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INTERNATIONAL JOURNAL OF ENVIRONMENT AND GEOSCIENCES
Published by Universitas Udayana
ISSN : -     EISSN : 25498878     DOI : https://doi.org/10.24843/ijeg.2017.v01.i01
Core Subject : Science, Agriculture, Social,
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science
International Journal of Environment and Geosciences (e-ISSN 2549-8878) is a peer-reviewed journal and an international scholarly refereed research journal which aims to promote the theory and practice of environmental sciences, geosciences, earth sciences, engineering and management. This journal presents original research articles, letters as well as review articles, publishes the latest achievements and developments in the field of environmental studies (abiotics, biotics and cultural/socials) and geosciences. All contributions shall be rigorously refereed and selecting on the basis of quality and originality of the work as well as the breadth of interest to readers. Accepted papers will immediately appear online.
Arjuna Subject : Ilmu Lingkungan (semua ketegori) - Ilmu Lingkungan (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 1 No 1 (2017)" : 5 Documents clear
Application of GSMaP Product and Rain Gauge Data for Monitoring Rainfall Condition of Flood Events in Indonesia Nyoman Sugiartha; Kakuji Ogawara; Tasuku Tanaka; Made Sudiana Mahendra
International Journal of Environment and Geosciences Vol 1 No 1 (2017)
Publisher : Graduate Study of Environmental Sciences, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/ijeg.2017.v01.i01.p05

Abstract

Rainfall is one of main causes of floods. Monitoring of the rainfall is essential for understanding flood mechanism and early warning. Ground-based rain gauge is a conventional device to measure rainfall amount and considered as a point measurement. Satellite-based rainfall estimates provides complement measurement over wide area having few or even no in situ data. This study evaluates rainfall intensity variation and patterns preceding flood events in Indonesia for the period of 2003-2010 using the GSMaP_MVK satellite-based rainfall product with one hour and 0.1o x 0.1o resolutions and rain gauge station data as a benchmark. The analysed data are 3-hourly average and daily accumulation time steps. The chosen research locations were Medan City, Pekanbaru City, Indragiri Hulu Regency, Samarinda City and Manado City. Graphical comparisons of the GSMaP_MVK with the rain gauge data show discrepancies in capturing rainfall events and intensity. The GSMaP_MVK performs underestimation for the most areas, except Samarinda City, which is overestimated. Short-term period rainfall pattern is the most frequent occurred preceding flood events for the entire study areas which indicate that the areas are more susceptible to flash floods and river overflows. Overall, the GSMaP_MVK product provides promising potentiality for the application of monitoring rainfall conditions preceding flood events over the research locations. Statistical verifications reveal that on average, correlation coefficients are (0.22-0.54) and (0.65-0.83) for 3-hourly and daily scale, respectively. While, probability of rain detections (PODs) are (0.57-0.75) and (0.93-0.99), accordingly.
Multi-temporal Analysis for Differential Interferometry Synthetic Aperture Radar (D-InSAR) and Its Application to Monitoring Land Surface Displcements Putu Edi Yastika; Norikazu Shimizu; Tasuku Tanaka; Takahiro Osawa
International Journal of Environment and Geosciences Vol 1 No 1 (2017)
Publisher : Graduate Study of Environmental Sciences, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/ijeg.2017.v01.i01.p01

Abstract

Land subsidence rate in Semarang has been observed by D-InSAR technique based on ALOS-PALSAR data on ascending orbits, which is processed by GMTSAR and ArcGIS software. Two kind of methods namely single D-InSAR and Multi-Temporal D-InSAR has been done. By employing SRTM3 and ASTER1 DEM data to remove the topography component, total 67 pairs of inteferogram has generated. Northeast area and shoreline area has largest subsidence about 20-32 cm for 4 years or average rate 5-8 cm/year. Since the northwest area and center area has lower subsidence rate and even no remarkable subsidence occurred, this area seems to be stable comparing the northeast area. Removing the topography component phase to get displacement phase from the phase interferogram by using SRTM3 DEM and ASTER1 DEM data respectively, the both results coincided with 0.995 correlation value. The coherence threshold is an important factor to get better accuracy, but if setting the threshold too high, the process of interference will be failed and not be able to obtain the results in a lot of area. The perpendicular baseline and the temporal baseline (time period) is an important factor to determining the coherence threshold. By using many scenes the Multi-Temporal D-InSAR was applied, and by selecting good pairs of the interferograms, accuracy of the results will be improved. The correlation value for GPS data eventually increased from 0.63 to 0.77.
Remote Sensing Application to Estimate Groundwater Recharge in Denpasar and Surrounding Areas I Nyoman Artabudi; Takahiro Osawa; I Wayan Budiarsa Suyasa
International Journal of Environment and Geosciences Vol 1 No 1 (2017)
Publisher : Graduate Study of Environmental Sciences, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/ijeg.2017.v01.i01.p02

