Spatial correlations of NDVI and MSAVI2 indices of green and forested areas of urban agglomeration, case study Warsaw, Poland

Abstract

AimThe aim of this study was to analyze spatial correlations of NDVI and MSAVI2 indices in a large urban agglomeration. The study area, encompassing the Warsaw agglomeration, was located almost in the center of Poland and the central part of Europe. MethodsThe study was based on the Sentinel 2 images with 0% cloud coverage that were taken in the years 2017, 2018, 2019, and 2020. After the NDVI and MSAVI2 indices were calculated, resulting rasters were exported to the text files and imported to the Stanford Geostatistical Modeling Software (SGeMS) software. Experimental variograms were calculated using values of vegetation indices from each pixel, separately for areas covered with natural forests, with a predominance of grass vegetation, and for areas with only rare vegetation of various types. Next, experimental variograms were modeled using the spherical or exponential model, and its parameters: range of correlation, nugget effect, and a sill. ResultsSpatial differences in the extents of green areas determined using NDVI and MSAVI2 indices were observed, especially for areas characterized by low values of both indices. Temporal variation of the extents of the green area was minimal and could have resulted from usual variability related to weather conditions, precipitation, and other factors.The longest ranges of correlation of NDVI and MSAVI2 were observed in natural forests, probably because they represent the greatest spatial continuity and homogeneity of all the examined areas. Long ranges of correlation were observed in strictly urban areas where the vegetation was relatively sparse and scattered. Despite the NDVI and MSAVI2 values being not high, this area was characterized by a relatively good spatial continuity of urban infrastructures such as buildings and roads. The shortest correlations ranges were observed in areas with a relatively large share of grasslands.