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全球尺度多源土地覆被数据融合与评价研究
Data fusion and accuracy evaluation of multi-source global land cover datasets

查看参考文献33篇

白燕 1,2   冯敏 3  
文摘 精确的全球及区域尺度土地覆被遥感分类数据是全球变化、陆地表层过程模拟、生态文明建设及区域可持续发展等研究的重要基础数据。本文以5套全球土地覆被数据集GLCC、 UMD、GLC2000、MODIS LC、GlobCover为研究对象,结合MODIS VCF、MODIS Cropland Probability以及AVHRR CFTC数据集,设计一种基于模糊逻辑思想的证据融合方法实现上述多源土地覆被信息的决策融合,生成一套依据植物功能型分类的全球1 km土地覆被融合数据SYNLCover。结果显示,与5套源土地覆被数据集相比:①在总体一致性精度上,SYNLCover的8个生物形态类型和12个目标类型的平均总体一致性精度最高,分别约为65.6%和59.4%,其次依次是MODIS LC、GLC2000、GLCC和GlobCover,UMD的最低,分别约为48.9%和42.6%,而且SYNLCover与5套源土地覆被数据集两两相比的总体一致性都是最好的;②在类型一致性精度上,除灌丛类型外,SYNLCover中包括森林、草地、耕地、湿地、水体、城镇建筑和其他7种生物形态类型,以及森林类型的5种叶属性的平均一致性精度也是最高的,如其他类型的平均一致性精度可达67.73%;③除灌丛和湿地类型外,SYNLCover的其余6种生物形态类型的平均一致性精度均比其在5套源数据中相应的一致性精度的最大值提高了10%~15%左右;森林类型的5种叶属性的一致性精度也提高了约10%。SYNLCover分类精度的提高反映了本研究设计的多源数据融合方法的可行性和有效性。
其他语种文摘 Accurate global and regional land cover classification datasets based on remote sensing are of fundamental importance in research on global changes, land surface process modeling, ecological progress, and regional sustainable development and so on. The overall objective of this study is to present a decision-fuse method that integrates existing multi-source land cover information into a 'best-estimate' dataset using fuzzy logic. Combined with another three global datasets, i.e., MODIS VCF (Vegetation Continuous Field), MODIS Cropland Probability, and AVHRR CFTC (Continuous Fields of Tree Cover), this method is applied to five global land cover datasets (GLCC, UMD, GLC2000, MODIS LC, and GlobCover) to generate a new 1-km global land cover product SYNLCover with desired legends, which are properly defined in terms of plant functional types. Pixel-based comparisons among these six global land cover datasets are performed, and results reveal that compared with five original global land cover datasets: (1) In terms of map- specific consistency, overall consistencies of both eight life forms and twelve objective legends of SYNLCover are the highest, accounting for about 65.6% and 59.4%, respectively; followed by the accuracy of MODIS LC, GLC2000, GLCC, and GlobCover in a descending order, and the lowest map-specific consistencies of life forms and objective legends are separately 48.9% and 42.6% in UMD. Besides, among all dataset pairs, SYNLCover agrees best with each original land cover dataset regarding the occurrences of life forms and leaf attributes. (2) In terms of class- specific consistency, it is suggested that SYNLCover gets the highest average class consistencies for all the five leaf attributes, as well as major life forms except Shrubland, among which the consistency for Others in SYNLCover is up to 67.73%. (3) For Trees, Grassland, Cropland, Water, Urban and built- up and Others, SYNLCover shows particular improved average class- consistencies by about 10% to 15% over the maximum consistency of original datasets, and the consistencies of five leaf attributes in SYNLCover also increases by about 10% . This study indicates a successful integration of multi- source land cover information into a new refined dataset with improved characteristics scientifically.
来源 地理学报 ,2018,73(11):2223-2235 【核心库】
DOI 10.11821/dlxb201811013
关键词 土地覆被 ; 模糊逻辑 ; 相关性分值 ; 数据融合 ; 一致性精度评价 ; 多源信息
地址

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. 江苏省地理信息资源开发与利用协同创新中心, 江苏省地理信息资源开发与利用协同创新中心, 南京, 210023  

