• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.146-148
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• 2005

This study investigates to detect sea surface temperature (SST) and land cover change after tide embankment construction using Landsat Thematic Mapper (TM) thermal infrared (TIR) band data at Shihwa Lake and surrounding area. SST measurement is important for studies of both the structure of the ocean and as the thermal boundary between the ocean and the atmosphere. The TIR band of TM images can be used to detect SST change whose shoreline is complicated and narrow like the study site. The purpose of this study is to estimate SST and land cover change at Shihwa Lake and surrounding area.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.13-23
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• 2002

A radiometric correction method is developed to apply multi-temporal KOMPSAT-1 EOC satellite images for the detection of land-cover changes b\ulcorner recognizing changes in reflection pattern. Radiometric correction was carried out to eliminate the atmospheric effects that could interfere with the image properly of the satellite data acquired at different multi-times. Four invariant features of water, sand, paved road, and roofs of building are selected and a linear regression relationship among the control set images is used as a correction scheme. It is found that the utilization of panchromatic multi-temporal imagery requires the radiometric scene standardization process to correct radiometric errors that include atmospheric effects and digital image processing errors. Land-cover with specific change pattern such as paddy field is extracted by seasonal change recognition process.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.601-611
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• 2011

Land cover changes are occurring for a variety of reasons such as urbanization, infrastructure construction, desertification, drought, flood, and so on. Many researchers have studied the cause and effect of land cover changes, and also the methods for change detection. However, most of the detection methods are based on the dichotomy of "change" and "not change" according a threshold value. In this paper, we present a change detection method with the integration of probability, spatial autocorrelation, and hotspot detection. We used the AMOEBA (A Multidirectional Ecotope-Based Algorithm) and developed the AMOEBA-CH (core hotspot) because the original algorithm tends to produce too many clusters. Our method considers the probability of land cover changes and the spatial interactions between each pixel and its neighboring pixels using a local spatial autocorrelation measure. The core hotspots of land cover changes can be delineated by a contiguity-dominance model of our AMOEBA-CH method. We tested our algorithm in a simulation for land cover changes using NDVI (Normalized Difference Vegetation Index) data in South Korea between 2000 and 2008.

• Journal of the Korean Geographical Society
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• v.52 no.1
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• pp.123-141
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• 2017

This study predicted urban green spaces for 2020 based on two scenarios keeping or freeing the green-belt in the Daegu metropolitan city using a hybrid Cellular Automata(CA)-Markov model and analyzed the spatial dynamics of urban green spaces between 2009 and 2020 using a land cover change detection technique and spatial metrics. Markov chain analysis was employed to derive the transition probability for projecting land cover change into the future for 2020 based on two land cover maps in 1998 and 2009 provided by the Ministry of Environment. Multi-criteria evaluation(MCE) was adopted to develop seven suitability maps which were empirically derived in relation to the six restriction factors underlying the land cover change between the years 1998 and 2009. A hybrid CA-Markov model was then implemented to predict the land cover change over an 11 year period to 2020 based on two scenarios keeping or freeing the green-belt. The projected land cover for 2009 was cross-validated with the actual land cover in 2009 using Kappa statistics. Results show that urban green spaces will be remarkably fragmented in the suburban areas such as Dalseong-gun, Seongseo, Ansim and Chilgok in the year 2020 if the Daegu metropolitan city keeps its urbanization at current pace and in case of keeping the green-belt. In case of freeing the green-belt, urban green spaces will be fragmented on the fringes of the green-belt. It is thus required to monitor urban green spaces systematically considering the spatial change patterns identified by this study for sustainably managing them in the Daegu metropolitan city in the near future.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.82-94
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• 2014

The purpose of this study is to investigate the cause of increasing dry zones through analyzing relationships between land cover and Vegetation Temperature Condition Index(VTCI) using Landsat 4-5 TM satellite images in Central Dry Zones of Myanmar. As a result of land cover classifications, while vegetation areas gradually decrease, residential area and cropland were increased. VTCI analysis shows that region (a) showed a gradual decrease in the area of severely arid, and increase in the area of moderate dry and wet, which sums up to a slight decrease in aridity. Region (b) also showed to increase in dry areas and severe aridity. The result of relational analysis between VTCI and land cover change showed high ratio of land cover change, from severe arid area to forest and residential farmland. The average VTCI decreased in the changed land covers, which indicates the relationship between aridity and land cover change and a gradual increase in the arid area was identified.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.525-531
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• 2016

