As an important part of the city, urban green space (UGS) plays an essential role in enhancing human well-being by virtue of multiple environmental, social and economic benefits. Study on landscape pattern of UGS is a focal point and hotspot in landscape ecology. The latest studies demonstrated that landscape metrics provides an effective method in quantifying UGS pattern. However, the study of the scale effect of landscape metrics should be strengthened. The objective of scale related research in UGS is to determine the appropriate scale in the measurement and evaluation of UGS and to find the underlying mechanisms by use of the selected scales.
This study aims to identify the scale characteristics and scale domain of UGS pattern, and provide basic information for pattern analysis and scaling in UGS research. In this paper, taking the central urban area of Székesfehérvár in Hungary as an example, we firstly extracted UGS from WordView-2 multi-spectral image (2m), then obtained a series of grain sizes by upscaling, and finally calculated and analyzed the characteristics of different landscape metrics with varying grain sizes. In this study, both the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Green Index (NDGI) were used to ensure the accuracy of the green space extraction in high spatial resolution image. On the basis of green space extraction, the green space patterns at different grain sizes were obtain by the assembly of grid cells. A total of 20 grain sizes were selected in this paper, ranging from 2 m to 40 m with a step size of 2 m. Landscape metrics both under class and landscape levels, including Patch Density (PD), Percentage of Landscape (PLAND), Mean Perimeter-Area Fractal Dimension (FRAC_MN), Division Index (DIVISION), Cohesion Index (COHESION), and Shannon’s Evenness Index (SHEI) were calculated.
The results demonstrated that with the increase of grain size, the landscape metrics under class level and landscape level were significantly affected by the grain size, and there was obvious critical grain size. On the whole, 16 m is the critical grain size of the green space pattern, and the suitable grain size for landscape metrics calculation of UGS ranges from 2 m to 16 m. The responding curves were varied by landscape metrics. Some metrics had clear changing trend and obvious turning grain size, while the others also had obvious turning grain size, but without clear changing trend. According to scale inflexions and responding curves discussed in the paper, scale domains of landscape metrics were confirmed. Generally, from 2 m to 16 m was the scale domain of UGS pattern, which means that related ecological model of UGS can be scaled across this scale extent by ordinary transformation. The study of impacts of changing scale on UGS can provide a reference for understanding the ecological benefits of UGS and optimizing the green space pattern.
The urban impervious surface, an important part in the city system, has a great influence on theecologicalenvironment in urban areas. The coverage of it is an important indicator for the evaluation ofurbanization. TheRemotesensing data has prominent features such as information-rich and accurate and it can provide data basis for large area extraction of impervious surface. GF-1 satellite is the first satellite of high-resolution earth observation system in China. With the homemade GF-1 satellite remote sensing image date as a resolution, this research, by the combination of V-I-S model and linear spectral mixture model, has first made estimation on the impervious surface of Tianjin City and then employed the remote sensingimage date with high resolution to test the precision of the estimated results. The results not only show that this method will make high precision available, but also reveal that Tianjin City has a wide coverage of impervious surface in general level, especially a high coverage rate both in the center and the coastal areas. The average coverage of impervious surface of the Tianjin city is very high and the coverage of impervious surface in the center and the coastal areas of Tianjin city reach seventy percent.City managers can use these data to guide city management and city planning.
This paper evaluates the usefulness of the WFV (Wide Field View) imager onboard GF-1 satellite in vegetation mapping.
Fractional vegetation cover (FVC) is an important surface microclimate parameter for characterizing land surface
vegetation cover. Three kinds of remote sensing inversion models (NDVI regression model, spectral mixture analysis
(SMA) model and dimidiate pixel model) were used to derive FVC with the GF-1/WFV data. The verification indicates
that the FVC results based on the dimidiate pixel model are well agreement with the in situ measurements. And the
estimated FVC result in Beijing-tianjin-hebei region demonstrate that the GF-1/WFV data are fit for studying vegetation
over large regions.