The high demand for palm oil has triggered the expansion of oil palm plantation across the world, and especially in Indonesia. This phenomenon is indeed contributing to the national income and represents an alternative energy source, but is concurrently leading to numerous environmental and land management problems. The emergence of private smallholder's oil palm plantations is complicating the quantification of the environmental impacts of oil palm expansion, since its sparse distribution in small patches is difficult to be identified. In Mesuji area of Southern Sumatra, Indonesia, this type of plantations has been rapidly growing and potentially affecting the land management especially for protected areas. This study aimed to explore the ability of the multi-sensor and multi-scale images obtained by Advanced Land Observing Satellite (ALOS) to detect the oil palms and to develop the effective methodology to accurately classify smallholder's oil palm plantation in Mesuji area. By utilizing the texture analysis, the triangular planting pattern was recognized as the unique characteristic of oil palm plantation reflected on Synthetic Aperture Radar (SAR) data to identify the small scale smallholder's plantation. Finally, the study also revealed the integration of mean-variance texture features extracted from ALOS PALSAR data in 11 x 11 moving window sizes with the use of all ALOS AVNIR-2 bands resulting in the best accuracy to detect smallholder's oil palm plantation with 92.45% of producer's accuracy and 66.67% of user's accuracy for the mature oil palm. For the young stages, the accuracy was 64.44% and 63.04% for producer's and user's accuracy, respectively.
In recent years, wild boars (Sus scrofa) have caused growing damage to farm crops in a hilly and mountainous area of the Tohoku region. In particular, in designated evacuation zones following the accident at the Fukushima Dai-ichi nuclear power plant, there are growing concerns about the expanding range of wild boars and the resulting degradation of farmland. To assess the influence of reduced human activity on encroachment on farmland by wild boars, this study selected two adjacent study sites—the Yamakiya district (40 km2) in Kawamata town, designated as the Evacuation Directive Lift Prepared Area, and the Iwashiro and Towa districts (80 km2) in Nihonmatsu city—and recorded locations of damage (feeding, trampling, rooting) to farmland and farm crops caused by wild boars during the period from June to December in 2013. The locations at which wild boar feces were found were also recorded and collected. These feces, as well as muscle tissue samples collected from individuals trapped during the period, were subjected to DNA microsatellite analysis to identify individual animals. Values for the probability of identity for siblings (PID-sib) were used to assess the accuracy of identification. More locations damaged by wild bores were found in Kawamata town (150) than in Nihonmatsu city (94) (generalized linear model, P < 0.001). The total number of feces was also higher in Kawamata town (332) than in Nihonmatsu city (62). The number of feces found within each location was 0.49–0.74 during the summer but increased to 1.70–3.67 in autumn. These results suggest reduced human activity expands the range of wild boars, particularly in autumn. The accuracy with which individuals could be identified by microsatellite analysis differed with the primer sets used. The best identification results were obtained using nine primers (six primers reported as applicable for individuals in Japan [Tamate, 2012] and three primers reported in Europe [Frantz et al., 2012]) (PID-sib = 0.011). Successful individual identification was achieved for 38 fecal samples (9.6% of total feces), including three pairs of fecal sample derived from the same individual. However, the fecal sample pairs were collected within the same location and on the same measurement occasion. Thus, they provide no evidence regarding the seasonal migration of particular animals.
The depth is basic and important parameter for lake water resource management. In Southeast Asian countries where are attacked by typhoon and flood every year and face to water pollution risks by rapid urbanization, it is urgent issue to construct water level monitoring system for lakes and rivers. On the other hand, there are two issues for updating the information regularly, budget constraint and accessibility constraint. In this research, we developed the simple depth measurement method using fish finder and apply to create bathymetric map on LAGUNA Lake, Philippines. It identified that the method is efficient to improve those issues and available to aggregate depth data more effectively for contributing water resource management policy and the evaluation.