The application of remote sensing technology and precision agriculture

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In the past, oil palm density has been determined by manually counting trees every year in oil palm plantations. The measurement of density provides important data related to palm productivity, fertilizer needed, weed control costs in a circle around each tree, labourers needed, and needs for other activities. Manual counting requires many workers and has potential problems related to accuracy. Remote sensing provides a potential approach for counting oil palm trees. The main objective of this study is to build a robust and user-friendly method that will allow oil palm managers to count oil palm trees using a remote sensing technique. The oil palm trees analysed in this study have different ages and densities. QuickBird imagery was applied with the six pansharpening methods and was compared with panchromatic QuickBird imagery. The black and white imagery from a false colour composite of pansharpening imagery was processed in three ways: (1) oil palm tree detection, (2) delineation of the oil palm area using the red band, and (3) counting oil palm trees and accuracy assessment. For oil palm detection, we used several filters that contained a Sobel edge detector; texture analysis co-occurrence; and dilate, erode, high-pass, and opening filters. The results of this study improved upon the accuracy of several previous research studies that had an accuracy of about 90-95%. The results in this study show (1) modified intensity-hue-saturation (IHS) resolution merge is suitable for 16-year-old oil palm trees and have rather high density with 100% accuracy; (2) colour normalized (Brovey) is suitable for 21-year-old oil palm trees and have low density with 99.5% accuracy; (3) subtractive resolution merge is suitable for 15- and 18-year-old oil palm trees and have a rather high density with 99.8% accuracy; (4) PC spectral sharpening with 99.3% accuracy is suitable for 10-year-old oil palm trees and have low density; and (5) for all study object conditions, colour normalized (Brovey) and wavelet resolution merge are two pansharpening methods that are suitable for oil palm tree extraction and counting with 98.9% and 98.4% accuracy, respectively

Plastic is one of the most abundant pollutants in the environment. As a result of natural physical processes, large plastic waste is degraded into microsized particles (<5 mm) called microplastics. Because of their size, abundance, and durability, microplastics are widely distributed in the environment, contaminating food and water intended for human consumption. The extent of microplastic contamination in the human body is still unclear because there are few studies concerning microplastic contamination in human specimens and, in most studies, data were collected from city dwellers. Despite having the fourth largest population and being the fourth largest plastic waste producer in the world and second largest plastic polluter in the ocean, there are currently no data with respect to microplastic exposure for the Indonesian population. Several studies have reported on microplastic contamination in seafood and freshwater organisms from Indonesia, and it is likely that microplastics have contaminated the gastrointestinal tracts of Indonesians. Using Raman spectroscopy, we detected microplastic contamination in 7 out of 11 analyzed stool samples collected from a farming community in the highland village of Pacet, East Java, Indonesia. Polypropylene (PP) was the most abundant and prevalent type of microplastic observed, and it was found in four of the positive samples with an average concentration of 10.19 microgram per gram of feces (μg/g). Microplastics were also detected at high concentrations in tempeh (soybean cake, a staple protein source for Indonesians), table salts, and toothpaste, which were regularly consumed and used by the study participants. PP was particularly high in table salts (2.6 μg/g) and toothpaste (15.42 μg/g), suggesting that these products might contribute to the gastrointestinal contamination in the studied population. This pilot study indicated microplastic contamination in the rural Indonesian population and in their daily consumables, demonstrating the far-reaching extent of microplastic pollution beyond urban areas.