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Oil palm dry season analysis based on moderate-resolution imaging spectroradiometer (MODIS) satellite indices

Nurul Fatin, M., Mohd Razali, Sheriza, Ahmad, A. Ainuddin, Mohd Shafri, Zulhaidi M. S.
International journal of remote sensing 2019 v.40 no.19 pp. 7663-7678
Elaeis guineensis, atmospheric precipitation, carbon, computer software, drought, dry season, economic valuation, image analysis, meteorology, moderate resolution imaging spectroradiometer, normalized difference vegetation index, oils, reflectance, remote sensing, satellites, water stress, Malaysia
Oil palm is the most important crop in Malaysia. It plays a key role in maintaining carbon balance and it possesses high economic value. However, oil palm productivity is really sensitive to environmental changes especially during the long-term dry season. This has warranted studies on frequent observation of dry season for the plantation of oil palm. In this study, Moderate-Resolution Imaging Spectroradiometer (MODIS) surface reflectance data were utilized to generate an index for the crop assessment at Felcra Mendom Oil Plantation area, Negeri Sembilan. The indices of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and shortwave indices, namely Shortwave Infrared Water Stress Index (SWISI), at three different channels of 2, 5, and 6 were utilized. The main aim is to identify drought year based on MODIS-SPI-based index calculated and evaluated indices developed from MODIS images. The precipitation data retrieved from Malaysia Meteorology Department starting from year 1997 until 2017 and later are classified using Standardised Precipitation Index (SPI). Then by using the data from precipitation and SPI, the MODIS images were extracted from Land Process Distributed Active Archive Center (LP DAAC). Next, the images were processed and analysed by using ENVI Version 5.3 software to extract the indices used. The SPI-3 and SPI-1 were classified year 2015 as extreme drought with ‘extreme’ and ‘mild’, respectively. Meanwhile, the vegetation indices were calculated and average showed both NDVI and EVI approaching +1.00 value at the highest NDVI is 0.79 during 2017 and the highest EVI is 0.62 during years 2005 and 2013, respectively. Both SIWSI showed similar pattern, indicating high-moisture content as the index approaching −1.00. The result does not represent the overall condition of the specific study area, but the SPI is reliable to display the whole area and the utilization of MODIS and SPI can be used in further study.