Papers - SAWAHIKO Shimada
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Nomadic responses to rainfall: Nighttime light evidence from wadis in Djibouti Reviewed International coauthorship International journal
Bouh Omar Ali, Yutaka Ito, Shuichi Oyama, Sawahiko Shimada & Yuki Yamamoto
Scientific African 25 e02337 2024.09
Language：English Publishing type：Research paper (scientific journal) Publisher：Elsevier B.V.
This study examined how precipitation affects human activity in dry areas, focusing on Djibouti's nomads. Using satellite data, researchers found increased nighttime light brightness near wadis after rainfall, indicating higher nomadic activity. This effect decreased with distance from wadis and was absent in urban areas. The findings highlight water's crucial role in nomadic settlements and resource management, providing valuable insights for policymakers in African countries.
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Comprehensive Analysis of Land Use and Cover Dynamics in Djibouti Using Machine Learning Technique: A Multi-Temporal Assessment from 1990 to 2023 Reviewed International coauthorship International journal
Pandit S, Shimada S & Dube T
Environmental Challenges 15 100920 2024.04
Language：English Publishing type：Research paper (scientific journal) Publisher：Elsevier
The study focuses on analyzing land use changes in Djibouti from 1990 to 2023 using remote sensing and machine learning techniques. We identified seven major land cover classes shows declines in mangroves and farmland, and highlights expansions in built-up areas, water bodies, and barren lands over time.
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High‑resolution mapping of seasonal snow cover extent in the Pamir Hindu Kush using machine learning‑based integration of multi‑sensor data International journal
Abdul Basir Mahmoodzada, Pragyan Das, Divyesh Varade, Mohd Arslaan Akhtar, Sawahiko Shimada
Acta Geophysica 71 ( 6 ) 2024.01
Authorship：Last author Language：English Publishing type：Research paper (scientific journal) Publisher：Springer Link
This study proposes a framework to develop high-resolution snow cover area (SCA) products using freely available Sentinel-1 and MODIS data. Various Sentinel-1 parameters sensitive to snow are integrated with resampled MODIS normalized difference snow index (NDSI) data to estimate an equivalent NDSI for determining 15m resolution SCA. Equivalent NDSI is derived using machine learning regression with support vector machines (SVMs) and multilayer perceptron (MLP). Experiments were performed for northern Hindu Kush mountain regions in February and March 2019. SCA evaluation used thresholded NDSI from Landsat-8. SVM regression showed better SCA performance over MLP. Both SVM and MLP improved snow classification accuracy over resampled MODIS NDSI alone, with higher mean conditional kappa coefficients.
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Quantification of Amu River Riverbank Erosion in Balkh Province of Afghanistan during 2004–2020 Reviewed International journal
Abdul Basir Mahmoodzada, Divyesh Varade, Sawahiko Shimada, Hiromu Okazawa, Shafiqullah Aryan, Gulbuddin Gulab, Abd El-Zaher M. A. Mustafa, Humaira Rizwana, Yogesh K. Ahlawat and Hosam O. Elansary
land 12 ( 10 ) 1890 2023.10
Language：English Publishing type：Research paper (scientific journal) Publisher：MDPI
This study quantifies riverbank erosion along the Amu River in Afghanistan's Kaldar District from 2004-2020 using modeled river discharge data. A framework integrating multi-source data models erosion area based on: river discharge, river width, and erosion area. Discharge was modeled using ECMWF and ground data. River width was manually determined from Landsat imagery. Erosion area was calculated through shoreline analysis. From 2008-2020, average annual erosion was 5.4 km2, totaling 86.3 km2 during 2004-2020 due to flooding. Peak erosion occurred in 2008-2009, 2011-2012 and 2015-2016. Erosion area correlated linearly with discharge intensity and stream power (R2=0.84).
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FRACTURE-FAULT DETECTION USING DEEP LEARNING WITH STEPWISE ELIMINATION FROM SATELLITE IMAGES IN DJIBOUTI Reviewed International coauthorship International journal
Rubanga DP, May-Cuevas SA, Arvelyna Y & Shimada S
International Journal of GEOMATE 25 ( 108 ) 241 - 248 2023.08
Authorship：Last author Language：English Publishing type：Research paper (scientific journal)
This study focuses on accurately detecting fracture-fault structures in Djibouti using WV-3 high resolution imagery. A deep learning approach using a deep convolutional neural network (Deep-CNN) model is proposed. The model successfully identifies fracture-fault lines, contributing to sustainable water management and improving water security in Djibouti.
