1＂排他性结果的不足,保证了冬小麦的识别精度,为大范围进行冬小麦识别以及其他作物的变化检测识别提供前期的试验基础。
Bibliography:Zhu Shuang, Zhang Jinshui （1. Beijing Polytechnic College, Beijing 100042, China; 2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China; 3. College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China）
11-2047/S
Soft and hard change detection method（SHCD） is a newly proposed approach and previous studies have showed that this method is useful for accurately identifying crop. In this paper, SHCD was used for classifying winter wheat in both simple, homogeneous, low fragmented regions and complicated, heterogeneous, discontinuous regions, and the impact of agricultural landscape pattern and image resolution on the accuracy of winter wheat identification was quantified.Experimental process included simulation image creation, winter wheat mapping by SHCD and result analysis. Simulated images were obtained by the crop change detection model, the winter wheat phenology and the effects of parcel fragmentation. Winter w
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2016.10.023