Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing

2018 ◽  
Vol 85 ◽  
pp. 190-203 ◽  
Author(s):  
Thilo Wellmann ◽  
Dagmar Haase ◽  
Sonja Knapp ◽  
Christoph Salbach ◽  
Peter Selsam ◽  
...  
2020 ◽  
Vol 12 (3) ◽  
pp. 370
Author(s):  
Shuqi He ◽  
Xingpeng Chen ◽  
Zilong Zhang ◽  
Zhaoyue Wang ◽  
Mengran Hu

As an open artificial ecosystem, the development of a city requires the continuous input and output of material and energy, which is called urban metabolism, and includes catabolic (material-flow) and anabolic (material-accumulation) processes. Previous studies have focused on the catabolic and ignored the anabolic process due to data and technology problems. The combination of remote-sensing technology and high-resolution satellite images facilitates the estimation of cumulative material amounts in urban systems. This study focused on persistent accumulation, which is the metabolic response of urban land use/urban land expansion, building stock, and road stock to land-use changes. Building stock is an extremely cost-intensive and long-lived component of cumulative metabolism. The study measured building stocks of Jinchang, China’s nickel capital by using remote-sensing images and field-research data. The development of the built environment could be analyzed by comparing the stock of buildings on maps representing different time periods. The results indicated that material anabolism in Jinchang is a distance-dependent function, where the amounts and rates of material anabolism decrease with changes in distance to the central business district (CBD) and city administration center (CAC). The cumulative metabolic rate and cumulative total metabolism were observed to be increasing, however, the growth rate has decreased.


2018 ◽  
Vol 10 (3) ◽  
pp. 446 ◽  
Author(s):  
Yuanxin Jia ◽  
Yong Ge ◽  
Feng Ling ◽  
Xian Guo ◽  
Jianghao Wang ◽  
...  

2013 ◽  
Vol 726-731 ◽  
pp. 4645-4649
Author(s):  
Jia Hua Zhang ◽  
Cui Hao ◽  
Feng Mei Yao

We developed an approach to assess urban land use changes that incorporates socio-economic and environmental factors with multinomial logistic model, remote sensing data and GIS, and to quantify the impact of macro variables on land use of urban areas for the years 1990, 2000 and 2010 in Binhai New Area, China. The Markov transition matrix was designed to integrate with multinomial logistic model to illustrate and visualize the predicted land use surface. The multinomial logistic model was evaluated by means of Likelihood ratio test and Pseudo R-Square and showed a relatively good simulation. The prediction map of 2010 showed accurate rates 78.54%, 57.25% and 70.38%, respectively.


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