Estimating Plant Dry Matter Productivity for AL-Sweeda Badia Rangeland (Syria) at Different Processing Levels of BKA, KVA Satellite Images

Estimation of plant dry matter to management of rangelands with high accuracy is important for managers. This research aims to compare Plant Dry Matter Productivity (PDMP) values estimated by Normalized Difference Vegetation Index (NDVI) derived from satellite images of BKA and KVA according to different levels of satellite image processing for AL-Sweeda Badia (Syria) during April and July in 2015 and October 2014. NDVI was calculated according to Digital Number values (DN); then, Top of Atmosphere values (TOA), and Ground Surface (GS) values after Atmospheric Correction (AC) were computed from L8 satellite images simultaneously with field measurements. A relationship between two time-dependent satellite images was created. Then, the derived relationships were adopted by L8 (PDMP) relationship estimation. Matter productivity average values according to TOA and GS were 15-42, 969-214, 3254-22 and 576-563 kg/h for the previous dates, respectively. There was a weak non-significant correlation between DN values and Matter productivity (≤0.063). an‎d for TOA level, the relationship was relatively weak but significant (≤0.5). After atmospheric correction, it was strong (≥0.7) and significant at 1% and 5% levels and field verification measurements were consistent with 2014. A relationship between NDVI and PDMP for each previous value was determined according to NDVI values of modern images. Previous relationships were applied to estimate PDMP; then, objective maps were produced. DN satellite images as well as TOA values but at lower rate contained geometrical distortions resulting from terrain, climate, velocity changes, and sensor height and radiation refraction in atmosphere. Using GS after AC was good in rangelands for predicting and estimating PDMP.