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Spatiotemporal characterization of land surface temperature in Mount Kilimanjaro using satellite data
- Maeda, Eduardo Eiji, Hurskainen, Pekka
- Theoretical and applied climatology 2014 v.118 no.3 pp. 497-509
- altitude, biodiversity, ecosystems, habitats, land cover, landscapes, satellites, savannas, surface temperature, tropical montane cloud forests, Africa
- Mount Kilimanjaro is considered the highest free-standing mountain in the world and a symbol of the African continent. Steep slopes and high altitudes are on the backdrop of unique biophysical characteristics, in which changes between savannas, tropical cloud forests, and subalpine vegetation can be observed in relatively small distances. In the context of this complex and heterogeneous landscape, describing the interactions between climatic variables and ecosystem functions is crucial for understanding the drivers of biodiversity. However, the characterization of climatic variables, especially surface temperature, still remains a critical bottleneck for a comprehensive understanding of habitats in Kilimanjaro. This study applies satellite-based estimates of land surface temperature (LST), from 2001 to 2011, to delineate a thorough characterization of the spatiotemporal patterns of surface temperature in Mount Kilimanjaro. The ample spatial coverage and continuous observations provided by the satellite measurements allowed the detailed description of characteristics so far poorly understood or not yet described in the literature. We demonstrate that the spatial patterns of LST in this region are rather complex, in the sense that it is characterized by non-linear behaviors and strong interactions with land cover and topography. Daytime observations (measured at 10:30 am) were shown to be strongly influenced by land cover characteristics, which is responsible for defining not only the spatial patterns (e.g., lapse rate) but also the seasonal signature of LST. At nighttime measurements (10:30 pm), the influence of land cover virtually disappears and the spatial patterns are mostly driven by altitude. Moreover, this study provides a brief assessment of LST trends observed within the analyzed period.