Surface and Near-surface Moisture Content Assessment using Multi-Temporal Satellite Images over Perak Tengah and Manjung Regions, Malaysia

• Main Authors: A. Hassaballa , Abdalhaleem, Matori , Abdul Nasir, M. Shafri, Helmi Z.
• Format: Conference or Workshop Item
• Published: 2013
• Online Access: http://eprints.utp.edu.my/10791/1/ISDE2013.pdf; http://eprints.utp.edu.my/10791/
• Institution: Universiti Teknologi Petronas

Soil moisture is considered as the most significant boundary condition controlling precipitation, especially in the semi-arid zones. On the regional scale, the importance of soil moisture appears in agricultural assessment (crops yield management, irrigation management, etc.), flood and draught control. Based on these principles, the study was carried out to estimate surface moisture content (θ) over Perk Tengah and Manjung districts in Malaysia using optical images from multi-temporal satellites which are NOAA/AVHRR and MODIS. In order to generate the moisture maps, “Universal Triangle” algorithm was used for NOAA/AVHRR based on land Surface Temperature (Ts) and the Normalized Difference Vegetation Index (NDVI) extracted from images beside field measurements of θ. θ also estimated from MODIS through the extraction of soil wetness index (SWI) which is a sensitive parameter that controls the mechanism of land surface and the processes at the atmosphere. Throughout the study area, θ was measured using soil moisture probe for some parts of the study area and the oven method for the others; both Ts and θ were measured at time of satellites overpass in two different near surface depths 5 cm and 10 cm to examine the depth influence on θ and Ts magnitudes. The study area was divided into three basic classes according to the nature of surface cover which were: urban area, agricultural area and multi-types surface cover area. Moisture content maps were generated from both satellites for each surface cover type then; generalized moisture maps were produced through correlating the three different surface cover types for each satellite using weightage method. Finally, two sets of validation were applied to the resultant moisture maps. Firstly, experimental validation was performed between the satellites estimated θ and θ values measured in-situ. Good relationships were found with R 2 reached 0.79 and 0.76 for NOAA and MODIS sensors respectively. Secondly, a success rate curve based on spatiostatistical technique was used for validating the generalized maps in order to study the high-low distribution of θ within NOAA and MODIS generalized maps. The resultant validation reflected a high compatibility represented by area under curve of (0.81) 80%.