A Study On Landscape Pattern And Relative Scale Effect In Different Landforms

Spatial heterogeneity is ubiquitous across all scales of natural systems. Spatial pattern heterogeneity is also scale dependent. Scale effects mean how ecological properties change with scales. Effects of changing scale on spatial analysis have been studied for decades in geography and ecology. After a review on a great deal of domestic and international documents, the CBERS images in2007were used to study landscape patterns of Fengqiu County and Gaochun County and the related grain and extent effect with the application of GIS and landscape statistics software (FRAGSTASTS3.3).The main conclusions are:1In2007the majority area of land in Fengqiu County was for agriculture while the main types in Gsochun County included both grassland and construction land. Thus the distribution of the main land type in Fengqiu was more concentrated than that in Gaochun due to variations in physical and socio-economic conditions between the two counties. In Fengqiu, among all land types the grassland had the maximum conversion rate to construction land, while in Gaochun it was wild land with the maximum rate. The fragmentation and complexity of landscapes in study regions was determined by the extent to which human beings interfered with the environment.2Based on the shape of the scale effect curves and scaling relations, the13landscape indices in this study were divided into three groups/types. Type Ⅰ indices decreased monotonically with increasing grain size, showing a power-law decay scaling relation, with the characteristics of spatial pattern having little impact on scaling relations. This group included9landscape metrics:number of patches, patch density, total edge, edge density, landscape shape index, Type Ⅱ indices also decreased with increasing grain size, but not monotonically. There was no single scaling relation for each index, and scaling relations were related to spatial patterns. This group included6metrics:mean patch shape index, Shannon’s diversity index, Shannon Evenness Index, area-weighted mean patch shape index, and area-weighted mean patch fractal dimension and largest patch index. Type III indices increased with increasing grain size. The shapes of the scale effect curves were various. There were2indices in this group:mean patch size and area/edge fractal dimension.3Based on the shape of the scale effect curves and the predictability of the scaling relations. The13landscape metrics could be divided into two groups. The first group included3indices:number of patches, total edge and landscape shape index. The behavior of this group of indices with change in extent was very predictable for both2landscape types. And there were simple scaling relations for the3indices. NP and TE increased in a power-law function with increasing extent. And there was an increasing linear relationship in LSI increased with increasing extent in staircase fashion for two real landscapes. General scaling relations could be valuable in choosing the extent while com-different landscapes and extrapolating ecological information among different. The second group included10indices:patch density, largest patch index, edge density, mean patch size, mean patch shape index, area weighted mean patch shape index, area/edge fractal dimension, area-weighted mean patch fractal dimension, Shannon’s diversity index and Shannon Evenness Index. The scaling behavior of this group of indices was generally unpredictable and related to the specific spatial pattern of a landscape. In general the predictability of scaling relations of these indices increased with increasing number of classes equality of class dominance and randomness of spatial distribution.