地理学报

地理学报 ›› 2022, Vol. 77 ›› Issue (5): 1056-1071.doi: 10.11821/dlxb202205002

• 土地利用与土地覆被变化 • 上一篇    下一篇

2015—2020年中国土地利用变化遥感制图及时空特征分析

匡文慧1(), 张树文2, 杜国明3, 颜长珍4, 吴世新5, 李仁东6, 陆灯盛7, 潘涛8, 宁静3, 郭长庆1, 董金玮1, 包玉海9, 迟文峰10, 窦银银1, 侯亚丽1,11, 尹哲睿8, 常丽萍2, 杨久春2, 谢家丽4, 邱娟6, 张汉松3, 张宇博2,12, 杨仕琪1,11, 萨日盖9, 刘纪远1   

  1. 1.中国科学院地理科学与资源研究所 中国科学院陆地表层格局与模拟重点实验室,北京 100101
    2.中国科学院东北地理与农业生态研究所,长春 130102
    3.东北农业大学,哈尔滨 150030
    4.中国科学院西北生态环境资源研究院,兰州 730000
    5.中国科学院新疆生态与地理研究所,乌鲁木齐 830011
    6.中国科学院精密测量科学与技术创新研究院,武汉 430071
    7.福建师范大学,福州 350007
    8.曲阜师范大学,日照 276826
    9.内蒙古师范大学,呼和浩特 010028
    10.内蒙古财经大学,呼和浩特 010070
    11.中国科学院大学,北京 100049
    12.吉林大学,长春 130000
  • 收稿日期:2022-03-25 修回日期:2022-04-18 出版日期:2022-05-25 发布日期:2022-07-25
  • 作者简介:匡文慧(1978-), 男, 研究员, 博士生导师, 主要从事土地利用/覆盖变化、城市生态学研究。E-mail: kuangwh@igsnrr.ac.cn
  • 基金资助:
    中国科学院战略性先导科技专项(XDA23100201);国家重点研发计划(2018YFC1800103);第二次青藏高原综合科学考察研究(2019QZKK0608)

Remotely sensed mapping and analysis of spatio-temporal patterns of land use change across China in 2015-2020

KUANG Wenhui1(), ZHANG Shuwen2, DU Guoming3, YAN Changzhen4, WU Shixin5, LI Rendong6, LU Dengsheng7, PAN Tao8, NING Jing3, GUO Changqing1, DONG Jinwei1, BAO Yuhai9, CHI Wenfeng10, DOU Yinyin1, HOU Yali1,11, YIN Zherui8, CHANG Liping2, YANG Jiuchun2, XIE Jiali4, QIU Juan6, ZHANG Hansong3, ZHANG Yubo2,12, YANG Shiqi1,11, SA Rigai9, LIU Jiyuan1   

  1. 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Northeast Institute of Geography and Agroecology, CAS, Changchun 130102, China
    3. Northeast Agricultural University, Harbin 150030, China
    4. Northwest Institute of Eco-Environment and Resources, CAS, Lanzhou 730000, China
    5. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China
    6. Innovation Academy for Precision Measurement Science and Technology, CAS, Wuhan 430071, China
    7. Fujian Normal University, Fuzhou 350007, China
    8. Qufu Normal University, Rizhao 276826, Shandong, China
    9. Inner Mongolia Normal University, Hohhot 010028, China
    10. Inner Mongolia University of Finance and Economics, Hohhot 010070, China
    11. University of Chinese Academy of Sciences, Beijing 100049, China
    12. Jilin University, Changchun 130000, China
  • Received:2022-03-25 Revised:2022-04-18 Published:2022-05-25 Online:2022-07-25
  • Supported by:
    The Strategic Priority Research Program of Chinese Academy of Sciences(XDA23100201);National Key R&D Program of China(2018YFC1800103);The Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0608)

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摘要：

持续地开展国家尺度土地利用/覆盖变化遥感监测对于新时代国土空间规划和“美丽中国”蓝图绘制具有重要的科学价值。本文采用Landsat 8 OLI、GF-2等卫星遥感数据,融合遥感大数据云计算和专家知识辅助人机交互解译方法,研发了中国土地利用变化（2015—2020年）和2020年土地利用现状矢量数据（CLUD 2020）,建立了完整的30 a（20世纪80年代末—2020年）每隔5 a的30 m分辨率中国土地利用动态数据库。基于CLUD 2020数据,从全国和区域两个尺度揭示了2015—2020年中国土地利用变化的总体规律、区域分异和主要特征。研究表明：将遥感大数据云计算生成的30 m分辨率植被覆盖变化和地表类型变化检测信息融入到人机交互遥感解译方法,可有效地提高大范围土地利用变化遥感制图的效率和变化图斑辨识的准确性;精度评价表明,CLUD 2020一级类型制图的综合精度达95%。总体上,全国范围内国土空间开发强度与2010—2015年比较进入相对稳定状态。期间全国耕地面积仍保持减少态势,空间分异特征为耕地南减北增,东北松嫩平原及其与三江平原交界区大规模的旱地向水田转移,西北新疆南部开垦和北部退耕/撂荒并存;全国城乡建设用地持续增加,空间分异特征表现为由以往的沿海地区和超大、大城市集聚转向中西部地区的大中小城镇周边蔓延为主。全国范围的林草自然生态用地面积持续减少,但强度与2010—2015年比较有所下降;受气候变化的持续影响,青藏高原地区的河流湖泊等水域面积显著增加。以上土地利用变化格局与“十三五”期间国家高质量发展、生态文明建设宏观战略和气候变化的影响密切相关。

关键词: 土地利用, 空间格局, 耕地变化, 城市扩展, 云计算, 遥感, 中国

Abstract:

The continuous remote sensing monitoring of land use/cover change at the national scale is of great scientific significance for land spatial planning and blueprint drawing of "Beautiful China" in the new era. Landsat 8 OLI, GF-2 and other satellite remote sensing data were used to develop the data of land use change across China during 2015-2020 and China Land Use/Cover Dataset in 2020 (CLUD 2020) by integrating remote sensing big data and expert knowledge-assisted human-computer interaction interpretation methods. Long time series land use dynamic database at a 30-m resolution in China was established at 5-year interval in the end of 1980s-2020. On this basis, the general trend, regional differences and main characteristics of land use change in 2015-2020 were revealed from national and regional scales. The research indicated that integrating vegetation cover change at a 30-m resolution and land change information generated by remotely sensed big-data cloud calculation into the expert human-computer interaction interpretation can effectively improve the efficiency of mapping and the accuracy of land use change detection. The overall accuracy of CLUD 2020 first-level type mapping reaches 95%. In general, the intensity of territorial development entered a stable state compared with 2010-2015. During the period, the cropland continued to decrease. Nationwide farmland was encroached by urban development and construction, paddy fields in Northeast China continued to decrease, and cultivated land in Xinjiang was reclaimed in the south and abandoned in the north. The built-up land continued to increase, showing a spatial pattern that "the expansion of built-up land changed from the agglomeration of coastal areas and mega and large cities in 2010-2015 to the surrounding sprawl of large, medium and small towns in the central and western regions in 2015-2020". Although the area of natural ecological land for forest and grass continued to decrease nationwide, the intensity decreased compared with 2010-2015. Under the continuous impact of climate change, the area of water in the Qinghai-Tibet Plateau increased significantly. The pattern of land use change is closely related to the national macro strategy for high-quality development during the "13th Five-Year Plan" period (2016-2020) and ecological civilization construction, as well as the impact of climate change.

Key words: land use, spatial pattern, cultivated land, urban expansion, cloud computation, remote sensing, China