Author :
Villa, Paolo ; Malucelli, Francesco ; Scalenghe, Riccardo
Abstract :
Peri-urban areas are the extension of cities into contiguous areas, where households and farms coexist. Carbon stocks (CSs) assessment, a concept here extended to urban features, has not yet been studied in depth over peri-urban areas due to uncertainties in such CSs quantification, level of detail required about construction materials, and the high spatial variability of those stocks. Remote sensing (RS)-based techniques have been successfully utilized in urban areas for assessing phenomena such as soil sealing, sprawl patterns, and dynamics of surface imperviousness, especially focusing on land cover classification at high to medium spatial scales. Over the floodplain study area of Emilia-Romagna region (Italy), we compared mapping products derived from Landsat multiseasonal data with different CSs, in soils and impervious surfaces, such as buildings and roads. A multiscale correlation analysis and regression assessment between CSs layers and satellite products were run at different grid cell sizes (100, 250, 500, and 1000 m). Results show that RS products from processing of midresolution satellite data can effectively perform well enough to estimate CSs in peri-urban areas, especially at 500-1000 m scale. Urban Fraction Cover method, derived through weighting urban land cover classes (including dense, sparse, and industrial urban features) can represent a good proxy of the ratio of anthropogenic over natural CSs (R2 up to 0.75). Imperviousness Index (II) product scored high positive correlation with CSs over built-up areas (R2 up to 0.77), and strong negative correlation with organic carbon density in soil (R2 up to 0.73).
Keywords :
carbon; land cover; organic compounds; remote sensing; soil; CS assessment; CS high positive correlation; CS layer regression assessment; CS quantification uncertainty; Emilia-Romagna region; Italy; Landsat multiseasonal data mapping product; RS product; RS-based technique; anthropogenic CS ratio; building; built-up area; carbon stock assessment; city extension; construction material; contiguous area; dense urban feature; floodplain study area; grid cell size; high spatial scale; household-farm coexistence; impervious surface; imperviousness index product; industrial urban feature; land cover classification; medium spatial scale; mid-resolution satellite data processing; multiscale correlation analysis; natural CS ratio; peri-urban area carbon stock; remote sensing capability; remote sensing-based technique; road; satellite product; soil organic carbon density; soil sealing phenomena assessment; sparse urban feature; sprawl pattern; stock high spatial variability; surface imperviousness dynamic; urban fraction cover method; weighting urban land cover class; Cascading style sheets; Earth; Erbium; Indexes; Remote sensing; Satellites; Soil; Carbon stocks (CSs); Landsat; peri-urban area; remote sensing (RS);