Thursday, October 08, 2015

Spectral reflectance of floodplain vegetation communities of the Okavango Delta

K. Thito • P. Wolski • M. Murray-Hudson

Knowledge of wetland vegetation spectral reflectance signatures can assist in spectral classification of remotely sensed images for monitoring of wetland hydroperiod. This study aimed at assessing the differences between wetland vegetation communities of varying species composition and density in terms of spectral reflectance. The investigation was carried out in floodplains at Nxaraga and Seronga in the Okavango Delta, Botswana. Spectral measurements were conducted during rising and receding flood stages. In each study area, 2 transects were located in homogeneous macrophyte stands, and in each transect 5–10 1 m2 quadrats were randomly set. In each quadrat, water depth and cover percentages (green leaved and senescent) of macrophyte vegetation were recorded, and a full reflectance spectrum between 325 and 1,075 nm  wavelengths captured using a handheld spectroradiometer. 

Multiple regression analysis with stepwise selection of significant variables based on AIC was performed to determine the influence of various stand characteristics on spectral reflectance and vegetation indices (NDVI and EVI). The results showed that stand characteristics explained a large proportion of variance in spectral vegetation indices with r2 = 0.67 for NDVI and r2 = 0.75 for EVI. For NDVI, the significant explanatory variables were percentage green cover, senescent cover and water depth, while for EVI it was the total vegetation cover.
Analysis of regression residuals for the various vegetation community classes showed significant differences between the classes in their NDVI, but no differences in EVI, with the exception of the Panicum repens class. Reflectance in visible wavelengths did not vary significantly between sites and seasons, but the NIR reflectance differed across sites and seasons. The results indicate that the simple vegetation indices in the Okavango Delta respond strongly to stand characteristics and thus can be used to derive these from remote sensing imagery. The scope for determination of vegetation communities from these indices is limited,however

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