• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.651-664
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• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.71-78
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• 2013

An exceptional case of inhabitation of a Sphagnum sp. was firstly confirmed at abandoned paddy terrace (APT) wetland in Ansan. Water sampling for analyzing of physicochemical conditions including nutrients such as NP, $Ca^{2+}$ and $Mg^{2+}$ was performed and the vegetation map for distribution of Sphagnum sp., topographical map, and flora list for companion species were made at field in June 2011. From the results, the Sphagnum sp. in the study site was identified as S. palustre and it covered about 8% of the wetland cover of 3,200 $m^2$. Most distributions of S. palustre were observed at tussock structures as micro-topography by sedges and grasses within a wetland (74%) and the shaded slope area under Pinus densiflora's canopy in wetland boundary (26%). Despite that APT in Ansan is relatively lower wetland in altitude than high moors, the contents of calcium ($0.45{\pm}0.2$) and magnesium ($1.48{\pm}0.6$) ion which are critical limiting factors for Sphagnum spp. were very low levels as well as NP ($PO_4$-P, $0.02{\pm}0.0$; $NO_3$-N, $0.25{\pm}0.3$; $NH_4$-N, $0.06{\pm}0.1$) and it could enable the inhabitation of S. palustre in lower APT.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.291-304
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• 2021

Updating a forest type map is essential for sustainable forest resource management and monitoring to cope with climate change and various environmental problems. According to the necessity of efficient and wide-area forestry remote sensing, CAS500-4 (Compact Advanced Satellite 500-4; The agriculture and forestry satellite) project has been confirmed and scheduled for launch in 2023. Before launching and utilizing CAS500-4, this study aimed to pre-evaluation the possibility of satellite-based tree species classification using RapidEye, which has similar specifications to the CAS500-4. In this study, the study area was the Chuncheon forest management complex, Gangwon-do. The spectral information was extracted from the growing season image. And the GLCM texture information was derived from the growing and non-growing seasons NIR bands. Both information were used to classification with random forest machine learning method. In this study, tree species were classified into nine classes to the coniferous tree (Korean red pine, Korean pine, Japanese larch), broad-leaved trees (Mongolian oak, Oriental cork oak, East Asian white birch, Korean Castanea, and other broad-leaved trees), and mixed forest. Finally, the classification accuracy was calculated by comparing the forest type map and classification results. As a result, the accuracy was 39.41% when only spectral information was used and 69.29% when both spectral information and texture information was used. For future study, the applicability of the CAS500-4 will be improved by substituting additional variables that more effectively reflect vegetation's ecological characteristics.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.330-338
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• 2023

To investigate the impact of forestry projects on the carbon stocks of forests, we estimated the carbon stock change of above-ground and soil before and after forestry projects using forest type maps, forestry project information, and soil information. First, we selected six map sheet with large areas and declining age class based on forest type map information. Then, we collected data such as forest type maps, growth coefficients, soil organic matter content, and soil bulk density of the estimated areas to calculate forest carbon storage. As a result, forest carbon stocks decreased by about 34.1~70.0% after forestry projects at all sites. In addition, compared to reference studies, domestic forest soils store less carbon than the above-ground, so it is judged that domestic forest soils have great potential to store more carbon and strategies to increase carbon storage are needed. It was estimated that the amount of carbon stored before forestry projects is about 1.5 times more than after forestry projects. The study estimated that it takes about 27 years for forests to recover to their pre-thinning carbon stocks following forestry projects. Since it takes a long time for forests to recover to their original carbon stocks once their carbon stocks are reduced by physical damage, it is necessary to plan to preserve them as much as possible, especially for highly conservative forests, so that they can maintain their carbon storage function.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Korean Journal of Environment and Ecology
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• v.16 no.2
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• pp.188-194
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• 2002

Assessment institution of urban ecosystem is divided into ‘Urban Planning Act’and ‘Environmental Management Act’in Korea. The assessment institution of urban planning is divided into ‘Standard of land development approval’and ‘Environmental assessment of urban planning’. The institution of environmental management is divided into ‘Environmental impact assessment’and ‘Advance environmental assessment’. Assessment institution of urban ecosystem is progressed very slowly, because of development oriented policy. And so there are many problems that objective assessment method is not invented except ‘Degree of growing tree number per unit area’and ‘Degree of human disturbance of vegetation’, and insufficiency of conservation measures or post evaluation, etc. Activation of assessment institution of urban ecosystem is necessary followed countermeasures in Korea. (1) Development of objective assessment method for urban ecosystem as biotope map, (2) Appointment of censer-vation zone or consideration of damage for high value in conservation, (3) Parallel establishment of development and ecosystem conservation plan, and enforcing post evaluation