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THE CHARACTERISTICS AND DISTRIBUTION OF DEEP GROUNDWATER IN DJIBOUTI Reviewed International journal
Asakura Y, Shimada S, Hinokidani K, & Nakanishi Y
International Journal of GEOMATE 24 ( 104 ) 93 - 100 2023.04
Language：English Publishing type：Research paper (scientific journal)
This study examines the characteristics of groundwater quality in Djibouti using ion chromatography, stable isotope ratios of hydrogen and oxygen, and tritium concentrations. The results show that most groundwater samples are mixed with seawater or hot spring water and fossil seawater, and the concentration of NO3- is high at some sites.
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FAULT DETECTION USING PALSAR-1/2 IMAGE DATA FOR GROUNDWATER ANALYSIS IN CENTRAL AND SOUTHWEST OF DJIBOUTI Reviewed International coauthorship International journal
Arvelyna Y, Shimada S, May Cuevas S A, & Malow F A
International Journal of GEOMATE 24 ( 104 ) 109 - 116 2023.04
Language：English Publishing type：Research paper (scientific journal)
This study discusses a study that uses fault mapping to observe the possibility of fault-driven groundwater flow in Djibouti using PALSAR-1 and 2 data. The Geology Scoring Index was introduced to analyze the correlation of groundwater data with the geology setting of borehole sites.
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Peatland groundwater level in the Indonesian maritime continent as an alert for El Niño and moderate positive Indian Ocean dipole events Reviewed International coauthorship International journal
Albertus Sulaiman, Mitsuru Osaki, Hidenori Takahashi, Manabu D. Yamanaka, Raden Dwi Susanto, Sawahiko Shimada, Keiji Kimura, Takashi Hirano, Rahmawati Ihsani Wetadewi, Silsigia Sisva, Tsuyoshi Kato, Osamu Kozan, Hideyuki Kubo, Awaluddin Awaluddin & Nobuyuki Tsuji
scientific reports 13 939 2023.01
Language：English Publishing type：Research paper (scientific journal) Publisher：Springer Nature
The condition of Indonesia's peatlands drought and fire can occur before El Niño and after IOD+ peaks. This is attributed to a dropped sea surface temperature anomaly and decreased local rainfall, causing a sharp drop in GWL. The research suggests monitoring GWL variability in peatland to serve as an alert for extreme climate events associated with El Niño and/or moderate IOD+.
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Water resources modeling of the Ali Faren catchment in the Ambouli watershed, Djibouti Reviewed
Hiroyuki TOSAKA, Aurelien HAZART, Toru YORITATE, Sergio Azael MAY CUEVAS, Sawahiko SHIMADA, Yasuhiro NAKANISHI, Fadoumo A. MALOW
Journal of Arid Land Studies 32 ( S ) 313 - 317 2022.12
Language：English Publishing type：Research paper (international conference proceedings)
This study explores the potential of groundwater in Djibouti. A numerical hydrological model and field survey technologies were used to analyze the water cycling in Ali Faren catchment.
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Teruaki IRIE, Shuhei SAITO, Sergio Azael MAY CUEVAS, Shinji SUZUKI, Fumio WATANABE, Sawahiko SHIMADA, Hassan A. BARKAD
Journal of Arid Land Studies 32 ( S ) 193 - 197 2022.12
Language：English Publishing type：Research paper (international conference proceedings)
The study investigated the meteorological conditions of a farm in Dikhil, Djibouti, and evaluated the windbreak effect of hedgerows to plan a pilot farm in Ali Faren based on wind dynamics simulated using observed meteorological parameters.
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Applicability of farmlands detection in Djibouti from satellite imagery using deep learning Reviewed
Takumi SATO, Ayako SEKIYAMA, Syuhei SAITO, Sawahiko SHIMADA
Journal of Arid Land Studies 32 ( S ) 181 - 185 2022.12
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
The study investigated the use of Mask-R-CNN and SVM for farmland detection in Djibouti using Sentinel-2 data.
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Sergio Azael MAY CUEVAS, Denis Pastory RUBANGA, Shuhei SAITO, Ayako SEKIYAMA, Sawahiko SHIMADA, Dayah Aden GUIRREH, Abdillahi Houssein ABDALLAH
Journal of Arid Land Studies 32 ( S ) 165 - 169 2022.12
Language：English Publishing type：Research paper (international conference proceedings)
The study explores the use of Unmanned Aerial Vehicles (UAV) and 3D cloud point data generated in Djibouti. The study found a high accuracy for identifying "Ground" and "High vegetation".
