Abstract
Abstract. The advancement of remote sensing technologies is a huge advantage in various environmental applications including the monitoring of the rapid development in an urban area. This study aims to estimate the composition of the different classes (vegetation, impervious surfaces, soil) in Metro Manila, Philippines using a 300-meter spatial resolution Sentinel-3 Ocean and Land Colour Instrument image. The relationship between these land cover fractions with the spatial distribution of land surface temperature at this scale is evaluated. Sentinel-3 image has a higher spectral resolution (i.e. 21 bands), as compared with other Landsat and Sentinel missions, which is a requirement for an accurate cover mapping. Linear Spectral Unmixing (LSU), a sub-pixel classification method, was employed in identifying the fractional components in the image based on their spectral characteristics. Field survey using spectroradiometer was conducted to acquire spectral signatures of an impervious surface, vegetation, and soil which were used as the endmembers in the unmixing process. To assess the accuracy of the resulting vegetation fractional image, this was compared with a separate land cover pixel-based classification result using a 3-meter high spatial resolution PlanetScope image and with another vegetation index product of Sentinel-3. The results indicate that the recently available Sentinel-3 image can accurately estimate vegetation fraction with R2 = 0.84 and 0.99, respectively. In addition, the land surface temperature (LST) retrieved from Climate Engine is negatively correlated with the vegetation fraction cover (R2 = 0.81) and positively correlated with the impervious surface fraction cover (R2 = 0.66). Soil, on the other hand, has no correlation with the LST.
Highlights
Worldwide urbanization rate increase in the recent decades has led to various consequences, in sustainable urban development such as the significant reduction of agricultural lands, infrastructure planning, and extensive urban sprawls (Maktav, Erbek, & Jürgens, 2005)
It is observed that higher fractions of impervious class were found in most cities of Metro Manila, while higher fractions of vegetation were associated with forests, parks, and green spaces (e.g. UP Diliman and La Mesa Ecopark in Quezon City)
This study demonstrates the use of remote sensing technologies in identifying the land cover composition in an area and recognizing its effect in the observed surface temperature
Summary
Worldwide urbanization rate increase in the recent decades has led to various consequences, in sustainable urban development such as the significant reduction of agricultural lands, infrastructure planning, and extensive urban sprawls (Maktav, Erbek, & Jürgens, 2005). This highlights the need for systematic monitoring of the changes in urban landscapes, as well as its detrimental impacts to the environment, one of which is the substantial rise in land surface temperature within highlyurbanized and rapidly urbanizing cities due to the conversion of vegetated areas and bare soil to impervious surfaces such as buildings and roads. This makes balancing the two resolutions necessary when selecting the imagery to be used and in some cases, requires the application of additional image processing methods since urban landscapes are composed of various land cover types and building elements with different spatial attributes (Maktav et al, 2005)
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