Abstract

Water is one of the most important resources for human life, both to support the daily activities and for irrigation purposes as well as supporting tourism industry. Until now the groundwater is still ranked as the major needs, especially in densely populated areas like Denpasar. Groundwater is renewable natural resources, and plays an important role in the provision of water supplies for various purposes. Understanding the spatial variability of groundwater recharge is very important for proper water resource management. Precipitation measurement by satellite especially Global Satellite Mapping for Precipitation, can be applied to large areas only, it can be stated that use of satellite data always results in an improvement of the spatial precipitation estimate if gauge density is low. The aim of this research was to determine precipitation patterns, precipitation groundwater relationship and to estimate local groundwater recharge rate across the Southern Bali basin using remote sensing. This study considers the direct estimation of recharge using recovery of the groundwater level (?H) and total precipitation (Pt) during the wet period. Groundwater recharge was estimated from these two variables using a simple regression equation. The patterns of precipitation in research area was monsoonal dry season occurred in July to August, wet season occurs during November to April and punctuated by transitional season. Precipitation influence on groundwater oscillation occurred on 1~2 months earlier. The amount of recharge rate in the study area based on the results of the study period 2005~2009, for the precipitation data from Global Satellite Mapping for Precipitation ranges from 218 ~ 220 mm per year or about 26 percent of the annual average of precipitation and 650 ~ 660 mm per year or about 32 percent based on the rain gauge data.
Land Cover Change Detection Using Landsat Data in Giao Thuy District, Nam Dinh Province, Vietnam Nguyen Tuyet Lan; Takahiro Osawa; I Wayan Nuarsa; Ngo The An
International Journal of Environment and Geosciences Vol 1 No 1 (2017)
Publisher : Graduate Study of Environmental Sciences, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/ijeg.2017.v01.i01.p03

Abstract

Giao Thuy located a coastal area, which has fully the characteristed of microclimate Red River delta. This study was conducted to detect the land cover changes from 2000 to 2015 and the causes. The changes are evaluated using Landsat data by method of land use classification combined with interviews. The results showed that most portion of the land cover class was crops land and land cover change was crops land decreases, forest land rises, aquaculture ponds increase, surface water reduces and unuse flat land area increases. The causes were policy issuses, market, economic, salinity intrusion, climate change and deposits alluvial.
Remote Sensing and GIS Approach for Landslide Susceptibility Mapping: A Case Study in Hofu City, Yamaguchi, Japan Benita Nathania; Fusanori Muira
International Journal of Environment and Geosciences Vol 1 No 1 (2017)
Publisher : Graduate Study of Environmental Sciences, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/ijeg.2017.v01.i01.p04

Abstract

Landslide is one of the natural hazards that often initiates by the interaction between environmental factors and triggering factor. The identi?cation of areas where landslides are likely to occur is important for the reduction of potential damage. This study utilizes remote sensing data and Geographic Information System (GIS) to identify areas where landslides are likely to occur and generates landslide susceptibility map based on logistic regression model. The study area is located in Hofu city, Yamaguchi prefecture, Japan. The data that were used in this study are satellite imagery from ALOS AVNIR-2, elevation and geology data from GSI, Rainfall data from AMEDAS, and landslide inventory map provided from Ministry of Land, Infrastructure, Transportation and Tourism. The result from this study revealed that elevation from > 50 to < 350 m, slope angle from> 5° to < 50°, slope direction of north and northeast, land cover of agriculture, urban, bare soil, and forest, and lithology of graniodorite, fan deposits, and middle terrace are favorable for landslide occurrence. The landslide susceptiility map showed that 98% of the result calculations of logistic regression are similar to the historical data of landslide event which is among 911 landslide points, 899 points were existed in high and very high susceptibility areas.

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