scholarly journals Spatial Scale Effect of Land Use Landscape Pattern in Guangling District of Yangzhou City

2020 ◽  
Vol 08 (02) ◽  
pp. 107-116
Author(s):  
小娅 杜
2020 ◽  
Vol 12 (17) ◽  
pp. 6850
Author(s):  
Yu Song ◽  
Xiaodong Song ◽  
Guofan Shao

Land use/land cover (LULC) pattern change due to human activity is one of the key components of regional and global climate change drivers. Urban green space plays a critical role in regulating urban thermal environment, and its cooling effect has received widespread attention in urban heat island (UHI) related studies. To fully understand the effects of the landscape pattern of an urban green space in regulating the urban thermal environment, it is necessary to further study the thermal effects of the landscape pattern of the urban green space and its characteristics under varied spatial–temporal scales. In this paper, we took the urban core area of Hangzhou City as the study area and analyzed the relationships between the landscape metrics of the urban green space and land surface temperature (LST) under varied spatial scales by using correlation analysis and redundancy analysis (RDA) methods. Multi-temporal Landsat 8 thermal infrared sensor data were used to retrieve the spatial and temporal dynamics of LSTs in four consecutive seasons, and the land use classification was interpreted using SPOT (Systeme Probatoire d’Observation de la Terre) satellite imagery. The results showed that landscape dominance metrics—e.g., percentage of landscape (PLAND) and largest patch index (LPI)—were the most influential factors on urban LST. The spatial configuration of urban landscape, as represented by the fragmentation and aggregation and connectedness, also showed significant effects on LST. Furthermore, landscape pattern metrics had varied spatial scale effects on LST. Specifically, the landscape dominance metrics of urban forest showed an increased influence on LST as the spatial scale increased, while for urban water, the trend was opposite. These findings might have some practical significance for urban planning about how to spatially arrange urban green space to alleviate UHI at local and regional scales.


2014 ◽  
Vol 641-642 ◽  
pp. 514-518
Author(s):  
Hai Hong Song ◽  
Yun Feng Tan

This article analyzes the general characteristics and its causes of the landscape pattern of land use, taking the Tuanjie town of DaoWai district in Harbin as an example. Using GIS and Fragstats software to calculate a series of landscape index, the data show that Tuanjie town is given priority to with agriculture landscape, and the landscape patch connectivity is stronger; the overall landscape patch shape is complex, showing the human activities interfere significantly; and each patch type concentration and fragmentation is quite different. Therefore, based on the use of their own advantages, put forward reasonable suggestions to the landscape optimization of Tuanjie town land use.


2017 ◽  
Vol 10 (1) ◽  
pp. 20-34
Author(s):  
Alvin Spivey ◽  
Anthony Vodacek

AbstractExtending the Landscape Pattern Metric (LPM) model analysis in Smith et al. (2001) into a LPM decision model, decadal scale prediction of fecal coliform compromised South Carolina watersheds is developed. The model’s parameter variability identifies the greatest contributors to a compromised watershed’s prediction. The complete set of model parameters include Land Cover Land Use (LCLU) & slope,along stream proportion, Fourier Metric of Fragmentation (FMF), Fourier Metric of Proportion (FMP), and Least Squares Fourier Transform Fractal Dimension (LsFT). The 1992 National Land Cover Data (NLCD) Land Cover Land Use (LCLU) within fecal coliform compromised watersheds is used to train the model parameters, and the 2001 NLCD LCLU is used to test the LPM model. The most significant model parameters arealong stream bare rock LsFT,FMF between urban/recreational grasses and evergreen forests, andFMF between deciduous forests and high density residential areas. These metrics contribute significantly more than the bestproportiondescriptor:proportion of urban/recreational grasses. In training, the proposed model correctly identified 92 % of the compromised watersheds; while the Smith et al. (2001) model 94 % of the compromised watersheds were correctly identified. This study reveals the ability of Fourier metrics to interpret ecological processes, and the need for more appropriate landscape level models.


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