• 대한공간정보학회지
• /
• 제16권1호
• /
• pp.33-41
• /
• 2008

특정 기간 사이의 토지의 변화들을 파악하는 것은 매우 중요하다. 그러나, 토지를 변화 시킬 수 있는 요소들은 많이 존재할 수 있기 때문에 그러한 요인들을 규명하기란 쉽지 않다. 따라서 본 연구에서는 이러한 토지 변화 요인들을 정량적으로 사용하여 시뮬레이션을 수행하고자 하였다. CLUE-S 모델을 이용하여 사용한 자료는 1987년 Landsat TM 영상과 2001년 Landsat ETM+ 영상이며, 1987년부터 2010년까지 23년 동안의 토지 이용도를 시뮬레이션 하였다. 그 결과, 2001년 영상의 감독 분류 결과와 시뮬레이션을 수행한 2001년 결과 사이의 정확도는 93.69%가 나왔으며, 이러한 결과를 통해 미래의 토지 피복 현황도를 예측할 수 있었다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2008년도 학술발표회 논문집
• /
• pp.194-198
• /
• 2008

Significant soil erosion and water quality degradation issues are occurring at highland agricultural areas of Kangwon province because of agronomic and topographical specialities of the region. Thus spatial and temporal modeling techniques are often utilized to analyze soil erosion and sediment behaviors at watershed scale. The Soil and Water Assessment Tool (SWAT) model is one of the watershed scale models that have been widely used for these ends in Korea. In most cases, the SWAT users tend to use the readily available input dataset, such as the Ministry of Environment (MOE) land cover data ignoring temporal and spatial changes in land cover. Spatial and temporal resolutions of the MOE land cover data are not good enough to reflect field condition for accurate assesment of soil erosion and sediment behaviors. Especially accelerated soil erosion is occurring from agricultural fields, which is sometimes not possible to identify with low-resolution MOD land cover data. Thus new land cover data is prepared with cadastral map and high spatial resolution images of the Doam-dam watershed. The SWAT model was calibrated and validated with this land cover data. The EI values were 0.79 and 0.85 for streamflow calibration and validation, respectively. The EI were 0.79 and 0.86 for sediment calibration and validation, respectively. These EI values were greater than those with MOE land cover data. With newly prepared land cover dataset for the Doam-dam watershed, the SWAT model better predicts hydrologic and sediment behaviors. The number of HRUs with new land cover data increased by 70.2% compared with that with the MOE land cover, indicating better representation of small-sized agricultural field boundaries. The SWAT estimated annual average sediment yield with the MOE land cover data was 61.8 ton/ha/year for the Doam-dam watershed, while 36.2 ton/ha/year (70.7% difference) of annual sediment yield with new land cover data. Especially the most significant difference in estimated sediment yield was 548.0% for the subwatershed #2 (165.9 ton/ha/year with the MOE land cover data and 25.6 ton/ha/year with new land cover data developed in this study). The results obtained in this study implies that the use of MOE land cover data in SWAT sediment simulation for the Doam-dam watershed could results in 70.7% differences in overall sediment estimation and incorrect identification of sediment hot spot areas (such as subwatershed #2) for effective sediment management. Therefore it is recommended that one needs to carefully validate land cover for the study watershed for accurate hydrologic and sediment simulation with the SWAT model.

• 대한원격탐사학회지
• /
• 제20권5호
• /
• pp.315-327
• /
• 2004

Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.

• 한국환경과학회지
• /
• 제11권9호
• /
• pp.925-931
• /
• 2002

Land-use types should be included in air pollutant diffusion model because a complex mixture of various land-use patterns with computational grid can make errors in calculation of several parameters. However, the air pollutant diffusion model has generally been treated with a uniform component with land-use type in each mesh because of the complexity of the simulation. This study presents a numerical simulation of the horizontal distribution of $O_3$dry deposition velocity during summertime in Busan metropolitan city. The calculation of the meteorological field was conducted using the land cover data. Simulation has been performed by the following two scenarios : (1) one with current land cover data, and (2) the other with only land and sea for the surface characteristics. The results from each scenario reveals considerable differences on the meteorological fields and these differences can cause changes in the calculation values of $O_3$deposition velocity.

