• Journal of the Korean earth science society
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• v.25 no.8
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• pp.764-773
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• 2004

The soil in wildfire area Sacheon-myeon, Gangneung, Gangweon Province, Korea, were investigated to clarify pattern of the soils. The soils were classified into 5 types on the basis of vegetation, types of organic matter. thickness of soil horizons, and completeness of soil profile. Each type showed different erosion pattern and Landsat ETM image. Coverage of plant leaves, litter, root, ash and other organic matter was an important component that affected soil color and reflectance of Landsat image (digital number). Although the NDVI (Normalized Distribution Vegetation Index) method in the wildfire area did not show much difference in soil types, the applied supervised classification method showed characteristic pattern of Landsat ETM image of soil types. This study showed that the applied supervised Landsat TM image classification in wildfire area is an effective way to estimate the distribution of erosion pattern of soil in wildfire area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.4
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• pp.41-49
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• 2012

The objective of this study is to investigate the characteristics of the location and prospects of the bear shelves built by Asiatic black bears in the Jirisan National Park. Previous researchers have been analyzed bear shelves in terms of places for resting and eating, but we are going to analyze based on the prospect-and-refuge theory. Characteristics of the sites of bear shelves are measured through field survey and topographic analysis by using digital elevation model (DEM). The normalized difference vegetation index (NDVI) is used to evaluate the optimum location of bear shelves in terms of crown density. Man-made objects are identified by viewshed analysis based on geographical information system (GIS). Findings of this paper can be summarized as follows. First, most bear trees are located deep inside of the mountainous national park, slopes of 30~40 degrees, altitude of 400~1,200m, and relatively low vegetation density with NDVI value of 0.4~0.6 compared to the average NDVI of the park. Second, the average height of bear shelves is 12.44m, or 74% of the average height of bear trees. They are located at suitable places to observe nearby trails and other park facilities. Third, man-made objects within the 100m radius of bear trees include lodge, bear training center, beekeeping camp, and hiking trails. Thus we may temporarily conclude that one of the main criteria of the bear tree selection in the park has been to identify optimum places for the monitoring of human activities in their habitat.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.61-72
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• 2008

Leaf area index (LAI) is a key biophysical variable influencing land surface processes such as photosynthesis, transpiration and energy balance, and is a required input to estimate evapotranspiration in various ecological and hydrological models. The development of more correct and useful LAIs estimation techniques is required by these importance, but LAIs had been assumed in most LAI research through simple relations with the normalized difference vegetation index (NDVI) because the field measurement is difficult on wide area. This paper is to evaluate the MODIS LAI Product's practical use by comparing with LAIs that is derived from NOAA AVHRR NDVIs and the 2 years (2003-2004) measured LAIs of Korea Forest Research Institute in Gyeongancheon watershed (561.12 $Km^2$). As a result, the MODIS LAIs of deciduous forests showed higher values about 14 % and 15~30 % than the measured LAIs and NOAA LAIs. In the year of 2003, the MODIS LAIs in coniferous forests were 5 % higher than the measured LAIs, and showed about 7 % differences comparing with the NOAA LAIs except April. These differences come from the insufficient field data measured in partial points of the target area, and the extracted reference data from MODIS LAIs include the limits of spatial resolution and the error of incorrect land cover classification. Thus, using the MODIS data by the proper correction with the measured data can be useful as an input data for ecological and hydrological models which offers the vegetation information and simulates the water balance of a given watershed.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.981-996
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• 2018

In agriculture, remote sensing data using earth observation satellites have many advantages over other methods in terms of time, space, and efficiency. This study analyzed the changes of reflectance and vegetation index according to atmospheric correction of images before using satellite images in agriculture. Top OF Atmosphere (TOA) reflectance and surface reflectance through atmospheric correction were calculated to compare the reflectance of each band and Normalized Vegetation difference Index (NDVI). As a result, the NDVI observed from field measurement sensors and satellites showed a higher agreement and correlation than the TOA reflectance calculated from surface reflectance using atmospheric correction. Comparing NDVI before and after atmospheric correction for multi-temporal images, NDVI increased after atmospheric corrected in all images. garlic and onion cultivation area and forest where the vegetation health was high area NDVI increased more 0.1. Because the NIR images are included in the water vapor band, atmospheric correction is greatly affected. Therefore, atmospheric correction is a very important process for NDVI time-series analysis in applying image to agricultural field.

