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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lm57ugzxwjehna44tee4sjxr4u" style="color: black;">Remote Sensing of Environment</a>
Understanding of mechanisms underlying carbon flux dynamics in the Eastern Arc Mountains and their catchment areas is lacking, due to data shortage (e.g. biome specific canopy structure) and spatial heterogeneity of tropical ecosystems. This study focuses on documenting leaf area index (LAI) for the main biomes in the Eastern Arc Mountains and their surroundings. In situ optical instruments, i.e. hemispherical photography and a SunScan device, were used to acquire ground LAI measurements.<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.rse.2011.11.009">doi:10.1016/j.rse.2011.11.009</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4fd7lkizerd4ndgv2heuao4ega">fatcat:4fd7lkizerd4ndgv2heuao4ega</a> </span>
more »... al vegetation indices (VIs) extracted from Landsat Enhanced Thematic Mapper (ETM +) and Système Probatoire d'Observation de la Terre (SPOT) reflectance data were used, along with mean annual precipitation (MAP), as explanatory variables of LAI variation. The results indicate that LAI significantly increases with increasing MAP for woody biomes. Implementing long-term MAP as a second predictor variable into the VI-LAI models significantly improved LAI predictions by up to 10% using the normalised difference vegetation index (NDVI), modified soil adjusted vegetation index (MSAVI 2) and 2-band enhanced vegetation index (EVI 2). Varying forest disturbances and agricultural management practises may have contributed to observed discrepancies of LAI with MAP across biomes. The importance of altitudinal gradients is yet to be explained fully with more study required. However, LAI appears to be higher in low-altitude forests compared to forests at higher altitudes. Our results indicate that SPOT and Landsat-derived VIs, in combination with long-term MAP, may be a suitable tool to develop landscape maps of LAI in Eastern Africa. This study also presents the in situ LAI measurements for further validation of global products for areas that are currently under-represented in Earth Observation (EO) global validation networks.
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