• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.671-680
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• 2018

Compared to the imagery produced by traditional satellites, PlanetScope satellite imagery has made it possible to easily capture remotely-sensed imagery every day through dozens or even hundreds of satellites on a relatively small budget. This study aimed to detect changed areas and update a land cover map using a PlanetScope image. To generate a classification map, pixel-based Random Forest (RF) classification was performed by using additional features, such as the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI). The classification result was converted to vector data and compared with the existing land cover map to estimate the changed area. To estimate the accuracy and trends of the changed area, the quantitative quality of the supervised classification result using the PlanetScope image was evaluated first. In addition, the patterns of the changed area that corresponded to the classification result were analyzed using the PlanetScope satellite image. Experimental results found that the PlanetScope image can be used to effectively to detect changed areas on large-scale land cover maps, and supervised classification results can update the changed areas.

• Spatial Information Research
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• v.11 no.2
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• pp.101-117
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• 2003

High resolution satellite image analysis has been recognized as an effective technique for monitoring local land-cover and atmospheric changes. In this study, a new high resolution map for land-cover was generated using both high-resolution IKONOS image and conventional land-use mapping. Fuzzy classification method was applied to classify land-cover, with minimum operator used as a tool for joint membership functions. In separateness analysis, the values were not great for all bands due to discrepancies in spectral reflectance by seasonal variation. The land-cover map generated in this study revealed that conifer forests and farm land in the ground and tidal flat and beach in the ocean were highly changeable. The kappa coefficient was 0.94% and the overall accuracy of classification was 95.0%, thus suggesting a overall high classification accuracy. Accuracy of classification in each class was generally over 90%, whereas low classification accuracy was obtained for classes of mixed forest, river and reservoir. This may be a result of the changes in classification, e.g. reclassification of paddy field as water area after water storage or mixed use of several classification class due to similar spectral patterns. Seasonal factors should be considered to achieve higher accuracy in classification class. In conclusion, firstly, IKONOS image are used to generated a new improved high resolution land-cover map. Secondly, IKONOS image could serve as useful complementary data for decision making when combined with GIS spatial data to produce land-use map.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1461-1473
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• 2021

The purpose of this study is to ascertain how the level of resolution of land cover data affects on the local distribution and diffusion of fine dust. the CALPUFF model, which considers the spatio-temporal terrain conditions and changes in weather conditions, was used to estimate PM10 concentration in the Pyeongchon, Anyang-si, Gyeonggi-do. Three different resolutions of land cover data including 20 m, 50 m, and 100 m were compared as the input of the modeling. Using higher resolution land cover data (20 m), the wind speed of the simulated region was the largest and the PM10 concentration was the lowest. Through this study, we confirm that the resolution level of land-use/cover data can affect the local distribution and diffusion of fine dust, which can be detected by CALPUFF. Therefore, when using CALPUFF to simulate fine dust in the future, it can be suggested that checking the impact on spatial resolution according to the form of land cover in advance and proceeding with the simulation can achieve mote accurate results.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.3
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• pp.25-39
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• 2013

In this study, the change of the discharge according to the land cover change which acts as one of dominant factors for the outlook of future discharge was analyzed using SWAT(Soil and Water Assessment Tool) model for Yongdam and Daecheong Dam Watershed in the Geum River Basin. The land cover maps generated by Landsat TM satellite images in the past 1990 and 1995 were used as observed data to simulate the land cover in 2000 by CA-Markov serial technique and after they were compared and verified, the changes of land cover in 2050 and 2100 in the future were simulated. The discharge before and after the change of land cover by using input data of SWAT model was compared and analyzed under the A1B scenario. As a result of analyzing the trend in the elapses of year on the land cover in the Geum River Basin, the forest and rice paddy class area steadily decreased while the urban, bare ground and grassland classes increased. As a result of analyzing the change of discharge considering the future change of the land cover, it appeared that the discharge considering the change of land cover increases by 1.83~2.87% on the whole compared to the discharge not considering the change of land cover.

• 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.

• Journal of Korean Society on Water Environment
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• v.27 no.2
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• pp.159-166
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• 2011

The use of land cover was sharply changed during 1975~2007 in the Kyungan watershed $(561.12 km^2)$. The changes occurred over an area of more than $227.65 km^2$ during the overall period at changing rates of 1.04% per year for water area, 1.79% per year for residential area, 2.99% per year for bare area, 3.03% per year for wetland area, 3.04% per year for grass area, 0.87% per year for forest and 2.32% per year for agriculture area. Water, residential, bare and wetland areas increased, while grass, forest and agriculture areas decreased during the last 32 years. BOD concentrations of representative sites for each sub-watershed continuously increased until the early 2000s as residential area increased with the highest discharged load, but decreased after the mid 2000s except upper Kyungan watershed. Such decline appears to be associated with the planning of Total Maximum Daily Load management for Gwangju city and expansion of waste water treatment plant. It is necessary to control land use/cover changes of the upper watershed and to prepare appropriate watershed management system for improvement in river environment including water quality, stream flow and bio-diversity.

