• The Journal of Engineering Geology
• /
• v.31 no.4
• /
• pp.549-559
• /
• 2021

The Arctic Circle's huge amounts of fossil fuels and mineral resources are being developed and subjected to active construction projects. Global efforts are continuing to actively respond to climate change, but the dependence on fossil fuels remains high. This study reports a preliminary survey conducted in Alberta, Canada, where oil sand resources are actively developed. A land cover map was prepared using satellite imagery to reduce the cost and time of surveying a wide area. Results likely useful to resource development projects such as ground surface temperature and snow cover distribution were derived by using the obtained image classification results. It is expected that the results of the present research and analysis will be used to establish strategies for the successful promotion and operation of projects to develop resources in the Arctic.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.4
• /
• pp.45-53
• /
• 2013

Global warming causes sea levels to rise and global changes apparently taking place including coastline changes. Coastline change due to sea level rise is also one of the most significant phenomena affected by global climate change. Accordingly, Coastline change detection can be utilized as an indicator of representing global climate change. Generally, Coastline change has happened mainly because of not only sea level rise but also artificial factor that is reclaimed land development by mud flat reclamation. However, Arctic coastal areas have been experienced serious change mostly due to sea level rise rather than other factors. The purposes of this study are automatic extraction of coastline and identifying change. In this study, in order to extract coastline automatically, contrast of the water and the land was maximized utilizing modified NDWI(Normalized Difference Water Index) and it made automatic extraction of coastline possibile. The imagery converted into modified NDWI were applied image processing techniques in order that appropriate threshold value can be found automatically to separate the water and land. Then the coastline was extracted through edge detection algorithm and changes were detected using extracted coastlines. Without the help of other data, automatic extraction of coastlines using LANDSAT was possible and similarity was found by comparing NLCD data as a reference data. Also, the results of the study area that is permafrost always frozen below $0^{\circ}C$ showed quantitative changes of the coastline and verified that the change was accelerated.

• Journal of Environmental Impact Assessment
• /
• v.17 no.5
• /
• pp.321-330
• /
• 2008

Methane is a potent greenhouse gas and methane emissions from landfills have been linked to global warming. In this study, LandGEM (Landfill Gas Emission Model) was applied to predict landfill gas quantity over time, and then this result was compared with the data surveyed on the site, Cheongju Megalo Landfill. LandGEM allows the input of site-specific values for methane generation rate (k) and potential methane generation capacity $L_o$, but in this study, k value of 0.05/yr and $L_o$ value of $170m^3/Mg$ were considered to be most appropriate for reflecting non-arid temperate region conventional landfilling, Cheongju Megalo Landfill. High discrepancies between the surveyed data and the predicted data about landfill gas seems to be derived from insufficient compaction of daily soil-cover, inefficient recovery of landfill gas and banning of direct landfilling of food garbage waste in 2005. This study can be used for dissemination of information and increasing awareness about the benefits of recovering and utilizing LFG (landfill gas) and mitigating greenhouse gas emissions.

• Korean Journal of Remote Sensing
• /
• v.39 no.1
• /
• pp.23-45
• /
• 2023

Tuvalu is a small reef islands country in the Pacific Ocean. Its coastal regions are very much dynamic due to the profound effects of tropical cyclones and sea level rise (SLR). However, research works on coastline dynamics of Tuvalu mainly cover its capital, Funafuti. Therefore, this review summarizes the extent of long-term coastal changes in different islets of Funafuti and on overall Tuvalu. In Funafuti, highly accreting areas are Te Afualiku, Fuafatu, Motugie, and Amatuku, and highly eroding areas are Fuagea and Tefala with the fully disappeared islet of Vasafua after 2005. However, in spite of different causes and supposition of scientists on disappearing these lands the accretion is more dominant than erosion which resulted in 7.3% net increase of land areas of Tuvalu over 117 years till 2015. Severe tropical cyclones mainly caused accretion of land areas by forming coral rubble rampart formation and further reworks and erosion to small sandy islands whereas frequent low-energy cyclones mainly caused erosion. Though, till now severe erosion of coastal areas are not evident by global SLR, islets of Funafuti experienced remarkable shoreline increase as formation of 30-40 m wide rubble rampart formation along 19 km in 1971 by tropical cyclone Bebe and net increase of area of 3.45 ha by tropical cyclone Pam in 2015. In spite of such overall accretion of coastal areas several scientists suspect drowning of its areas in future because of high SLR (~5.1±0.7 mm/year) at Funafuti which supposedly will not work as a breakwater anymore. Thus, protection measures should be taken to prevent coastline erosion as well as land reclamation activities should be done following the global examples.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.52 no.3
• /
• pp.39-45
• /
• 2010