• Atmosphere
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• v.17 no.2
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• pp.159-169
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• 2007

A comparison of the three land cover data sets (United States Geological Survey: USGS, International Geosphere Biosphere Programme: IGBP, and University of Maryland: UMd), derived from 1992-1993 Advanced Very High Resolution Radiometer(AVHRR) data sets, was performed over the Asian continent. Preprocesses such as the unification of map projection and land cover definition, were applied for the comparison of the three different land cover data sets. Overall, the agreement among the three land cover data sets was relatively high for the land covers which have a distinct phenology, such as urban, open shrubland, mixed forest, and bare ground (>45%). The ratios of triple agreement (TA), couple agreement (CA) and total disagreement (TD) among the three land cover data sets are 30.99%, 57.89% and 8.91%, respectively. The agreement ratio between USGS and IGBP is much greater (about 80%) than that (about 32%) between USGS and UMd (or IGBP and UMd). The main reasons for the relatively low agreement among the three land cover data sets are differences in 1) the number of land cover categories, 2) the basic input data sets used for the classification, 3) classification (or clustering) methodologies, and 4) level of preprocessing. The number of categories for the USGS, IGBP and UMd are 24, 17 and 14, respectively. USGS and IGBP used only the 12 monthly normalized difference vegetation index (NDVI), whereas UMd used the 12 monthly NDVI and other 29 auxiliary data derived from AVHRR 5 channels. USGS and IGBP used unsupervised clustering method, whereas UMd used the supervised technique, decision tree using the ground truth data derived from the high resolution Landsat data. The insufficient preprocessing in USGS and IGBP compared to the UMd resulted in the spatial discontinuity and misclassification.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.1
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• pp.55-63
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• 2006

This study was carried out to analyze community character and classify forest community with phytosociological method and quadrat method to forest of Mt. Busosan in Buyeo-Gun.1. Communities by phytosociological method were classified into Pinus densiflora community and Quercus sp. community. With the classification of TWINSPAN, the community was categorized into Pinus densiflora - Quercus variabilis community and Pinus densiflora - Styrax japonica community.2. The importance value of Pinus densiflora, Quercus acutissima, Prunus sargentii, Styrax japonica, Quercus serrata, Quercus variabilis, Pinus rigida, Quercus aliena in tree layer were 83.20, 41.87, 30.93, 24.85, 23.27, 20.97, 20.28, and 9.46, respectively. The relative coverage of Stephanandra incisa, Quercus serrata, Styrax japonica, Parthenocissua tricuspidata, Rhododendron mucronulatum, Lindera obtusiloba, Prunus sargentii, Quercus variabilis, Indigofera kirilowii, Quercus acutissima, Lespedeza maximowiczii, and Acer pseudosibolianum in shrub layer were 9.62%, 9.55%, 9.18%, 7.85%, 6.18%, 5.25%, 4.82%, 4.15%, 3.98%, 3.98%, 3.55%, and 2.98%, respectively.3. According to size distribution map of diameter breast height of dominant species, the dominant species of Mt. Busosan was Pinus densiflora, and Quercus sp. such as Quercus acutissima, Quercus variabilis, and Quercus serrata may compete with the Pinus densiflora in the future.4. According to the ordination analysis of Mt. Busosan forest, Pinus densiflora - Styrax japonica community was found in moist site and Pinus densiflora - Quercus variabilis community was found in dry site.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.81-90
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• 2005

Based on the landslide hazard scoring system of Korea Forest Research Institute, a GIS model for predicting landslide hazards was developed. The risk of landslide hazards was analyzed as the function of 7 environmental site factors for the terrain, vegetation, and geological characteristics of the corresponding forest stand sites. Among the environmental factors, slope distance, relative height and shapes of slopes were interpreted using the forestland slope interpretation module developed by Chung et al. (2002). The program consists of three modules for managing spatial data, analyzing landslide hazard and report-writing, A performance test of the model showed that 72% of the total landslides in Youngin-Ansung landslides area took place in the highly vulnerable zones of grade 1 or 2 of the landslide hazard scoring map.