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 (...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.展开更多
This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014.Multiple theoretical perspec-tives on housing demand,supply,and market,are ...This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014.Multiple theoretical perspec-tives on housing demand,supply,and market,are combined to establish a housing price model to explore the impact of land prices on housing prices.The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geo-graphical detector technique.Finally,the influencing mechanism of land prices on housing prices is discussed.The main conclusions are as follows.(1)Housing prices have a pyra-mid-ranked distribution in China,where higher housing prices are linked to smaller urban populations.(2)Land prices are the primary driver of housing prices,and their impacts on housing prices vary over different administrative levels.To be specific,the effect of land prices is the strongest in the urban districts of provincial capital cities.(3)The internal influ-ence mechanisms for land prices driving housing prices are:topographic factors,urban con-struction level,the agglomeration degree of high-quality public service resources,and the tertiary industrial development level.The urban land supply plan(supply policies)is the in-trinsic driver that determines land prices in cities;through supply and demand,cost,and market mechanisms,land prices then impact housing prices.展开更多
Comprehensive study on land-use change of spatial pattern and temporal process is the key component in LUCC study nowadays. Based on the theories and methods of Geo-information Tupu (Carto-methodology in Geo-informati...Comprehensive study on land-use change of spatial pattern and temporal process is the key component in LUCC study nowadays. Based on the theories and methods of Geo-information Tupu (Carto-methodology in Geo-information, CMGI), integration of spatial pattern and temporal processes of land-use change in the Yellow River Delta (YRD) are studied in the paper, which is supported by ERDAS and ARC/INFO software. The main contents include: (1) concept models of Tupu by spatial-temporal integration on land-use change, whose Tupu unit is synthesized by "Spatial·Attribute·Process" features and composed of relatively homogeneous geographical unit and temporal unit; (2) data sources and handling process, where four stages of spatial features in 1956, 1984, 1991, and 1996 are acquired; (3) integration of series of temporal-spatial Tupu, reconstruction series of "Arising" Tupu, spatial-temporal Process Tupu and the spatial temporal Pattern Tupu on land-use change by remap tables; (4) Pattern Tupu analysis on land-use change in YRD during 1956-1996; and (5) spatial difference of the Pattern Tupu analysis by dynamic Tupu units. The various landform units and seven sub-deltas generated by the Yellow River since 1855 are different. The Tupu analysis on land-use in the paper is a promising try on the comprehensive research of "spatial pattern of dynamic process" and "temporal process of spatial pattern" in LUCC research. The Tupu methodology would be a powerful and efficient tool on integrated studies of spatial pattern and temporal process in Geo-science.展开更多
Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information syst...Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong展开更多
基金supported by the National Natural Science Foundation of China(40371093)the Special Funds for Major State Basic Research Project(G20000779,2002CB412408)+2 种基金Opening Fund projects of State Key Laboratory of Remote Sensing Science in the Institute of Remote Sensing Applications(SK040006)Opening Fund projects of State Key Laboratory of Estuarine and Coastal Research of East China Normal University,China Postdoctoral Science Foundationthe Project from'863'Marine Monitor of Hi-Tech Research and Development Program of China(2001AA633010).
文摘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.
基金National Natural Science Foundation of China,No.41601151Natural Science Foundation of Guangdong Province,No.2016A030310149Pearl River S&T Nova Program of Guangzhou
文摘This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014.Multiple theoretical perspec-tives on housing demand,supply,and market,are combined to establish a housing price model to explore the impact of land prices on housing prices.The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geo-graphical detector technique.Finally,the influencing mechanism of land prices on housing prices is discussed.The main conclusions are as follows.(1)Housing prices have a pyra-mid-ranked distribution in China,where higher housing prices are linked to smaller urban populations.(2)Land prices are the primary driver of housing prices,and their impacts on housing prices vary over different administrative levels.To be specific,the effect of land prices is the strongest in the urban districts of provincial capital cities.(3)The internal influ-ence mechanisms for land prices driving housing prices are:topographic factors,urban con-struction level,the agglomeration degree of high-quality public service resources,and the tertiary industrial development level.The urban land supply plan(supply policies)is the in-trinsic driver that determines land prices in cities;through supply and demand,cost,and market mechanisms,land prices then impact housing prices.
文摘Comprehensive study on land-use change of spatial pattern and temporal process is the key component in LUCC study nowadays. Based on the theories and methods of Geo-information Tupu (Carto-methodology in Geo-information, CMGI), integration of spatial pattern and temporal processes of land-use change in the Yellow River Delta (YRD) are studied in the paper, which is supported by ERDAS and ARC/INFO software. The main contents include: (1) concept models of Tupu by spatial-temporal integration on land-use change, whose Tupu unit is synthesized by "Spatial·Attribute·Process" features and composed of relatively homogeneous geographical unit and temporal unit; (2) data sources and handling process, where four stages of spatial features in 1956, 1984, 1991, and 1996 are acquired; (3) integration of series of temporal-spatial Tupu, reconstruction series of "Arising" Tupu, spatial-temporal Process Tupu and the spatial temporal Pattern Tupu on land-use change by remap tables; (4) Pattern Tupu analysis on land-use change in YRD during 1956-1996; and (5) spatial difference of the Pattern Tupu analysis by dynamic Tupu units. The various landform units and seven sub-deltas generated by the Yellow River since 1855 are different. The Tupu analysis on land-use in the paper is a promising try on the comprehensive research of "spatial pattern of dynamic process" and "temporal process of spatial pattern" in LUCC research. The Tupu methodology would be a powerful and efficient tool on integrated studies of spatial pattern and temporal process in Geo-science.
基金financially supported by the National Natural Science Foundation of China (41471365,41531179)
文摘Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong
