• 대한원격탐사학회지
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• 제36권5_1호
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• pp.735-747
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• 2020

본 연구는 청천일 조건에서 직접적 보정 방식으로 산정한 반사율 및 식생지수의 일주기 변화를 분석하여 시계열 작황 모니터링을 위한 무인비행체 영상의 특성을 구명하고자 수행하였다. 무인기에 다중분광센서를 장착하여 청천일이었던 2020년 3월 23일과 3월 24일에 반사율 보정용 반사판, 콘크리트 및 작물 시험구를 대상으로 시간대별, 비행경로별 항공영상을 촬영하여 직접적 방식으로 반사율을 산정하고 작물 시험구를 대상으로 식생지수를 계산하여 비교하였다. 반사율 보정용 반사판, 콘크리트 및 작물 시험구의 무인기 영상 반사율은 시간대 및 비행경로별로 일정한 변화 경향을 보이지 않을 뿐 아니라 일간 재현성 있는 값을 보이지 않아 시계열적으로 비교·활용 하는 것에는 한계가 있을 것으로 판단된다. 그러나 작물 시험구의 NDVI는 값이 높을수록 일중 및 일간 변동성이 적었으며 식생의 활력이 부족한 식생 제어 시험구에서도 일 중 5% 미만의 변동계수를 보여 반사율과 달리 대체로 일정한 값을 유지하는 것으로 나타났다. 또한 3월 23일과 3월 24일 동일한 시간대에 촬영한 무인기 영상으로 산정한 NDVI의 평균 절대 오차도 0.76~3.97%의 범위를 보여 시계열 작황모니터링에 활용이 가능할 것으로 판단된다.

• 대한원격탐사학회지
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• 제39권6_1호
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• pp.1437-1449
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• 2023

본 연구의 목적은 도시지역의 투수면적 및 불투수면적이 수목의 생장에 영향을 미치는지 분석하는 것이다. 이를 위해 동일한 시기에 식재한 나무 6종의 생장 차이를 알아보기 위해 Sentinel-2를 이용하여 제작한 Normalised Difference Vegetation Index (NDVI)와 환경부의 세분류 토지피복지도를 이용하여 투수면적과 불투수면적이 수목 생장에 미치는 영향을 분석했다. 이를 위해 Geospatial eXplainable Artificial Intelligence (GeoXAI) 개념을 적용했다. 분석결과 소나무는 10 m 범위, 느티나무, 메타세콰이어, 은행나무는 20 m 범위, 양버즘나무는 30 m 범위, 왕벚나무는 40 m 범위에 포함된 토지피복들의 면적을 고려했을때 모델의 설명력이 가장 우수한 것으로 나타났다. 그리고 투수 면적이 넓을수록 수목의 생장이 활발하다는 양의 상관관계를 나타내었으며, 주변에 인공지반과 같이 불투수 면적이 넓을 경우 수목의 생장과 음의 상관관계를 보였다. 이는 수목의 생장에 있어 주변의 투수 및 불투수 면적이 수목의 생장에 영향을 미침을 알 수 있었으며, 수종에 따라 영향을 미치는 범위 또한 다르다는 것을 알 수 있었다.

• 환경영향평가
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• 제27권3호
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• pp.279-290
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• 2018

도시화와 인간의 영향으로 도심 내 산림 임연부가 증가함에 따라 도시 산림 관리 측면에서 도시 산림 임연부의 현황 파악과 모니터링의 중요성이 대두되고 있다. 본 연구는 도시 산림 임연부의 현황파악을 위해 시간적 예측, 공간적 예측에서 정확도가 높은 FSDAF(Flexible Spatio-temporal DAta Fusion) 융합 영상 기법을 활용하여 도출한 $NDVI_{max}$ 영상을 사용하여 인접한 토지피복 유형에 따른 도시 산림 임연부의 식생 활력도 차이를 평가하는데 목적이 있다. 서울시 내 도시 산림 임연부를 대상으로 분석해 본 결과, 산림 내부로 갈수록 식생활력도가 증가하는 경향이 나타났다. 임연부에 인접한 4가지 토지피복 유형 중 도로가 산림 임연부에 미치는 영향이 가장 큰 것으로 나타났다. 특히, 도로로부터 산림 임연부의 30m까지 그 영향이 가장 두드러지게 나타났으며, 90m까지 영향을 미치는 것으로 나타났다. 본 연구의 결과는 도시 산림 모니터링 및 도시 산림 임연부 관리 측면에서 토지 피복 유형과 토지피복 변화가 인접한 산림에 미치는 영향을 평가하는데 활용 가능할 것으로 기대된다.

