The effects of water depth on estimating Fractional Vegetation Cover in mangrove forests

摘要: Abstract Maps of mangroves have often been limited to showing the presence or absence mangrove trees and seldom studies shown an important indicator ecosystem integrity such as vegetation cover. Fractional Vegetation Cover (FVC) is used assess health, land cover carbon stocks, hence accurately measuring FVC task for scientists managers. Many methods proposed measure simple linear models are commonly used. We created experiment that allowed us to: 1) acquire very detailed hyperspectral imagery (1 mm pixel size) from a simulated forest, 2) effect water depth on estimations, 3) compare relationship eight spectral bands indices with using non-linear models. After acquiring we corrected dark signal white reference, performed spatial resampling, across four sizes. Our results suggest beta similar performance all sizes; Soil Adjusted Index (SAVI), Modified Index2 (MSAVI2) Enhanced (EVI) perform better than Normalized Difference (NDVI), and, our at fine sizes coarse scales. tested high-resolution satellite therefore, recommend SAVI, EVI MSAVI2 when predicting instead NDVI.