地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (10): 1215-1223.doi: 10.3724/SP.J.1047.2015.01215

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亚像元制图适应性分析与评价——以天津市津南区和北京市海淀区土地覆被制图为例

江昱1,2(), 葛咏1,3*(), 陈跃红1,2, 宋海荣4, 胡建龙5   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京100101
    2. 中国科学院大学,北京 100049
    3. 江苏省地理信息资源开发与利用协同创新中心, 南京 210023
    4. 中国土地勘测规划院,北京 100035
    5. 山西大学计算机与信息技术学院,太原 030006
  • 收稿日期:2014-12-08 修回日期:2015-02-27 出版日期:2015-10-10 发布日期:2015-10-10
  • 作者简介:

    作者简介:江昱(1990-),女,安徽合肥人,硕士生,主要从事遥感亚像元制图应用研究。E-mail: jiangy@lreis.ac.cn

  • 基金资助:
    国家自然科学基金项目(41471296);国家科技支撑计划课题(2012BAH33B01)

Reliability Analysis and Assessment of Sub-Pixel Mapping: A Case Study with Landsat-5Image and HJ-1A Image Based on VBSPM

JIANG Yu1,2(), GE Yong1,3,*(), CHEN Yuehong1,2, SONG Hairong4, HU Jianlong5   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    4. China Land Surveying and Planning Institute, Beijing 100035, China
    5. School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
  • Received:2014-12-08 Revised:2015-02-27 Online:2015-10-10 Published:2015-10-10
  • Contact: GE Yong E-mail:jiangy@lreis.ac.cn;gey@lreis.ac.cn
  • About author:

    *The author: CHEN Nan, E-mail:fjcn99@163.com

摘要:

亚像元制图作为一种降尺度分类方法,可利用低分辨率影像获取高分辨率分类图。本文旨在探讨亚像元制图的降尺度分类结果与高分辨率影像分类精度和分类特征上的一致性。实验以天津市津南区和北京市海淀区为研究区,分别对中空间分辨率影像(TM或HJ)进行亚像元制图和对高空间分辨率影像(ALOS或ZY)进行硬分类得到相同空间分辨率的分类结果,从绝对精度、相对精度、空间结构和空间格局上,对2幅分类结果进行分析和评价。实验结果显示:(1)分类精度上,TM和HJ影像的亚像元制图结果,以地面验证样本为参考的绝对总体精度分别为84%和82%,以高分辨率影像(ALOS和ZY影像)硬分类结果,为参考的相对总体精度分别为82%和77%;(2)分类特征上,中空间分辨率影像亚像元制图结果的空间相关性较强、斑块数量较少、聚集度较高,但与高分辨率影像分类结果的总体结构相似,各类别的面积比例基本一致。因此,亚像元制图结果在分类精度和分类特征上与高空间分辨率影像分类结果具有较强的一致性,在缺少高分辨率土地覆被制图时,可将亚像元制图获取的降尺度分类图作为替代数据。

关键词: 遥感分类, 亚像元制图, 一致性, Landsat, HJ

Abstract:

Some high-resolution land cover maps are not free or available for direct use due to its economic value, the impact of weather or its confidentiality. As a downscaling classification method, sub-pixel mapping (SPM) can produce classification data with spatial resolutions finer than the original input data. We aim to explore the consistency between SPM results and classification data extracted from high-resolution remote sensing images on their accuracy and spatial characteristics. Two experiments were performed: one is in Jinnan District, Tianjin City with Landsat-5 TM image, and the other is in Haidian District, Beijing City with HJ image. Results show that the overall absolute accuracies of SPM results produced by TM and HJ images are 84% and 82% respectively. The overall relative accuracies of Landsat-5 and HJ SPM results were 82% and 77% by taking high-resolution classifications as reference. Furthermore, the overall structures and proportions based on the results using the proposed method are similar with high-resolution classifications. Therefore, with the absence of high-resolution land cover map, results generated by SPM could provide an alternative for land cover data source.

Key words: remote sensing classification, sub-pixel mapping, adaptability, ALOS, Landsat TM