Rapid economic development has led to intensive logging, drainage, and conversion of tropical peatlands to commercial plantations such as oil palm, which has led to large increases in carbon emissions. Therefore, proper management of tropical peatland is a necessary component in carbon emission control. The first step in realizing the management of tropical peatlands is establishment of a reliable monitoring technique. Synthetic Aperture Radar (SAR) offers cloud-free observation for tropical peatland monitoring by remote sensing. However, few studies have identified tropical peatland using L-band full polarimetric SAR data. This study was carried out to identify tropical peatland using L-band full polarimetric ALOS PALSAR data. Two study areas, 5 x 5 km in size, were selected to represent the conditions of tropical peatland in Central Kalimantan, Indonesia.
Three polarimetric decompositions (PDs) and the radar vegetation index (RVI) were evaluated for their capability to identify tropical peatland characteristics from the viewpoint of L-band full polarimetric SAR. Overall, a combination of classes derived from unsupervised classification of polarimetric parameters of Freeman-Durden three-component decomposition, integrated with the broad interval class of RVI that represents the amount of vegetation cover in the scattering mechanisms, successfully identified tropical peatland. Subsequently, the tropical peatland identified in study area 1 yielded a producer accuracy of 75.8% and a user accuracy of 80.9%. Study area 2 gave accuracies of 77.6% and 76.0% for producers and users, respectively. These results indicate that L-band full polarimetric SAR is advantageous for monitoring tropical peatlands.
The Great East Japan Earthquake in March 11, 2011 caused economic and ecological damages along with the coastal area of Pacific Ocean in east Japan. The huge tsunami was generated due to the earthquake registered 9.0 on the Richter scale. Most things such as buildings, trees, cars etc. were swept up by the tsunami. After the tsunami, wind environment in open areas near the coastal line which had been rice field and cultivation changed for the worse because almost of all windbreak trees planted along with the coastal line over 10km swept away by the tsunami. Actually, reconstructed PVC greenhouses for strawberry were broken down by strong wind. Such situations also have the potential for increasing an occurrence frequency of blown sand from open areas.
This study aims to assess current wind environment in Watari area located around 20 km south from Sendai city as an example and to investigate the effects of new windbreak trees and coastal breakwaters which will be put into the place on flow field by using OpenFOAM. First, we analyzed observed frequency of occurrence of mean wind speed during 10 minutes in each wind direction at an Automated Meteorological Data Acquisition System (AMeDAS) site in Watari as a reference point. Wind speed was measured at 10m high in the Watari AMeDAS site. The Weibull parameters for each direction were calculated from the observed wind speed. Second, CFD analyses for each wind direction in current situation were conducted to obtain the horizontal distribution of wind speed at ground level. Then, in order to calculate the exceedance frequency of wind speed at ground level, the ratios of wind speed in each point to the wind speed at the reference AMeDAS site were calculated in each wind direction. Next, CFD analyses were carried out with the condition where the new windbreak trees and the coastal breakwaters were reproduced in the computational domain to investigate their effects on the flow field. Finally, the simulation results with the new windbreak trees and the coastal breakwaters were compared with the result in current situation without the windbreak trees. In addition, the horizontal distribution of the occurrence frequency of blown sand was estimated by combining the occurrence frequency of wind speed with the threshold wind speed for blown sand. We showed that the windbreak trees reduced the occurrence frequency of blown sand to -25% in the area of 1km from the coast.
The objective of this study was to explore the potential of near-infrared reflectance (NIR) spectroscopy to determine single kernel composition in purple corn. NIR spectra and analytical measurements of anthocyanin contents and antioxidant activity (1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging activity) were collected from 120 single purple corn kernels. Partial least-squares (PLS) regression models were developed with 90 purple corn accessions randomly assigned to calibration data set and 30 accessions randomly assigned to an external validation set. PLS regression for anthocyanin contents and DPPH radical-scavenging activity had sufficient accuracy for kernel sorting applications, with the external validation set having a standard error of prediction (SEP) =3.04 μmol Cy3Glc eq/g D.W. and 1.66 μmol Trolox eq/g D.W. The validation correlation and standard deviation/square error of validation values (RPD) and the coefficient of determination for validation (R 2v) were determined to be as follows: anthocyanin contents, 0.84 and 2.5; DPPH radical-scavenging activity, 0.87 and 2.7. These present results indicated that prediction of anthocyanin content and DPPH radical-scavenging activity of single purple corn kernel could be measured using NIR spectroscopy, nondestructively.
In recent years, there were attempts of study by using text mining in the agricultural sector in Japan as well. The subjects cover a wide range, but there are still only a few papers. The reasons are that the information system is required for morphological analysis of the text, and digitizing for using extracted morphemes in the statistical analysis is a large-scale work. Therefore, in this paper, we have developed a text mining tool, iTM (internet Text Mining), which can sequentially perform Japanese language morphological analysis, parsing, chi-square test and so on, only by clicking buttons on a webpage that is familiar not only with researchers but also with internet users, such as certified farmers. To confirm the utility of the system, we used a web type questionnaire survey tool that is equipped with iTM, and conducted a case study that is targeting, for free, description answer sentences that have been acquired. As a result, it was revealed that we can feel free to carry out the text mining by using the button click function, which is a feature of iTM, since this function makes it possible to eliminate installations such as a morphological analysis engine and the digitizing works of text data. As an evaluation method for word appearing repeatedly, by applying and comparing with a 1≦Y<2 valuation method which was uniquely devised by us, it has been suggested that it is possible to deepen the consideration for the analysis results.