Article
Environmental Sciences
Amandangi Wahyuning Hastuti, Masahiko Nagai, Komang Iwan Suniada
Summary: This research aims to develop a Coastal Vulnerability Index (CVI) using remote sensing and GIS approaches to assess the vulnerability of the coastal zone in Bali Province to sea-level rise. The study reveals that approximately 22% of the mapped shoreline is classified as being at very high vulnerability, and 26% of shoreline is at high vulnerability. The remaining shoreline is categorized as having moderate and low risk of coastal vulnerability.
Article
Environmental Sciences
Mitria Widianingtias, Shinobu Kazama, Sawangjang Benyapa, Satoshi Takizawa
Summary: Bali Province in Indonesia is facing serious water shortages and groundwater over-abstraction due to rising water demand. This study assessed the potential for water reclamation and reuse in Bali Province by examining the operational performance of two wastewater treatment plants. Although the Suwung WWTP has the capacity to produce reclaimed water for irrigation and landscape, several management issues need to be addressed, including fluctuating water demand, limited customer base, concerns about water quality and safety, and cultural perceptions of reclaimed water. Additionally, the Suwung WWTP's treatment performance was found to be significantly lower than that of the ITDC WWTP, which achieved high removal rates of BOD, COD, and TSS through good maintenance practices and dissolved air flotation (DAF) treatment.
Article
Agronomy
Chunling Sun, Hong Zhang, Lu Xu, Chao Wang, Liutong Li
Summary: Timely and accurate rice distribution information is essential for sustainable food production and security. This study proposes a framework for accurate rice extraction and mapping using multitemporal Sentinel-1A Data, which showed promising results in improving efficiency and accuracy of rice sample production.
Article
Geochemistry & Geophysics
Shilan Felegari, Alireza Sharifi, Mohammad Khosravi, Sergei Sabanov
Summary: Remote sensing technology integrated with machine learning is an effective and low-cost approach for environmental and earth sciences studies. This study aimed to accurately map cadmium concentration using different regression models, including SVR, PLSR, and ANNs. Multitemporal images were found to be more suitable for monitoring heavy metal concentrations compared to single-date images. Among the investigated features, the original band was identified as the most appropriate for regression analysis. The SVR model with the original band as input provided the most accurate estimation of cadmium concentration in the range of 8-26 mg/kg.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Environmental Sciences
Marcin Kluczek, Bogdan Zagajewski, Marlena Kycko
Summary: Climate change and human activities have significant impacts on plant communities, reducing their biodiversity. By using airborne hyperspectral remote sensing and satellite data, we successfully mapped the plant communities in Tatra Mountains and analyzed the effects of digital elevation models on the mapping accuracy.
Article
Immunology
Wayan Citra Wulan Sucipta Putri, Anak Agung Sagung Sawitri, Putu Cintya Denny Yuliyatni, I. Made Dwi Ariawan, Hashta Meyta, Sofya Umi Labiba, I. Gusti Ngurah Made Suwarba, I. Nyoman Sutarsa
Summary: This study conducted a retrospective economic analysis of the Japanese Encephalitis (JE) vaccination program in Bali Province, Indonesia, and found that a routine vaccination program is the most cost-effective strategy.
Article
Agriculture, Multidisciplinary
Chenxi Yan, Ziming Li, Zhicheng Zhang, Ying Sun, Yidan Wang, Qinchuan Xin
Summary: Obtaining accurate information on the area of rice fields through remote sensing is crucial for precision agriculture. However, current methods based on low spatial resolution remote sensing images are not suitable for efficient agricultural management and production. This research proposes a deep learning network named Enhanced-TransUnet (ETUnet) to identify paddy rice fields from very-high-resolution images obtained from Unmanned Aerial Vehicles (UAV). The study demonstrates the effectiveness of ETUnet in accurately extracting paddy fields during different growth stages, providing valuable insights for studying crop phenology changes.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Environmental Sciences
Youssef Lebrini, Abdelghani Boudhar, Ahmed Laamrani, Abdelaziz Htitiou, Hayat Lionboui, Adil Salhi, Abdelghani Chehbouni, Tarik Benabdelouahab
Summary: Changing land use patterns is crucial in environmental studies and land use management in arid regions. Sparse ground data can lead to uncertainties in characterizing phenological changes, but remote sensing methods offer a solution. This study in Morocco analyzed farming systems using NDVI time-series data and found significant plant cover dynamics driven by farmers' cultivation behaviors, with variations linked to weather conditions and rainfall patterns.
Article
Environmental Sciences
Lai Lai, Yuchao Zhang, Zhen Cao, Zhaomin Liu, Qiduo Yang
Summary: This study developed a machine learning algorithm based on MODIS data to estimate algal biomass in eutrophic lakes. The algorithm showed higher accuracy compared to traditional methods and demonstrated potential for widespread use.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Geosciences, Multidisciplinary
Chong Luo, Xinle Zhang, Xiangtian Meng, Houwen Zhu, Chunpeng Ni, Meihe Chen, Huanjun Liu
Summary: The study proposed a high spatial resolution SOM mapping method based on multitemporal synthetic images in the Songnen Plain, Northeast China. The use of spectral index combined with image band input improved SOM prediction accuracy. The median synthetic image had higher accuracy compared to average, maximum, and minimum synthesized images, and more years of synthesized images provided more robust SOM prediction results. May was identified as the optimal time window for SOM mapping on the Songnen Plain.