3. 马里兰大学地理科学系, 美国, 马里兰, 20742

语种 中文
文献类型 研究性论文
ISSN 0375-5444
学科 测绘学
基金 科技基础资源调查专项课题 ;  资源与环境信息系统国家重点实验室青年人才培养基金 ;  国家科技基础条件平台项目—国家地球系统科学数据共享服务平台
文献收藏号 CSCD:6364813

参考文献 共 33 共2页

1.  陈军. 全球地表覆盖高分辨率遥感制图. 地理信息世界,2011(2):12-14 被引 49 次    
2.  Cramer W. Comparing global models of terrestrial net primary productivity (NPP): Overview and key results. Global Change Biology,1999,5(Suppl.1):1-15 被引 226 次    
3.  Foley J A. Global consequences of land use. Science,2005,309(5734):570-574 被引 684 次    
4.  Alcamo J. Future long-term changes in global water resources driven by socio-economic and climatic changes. Hydrological Sciences Journal,2007,52(2):247-275 被引 12 次    
5.  Liu J. Estimating California ecosystem carbon change using process model and land cover disturbance data: 1951-2000. Ecological Modelling,2011,222(14):2333-2341 被引 2 次    
6.  Bounoua L. Effects of land cover conversion on surface climate. Climatic Change,2002,52(1/2):29-64 被引 23 次    
7.  Douglas I. Hydrological investigations of forest disturbance and land cover impacts in South-East Asia: A review. Philosophical Transactions of the Royal Society B-Biological Sciences,1999,354(1391):1725-1738 被引 5 次    
8.  Chapin F S. Consequences of changing biodiversity. Nature,2000,405(6783):234-242 被引 127 次    
9.  Lambin E F. Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources,2003,28:205-241 被引 70 次    
10.  Loveland T. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR Data. International Journal of Remote Sensing,2000,21(6/7):1303-1330 被引 180 次    
11.  Friedl M A. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment,2010,114(1):168-182 被引 163 次    
12.  Hansen M C. Global land cover classification at 1 km spatial resolution using a classification tree approach. International Journal of Remote Sensing,2000,21(6/7):1331-1364 被引 170 次    
13.  Bartholome E. GLC2000: A new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing,2005,26(9):1959-1977 被引 132 次    
14.  Bontemps S. Globcover 2009: Products Description and Validation Reports,2011 被引 1 次    
15.  Tateishi R. Production of global land cover data-GLCNMO2008. Journal of Geography and Geology,2014,6(3):99-122 被引 7 次    
16.  Latham J. Global Land Cover SHARE (GLC-SHARE) database Beta-Release Version 1.0,2014 被引 2 次    
17.  ESA. CCI-LC Product User Guide v2.4,2014 被引 3 次    
18.  Gong P. Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. International Journal of Remote Sensing,2013,34(7):2607-2654 被引 165 次    
19.  Chen J. Global land cover mapping at 30 m resolution: A pok-based operational approach. ISPRS Journal of Photogrammetry and Remote Sensing,2015,103:7-27 被引 200 次    
20.  Congalton G R. Global land cover mapping: A review and uncertainty analysis. Remote Sensing,2014,6(12):12070-12093 被引 1 次    
引证文献 8 篇

1 范泽孟 新亚欧大陆桥经济走廊土地覆被变化及驱动力分析 生态学报,2019,39(14):5015-5027
被引 4 次

2 陈逸聪 2015年长三角地区30 m土地覆被融合数据 中国科学数据,2022,7(1):1-19-19-19
被引 0 次

显示所有8篇文献

论文科学数据集

1. 非洲萨赫勒地区30m土地利用/覆盖数据集（1990-2020）

2. 中巴经济走廊及天山山脉土地覆盖（2020）

3. 2000年中国土地覆盖图

数据来源：
国家青藏高原科学数据中心

1. 恰巴哈尔港(伊朗)至奥尔马拉港(巴基斯坦)沿岸40 km内土地覆被数据集(1990，2000，2010，2017)

2. 吉大港(孟加拉)至皎漂港(缅甸)沿岸40 km内土地覆被数据集(1990，2000，2010，2017)

3. 首都生态圈土地覆盖数据集（2010）

数据来源：
国家对地观测科学数据中心
PlumX Metrics
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