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Preliminary study on improvement of soil water retention characteristics by Spirulina. Reviewed
Shinji SUZUKI, Satoru WATANABE, Abdillahi Ismail OMAR, Fumio WATANABE, Sawahiko SHIMADA
Journal of Arid Land Studies 32 ( S ) 49 - 52 2022.12
Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)
The study investigates the effect of Spirulina and Extracellular Polymeric Substances (EPS) on the water holding capacity of soil.
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Satoru TANAKA, Shimpei TAKAHASHI, Rikako KIMURA, Sawahiko SHIMADA
Journal of Arid Land Studies 32 ( S ) 19 - 23 2022.12
Language：English Publishing type：Research paper (international conference proceedings)
Using of the GBIF database on plant species in Djibouti , a total of 6982 vascular plants from 561 species were found, representing 71.6% of the species reported in the literature.
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Assessment of Three Automated Identification Methods for Ground Object Based on UAV Imagery
Ke Zhang, Sarvesh Maskey, Hiromu Okazawa, Kiichiro Hayashi, Tamano Hayashi, Ayako Sekiyama, Sawahiko Shimada, Lameck Fiwa
Sustainability 14 ( 21 ) 14603 2022.11
Publisher：MDPI AG
<jats:p>Identification and monitoring of diverse resources or wastes on the ground is important for integrated resource management. The unmanned aerial vehicle (UAV), with its high resolution and facility, is the optimal tool for monitoring ground objects accurately and efficiently. However, previous studies have focused on applying classification methodology on land use and agronomy, and few studies have compared different classification methods using UAV imagery. It is necessary to fully utilize the high resolution of UAV by applying the classification methodology to ground object identification. This study compared three classification methods: A. NDVI threshold, B. RGB image-based machine learning, and C. object-based image analysis (OBIA). Method A was the least time-consuming and could identify vegetation and soil with high accuracy (user’s accuracy > 0.80), but had poor performance at classifying dead vegetation, plastic, and metal (user’s accuracy < 0.50). Both Methods B and C were time- and labor-consuming, but had very high accuracy in separating vegetation, soil, plastic, and metal (user’s accuracy ≥ 0.70 for all classes). Method B showed a good performance in identifying objects with bright colors, whereas Method C showed a high ability in separating objects with similar visual appearances. Scientifically, this study has verified the possibility of using the existing classification methods on identifying small ground objects with a size of less than 1 m, and has discussed the reasons for the different accuracy of the three methods. Practically, these results help users from different fields to choose an appropriate method that suits their target, so that different wastes or multiple resources can be monitored at the same time by combining different methods, which contributes to an improved integrated resource management system.</jats:p>
DOI： 10.3390/su142114603
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Vegetation change in Tokyo's urban forest of Kinuta Park in last 30 years.
Kamimura Shumpei, Hinokidani Ko, Shimada Sawahiko
The Japanese Forest Society Congress 133 ( 0 ) 451 2022.05
Language：Japanese Publisher：THE JAPANESE FORESTRY SOCIETY
<p>[in Japanese]</p>
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Capability assessment of Sentinel-1 data for estimation of snow hydrological potential in the Khanabad watershed in the Hindu Kush Himalayas of Afghanistan Reviewed
Mahmoodzada AB, Varade D, Shimada S, Rezazada FA, Mahmoodzada AS, Jawher AN, Toghyan
Remote Sensing Applications: Society and Environment 26 1 - 11 2022.04
Language：English Publishing type：Research paper (scientific journal)
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Factors Influencing Farmers’ Adoption of Soil Conservation Development Reviewed
Anissa Gara, Edwin P. Mhede, Sawahiko Shimada, Hiromichi Toyoda
Journal of Social Economics Research 7 ( 2 ) 83 - 90 2020.12
Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)
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Efficiency Evaluation of Solar Pumping System for Wadi Agriculture in Djibouti Reviewed
MAKOTO SHINOZAKI, SAWAHIKO SHIMADA, AYAKO SEKIYAMA, KIYOSHI TAJIMA, HASSAN ALI BARKAD
International Journal of Environmental and Rural Development 11 ( 2 ) 98 - 103 2020.12
Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)
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Early identification of Tuta absoluta in tomato plants using deep learning Reviewed
Lilian Mkonyi, Denis Rubanga, Mgaya Richard, Never Zekeya, Shimada Sawahiko, Baraka Maiseli, Dina Machuve
Scientific African 10 2020.11
Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)