Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this app...Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41930102,41571383,41771415,41801321,and 41701450).
文摘Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.
