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All Journal Journal of Marine and Aquatic Sciences Bumi Lestari Ecotrophic, Journal of Environmental Science International Journal of Remote Sensing and Earth Sciences (IJReSES) The International Journal of Remote Sensing and Earth Sciences (IJReSES)

I Wayan Nuarsa

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Author-ID : 2947163

Agriculture, Biological Sciences & Forestry Humanities Earth & Planetary Sciences Energy Environmental Science

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Title

AN APPLICATION OF SEGNET FOR DETECTING LANDSLIDE AREAS BY USING FULLY POLARIMETRIC SAR DATA I Made Oka Guna Antara; Norikazu Shimizu; Takahiro Osawa; I Wayan Nuarsa
ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) Vol 13 No 2 (2019)
Publisher : Master Program of Environmental Science, Postgraduate Program of Udayana University

The study location of landslide is in Hokkaido, Japan which occurred due to the Iburi Earthquake 2018. In this study the landslide has been estimated by the fully Polarimetric SAR (Pol-SAR) technique based on ALOS-2 PALSAR-2 data using the Yamaguchi’s decomposition. The Yamaguchi's decomposition is proposed by Yoshio Yamaguchi et.al. The data has been analyzed using the deep learning process with SegNet architecture with color composite. In this research, the performance of SegNet is fast and efficient in memory usage. However, the result is not good, based on the Intersection over Union (IoU) evaluation obtained the lowest value is 0.0515 and the highest value is 0.1483. That is because of difficulty to make training datasets and of a small number of datasets. The greater difference between accuracy and loss graph along with higher epochs represents overfitting. The overfitting can be caused by the limited amount of training data and failure of the network to generalize the feature set over the training images.

ESTIMASI PRODUKSI PADI DENGAN ANALISIS CITRA SATELIT LANDSAT 8 DI KABUPATEN KLUNGKUNG PROVINSI BALI Made Arya Bhaskara Putra; I Wayan Nuarsa; I Wayan Sandi Adnyana
ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) Vol 12 No 1 (2018)
Publisher : Master Program of Environmental Science, Postgraduate Program of Udayana University

Rice crop is one of the important commodities that must always be available, so estimation of rice production becomes very important to do before harvesting time to know the food availability. The technology that can be used is remote sensing technology using Landsat 8 Satellite. The aims of this study were (1) to obtain the model of estimation of rice production with Landsat 8 image analysis, and (2) to know the accuracy of the model that obtained by Landsat 8. The research area is located in three sub-districts in Klungkung regency. Analysis in this research was conducted by single band analysis and analysis of vegetation index of satellite image of Landsat 8. Estimation model of rice production was developed by finding the relationship between satellite image data and rice production data. The final stage is the accuracy test of the rice production estimation model, with t test and regression analysis. The results showed: (1) estimation of rice production can be calculated between 67 to 77 days after planting; (2) there was a positive correlation between NDVI (Normalized Difference Vegetation Index) vegetation index value with rice yield; (3) the model of rice production estimation is y = 2.0442e1.8787x (x is NDVI value of Landsat 8 and y is rice production); (4) The results of the model accuracy test showed that the obtained model is suitable to predict rice production with accuracy level is 89.29% and standard error of production estimation is + 0.443 ton/ha. Based on research results, it can be concluded that Landsat 8 Satellite image can be used to estimate rice production and the accuracy level is 89.29%. The results are expected to be a reference in estimating rice production in Klungkung Regency.

Co-Authors Abd. Rahman As-syakur Atsushi Ono CHAOFANG ZHAO Chiharu Hongo Fumihiko Nishio I Gede Hendrawan I Ketut Swardika I Made Oka Guna Antara I Wayan Sandi Adnyana Ida Bagus Mandhara Brasika Made Arya Bhaskara Putra Maria Laurensyelen Wulu Beda Rianghepat Norikazu Shimizu Susumu Kanno SWARDIDAI I KETUT Takahiro Osawa YASUHIROSUGIMORI Yasuo Furushima

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Journal : Ecotrophic, Journal of Environmental Science