The Conversion of Land Use and its Effects at Small regional extent （CLUE-S） model is a widely used method to simulate land use change. An ordinary logistic regression model was integrated into the CLUE-S model to i...The Conversion of Land Use and its Effects at Small regional extent （CLUE-S） model is a widely used method to simulate land use change. An ordinary logistic regression model was integrated into the CLUE-S model to identify explanatory variables without considering the spatial autocorrelation effect. Using image-derived maps of the Changsha- Zhuzhou-Xiangtan urban agglomeration, the CLUE-S model was integrated with the ordinary logistic regression and autologistic regression models in this paper to simulate land use change in 2000, 2005 and 2009 based on an observation map from 1995. Significant positive spatial autocorrelation was detected in residuals of ordinary logistic models. Some variables that were much more significant than they should be were selected. Autologistic regression models, which used autocovariate incorporation, were better able to identify driving factors. The Receiver Operating Characteristic Curve （ROC） values of autologistic regression models were larger than 0.8 and the pseudo R^2 values were improved, compared with results of logistic regression model. By overlapping the observation maps, the Kappa values of the ordinary logistic regression model （OL）-CLUE-S and autologistic regression model （AL）-CLUE-S models were larger than 0.75. The results showed that the simulation results were indeed accurate. The Kappa fuzzy （Kfuzzy） values of the AL-CLUE-S models （0.780, 0.773, 0.606） were larger than the values of the OL-CLUE-S models （0.759, 0.760, 0.599） during the three periods. The AL-CLUE-S models performed better than the OL-CLUE-S models in the simulation of land use change. The results showed that it is reasonable to integrate autocovariates into CLUE-S models. However, the Kfuzzy values decreased with prolonged duration of simulation and the maximum range of time was not discussed in this paper.展开更多
Urban agglomeration is caused by the continuous acceleration of the urbanization process in China. Studying the expansion of construction land can not only know the changes and development of urban agglomeration in ti...Urban agglomeration is caused by the continuous acceleration of the urbanization process in China. Studying the expansion of construction land can not only know the changes and development of urban agglomeration in time, but also obtain the great significance of the future management. In this study, taking Changsha-Zhuzhou-Xiangtan(Chang-Zhu-Tan) urban agglomeration in Hunan province as a study area, Landsat images from 1995 to 2014 and Autologistic-CLUE-S model simulation data were used. Moreover, several factors including gravity center, direction, distance and landscape index were considered in the analysis of the expansion. The results revealed that the construction area increased by 132.18%, from 372.28 km^2 in 1995 to 864.37 km^2 in 2014. And it might even reach 1327.23 km^2 in 2023. Before 2014, three cities had their own respective and discrete development directions. However, because of the integration policy implementation in 2008, the Chang-Zhu-Tan began to gather, the gravity center moved southward after 2014, and the distance between cities decreased, which was in line with the development plan of urban expansion. The research methods and results were relatively reliable, and these results could provide some reference for the future land use planning and spatial allocation in the urbanization process of Chang-Zhu-Tan urban agglomeration.展开更多
To understand the pollution characteristics of atmospheric particles and heavy metals in winter in Chang-Zhu-Tan city clusters, China, total suspended particulate （TSP） and PMI0 samples were collected in cities of C...To understand the pollution characteristics of atmospheric particles and heavy metals in winter in Chang-Zhu-Tan city clusters, China, total suspended particulate （TSP） and PMI0 samples were collected in cities of Changsha, Zhuzhou and Xiangtan from December 2011 to January 2012, and heavy metals of Cd, Pb, Cr, and As were analyzed. It shows that the average TSP concentration in Changsha, Zhuzhou and Xiangtan were （183 ± 73）, （201± 84） and （190 ±66） μg/m3 respectively, and the average PM10 were （171 ± 82）, （178 ± 65） and （179 ± 55） μg/m3 respectively. The lowest TSP and PM10 concentrations occurred at the background Shaping site of Changsha. The average ratio of p（PM10）/p（TSP） was 91.9%, ranging from 81.3% to 98.9%. Concerning heavy metals, in TSP samples, the concentration of Cr, As, Cd and Pb were 28.8-56.5, 18.1-76.3, 3.9-26.1 and 148.0-460.9 ng/m3, respectively, while in PMI0 samples, were 16.4--42.1, 15.5-67.9, 3.3-22.2 and 127.9-389.3 ng/m3, respectively. The enrichment factor of Cd was the highest, followed by Pb and As, while that of Cr was the lowest.展开更多
