| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 506450 | Computers, Environment and Urban Systems | 2011 | 9 Pages |
Vegetation plays a key role in not only improving urban environments, but also conserving ecosystems. The spatial continuity of vegetation distributions can be expected to make green corridors for landscape management, wind paths against heat island phenomena. In this paper, we develop a spatial analysis method of vegetation distributions using remotely sensed data on a regional scale. The method consists of a spatial autocorrelation analysis, an overlay analysis, and a hydrological analysis with the Normalized Difference Vegetation Index (NDVI) adopted as the proxy of vegetation abundance. Application of the method leads to the extraction of the lines between the core areas and sparse areas of vegetation. The purpose of this study is to verify our method through applying a vegetation map digitized from aerial photographs. The map contained three vegetation types of land cover: grasslands, agricultural fields, and tree-covered areas. We use remotely sensed data collected at four different time periods at the regional scale, along with information on the seasonal fluctuations of the vegetation. As a result, the exclusion of seasonal land-cover changes, as in the reaping of agricultural fields, in the process of applying the proposed method produces an effect. The analysis reveals steady areas unaffected by the seasonal fluctuation of vegetation along the lines extracted by applying the proposed method.
► We verify spatial continuity of vegetation distributions using remotely sensed data. ► We extract dense areas of high vegetation-cover ratio between urban areas and suburbs. ► Exclusion of seasonal land-cover changes in our analysis method produces the effect. ► Steady areas unaffected by the seasonal fluctuation of vegetation are extracted.
