Fraction of vegetation (Fv) plays an important role in ecosystems. Estimation of Fv is essential for drought monitoring, natural resources studies, estimation of soil erosion volume etc. The aim of this study is to estimate Fv in an arid area in Iran using ALOS Imagery (June 2008). In order to find the best index for estimation of Fv, Seventeen vegetation indices (ARVI, DVI, EVI, GEMI, IPVI, MSAVI1, MSAVI2, NDVI, PVI, SAVI, SARVI, SARVI2, SR, TSAVI, WDVI) were used. The canopy cover percentage of 52 sample plots (50m by 50m) was measured in the field in June 2009. Regression models were used to assess the relationships between the field data and the calculated Fv. The 52 sample plots were randomly divided two times to 30 calibrations and 22 validations, and to 35 and 17 samples. Results revealed that selecting the calibration and validation data randomly leads to different results. Therefore, cross-validation method was used to reduce random division effect. Results indicated that, among all indices, vegetation indices such as MSAVI1, PVI, WDVI and TSAVI which are based on soil line have higher R2 and lower RMSE (R2 > 0.63, RMSE ˜ 3%). The results confirm the dominant effect of soil reflectance in arid areas.
|Publication status||Published - 2010|
|Event||Remote Sensing for Agriculture, Ecosystems, and Hydrology XII; Toulouse - |
Duration: 20 Sep 2010 → 22 Sep 2010
|Conference||Remote Sensing for Agriculture, Ecosystems, and Hydrology XII; Toulouse|
|Period||20/09/10 → 22/09/10|