• Journal of Forest and Environmental Science
• /
• 제39권3호
• /
• pp.167-179
• /
• 2023

The extent of change in the Land use/Land cover (LULC) of Okomu National Park (ONP) and fringe communities was evaluated. High resolution Landsat imagery was used to identify the major vegetation cover/land use systems and changes around the national park and fringe communities while field visits/ground truthing, involving the collection of coordinates of the locations was carried out to ascertain the various land cover/land use types identified on the images, and the extent of change over three-time series (2000, 2010 and 2020). The change detection was analyzed using area calculation, change detection by nature and normalized difference vegetation index (NDVI). The result of the classification and analysis of the LULC Change of ONP and fringe communities revealed an alarming rate of encroachment into the protected area. All the classification features analyzed had notable changes from 2000-2020. The forest, which was the dominant LULC feature in 2000, covering about 66.19% of the area reduced drastically to 36.12% in 2020. Agricultural land increased from 6.14% in 2000 to 34.06% in 2020 while vegetation (degraded land) increased from 27.18% in 2000 to 38.89% in 2020. The magnitude of the change in ONP and surroundings showed the forest lost -247.136 km² (50.01%) to other land cover classes with annual rate change of 10%, implying that 10% of forest land was lost annually in the area for 20 years. The NDVI classification values of 2020 indicate that the increase in medium (399.62 km² ) and secondary high (210.17 km² ) vegetation classes which drastically reduced the size of the high (38.07 km² ) vegetation class. Consequent disappearance of the high forests of Okomu is inevitable if this trend of exploitation is not checked. It is pertinent to explore other forest management strategies involving community participation.

• Journal of Forest and Environmental Science
• /
• 제37권1호
• /
• pp.44-51
• /
• 2021

Rapid urbanization and population growth have caused substantial land use land cover (LULC) change in the Kathmandu valley. The lack of temporal and geographical data regarding LULC in the middle mountain region like Kathmandu has been challenging to assess the changes that have occurred. The purpose of this study is to investigate the changes in LULC in Chandragiri Municipality between 1996 and 2017 using geographical information system (GIS) and remote sensing. Using Landsat imageries of 1996 and 2017, this study analyzed the LULC change over 21 years. The images were classified using the Maximum Likelihood classification method and post classified using the change detection technique in GIS. The result shows that severe land cover changes have occurred in the Forest (11.63%), Built-up areas (3.68%), Agriculture (-11.26%), Shrubland (-0.15%), and Bareland (-3.91%) in the region from 1996 to 2017. This paper highlights the use of GIS and remote sensing in understanding the changes in LULC in the south-west part of Kathmandu valley.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2016년도 학술발표회
• /
• pp.49-49
• /
• 2016

The impact of land cover changes on streamflow of the Akaki catchment will be assessed using Soil and Water Assessment Tool (SWAT) model. The study will analyze the historical land cover changes (1993 to 2016) that have taken place in the catchment and its effect on the streamflow of the study area. Arc GIS will be used to analysis the satellite images obtained from the United States Geological Survey (USGS). To investigate the impact of land cover change on streamflow the model set up will be done using readily available spatial and temporal data, and calibrated against measured discharge. Two third of the data will be used for model calibration (1993?2000) and the remaining one-third for model validation (2001?2004). Model performance will be evaluated by using Nash and Sutcliff efficiency (NS) and coefficient of determination (R2). The calibrated model will be used to assess two land cover change (2002 and 2016) scenarios and its likely impacts of land use changes on the runoff will be quantified. The evaluation of the model response to these changes on streamflow will be presented properly. The study will contribute a lot to understand land use and land cover change on streamflow. This enhances the ability of stakeholder to implement sound policies to minimize undesirable future impacts and management alternatives which have a significant role in future flood control of the study area.