Article
Automation & Control Systems
Chen Wu, Hongruixuan Chen, Bo Du, Liangpei Zhang
Summary: This article proposes an unsupervised deep learning method for feature extraction and change detection from VHR images without requiring labeled data. Theoretical analysis and experimental results demonstrate the effectiveness, robustness, and potential of the method.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Environmental Sciences
Jianbo Yang, Jianchu Xu, Ying Zhou, Deli Zhai, Huafang Chen, Qian Li, Gaojuan Zhao
Summary: This study improves the accuracy and stability of mapping by integrating a random forest classifier and phenological information, and maps the historical distribution of land use/land cover in the Honghe Hani Rice Terraces from 1989-1991 to 2019-2021 using the Google Earth Engine. The driving forces of land use types in the rice terraces are analyzed, and it is found that phenological information can improve the mapping accuracy and stability. In the past thirty years, a significant amount of paddy rice has been converted to forests, shrubs or grasslands, and other croplands.
Article
Agriculture, Multidisciplinary
Ning Qi, Hao Yang, Guowen Shao, Riqiang Chen, Baoguo Wu, Bo Xu, Haikuan Feng, Guijun Yang, Chunjiang Zhao
Summary: Tea is a highly demanded and valuable commodity in both domestic and international markets, and China is the largest producer and exporter. However, research on vegetation plantation monitoring has often neglected the spatial information for perennial tea trees. This study constructs a novel tea plantation mapping algorithm based on multitemporal spectral features, which proves to be an effective tool for regional or national annual tea plantation mapping.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Agronomy
Masoumeh Hamidi, Abdolreza Safari, Saeid Homayouni, Hadiseh Hasani
Summary: Accurate crop mapping is crucial in agricultural applications, but it is challenging due to the variabilities in spectral, spatial, and temporal characteristics. This study introduces a deep learning framework, called Guided Filtered Sparse Auto-Encoder (GFSAE), to improve the accuracy of crop mapping by incorporating field boundary information. The evaluation on two high-resolution image datasets shows that GFSAE achieves impressive improvements in terms of accuracy metrics compared to the traditional Sparse Auto Encoder (SAE).
Article
Environmental Sciences
Yu Iwahashi, Rongling Ye, Satoru Kobayashi, Kenjiro Yagura, Sanara Hor, Kim Soben, Koki Homma
Summary: The study analyzed changes in rice production in Pursat Province, Cambodia from 2003 to 2019. It found a major shift around 2010, with farmers adopting earlier-maturing cultivars. Different types of dry season cropping areas were identified through clustering of annual LAI transition, providing valuable information for sustainable and improved rice production strategies.
Article
Geochemistry & Geophysics
Abd. Rahman As-syakur, Takahiro Osawa, Fusanori Miura, I. Wayan Nuarsa, Ni Wayan Ekayanti, I. Gusti Bagus Sila Dharma, I. Wayan Sandi Adnyana, I. Wayan Arthana, Tasuku Tanaka
DYNAMICS OF ATMOSPHERES AND OCEANS
(2016)
Article
Meteorology & Atmospheric Sciences
Abd. Rahman As-syakur, I. Wayan Sandi Adnyana, Made Sudiana Mahendra, I. Wayan Arthana, I. Nyoman Merit, I. Wayan Kasa, Ni Wayan Ekayanti, I. Wayan Nuarsa, I. Nyoman Sunarta
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2014)
Article
Environmental Sciences
Abd. Rahman As-Syakur, I. Wayan Sandi Adnyana, I. Wayan Arthana, I. Wayan Nuarsa
Proceedings Paper
Agronomy
N. M. R. Suarni, N. G. A. M. Ermayanti, N. N. Wirasiti, I. G. Mahardika
Summary: This study found that substitution of moringa leaf meal in commercial feed has a positive effect on improving the sperm quality of male rabbits. The optimal substitution rate was found to be 30%, but substituting up to 45% also yielded good results.
7TH INTERNATIONAL CONFERENCE ON SUSTAINABLE AGRICULTURE, FOOD AND ENERGY
(2021)
Article
Agriculture, Dairy & Animal Science
Nyoman Sadra Dharmawan, I. Made Damriyasa, I. Gede Mahardika, Kadek Swastika, Luh Putu Hartiningsih, Kadek Karang Agustina
Proceedings Paper
Agriculture, Multidisciplinary
N. N. Suryani, I. W. Suarna, I. G. Mahardika
1ST INTERNATIONAL CONFERENCE ON FOOD AND AGRICULTURE 2018
(2018)
Article
Agriculture, Dairy & Animal Science
IG Mahardika, D Sastradipradja, T Sutardi, IK Sumadi
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
(2000)
Article
Agriculture, Dairy & Animal Science
IG Mahardika, D Sastradipradja, T Sutardi, IK Sumadi
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES
(2000)
