• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.2023-2027
• /
• 2008

교통과 산업의 발달로 농촌인구의 감소가 빠르게 진행되고, 도시로 유입된 인구의 거주 공간 확보를 위해 도시주변의 피복 변화가 빠르게 진행되고 있다. 도시 지표의 대부분이 아스팔트나 콘크리트 등으로 피복되어 있어 도심의 기온이 교외와 비교하여 높게 형성되는 도시열섬현상(urban heat island, UHI)이 두드러지고 있다. 따라서 도시열섬현상 해소 대책으로 다양한 방법들이 분야 별로 제안되고 있다. 본 연구에서는 청주시 소재(미호천과 무심천을 대상으로) 하천으로 부터 떨어진 거리에 따른 열환경에 대하여 토지 피복에 따른 공간적 특성 분석을 수행함으로서 하천이 도심지 열 환경에 미치는 영향에 대하여 조사하였다. 하천을 중심으로 $0{\sim}1000m$ 까지 200m 간격의 버퍼를 생성하고 Landsat 영상에 의한 NDVI와 온도분포도를 이용하여 청주시 하천의 근접성에 따른 NDVI 및 온도 분포 분석 결과, NDVI는 하천을 기준으로 거리가 멀어질수록 점차적으로 증가하는 경향을 보였고 온도는 감소하는 것으로 나타났다. 또한 Quick-bird 영상에 의한 토지피복도와 NDVI, 온도 데이터를 중첩분석한 결과 NDVI는 산림-경작지-초지-나지-시가지 및 건조지 순으로 나타났고 평균온도는 NDVI의 역순으로 나타났다. 특히, 시가지를 비롯하여 공업지, 상업지 등 건조지역과 나지는 평균 $24^{\circ}C$ 이상으로 인구밀집지역은 높은 온도분포를 나타내는 것을 알 수 있었다.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.21 no.2
• /
• pp.53-64
• /
• 2018

This study aims to quantitatively evaluate the conservation priorities of unexecuted urban parks in Seoul both from an ecological and public perspective. To this end, two methodologies, ecological network analysis based on graph and circuit theory and accessibility analysis, were employed in order to assess ecological connectivity of and public accessibility to unexecuted parks, respectively. This study applied linkage-mapping methods (shortest path and current flow betweenness centrality) of connectivity analysis to an integrated map of landscape permeability. The population-weighted accessibility to unexecuted parks was measured based on a negative exponential distance decay function. As a result, for both ecological connectivity and accessibility, Gwanaksan, Suraksan, and Bulamsan urban natural parks are found to be the most important (rank 1-3) to be conserved. For these sites, inner park areas with conservation priorities for connectivity and accessibility were identified. The findings of the study can be used for giving conservation priority to the unexecuted urban parks in terms of long-term sustainable urban planning.

• 한국공간정보시스템학회:학술대회논문집
• /
• 2002.03a
• /
• pp.45-52
• /
• 2002

Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

• 한국지형공간정보학회:학술대회논문집
• /
• 2002.11a
• /
• pp.101-109
• /
• 2002

Since the industrialization spread out, the metropolitan areas of Seoul have been urbanized rapidly in Korea, without concern for the quality of further development and sufficient environmental management. Due to this fact, it has become increasingly more apparent that natural hazards, such as floods and landslides, occur frequently after the summer's heavy rains, and because of that, the scale of damage is getting larger. The purpose of this study is first to analyze the relationship between development and floods in the sub-basins of the study area. In addition to this, I would like to compare the influences of geomorphological characteristics upon the floods occurring in both the whole study area and the developed area in sub-basins.

• Korean Journal of Remote Sensing
• /
• v.23 no.5
• /
• pp.473-481
• /
• 2007

Joint Forest Management(JFM) is a concept of developing partnerships between fringe forest user groups and the Forest Department(FD) on the basis of mutual trust and jointly defined roles and responsibilities with regard to forest protection and development. In India, JFM was started during 1992 and it was implemented in many states. However success rate of JFM activity was not promising. Though there are many factors attributed to the failures, one of the main factors is the JFM site. This paper deals with the significant ground works to be done before planning for JFM using recent technologies such as remote sensing(RS) and Geographic Information System(GIS). Also it deals with the advantages of weighted overlay analysis in selecting suitable sites for JFM taking into consideration the various criteria. As a result of weighted overlay analysis, there were four types of suitability classes viz., less, moderate, highly and un-suitable. The moderately suitable class occupied maximum area(13209.64 ha) than less and highly suitable classes. If JFM is implemented on the suitability area, then the failure could be avoided in the future.