• 대한원격탐사학회지
• /
• 제25권1호
• /
• pp.71-83
• /
• 2009

본 연구는 한반도 토지이용 및 토지피복 모니터링에 필요한 현존 자료의 특성과 활용 가능성을 분석하여 문제점을 파악하고 향후 한반도 전역의 국토모니터링을 위한 기술적 방안을 제시하고자 한다. 한반도 토지이용과 관련된 비 공간자료는 1911년부터 집계된 지적통계자료가 있다. 초기의 연도별 지적통계자료는 토지이용 변화의 추세를 가늠하는데 사용될 수 있지만, 분단 이후의 자료는 지목과 실제 토지이용 상태의 불일치로 토지 이용 모니터링에 직접적으로 사용하기에는 어려움이 있다. 한반도 토지 이용 및 토지 피복을 모니터링하기 위한 공간자료는 1970년대 이후 위성 영상자료를 이용하여 제작한 토지피복도가 주를 이루고 있다. 두 기관에서 독자적으로 제작된 서로 다른 시기의 북한 토지피복도를 이용하여 토지피복변화를 분석한 결과, 사용된 위성영상의 계절별 차이와 위성영상 분류과정에 적용된 분류등급과 분류방법의 불일치 등으로 직접 비교에 많은 어려움이 있었다. 지속적인 한반도 토지이용 및 토지피복 모니터 링을 위한 토지피복도 제작은 위성영상의 계절적 조건, 분류방법, 좌표등록 등에 호환성이 보장되도록 단일의 기준이 마련되어야 하며, 아울러 국제적인 토지피복 분류등급이나 정확도에서도 호환성을 갖추어야 한다.

• 한국측량학회지
• /
• 제35권4호
• /
• pp.249-260
• /
• 2017

UHI (Urban Heat Island) is an important environmental issue occurring in highly developed (or urbanized) area such as Seoul Metropolitan City of Korea due to modification of the land surface by man-made structures. With the advance of the remote sensing technique, land cover types and LST (Land Surface Temperature) influencing UHI were frequently investigated describing that they have a positive relationship. However, the concept of land cover considers material characteristics of the urban cover in a comprehensive way and does not provide information on how human activities influence on LST in detail. Instead, land use reflects ways of land use management and human life patterns and behaviors, and explains the relationship with human activities in more details. Using this concept, LST was segmented according to land use types from the Landsat imagery to identify the human-induced heat from the surface and interannual and seasonal variation of LST with GIS. The result showed that the LST intensity of Seoul was greatest in the industrial area and followed by the commercial and residential areas. In terms of size, the residential area could be defined as the major contributor among six urban land use types (i.e., residential, industrial, commercial, transportation, etc.) affecting UHI during daytime in Seoul. For temperature, the industrial area was highest and could be defined as a major contributor. It was found that land use type was more appropriate to understand the human-induced effect on LST rather than land cover. Also, there was no significant change in the interannual pattern of LST in Seoul but the seasonal difference provided a trigger that the human life pattern could be identified from the satellite-derived LST.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.96-99
• /
• 2003

Land cover map is a typical GIS database which shows the Earth's physical surface differentiated by standardized homogeneous land cover types. Satellite images acquired by Landsat TM were primarily used to produce a land cover map of 7 land cover classes; however, it now becomes to produce a more accurate land cover classification dataset of 23 classes thanks to higher resolution satellite images, such as SPOT-5 and IKONOS. The use of the newly produced high resolution land cover map of 23 classes for such activities to estimate non-point sources of pollution like water pollution modeling and atmospheric dispersion modeling is expected to result a higher level of accuracy and validity in various environmental monitoring results. The estimation of pollution from non-point sources using GIS-based modeling with land cover dataset shows fairly accurate and consistent results.