Comprehensive study on land-use change of spatial pattern and temporal process is the key component in land use/land cover changes (LUCC) study nowadays. According to the theories and methods of Geo-information Tupu (Carto-methodology in Geo-information, CMGI) for geospatial and temporal analysis and integration models of spatial pattern and temporal processes in GIS, the paper puts forward Tupu methodology of land-use change and names the basic synthetic unit of spatial-temporal information Tupu unit. Tupu unit is the synthetic unit for geospatial-temporal analysis, which is synthesized by “space·attribute·process”features and composed of relatively homogeneous geographic unit and temporal unit. Based on the spatial features of 4 stages of land-use change in 1956, 1984, 1991, and 1996, a series of Tupu on land-use change in the Yellow River Delta (YRD) are created and studied in the paper, which includes 3 temporal units of spatial-temporal Tupu, process Tupu of land-use changes during the last 40 years, and reconstructions of a series of “arisen”Tupu, “arisen”process Tupu and pattern Tupu on land-use changes in the last 40 years by remapping tables of a reclassifying system. There are 3 methods of Tupu analysis on land-use change that are used to disclose change processes of land-use spatial conversion in YRD, such as spatial query and statistics, order of Tupu units by area and land-use conversion matrixes. In order to reveal the spatial pattern of land-use change processes, we analyze spatial-temporal changes of each Tupu above in various temporal units and spatial difference of pattern Tupu in the last 40 years by dynamic Tupu units. Tupu analysis on regional land-use is a promising trial on the comprehensive research of “spatial pattern of dynamic process”and “temporal process of spatial pattern”in LUCC research. The geo-information Tupu methodology would be a powerful and efficient tool on integrated studies of spatial pattern and temporal process in geoscience.
YE Qinghua1,3,4,LIU Gaohuan2,TIAN Guoliang1,CHEN Shenliang3,HUANG Chong2,CHEN Shupeng1,2,LIU Qingshen2,CHANG Jun2 & SHI Yanan2 1.State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing Applications(IRSA),Chinese Academy of Science(CAS),Beijing 100101,China
