Spatial Correlograms And Landscape Metrics As Indicators Of Land Use Changes
Free (open access)
R. Aunap, E. Uuemaa, J. Roosaare & Ü. Mander
Land use changes over time can be analysed in several ways. We studied the spatial autocorrelation (Moran’s I) of raster format land use maps from three different time periods (1900, 1940, and 2000) in 13 study areas representing most of the landscape regions in Estonia. Human influence was taken into consideration in compiling a scale of the contrast between 10 land use groups. We introduce a simple characteristic based on spatial correlograms: a half-value distance lag, hI=0.5 – a distance where Moran’s I drops below 0.5. No significant change was detected in values of hI=0.5 over time. In addition, we did not detect a difference between lowlands and heights. In analysis of landscape metrics Edge Density (ED), Patch Density (PD), Contrast Weighted Edge Density (CWED), Mean Patch Area Distribution (AREA_MN), and Percentage of Like Adjacencies (PLADJ) showed significant changes comparing the year 2000 with 1900 and 1940. However, the results showed no significant change in landscape metrics between 1900 and 1940. ED, PD and CWED had higher values in 2000 than in 1900 and 1940. Therefore landscape heterogeneity has increased in recent decades. ED, PD, CWED, AREA_MN and PLADJ metrics also indicated a significant difference between lowlands and heights. It appeared that heights have a more heterogeneous landscape structure than lowlands. Generally, the heterogeneity of Estonia’s landscapes overall has changed within recent decades. Keywords: FRAGSTATS metrics, landscape pattern, landscape regions, land use change, Moran’s I, spatial autocorrelation. 1 Introduction Studies on land use changes is the basic area in landscape research [1, 2] being one of the key issues in global environmental change . Both natural and socio-
FRAGSTATS metrics, landscape pattern, landscape regions, land usechange, Moran’s I, spatial autocorrelation.