This study integrates the Universal Soil Loss Equation(USLE) with GIS method to assess the soil erosion for national land cover map between 2007 and 2014. The land cover change map and C factors of USLE were applied to the estimation of spatial distribution of sediment yield. However, they generated distinct results because of differences in their applied methods and calculation processes of national land cover map. To generate the USLE model, C factors of MOE(Ministry of Environment) were compared with soil erosion of Inje stadium development area at the Naerin watershed in Gangwon province to 2014. The several thematic maps of research area such as land cover map, topographic and soil maps, together with tabular precipitation data used for soil erosion calculation. The land cover change were carried with level-2 and high level land cover map of MOE and estimated maximum double of soil erosion.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.181-192
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• 1993

Image is composed of the digital numbers including information on natural phenomena, their condition and the kind of objects. Digital numbers change in geometric correction(that is preprocessing). This change of digital numbers gave an effect on results of land-cover classification. We intend to know the influence of resampling as classifying land-cover using the image reconstructed by geometric correction in this paper. Chun-cheon basin was selected the study area having most variable land-cover pattern in North-Han river valley and made on use of RESTEC data resampled in preprocessing. Land-cover is classified as six classes of LEVEL I using maximum likelyhood classification method. We classified land-cover using the image resampled by two methods in this study. Bilinear interpolation method was most accurate in five classes except bear-land in the result of comparing each class with topographic map. We should choose the method of resampling according to the class in which we put the importance in the image resampling of geometric correction. And if we use four-season's image, we may classify more accurately in case of the confusion in case of the confusion in borders of rice field and farm.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.135-148
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• 2015

This research is carried out for the land cover change detection in the Nakdong River basin before and after the 4 major rivers restoration project using the LiDAR DEM(Digital Elevation Model) and the multi-temporal Landsat imagery. Firstly the river basin polygon is generated by using the levee boundaries extracted from the LiDAR DEM, and the four river basin imagery are generated from the multi-temporal Landsat-5 TM(Thematic Mapper) and Landsat-8 OLI(Operational Land Imager) imagery by using the generated river basin polygon. Then the main land covers such as river, grass and bare soil are separately generated from the generated river basin imagery by using the image classification method, and the ratio of each land cover in the entire area is calculated. The calculated land cover changes show that the areas of grass and bare soil in the entire area have been significantly changed because of the seasonal change, while the area of the river has been significantly increased because of the increase of the water storage. This paper contributes to proposing an efficient methodology for the land cover change detection in the Nakdong River basin using the LiDAR DEM and the multi-temporal satellite imagery taken before and after the 4 major rivers restoration project.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.385-403
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• 2017

This study showed the national ecosystem classification for the spatial standards of ecosystems-based approaches to the risk assessments and adaptation plan. The characteristics of climate change risk assessment, implement national adaptation plans, and ecosystem/habitat classification status was evaluated. Focusing on the land cover classification widely utilized as spatial data for the assessments of biodiversity and ecosystem services in the UK and other countries in Europe, the applicability of the national land cover classification for climate change risk assessments was reviewed. Considering the ecosystem classification for climate change risk assessment and establishing adaptation measures, it is difficult to apply rough classification method to the land cover system because of lack of information on habitat trend by categorization. The results indicated that forest ecosystems and agro-ecosystem occupied 62.3% and 25.0% of land cover, respectively, of the entire country. Although the area is small compared with the land area, wetland ecosystem (2.9%), marine ecosystem (0.4%), coastal ecosystem (0.6%), and urban ecosystem (6.1%) can be included in the risk assessments. Therefore, it is necessary to subdivide below the medium classification for the forest and agricultural land, as well as Inland wetland, which has a higher proportion of habitat preference of taxa than land area, marine/coastal habitat, and transition areas such as urban and natural ecosystem.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.190-200
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• 2022

In this study, the island's land-use and land-cover change (LULCC) is analyzed in South Korea using remotely sensed land cover data(Globeland 30) acquired from 2000 to 2020 to meet the requirement of providing practical information for forest management. Analysis of LULCC between the 2000 and 2020 images revealed that changes to agricultural land were the most common type of change (7.6% of pixels), followed by changes to the forest (5.7%). The islands forests maintain 157,246 ha (42.2% of the total island area). Land cover types that changed to the forest from grasslands were 262 islands, while reverse cases have occurred on 421 islands. These 683 islands have a possibility of transition and disturbance. The artificial land class was newly calculated in 22 islands. The forests, which account for 42.2% of the 22 island area, turned into grassland, and 27.8% of agricultural land and grassland turned into forests. The development of artificial land often affects developed areas and surrounding areas, resulting in deforestation, management of agriculture, and landscaping. This study can provide insights concerning the fundamental data for assessing ecological functions and constructing forest management plans in islands ecosystems.