• Asian Journal of Turfgrass Science
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• v.25 no.2
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• pp.195-201
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• 2011

The seaweed (Ascophyllum nodosum) extracts and chitosan formulations were sprayed on species of creeping bentrgass (Agrostis palustris Huds) cultivar "Penn A1" and species of Kentucky bluegrass (Poa pratensis L.) mixed cultivars (Midnight 33%, Moonlight 33%, Prosperity 33%) during fall season in sod farm. Turf color, chlorophyll contents and NDVI (Normalized Difference Vegetation Index) to affect turf qualities were investigated. There were detected significantly difference on chlorophyll contents and DNVI with seaweed extracts and chitosan formulations treatments. The contents of chlorophyll and NDVI on species of Kentucky bluegrass mixed cultivars and species of creeping bentgrass cultivar "Penn A1" were significantly increased by foliar spray with chitosan formulations and seaweed extracts. There was not a significantly difference on leaf color in two species within cultivars. These results suggested that chitosan formulations and seaweed extracts may help for turfgrass managements in the golf course during fall season.

• Asian Journal of Turfgrass Science
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• v.24 no.1
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• pp.50-55
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• 2010

Five turfgrass species and 46 cultivars were investigated for difference of spring greenup and living ground cover. Turf color and Normalized Difference Vegetation Index (NDVI) for greenup were investigated between species and cultivars. Turf color and NDVI were showed significantly different among species and cultivars. Turf color was showed significantly different among 20 cultivars of kentucky bluegrass (Poa pratensis L.). NDVI was significantly difference among 20 cultivars of kentucky bluegrass and 6 cultivars of tall fescue (Festuca arundinacea Schreb). The percentage living ground cover was showed significantly different among creeping bentgrass (Agrostis palustris Huds) cultivars and fineleaf fescue cultivars in spring.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.545-560
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• 2019

Unlike other critical forest diseases, pine pitch canker in Korea has shown rather mild symptoms of partial loss of crown foliage and leaf discoloration. This study used high-resolution satellite images to detect and monitor canopy decline by pine pitch canker. To enhance the subtle change of canopy reflectance in pitch canker damaged tree crowns, multi-temporal analysis was applied to two KOMPSAT multispectral images obtained in 2011 and 2015. To assure the spectral consistency between the two images, radiometric corrections of atmospheric and shadow effects were applied prior to multi-temporal analysis. The normalized difference vegetation index (NDVI) of each image and the NDVI difference (${\Delta}NDVI=NDVI_{2015}-NDVI_{2011}$) between two images were derived. All negative ΔNDVI values were initially considered any pine stands, including both pitch canker damaged trees and other trees, that showed the decrease of crown foliage from 2011 to 2015. Next, $NDVI_{2015}$ was used to exclude the canopy decline unrelated to the pitch canker damage. Field survey data were used to find the spectral characteristics of the damaged canopy and to evaluate the detection accuracy from further analysis.Although the detection accuracy as assessed by limited number of field survey on 21 sites was 71%, there were also many false alarms that were spectrally very similar to the damaged canopy. The false alarms were mostly found at the mixed stands of pine and young deciduous trees, which might invade these sites after the pine canopy had already opened by any crown damages. Using both ${\Delta}NDVI$ and $NDVI_{2015}$ could be an effective way to narrow down the potential area of the pitch canker damage in Korea.

• Ecology and Resilient Infrastructure
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• v.3 no.4
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• pp.315-321
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• 2016

To identify the relationship between land use and thermal environment in an urban area, the air temperature was measured at different places of land use, and the changes of land use and air temperature were traced for 40 years in Incheon City. The relationship between land use and temperature was also investigated using satellite image data. The results of temperature measurements on a forest, a cropland (rice paddy), a bareland (school ground), and an urban area (asphalt road) from 19 to 21 August 2014 showed that air temperature was the highest on a pavement road. The temperature increased by about $1.4^{\circ}C$ ($0.035^{\circ}C/year$) for 40 years from 1975 to 2014 in Incheon. The changes in land use patterns of Incheon for the past 40 years showed that urban dry land, bareland and grassland have increased and cultivated land, wetland and forest land have decreased gradually. The land surface temperature (LST) was correlated with the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) extracted from Landsat satellite image. The land surface temperature was lower at higher NDVI, and higher at higher NDBI. Therefore, it is important to conserve and restore the land use of greenery, wetlands, and agricultural land in order to mitigate the heat island effect and improve the thermal environment in an urban area.