地球信息科学学报

地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (10): 1478-1488.doi: 10.12082/dqxxkx.2018.180184

• 遥感科学与应用技术 • 上一篇    下一篇

中国海岸带土地利用遥感制图及精度评价

侯西勇1,2,3(), 邸向红1,2,3, 侯婉1,2,3, 吴莉1,2,3, 刘静1,2,3, 王俊惠1,3,4, 苏红帆1,3, 路晓1,2,3, 应兰兰1,2,3, 于新洋1,3,4, 毋亭1,2,3, 朱明明1,2,3, 韩磊1,2,3, 李明杰1,2,3   

  1. 1. 中国科学院烟台海岸带研究所,烟台 264003
    2. 中国科学院大学,北京 100049
    3. 中国科学院海岸带环境过程与生态修复重点实验室,烟台 264003
    4. 鲁东大学资源与环境工程学院,烟台 264025
  • 收稿日期:2018-04-12 修回日期:2018-06-22 出版日期:2018-10-25 发布日期:2018-10-17
  • 作者简介:

    作者简介：侯西勇（1975-）,男,山东泰安人,博士,研究员,博士生导师,主要从事海岸带土地利用变化与海岸线变化遥感监测、海岸带脆弱性评价、海岸带综合管理等方面研究。E-mail: xyhou@yic.ac.cn

  • 基金资助:
    中国科学院战略性先导科技专项项目（XDA19060205、XDA11020305）;国家自然科学基金项目（31461143032、40801016）

Accuracy Evaluation of Land Use Mapping Using Remote Sensing Techniques in Coastal Zone of China

HOU Xiyong1,2,3(), DI Xianghong1,2,3, HOU Wan1,2,3, WU Li1,2,3, LIU Jing1,2,3, WANG Junhui1,3,4, SU Hongfan1,3, LU Xiao1,2,3, YING Lanlan1,2,3, YU Xinyang1,3,4, WU Ting1,2,3, ZHU Mingming1,2,3, HAN Lei1,2,3, LI Mingjie1,2,3   

  1. 1. Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Chinese Academy of Sciences, Yantai 264003, China
    4. School of Resources and Environmental Engineering, Ludong University, Yantai 264025, China
  • Received:2018-04-12 Revised:2018-06-22 Online:2018-10-25 Published:2018-10-17
  • Supported by:
    The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA19060205, XDA11020305;National Natural Science Foundation of China, No.31461143032, 40801016.

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摘要：

土地利用遥感制图结果是支撑全球气候变化和区域可持续发展等领域科学研究不可或缺的重要基础数据,而制图精度方面的评价信息则决定土地利用遥感制图结果的完整性、可靠性、可用性、可控性和可传播性。本文概述2000、2005、2010和2015年多时相中国海岸带土地利用遥感制图的数据源和技术方法,针对2010年和2015年制图结果,基于Google Earth高分影像通过目视判读获得精度评价所需的参考数据,进而建立混淆矩阵并评估制图的精度。结果表明：① 2010和2015年中国海岸带土地利用遥感制图结果的总体精度分别为95.15%和93.98%,Kappa系数分别为0.9357和0.9229,表明2个时相遥感制图结果的精度总体较好;② 中国海岸带土地利用遥感制图结果的精度水平存在较为显著的区域差异,2010年时相江苏沿海区域的精度最高,2015年时相津冀沿海区域、上海市、海南省和台湾省的精度均比较高,2个时相均以福建省沿海区域的精度最低;③ 中国海岸带土地利用遥感制图结果的精度水平存在显著的类型差异,总体上,耕地、林地、草地和滨海湿地的分类精度较高,而建设用地、内陆水体和人工咸水湿地的分类精度则相对较低,未利用土地则是错分最严重的类型;④ 耕地与林地之间、建设用地与草地之间相互误分比较显著,内陆水体容易被错分为耕地、林地和建设用地,人工咸水湿地容易被误分为耕地和建设用地,未利用土地容易被误分为耕地,这些都是未来时期数据持续更新过程中应该重视的问题。本文有望为海岸带土地利用变化遥感监测和科学研究提供必要的支持。

关键词: 土地利用, 遥感制图, 精度评价, 海岸带, 中国

Abstract:

Land use mapping using remote sensing techniques supplies essential datasets for scientific researches including global climate change, regional sustainable development and so on. The evaluation information on the accuracy of the land use mapping determines the integrity, reliability, usability, controllability and shareability of the land use maps obtained by the applications of remote sensing techniques. In this paper, the methods, processes and results of multiple temporal land use mapping for China's coastal zone using remote sensing techniques were overviewed, and the land use maps in 2010 and 2015 were selected for accuracy evaluation. The validation samples were collected based on Google Earth and the confusion matrices were established for the whole coastal zone and its sub-regions, respectively. Then, the overall accuracy and Kappa coefficient were calculated. Main findings are as follows: (1) Results of land use mapping in 2010 and 2015 using remote sensing techniques achieved high accuracy. For the entire coastal zone in China, the overall accuracy came to 95.15% and 93.98%, with the Kappa coefficients of 0.9357 and 0.9229 in 2010 and 2015, respectively. (2) The accuracy of land use mapping in China's coastal zone exhibited obvious regional differences. The best accuracy was found in the coastal area of Jiangsu province in 2010, and very high accuracy were found in the coastal area of Hebei-Tianjin, Shanghai city, Hainan province and Taiwan province in 2015, while the worst accuracy was found in the coastal area of Fujian province in both 2010 and 2015. (3) The accuracy of land use mapping in China's coastal zone exhibited obvious typological differences. The very high accuracy (both producer precision and user precision) were achieved for farmland, forest, grassland and saltwater wetlands, and the high accuracy for built-up, freshwater wetlands and human made saltwater wetland, while the worst accuracy for unused land. (4) The misclassification between cultivated land and forest land, construction land and grassland is quite significant. Inland water bodies were easily misclassified into cultivated land, forest land and construction land. Artificial salt water wetlands were easily misclassified into cultivated land and construction land, and unused land. It was easy to mistakenly classify the unused land as cultivated land. These are the issues that should be paid more attention during the continuous update of the land use maps in the future. This study provides supports for the dynamic monitoring and scientific researches on coastal land use changes.

Key words: land use, remote sensing mapping, accuracy evaluation, coastal zone, China