A fundamental theorem for eco-environmental surface modelling and its applications

作者：Tianxiang YUE,Na ZHAO,Yu LIU,Yifu WANG,Bin ZHANG,Zhengping DU,Zemeng FAN,Wenjiao SHI,Chuanfa CHEN,Mingwei ZHAO,Dunjiang SONG,Shihai WANG,Yinjun SONG,Changqing YAN,Qiquan LI,Xiaofang SUN,Lili ZHANG,Yongzhong TIAN,Wei WANG,Ying’an WANG,Shengnan MA,Hongsheng HUANG,Yimin LU,Qing WANG,Chenliang WANG,Yuzhu WANG,Ming LU,Wei ZHOU,Yi LIU,Xiaozhe YIN,Zong WANG,Zhengyi BAO,Miaomiao ZHAO,Yapeng ZHAO,Yimeng JIAO,Ufra NASEER,Bin FAN,Saibo LI,Yang YANG,John PWILSON

摘要：We propose a fundamental theorem for eco-environmental surface modelling(FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth’s surface system modeling(FTESM). The Beijing-Tianjin-Hebei(BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling(HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-meansquare error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 40%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.

发文机构：State Key L aboratory of Resources and Environment Information System College of Resources and Environment College of Land Resources and Environment College of Geomatics College of Forestry School of Land and Resources College of Geographical Information and Tourism Institutes of Science and Development Department of Information Engineering College of Resources College of Geography and Tourism Aerospace Information Research Institute School of Geographical Science National Disaster Reduction Center of China Department for Population Data Department for Industrial Standard The Academy of Digital China National Institute of Environmental Health School of Information Engineering Qian Xuesen Laboratory of Space Technology College of Architecture and Urban Planning Jiangsu Center for Collaborative Innov

关键词：HASMFTEEMSpatialupscalingSpatialdownscalingSpatialinterpolationDatafusionModel-dataassimilationModelcoupling

分类号： X171.1[环境科学与工程—环境科学]