This paper discusses the urban land grading system based on the self_developed GIS software.The system establishes the system template,the relevant data structure and the empirical formulas of the affecting factor and...This paper discusses the urban land grading system based on the self_developed GIS software.The system establishes the system template,the relevant data structure and the empirical formulas of the affecting factor and economic data of land use.Besides,the system can calculate the service radius,sum and land grade automatically.Furthermore,it can do statistics and query on various land information and show the result of land grading with spatial and attribute data.This paper illustrates the result by giving an example of the commercial land grading of the urban area of Wuhan City by the urban land grading system.展开更多
At present, paid urban landuse system is one of the most important economic reform in China. In the other words, landuse right can be transferred and land users must pay the rent to the state according to the quality ...At present, paid urban landuse system is one of the most important economic reform in China. In the other words, landuse right can be transferred and land users must pay the rent to the state according to the quality of land. It is necessary toapply the theory of rent and location to the economic appraisal of urban land. China is vast in territory. Is's geographical condition and economic development vary from place to place, so does the urban land value. In order to reveal the difference of land value between different cities, the following method is used. (1) Analysing the factors and elements that affect the quality of urban land. Six factors including 17 elements were selected in this paper: macrolocation of a city, benefit of urban aggregation, infrastructure investment, output value of urban land, potential of urban land, and investment intensity. (2) Deciding the weight andvalue of each factor. (3) Appraising each element separately. (4) Accountingthe value of all factors and getting the total appraisal score of each city. (5) Grouping the 430 Chinese cities into sevencategories according to the appraisal values.The result shows that all the cities in the category with the highest land output values are in the coast belt, whereas most cities in the inland and outlying areas are belong to the category with low rank. For example, 87% of the cities in the outlying regions are belong to the lowest rank. Although there are some relationship between the size of cities and urban land rank, generally speaking, the larger the city, the higher the urban land rank. In fact, the locational condition is the most important factor which influences the rank of urban land.展开更多
In order to make assessment on urbanization coordination, we developed a comprehensive model by integrating entropy weight method(EWM), coupling degree model(CDM), coupling coordination degree model(CCDM), multi-index...In order to make assessment on urbanization coordination, we developed a comprehensive model by integrating entropy weight method(EWM), coupling degree model(CDM), coupling coordination degree model(CCDM), multi-index grading method(MIGM) and Remote Sensing & Geographic Information System(RS & GIS) technology. Then we applied this integrated model to a case study in Jiangxi Province, China. Our study finds that: 1) EWM, CDM and CCDM can evaluate the temporal dynamic of urbanization. Urbanization process of Jiangxi Province can be divided into three periods, the stable development period(1990–2001), the accelerated development period(2002–2009) and the rapid development period(2010–2015). Coordinated development of urbanization in Jiangxi Province can be divided into two phases, an increasingly coordinated phase(1990–2003) and an increasingly incongruous phase(2003–2015). The state transition was due to low development rate of population urbanization. 2) RS & GIS technology is an effective tool for detecting urban growth. Urban construction land area of Jiangxi Province increased from 615.8 km^2 in 1990 to 2896.8 km^2 in2015, and the per capita urban construction land area(PCUCLA) reached 122.9 m^2, with the maximum value of 343 m^2 in Gongqingcheng City. 3) MIGM and RS & GIS technology can analyze spatial difference of urbanization. There is a significant spatial difference in socioeconomic development at county scale, with the maximum value six times the minimum value for both PCUCLA and per capita GDP in 2015. Population urbanization lag and excessive land use are the main reasons for uncoordinated urbanization. There were 15 counties with a lag in demographic urbanization and 33 counties where PCUCLA exceeded the national standard in 2015, among which 20 exceeded the national standard of PCUCLA by 50%(≥165 m^2). Since there are significant spatio-temporal differences in urbanization, it is necessary to carry out a comprehensive assessment to facilitate differential urbanization strategy making.展开更多
文摘This paper discusses the urban land grading system based on the self_developed GIS software.The system establishes the system template,the relevant data structure and the empirical formulas of the affecting factor and economic data of land use.Besides,the system can calculate the service radius,sum and land grade automatically.Furthermore,it can do statistics and query on various land information and show the result of land grading with spatial and attribute data.This paper illustrates the result by giving an example of the commercial land grading of the urban area of Wuhan City by the urban land grading system.
文摘At present, paid urban landuse system is one of the most important economic reform in China. In the other words, landuse right can be transferred and land users must pay the rent to the state according to the quality of land. It is necessary toapply the theory of rent and location to the economic appraisal of urban land. China is vast in territory. Is's geographical condition and economic development vary from place to place, so does the urban land value. In order to reveal the difference of land value between different cities, the following method is used. (1) Analysing the factors and elements that affect the quality of urban land. Six factors including 17 elements were selected in this paper: macrolocation of a city, benefit of urban aggregation, infrastructure investment, output value of urban land, potential of urban land, and investment intensity. (2) Deciding the weight andvalue of each factor. (3) Appraising each element separately. (4) Accountingthe value of all factors and getting the total appraisal score of each city. (5) Grouping the 430 Chinese cities into sevencategories according to the appraisal values.The result shows that all the cities in the category with the highest land output values are in the coast belt, whereas most cities in the inland and outlying areas are belong to the category with low rank. For example, 87% of the cities in the outlying regions are belong to the lowest rank. Although there are some relationship between the size of cities and urban land rank, generally speaking, the larger the city, the higher the urban land rank. In fact, the locational condition is the most important factor which influences the rank of urban land.
基金Under the auspices of open foundation of The Key Laboratory of Poyang Lake Environment and Resource Utilization(Nanchang University)Ministry of Education,China(No.PYH2015-02)
文摘In order to make assessment on urbanization coordination, we developed a comprehensive model by integrating entropy weight method(EWM), coupling degree model(CDM), coupling coordination degree model(CCDM), multi-index grading method(MIGM) and Remote Sensing & Geographic Information System(RS & GIS) technology. Then we applied this integrated model to a case study in Jiangxi Province, China. Our study finds that: 1) EWM, CDM and CCDM can evaluate the temporal dynamic of urbanization. Urbanization process of Jiangxi Province can be divided into three periods, the stable development period(1990–2001), the accelerated development period(2002–2009) and the rapid development period(2010–2015). Coordinated development of urbanization in Jiangxi Province can be divided into two phases, an increasingly coordinated phase(1990–2003) and an increasingly incongruous phase(2003–2015). The state transition was due to low development rate of population urbanization. 2) RS & GIS technology is an effective tool for detecting urban growth. Urban construction land area of Jiangxi Province increased from 615.8 km^2 in 1990 to 2896.8 km^2 in2015, and the per capita urban construction land area(PCUCLA) reached 122.9 m^2, with the maximum value of 343 m^2 in Gongqingcheng City. 3) MIGM and RS & GIS technology can analyze spatial difference of urbanization. There is a significant spatial difference in socioeconomic development at county scale, with the maximum value six times the minimum value for both PCUCLA and per capita GDP in 2015. Population urbanization lag and excessive land use are the main reasons for uncoordinated urbanization. There were 15 counties with a lag in demographic urbanization and 33 counties where PCUCLA exceeded the national standard in 2015, among which 20 exceeded the national standard of PCUCLA by 50%(≥165 m^2). Since there are significant spatio-temporal differences in urbanization, it is necessary to carry out a comprehensive assessment to facilitate differential urbanization strategy making.
