Modeling potential wetland distributions in China based on geographic big data and machine learning algorithms  

作　　者：Hengxing Xiang Yanbiao Xi Dehua Mao Tianyuan Xu Ming Wang Fudong Yu Kaidong Feng Zongming Wang 

机构地区：[1]State Key Laboratory of Black Soils Conservation and Utilization,Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Changchun,People’s Republic of China [2]International Institute for Earth System Science,Nanjing University,Nanjing,People’s Republic of China [3]School of Foreign Languages,Zhongnan University of Economics and Law,Wuhan,People’s Republic of China [4]College of Information and Technology,Jilin Agricultural University,Changchun,People’s Republic of China [5]National Earth System Science Data Center,Beijing,People’s Republic of China

出　　处：《International Journal of Digital Earth》2023年第1期3706-3724,共19页国际数字地球学报（英文）

基　　金：supported by the Natural Science Foundation of Jilin Province,China[YDZJ202301ZYTS218];the National Natural Science Foundation of China[42301430,42222103,42171379,U2243230,and 42101379];the Youth Innovation Promotion Association of the Chinese Academy of Sciences[2017277 and 2021227];the Professional Association of the Alliance of International Science Organizations[ANSO-PA-2020-14].

摘　　要：Climate change and human activities have reduced the area and degraded the functions and services of wetlands in China.To protect and restore wetlands,it is urgent to predict the spatial distribution of potential wetlands.In this study,the distribution of potential wetlands in China was simulated by integrating the advantages of Google Earth Engine with geographic big data and machine learning algorithms.Based on a potential wetland database with 46,000 samples and an indicator system of 30 hydrologic,soil,vegetation,and topographic factors,a simulation model was constructed by machine learning algorithms.The accuracy of the random forest model for simulating the distribution of potential wetlands in China was good,with an area under the receiver operating characteristic curve value of 0.851.The area of potential wetlands was 332,702 km^(2),with 39.0%of potential wetlands in Northeast China.Geographic features were notable,and potential wetlands were mainly concentrated in areas with 400-600 mm precipitation,semi-hydric and hydric soils,meadow and marsh vegetation,altitude less than 700 m,and slope less than 3°.The results provide an important reference for wetland remote sensing mapping and a scientific basis for wetland management in China.

关 键 词：Potential wetland distribution machine learning algorithms geographic big data China wetland geographic features 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]