Quantification of carbon absorption and understanding the human induced land use changes (LUC) forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by LUC through remote sensing technology. The Landsat imagery four time periods was classified with the hybrid classification method in order to quantify carbon absorption by LUC. Thereafter, for estimating the amount of carbon absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated with the crown width extracted from digital forest cover type map. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC guideline, was used to convert the stand biomass into the amount of carbon absorption. Total carbon absorption has been modeled by taking areal estimates of LUC of four time periods and carbon factors for land use type and standing biomass. Results of this study, through LUC suggests that over a period of construction, 7.10 % of forest and 9.43 % of barren were converted into urban. In the conversion process, there has been a loss of 6.66 t/ha/y (7.94 %) of carbon absorption from the study area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.2
• /
• pp.143-150
• /
• 2013

Recently, environmental issues such as climate warming, ozone layer depletion, reduction of tropical forests and desertification are emerging as global environmental problems beyond national problems. And international attention and effort have been carried out in many ways to solve these problems. In this study, the growth of green was calculated quantitatively using the technique of remote sensing and temperature change was figured out through temperature extraction in the city. The land-cover changes and thermal changes for research areas were analyzed using Landsat TM images on May 2002 and May 2009. Surface temperature distribution was calculated using spectral degree of brightness of Band 6 that was Landsat TM thermal infrared sensor to extract the ground surface temperature in the city. As a result of research, the area of urban green belt was increased by $2.87km^2$ and the ground surface temperature decreased by $0.6^{\circ}C{\sim}0.8^{\circ}C$ before and after tree planting projects. Henceforth, if the additional study about temperature of downtown is performed based on remote sensing and measurement data, it will contribute to solve the problems about the urban environment.

• Atmosphere
• /
• v.21 no.4
• /
• pp.337-347
• /
• 2011

In this paper, we developed a detection and correction method of noisy pixels embedded in the time series of normalized difference vegetation index (NDVI) data based on the spatio-temporal continuity of vegetation conditions. For the application of the method, 25-year (1982-2006) GIMMS (Global Inventory Modeling and Mapping Study) NDVI dataset over the Korean peninsula were used. The spatial resolution and temporal frequency of this dataset are $8{\times}8km^2$ and 15-day, respectively. Also the land cover map over East Asia is used. The noisy pixels are detected by the temporal continuity check with the reference values and dynamic threshold values according to season and location. In general, the number of noisy pixels are especially larger during summer than other seasons. And the detected noisy pixels are corrected by the iterative method until the noisy pixels are completely corrected. At first, the noisy pixels are replaced by the arithmetic weighted mean of two adjacent NDVIs when the two NDVI are normal. After that the remnant noisy pixels are corrected by the weighted average of NDVI of the same land cover according to the distance. After correction, the NDVI values and their variances are increased and decreased by 5% and 50%, respectively. Comparing to the other correction method, this correction method shows a better result especially when the noisy pixels are occurred more than 2 times consistently and the temporal change rates of NDVI are very high. It means that the correction method developed in this study is superior in the reconstruction of maximum NDVI and NDVI at the starting and falling season.

• Journal of Korean Society for Geospatial Information Science
• /
• v.22 no.3
• /
• pp.79-85
• /
• 2014

For the successful operation of unmanned ground vehicles(UGVs), optimal path planning should be considered with trafficability analysis, threat analysis, and so on. From among these, trafficability analysis is immensely important for safeness of UGVs especially in the case of driving the off-road such as unpaved road, grassland, and open fields. Geographical information has a pivotal role in extracting data and measuring cost for specified regions of interest. In this paper, we review possibilities to apply Land Cover Map(LCM) as a new, fundamental source and propose a new generation method of trafficability analysis map for optimal path planning of UGV. The simulation results show that the proposed method significantly improve the previous method by applying LCM either alone or in combination with the other GIS.

• Korean Journal of Agricultural Science
• /
• v.48 no.3
• /
• pp.433-446
• /
• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.3
• /
• pp.77-84
• /
• 2015

The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.