Ibrahim Busu

Evaluation of MODIS Gross Primary Productivity of tropical oil palm in southern Peninsular Malaysia

Evaluation of the MODIS Gross Primary Productivity (GPP) or the MOD17A2 product has not been carried out for croplands, such as oil palm ecosystems in tropical regions. Thus, evaluation of the MOD17A2 is important in order to determine its usefulness for carbon related studies of oil palm. MOD17A2 and its inputs, such as MODIS land cover (MOD12Q1), meteorological data from Global NCEP/DOE II reanalysis dataset, LAI/fPAR (MOD15A2) and light use efficiency (LUE) were evaluated. Of the area of oil palm identified from a land use map, only 40.22% was correctly identified by croplands of MOD12Q1 as oil palm and the remaining 59.78% was misclassified as croplands and forest. From Global NCEP/DOE II reanalysis dataset, photosynthetic active radiation shows the lowest correlation (R2=0.02) whilst daily minimum temperature (Tmin) only agreed moderately (R2=0.26) compared to in-situ meteorological data. LAI and fPAR were underestimated by 10.00–16.79% and 9.66–10.80% respectively by MOD15A2. GPP was underestimated 19.10–29.48% by MOD17A2. LUE from site is higher than MODIS LUE of croplands for 0.19 g/m2/MJ/day.

Neural Network and Multiple Linear Regression for Estimating Surface Albedo from ASTER Visible and Near-Infrared Spectral Bands

AbstractThe current Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-based broadband albedo model requires shortwave infrared bands 5 (2.145–2.185 nm), 6 (2.185–2.225 nm), 8 (2.295–2.365 nm), and 9 (2.360–2.430 nm) and visible/near-infrared bands 1 (0.52–0.60 nm) and 3 (0.78–0.86 nm). However, because of sensor irregularities at high temperatures, shortwave infrared wavelengths are not recorded in the ASTER data acquired after April 2008. Therefore, this study seeks to evaluate the performance of artificial neural networks (ANN) in estimating surface albedo using visible/near-infrared bands available in the data obtained after April 2008. It also compares the outcomes with the results of multiple linear regression (MLR) modeling. First, the most influential spectral bands used in the current model as well as band 2 (0.63–0.69 nm) (which is also available after April 2008 in the visible/near-infrared part) were determined by a primary analysis of the data acquired before April 2008. T...