• Advances in environmental research
• /
• v.9 no.4
• /
• pp.251-273
• /
• 2020

Soil degradation has become a major worldwide environmental problem, particularly in arid and semi-arid climate zones due to irregular rainfall and the intensity of storms that frequently generate heavy flooding. The main objective of this study is the use of geographic information system and remote sensing techniques to quantify and to map the soil losses in the Wadi Saida watershed (624 ㎢) through the revised universal soil loss equation model and a proposed model based on the surface erosive runoff. The results Analysis revealed that the Wadi Saida watershed showed moderate to moderately high soil loss, between 0 and 1000 t/㎢/year. In the northern part of the basin in the region of Sidi Boubkeur and the mountains of Daia; which are characterized by steep slopes, values can reach up to 3000 t/㎢/year. The two models in comparison showed a good correlation with R = 0.95 and RMSE = 0.43; the use of the erosive surface runoff parameter is effective to estimate the rate of soil loss in the watersheds. The problem of soil erosion requires serious interventions, particularly in basins with disturbances and aggressive climatic parameters. Good agricultural practices and forest preservation areas play an important role in soil conservation.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1277-1290
• /
• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.10 no.3
• /
• pp.80-92
• /
• 2007

Forest fire is the dominant large-scale disturbance mechanism in the Korean temperate forest, and it strongly influences forest structure and function. Moreover burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. Vegetation rehabilitation may specifically vary according to burn severity after fire. To understand burn severity and process of vegetation rehabilitation at the damaged area after large-fire is required a lot of man powers and budgets. However the analysis of burn severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. For classifying fire damaged area and analyzing burn severity of Samcheok fire area occurred in 2000, Cheongyang fire in 2002, and Yangyang fire in 2005 we utilized Normalized Burn Ratio(NBR) technique. The NBR is temporally differenced between pre- and post-fire datasets to determine the extent and degree of change detected from burning. In this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ imagery to compute the NBR and evaluate large-scale patterns of burn severity at 30m spatial resolution. 65% in the Samcheok fire area, 91% in the Cheongyang fire area and 65% in the Yangyang fire area were corresponded to burn severity class above 'High'. Therefore the use of a remotely sensed Differenced Normalized Burn Ratio(${\Delta}NBR$) by RS and GIS allows for the burn severity to be quantified spatially by mapping damaged domain and burn severity across large-fire area.

• Journal of Korea Water Resources Association
• /
• v.40 no.8
• /
• pp.617-628
• /
• 2007

The purpose of this paper is to prepare snowmelt parameters using RS and GIS and to assess the snowmelt impact in SLURP (Semi-distributed Land Use-based Runoff Process) model for Chungju-Dam watershed $(6,661.5km^2)$. Three sets of NOAA AVHRR images (1998-1999, 2000-2001, 2001-2002) were analyzed to prepare snow-related data of the model during winter period. Snow cover areas were extracted using 1, 3 and 4 channels, and the snow depth was spatially interpolated using snowfall data of ground meteorological stations. With the snowmelt parameters, DEM (Digital Elevation Model), land cover, NDVI (Normalized Difference Vegetation Index) and weather data, the model was calibrated for 3 years (1998, 2000, 2001), and verified for 1 year (1999) using the calibrated parameters. The average Nash-Sutcliffe efficiencies for 4 years (1998-2001) discharge comparison with and without snowmelt parameters were 0.76 and 0.73 for the full period, and 0.57 and 0.19 for the period of January to May. The results showed that the spatially prepared snow-related data reduced the calibration effort and enhanced the model results.

• Journal of Convergence for Information Technology
• /
• v.10 no.12
• /
• pp.201-207
• /
• 2020

In this study, the practicality of unmanned aerial vehicle photography information was identified. Therefore, a total of four consecutive surveys were conducted on the field-level survey areas among the areas subject to photography using unmanned aerial vehicles, and the changes in crop conditions were analyzed using pictures of unmanned aerial vehicles taken during each survey. It is appropriate to collect and utilize photographic information by directly taking pictures of the survey area according to the time of the on-site survey using unmanned aerial vehicles in the field layer, which is an area where many changes in topography, crop vegetation, and crop types are expected. And it turned out that it was appropriate to utilize satellite images in consideration of economic and efficient aspects in relatively unchanged rice paddies and facilities. If the survey area is well equipped with systems for crop cultivation, deep learning can be utilized in real time by utilizing libraries after obtaining photographic data for a certain area using unmanned aircraft in the future. Through this process, it is believed that it can be used to analyze the overall crop and shipment volume by identifying the crop status and surveying the quantity per unit area.