In a common agriculture resource, soil contamination monitoring is a prominent area of study. Nowadays, it is crucial to provide a database for the interpretation of ground penetrating radar (GPR) field data in monitoring soil contamination, such as diesel scatter migration. This study aims to assess the association between permittivity properties and soil water content (θw) for diesel contamination in Terap Red soil, which is classified as lateritic soil. Terap Red soil is an agro potential soil and available in more than 40% of distribution areas in Northern Malaysia (Agro-based State). In this research, 800 MHz shielded antenna GPR was applied for 24 hour measurement in a concrete simulation field tank, which was filled with Terap Red soil (1.5 m x 2.6 m x 1.5 m) located at Universiti Teknologi MARA (UiTM) Perlis, Malaysia. Embedded moisture content probe was simultaneously measured to monitor the response of volumetric water content in the contaminated soil. The GPR data were pre-processed and filtered by Reflexw 7.5. The calibrated Agilent Technologies Automated Vector Analyser (VNA) was used to verify the independent relative permittivity value from GPR. As a result, the evaluation of velocities and reflection of GPR data were influenced by the presence of diesel and contaminated vapour. A positive and significant correlation was obtained between relative permittivity and moisture content in the diesel-contaminated soil. In addition, a positive and strong linear regression analysis was also found between relative permittivity and moisture content. This analysis included an accurate total difference of root mean square error (RMSE) difference, which amounted to 0.04, with calibrated dielectric permittivity.
Unmanned aerial vehicle (UAV) recently has been proved to be used for slope mapping studies. Slope map can be created by gathering spatial information including elevations and surface features of the surrounding terrain. Spatial information on a slope is important to enhance the efficiency of slope modeling. Thus, the spatial information must be very accurate and reliable. This study aims to determine the effect of a slope on the vertical accuracy of spatial information acquired by using multi-rotor UAV. The objectives are to investigate the effect of slope elevation and to identify the effect of slope steepness on the vertical accuracy of spatial information acquired using multi-rotor UAV. Terrain Model (DTM), Contour Map, Triangular Irregular Network (TIN), and Slope Map is produced for analysis purpose. It was found that the vertical accuracy of spatial information increase when the elevation of slope and steepness of slope decrease. In conclusion, slope elevation and slope steepness do have an influence on the vertical accuracy of spatial information captured by UAV.
Remote sensing technology is the most common method used in monitoring conservation and restoration at mangrove areas. This study aims to classify the mangrove family at Bagan Datuk, Perak, using object-based image analysis techniques based on Pleiades’ image with 0.63m spatial resolution obtained from the Malaysian Remote Sensing Agency (ARSM). The segmentation was done by choosing a suitable scale and merge level. Two classifiers namely support vector machine (SVM) and k-nearest neighbor (KNN) were used to classify the mangrove family. The mangrove family map was produced from the higher accuracy of the classification. The results show that the overall accuracy of SVM is 63.81% (kappa = 0.55) while KNN is 59.83% (kappa = 0.50). In conclusion, SVM outperformed K-NN for mangrove family classification.
Unmanned Aerial Vehicle (UAV) is a new platform used in various applications such as landslide monitoring, agriculture, mapping, traffic control, mining, and others. In the photogrammetry survey, the use of UAV is cheaper and more effective for 3-dimensional modelling compared with traditional photogrammetry and Light Detection and Ranging (LIDAR). The ability of UAV to acquire data at a different altitude below the cloud coverage and easy to control has made it one of the most popular platforms in surveying applications. The objective of this paper is to count the numbers of the oil palm tree and define the most suitable flight attitude for tree counting based on the different UAV processing software. The study area is located at Felda Laka Temin in Chuping, Perlis. The comparison of flight altitude is 100m and 200m processed in Agisoft PhotoScan and Pix4D Mapper software. The analysis has been done with errors in Standard Deviation and Root Mean Square Error (RMSE) of Ground Control Point (GCP) which are generated using two different software.
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