基金National Natural Science Foundation of China,No.41171318National Key Technology Support Program,No.2012BAH32B03+1 种基金No.2012BAH33B05Special Fund for Forest Scientific Research in the Public Welfare,No.201204201
文摘The Conversion of Land Use and its Effects at Small regional extent （CLUE-S） model is a widely used method to simulate land use change. An ordinary logistic regression model was integrated into the CLUE-S model to identify explanatory variables without considering the spatial autocorrelation effect. Using image-derived maps of the Changsha- Zhuzhou-Xiangtan urban agglomeration, the CLUE-S model was integrated with the ordinary logistic regression and autologistic regression models in this paper to simulate land use change in 2000, 2005 and 2009 based on an observation map from 1995. Significant positive spatial autocorrelation was detected in residuals of ordinary logistic models. Some variables that were much more significant than they should be were selected. Autologistic regression models, which used autocovariate incorporation, were better able to identify driving factors. The Receiver Operating Characteristic Curve （ROC） values of autologistic regression models were larger than 0.8 and the pseudo R^2 values were improved, compared with results of logistic regression model. By overlapping the observation maps, the Kappa values of the ordinary logistic regression model （OL）-CLUE-S and autologistic regression model （AL）-CLUE-S models were larger than 0.75. The results showed that the simulation results were indeed accurate. The Kappa fuzzy （Kfuzzy） values of the AL-CLUE-S models （0.780, 0.773, 0.606） were larger than the values of the OL-CLUE-S models （0.759, 0.760, 0.599） during the three periods. The AL-CLUE-S models performed better than the OL-CLUE-S models in the simulation of land use change. The results showed that it is reasonable to integrate autocovariates into CLUE-S models. However, the Kfuzzy values decreased with prolonged duration of simulation and the maximum range of time was not discussed in this paper.
基金National Natural Science Foundation of China,No.41571077National Key Research and Development Program of China,No.2016YFC0503002
文摘Urban agglomeration is caused by the continuous acceleration of the urbanization process in China. Studying the expansion of construction land can not only know the changes and development of urban agglomeration in time, but also obtain the great significance of the future management. In this study, taking Changsha-Zhuzhou-Xiangtan(Chang-Zhu-Tan) urban agglomeration in Hunan province as a study area, Landsat images from 1995 to 2014 and Autologistic-CLUE-S model simulation data were used. Moreover, several factors including gravity center, direction, distance and landscape index were considered in the analysis of the expansion. The results revealed that the construction area increased by 132.18%, from 372.28 km^2 in 1995 to 864.37 km^2 in 2014. And it might even reach 1327.23 km^2 in 2023. Before 2014, three cities had their own respective and discrete development directions. However, because of the integration policy implementation in 2008, the Chang-Zhu-Tan began to gather, the gravity center moved southward after 2014, and the distance between cities decreased, which was in line with the development plan of urban expansion. The research methods and results were relatively reliable, and these results could provide some reference for the future land use planning and spatial allocation in the urbanization process of Chang-Zhu-Tan urban agglomeration.
基金supported by the National Department Public Benefit Research Foundation(No.201109005)the National Natural Science Foundation of China(No.41205093)
文摘To understand the pollution characteristics of atmospheric particles and heavy metals in winter in Chang-Zhu-Tan city clusters, China, total suspended particulate （TSP） and PMI0 samples were collected in cities of Changsha, Zhuzhou and Xiangtan from December 2011 to January 2012, and heavy metals of Cd, Pb, Cr, and As were analyzed. It shows that the average TSP concentration in Changsha, Zhuzhou and Xiangtan were （183 ± 73）, （201± 84） and （190 ±66） μg/m3 respectively, and the average PM10 were （171 ± 82）, （178 ± 65） and （179 ± 55） μg/m3 respectively. The lowest TSP and PM10 concentrations occurred at the background Shaping site of Changsha. The average ratio of p（PM10）/p（TSP） was 91.9%, ranging from 81.3% to 98.9%. Concerning heavy metals, in TSP samples, the concentration of Cr, As, Cd and Pb were 28.8-56.5, 18.1-76.3, 3.9-26.1 and 148.0-460.9 ng/m3, respectively, while in PMI0 samples, were 16.4--42.1, 15.5-67.9, 3.3-22.2 and 127.9-389.3 ng/m3, respectively. The enrichment factor of Cd was the highest, followed by Pb and As, while that of Cr was the lowest.