• Atmosphere
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• v.27 no.4
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• pp.399-409
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• 2017

The impact of land cover changed by tidal flats on local meteorology in Gyeonggi Bay was quantitatively evaluated based on a numerical modeling approach during 18 days (21 June to 9 July 2013). The analysis was carried out using three sets of simulation scenarios and the land cover of tidal flats for each simulation was applied as follows: (1) the herbaceous wetland representing coastal wetlands (i.e., EXP-BASE case), (2) the barren or sparsely vegetated representing low tide (i.e., EXP-LOW case), (3) the water bodies representing high tide (i.e., EXP-HIGH case). The area of tidal flats was calculated as about $552km^2$ (the ratio of 4.7% for analysis domain). During the daytime, the change (e.g. wetlands to water) of land cover flooded by high tide indicated the decrease of temperature (average $3.3^{\circ}C$) and the increase of humidity (average 13%) and wind speed (maximum $2.9m\;s^{-1}$). The changes (e.g. wetlands to barren or sparsely vegetated) of land cover induced by low tide were smaller than those by high tide. On the other hands, the effects of changed land cover at night were not apparent both high tide and low tide. Also, during the high tide, the meteorological change in tidal flats affected the metropolitan area (about 40 km from the tidal flat).

• Forest Science and Technology
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• v.14 no.4
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• pp.181-191
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• 2018

This study was carried out in the teaching and research forest of the University of Dschang in Belabo, with the aim of analysing land-cover and land-use changes as well as carbon stocks dynamic. The databases used are composed of three Landsat satellite images (5TM of 1984, 7ETM + of 2000 and 8OLI of 2016), enhanced by field missions. Satellite images were processed using ENVI and ArcGIS software. Interview, focus group discussion methods and participatory mapping were used to identify the activities carried out by the local population. An inventory design consisting of four transects was used to measure dendrometric parameters and to identify land-use types. An estimation of carbon stocks in aboveground and underground woody biomass was made using allometric models based on non-destructive method. Dynamic of land-cover showed that the average annual rate of deforestation is 0.48%. The main activities at the base of this change are agriculture, house built-up and logging. Seven types of land-use were identified; adult secondary forests (64.10%), young secondary forests (7.54%), wetlands (7.39%), fallows (3.63%), savannahs (9.59%), cocoa farms (4.28%) and mixed crop farms (3.47%). Adult secondary forests had the highest amount of carbon ($250.75\;t\;C\;ha^{-1}$). This value has decreased by more than 60% for mixed crop farms ($94.67\;t\;C\;ha^{-1}$), showing the impact of agricultural activities on both forest cover and carbon stocks. Agroforestry systems that allow conservation and introduction of woody species should be encouraged as part of a participatory management strategy of this forest.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.305-314
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• 2017

This study aimed to predict changes in forest area using a probability density function, in order to promote effective forest management in the area north of the civilian control line (known as the Minbuk area) in Korea. Time series analysis (2010 and 2016) of forest area using land cover maps and accessibility expressed by distance covariates (distance from buildings, roads, and civilian control line) was applied to a probability density function. In order to estimate the probability density function, mean and variance were calculated using three methods: area weight (AW), area rate weight (ARW), and sample area change rate weight (SRW). Forest area increases in regions with lower accessibility (i.e., greater distance) from buildings and roads, but no relationship with accessibility from the civilian control line was found. Estimation of forest area change using different distance covariates shows that SRW using distance from buildings provides the most accurate estimation, with around 0.98-fold difference from actual forest area change, and performs well in a Chi-Square test. Furthermore, estimation of forest area until 2028 using SRW and distance from buildings most closely replicates patterns of actual forest area changes, suggesting that estimation of future change could be possible using this method. The method allows investigation of the current status of land cover in the Minbuk area, as well as predictions of future changes in forest area that could be utilized in forest management planning and policymaking in the northern area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.85-94
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• 2018

The change of land covers in 2026 was prediceted based on the change of urbanization in 1996, 2006 and 2016 in Seoul and surrounding areas in this study. Landsat images were used as the basic data, and MLP (Multilayer Perceptron) and MCA (Markov Chain Analysis) were integrated for future prediction for the study area. The land cover transition potentials were calculated by setting up sub-models in MLP and the driving factors of land cover transition from 1996 to 2006 and transition probabilities were calculated using MCA to generate the land cover map of 2016. This was compared to the land cover map of 2016 from Landsat. MLP and MCA were verified and the future land covers of 2026 were predicted using the land cover map from Landsat in 2006 and 2016. As a result, it was predicted that the major land cover changes from 1996 to 2006 were from Barren Land and Grass Land to Builtup Area, and the same trend of transition will be remained for 2026. This study is meaningful in that it is applied for the first time to predict the future coating change in Seoul and surrounding areas by the MLP-MCA method.