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    Assessment of the suitability of land use for agriculture by analytical hierarchy process: Ahp in lower prachinburi watershed, Eastern Thailand
    (2020-09-01)
    Rukanee, Duangthip
    ;
    Sangchan, Songvoot
    ;
    Choomjaihan, Prasan
    The low Prachinburi watershed is a gateway to other regions of the country. Due to a rapid increase in population there, there is also an increase in agricultural production area. This study aims to assess the appropriateness of land use by using an analytical hierarchy process (AHP) for land use planning. The results of the study revealed that there is a moderate level of the appropriateness in land use development. The most appropriate area (S1) accounts for 22.07%; the moderately appropriate area (S2) accounts for 54.15%; the lowly appropriate area (S3) accounts for 10.25%; and the inappropriate area accounts 13.52% of the area. Regarding a guideline for agricultural area management, it is found to be most appropriate, particularly on field crop growing such as cassava, sugar cane, and maize growing and followed by rice growing and or charding (58.51%, 25.17%, and 6.04%, respectively). Only 10.25% of the total area is inappropriate for farming.
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    Identifying and comparing relatively high soil erosion sites with four DEMs
    (2018-09-01)
    Chen, Walter
    ;
    Li, Dong Huang
    ;
    Yang, Kai Jie
    ;
    Tsai, Fuan
    ;
    Seeboonruang, Uma
    Soil loss due to sheet or rill soil erosion is a critical problem in watersheds of Taiwan. However, an order-of-magnitude discrepancy of soil loss in the literature raises many questions. In this study, we conducted a new analysis using the most recent available data and the Universal Soil Loss Equation (USLE) to compute the amounts of sheet and rill erosion of the Shihmen reservoir watershed in northern Taiwan. Using four different Digital Elevation Models (DEMs), we identified relatively high soil erosion sites and found them to be located at similar locations despite of the difference in DEM. We also determined that the average soil erosion in the Shihmen reservoir watershed is comparable to other watersheds in Asia, but higher than those of the European Union. Furthermore, soil erosion is not uniformly distributed throughout the study area. It is found that the distribution of soil erosion is highly skewed to the right (right-tailed), which means that the majority of the distribution is concentrated to the left side (many cells with low soil erosion). Based on our model, approximately 2% of the areas account for 30% of the soil erosion. In other words, a small proportion of the areas contribute to a large proportion of the total soil loss. Moreover, the DEM created from airborne LiDAR yields the highest amount of soil erosion, the two DEMs created from satellite images yield the lowest amounts of soil erosion, and the DEM created from aerial photographs yields an in-between soil erosion amount. Their vertical resolutions range from high to low. It appears that the amount of soil erosion is influenced by the vertical accuracy of DEMs. In addition to the comparison of DEMs, we demonstrated rudimentary steps to visualize areas of high soil erosion risk using freely available tool for long-term monitoring.
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    K mean clustering based automated segmentation of overlapping cell nuclei in pleural effusion cytology images
    (2017-12-05)
    Win, Khin Yadanar
    ;
    Choomchuay, Somsak
    ;
    Hamamoto, Kazuhiko
    Automated segmentation of cell nuclei is crucial for the early diagnosis of cancer as the characteristics of the cell nuclei are mainly associated with the assessment of malignancy. Only a few research work has been done on automated segmentation of cell nuclei on cytology pleural effusion images, which is poorly handled by previous methods. In addition, cytology pleural effusion image itself is still challenging due to the poor contrast of images, a variety of cells, and overlapping cells. To deal with the remained problems, this paper presented the algorithm for automated segmentation of cell nuclei in pleural effusion cytology images which contain touching and overlapping cells. First, the preprocessing step is carried out to reduce noise and enhance the contrast using the median filter and CLAHE respectively. The cell nuclei are segmented using K Mean Clustering algorithm in LAB color space. Then, the boundaries are corrected and non-nuclei regions are eliminated by the morphological operations. Finally, the overlapping cell nuclei are isolated depending on the watershed method, subsequently, boundaries of isolated cell nuclei are estimated using ellipse fitting method. The proposed system is evaluated on the local dataset containing 35 images of cytology pleural effusions with normal benign and cancer cells. The experimental results yield the accuracy of Precision= 0.90, Recall=0.89, F-meas-ure=0.89, Dice Similarity Coefficient=94% and Piccard In-dex=89% respectively. The obtained results are verified and compared with the ground truth images manually annotated by experts.