ESTIMATING CROWN CLOSURE OF FOREST STANDS USING LANDSAT TM DATA: A CASE STUDY FROM TURKEY

Remote sensing data has been broadly used in assessing and monitoring natural resources. Monitoring forest resources with Landsat Thematic Mapper (TM) and other fine resolution sensors has become a challenging work in a wide variety of forest applications. In this paper, the relationships between stand crown closure with spectral reflectance values and some vegetation indices (VIs) obtained from Landsat TM were investigated in a case study area. The Pearson correlation and multiple regression analysis were used to estimate the crown closure. The regression analysis showed that a linear combination of Soil Adjusted Vegetation Index (SAVI), normalized difference 32 index (ND32) and normalized difference 57 index (ND57) are better predictors for estimating crown closure (adjusted R-2 = 0.757; root mean square error (RMSE)=2.5304%) than other TM bands (adjusted R-2=0.529; RMSE=4.0782%). The Pearson correlation analysis results demonstrated that NDVI, Simple ratio (SR), Difference Vegetation Index (DVI), Transformed Vegetation Index (TVI), Soil Adjusted Vegetation Index (SAVI) had the highest positive correlation (r=0.84) and Infrared Percentage Vegetation Index (IPWI) had the negative correlation (r=-0.84) with crown closure measurements. Furthermore, the TM 4 band showed the highest correlation (r=0.64) with crown closure between TM 1-5 and TM 7. This research concluded that forest managers could use Landsat TM imagery for estimating crown closure used for generating maps in developing forest management plans.