Urban green spaces have been arisen growing concern responded to the social and environmental costs of urban sprawl. A wide range of planning and policies has been and/or will be designed to protect urban green spaces...Urban green spaces have been arisen growing concern responded to the social and environmental costs of urban sprawl. A wide range of planning and policies has been and/or will be designed to protect urban green spaces and optimize their spatial pattern. A better design or planning of urban green space can make a major contribution to quality of environment and urban life, and furthermore can decide whether we can have a sustainable development in the urban area. Information about the status quo of urban green spaces can help planners design more effectively. However, how to quantify and capture such information will be the essential question we face. In this paper, to quantify the urban green space, a new method comprising gradient analysis, landscape metrics and GIS was developed through a case of Jinan City. The results demonstrate: 1) the gradient analysis is a valid and reliable instrument to quantify the urban green space spatial pattern precisely; 2) using moving window, explicit landscape metrics were spatially realized. Compared with quantifying metrics in the entire landscape, it would be better to link pattern with process and establish an important basis for analyzing the ecological and socioeconomic functions of green spaces.展开更多
Four urban greenbelt types including roadside greenbelt, resident-area greenbelt, landscape forest, and forest park, were simultaneously investigated in Shenzhen, China, in such measures as air temperature, air humidi...Four urban greenbelt types including roadside greenbelt, resident-area greenbelt, landscape forest, and forest park, were simultaneously investigated in Shenzhen, China, in such measures as air temperature, air humidity, wind speed, air anion ratio, and inhalabal particle concentration, which were strongly related with pleasing feeling of human body. The results show that the average air temperature in both forest park and landscape forest is much closer to the pleasing feeling of human body temperature than that of the rest two greenbelts, where it is 1.782 ℃ and 0.837℃ in forest park as well as 3.084 ℃ and 2.140 ℃ in landscape forest less than that of roadside and resident-area greenbelts, respectively. In terms of mean air humidity, forest park and landscape forest are 3.034% and 7.563% higher than that of roadside greenbelt, and 1.205% and 5.734% higher than that of resident-area greenbelt, respectively, implying a sound humidity feeling of human comfort in the former two types. The air cleanness holds a descending rank as forest park, landscape forest, resident-area greenbelt, and roadside greenbelt, whereas the rank in inhalable particle concentration is completely reverse. In general, landscape forest and forest park that mainly consist of trees have a comparatively higher feeling of human comfort whereas roadside and resident-area greenbelts fluctuate irregularly to some extent for the measures studied. The four greenbelt types investigated could be summarized in human comfort as the following descending rank, forest park, landscape forest, resident-area greenbelt, and roadside greenbelt.展开更多
文摘Urban green spaces have been arisen growing concern responded to the social and environmental costs of urban sprawl. A wide range of planning and policies has been and/or will be designed to protect urban green spaces and optimize their spatial pattern. A better design or planning of urban green space can make a major contribution to quality of environment and urban life, and furthermore can decide whether we can have a sustainable development in the urban area. Information about the status quo of urban green spaces can help planners design more effectively. However, how to quantify and capture such information will be the essential question we face. In this paper, to quantify the urban green space, a new method comprising gradient analysis, landscape metrics and GIS was developed through a case of Jinan City. The results demonstrate: 1) the gradient analysis is a valid and reliable instrument to quantify the urban green space spatial pattern precisely; 2) using moving window, explicit landscape metrics were spatially realized. Compared with quantifying metrics in the entire landscape, it would be better to link pattern with process and establish an important basis for analyzing the ecological and socioeconomic functions of green spaces.
文摘Four urban greenbelt types including roadside greenbelt, resident-area greenbelt, landscape forest, and forest park, were simultaneously investigated in Shenzhen, China, in such measures as air temperature, air humidity, wind speed, air anion ratio, and inhalabal particle concentration, which were strongly related with pleasing feeling of human body. The results show that the average air temperature in both forest park and landscape forest is much closer to the pleasing feeling of human body temperature than that of the rest two greenbelts, where it is 1.782 ℃ and 0.837℃ in forest park as well as 3.084 ℃ and 2.140 ℃ in landscape forest less than that of roadside and resident-area greenbelts, respectively. In terms of mean air humidity, forest park and landscape forest are 3.034% and 7.563% higher than that of roadside greenbelt, and 1.205% and 5.734% higher than that of resident-area greenbelt, respectively, implying a sound humidity feeling of human comfort in the former two types. The air cleanness holds a descending rank as forest park, landscape forest, resident-area greenbelt, and roadside greenbelt, whereas the rank in inhalable particle concentration is completely reverse. In general, landscape forest and forest park that mainly consist of trees have a comparatively higher feeling of human comfort whereas roadside and resident-area greenbelts fluctuate irregularly to some extent for the measures studied. The four greenbelt types investigated could be summarized in human comfort as the following descending rank, forest park, landscape forest, resident-area greenbelt, and roadside greenbelt.