• 대한토목학회논문집
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• 제30권2B호
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• pp.107-120
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• 2010

본 연구에서는 기후변화를 평가하기 위해 장기수문유출모형인 SLURP 모형이 선택되었으며, 모형의 적용성을 평가하기 위하여, 고도, 기상, 토지이용, 토양, 식생과 같은 기본 입력 자료를 구축하였고 공도 수위관측소 상류유역을 대상으로 유역 내에 포함되어 있는 농업용 저수지인 고삼과 금광저수지를 고려하기 위하여 저수위, 저수량, 내용적 곡선 자료를 수집하였다. 한편, 미래 기후변화를 분석하기 위해 미래 기상, 토지이용, 식생자료를 구축하였다. 미래 기상자료는 IPCC에서 제시하고 있는 SRES 특별보고서에 의한 GCMs 중 CCCma CGCM2 A2, B2 시나리오 결과자료를 수집한 후, 편이보정(bias correction) 및 CF(Change Factor) 다운스케일 기법을 적용하여 각 기상관측소별 기상자료를 재구축하였으며, 미래 토지이용자료는 과거 토지이용자료를 이용하여 개선된 CA-Markov기법에 의해 전망하였다. 또한 미래 식생자료는 NOAA/AVHRR을 이용하여 구축한 과거의 월 NDVI와 평균온도와의 선형 회귀식을 이용하여 기후변화 시나리오별 월 NDVI를 구축하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.449-451
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• 2007

In the commercially managed timber lands, the information such as height, age, stand density, canopy closure and leaf area index need to be collected periodically. Stand volume is the most fundamental information in the valuation of timber, however, stand age information is the primary element of forest inventory and these two are highly correlated. Conventional method of collecting stand age information by field surveys such as ring count method is accurate; however, it is expensive, labor-intensive and time consuming. In the present study it was aimed to collect stand age information using modem techniques in a commercially managed timberland situated in Tennessee, USA. The Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) of three different periods, Shuttle Radar Topography Mission (SRTM), National elevation dataset (NED) and field inventory data were used. Normalized difference vegetation index (NDVI) and Tasselled Cap (TC) transformation techniques were applied on the TM and ETM+ data. The regression analysis was carried out to identify the correlation between stand age and NDVI, TC. In the present study about 2,469 datasets were analyzed. The $R^{2}$ value for stand age estimation was 0.713. The NDVI, TC2 and TC3 were found to produce accurate timber age information.

• 대한원격탐사학회지
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• 제36권1호
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• pp.29-39
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• 2020

Forest fire is a critical disaster that causes massive destruction of forest ecosystem and economic loss. Hence, accurate estimation of the burned area is important for evaluation of the degree of damage and for preparing baseline data for recovery. Since most of the area size damaged by wildfires in Korea is less than 1 ha, it is necessary to use satellite or drone images with a resolution of less than 10m for detecting the damage area. This paper aims to detect wildfire-damaged area from a Kompsat-3 image using the indices such as NDVI (normalized difference vegetation index) and FBI (fire burn index) and to examine the classification characteristics according to the methods such as Otsu thresholding and ISODATA(iterative self-organizing data analysis technique). To mitigate the salt-and-pepper phenomenon of the pixel-based classification, a gaussian filter was applied to the images of NDVI and FBI. Otsu thresholding and ISODATA could distinguish the burned forest from normal forest appropriately, and the salt-and-pepper phenomenon at the boundaries of burned forest was reduced by the gaussian filter. The result from ISODATA with gaussian filter using NDVI was closest to the official record of damage area (56.9 ha) published by the Korea Forest Service. Unlike Otsu thresholding for binary classification,since the ISODATA categorizes the images into multiple classes such as(1)severely burned area, (2) moderately burned area, (3) mixture of burned and unburned areas, and (4) unburned area, the characteristics of the boundaries consisting of burned and normal forests can be better expressed. It is expected that our approach can be utilized for the high-resolution images obtained from other satellites and drones.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제1권1호
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• pp.31-40
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• 2020

The rapid development of technologies in unmanned aerial vehicles (UAVs) has led to their use in various areas. UAVs are mainly used for commercial purposes, but their utilization is increasingly important in other areas because their operation cost is less than satellites and aerial imaging. The utilization of UAVs in the environment/ecology area is relatively new. Therefore, identifying the trends of UAV-related spatial information is significant in basic research for UAV utilization. This study quantitatively identified domestic and international research trends related to UAV utilization and analyzed research areas. An attempt was also made to identify upcoming UAV-related topics in the environment/ecology research field using text mining to analyze the bibliographic information of global research literature. Domestic UAV-related studies were classified into seven clusters where basic research on "UAV technology/industry trends" was abundant, and studies on data collection and analysis through UAV remote sensing technology have increased since 2015. Eight clusters were identified for international studies where the most active research area international was "remote sensing technology/data analysis". In addition, Canopy, Classification, Forest, Leaf Area Index, Normalized Difference Vegetation Index, Temperature, Tree, and Atmosphere appeared as the main keywords related to environment and ecology. The appearance frequencies and association strengths were high because the advancement in UAV optical sensor technology and the rapid development of image processing technology enabled the acquisition of data that could not be obtained from existing spatial information. They are recognized as future research topics as related domestic studies have begun corresponding to international research.

• 한국토양비료학회지
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• 제47권3호
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• pp.217-224
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• 2014

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for predicting yield, biomass, and nitrogen stress during growing season. The objectives of this study were: 1) to assess biomass and nitrogen (N) status of tobacco (Nicotiana tabacum L.) plants under N stress using ground-based remote sensors; and 2) to evaluate the feasibility of spectral reflectance indices for estimating an application rate of N and predicting yield of tobacco. Dry weight (DW), N content, and N uptake at the 40th and 50th day after transplanting (DAT) were positively correlated with chlorophyll content and normalized difference vegetation indexes (NDVIs) from all sensors (P<0.01). Especially, Green NDVI (GNDVI) by spectroradiometer and Crop Circle-passive sensors were highly correlated with DW, N content and N uptake. The yield of tobacco was positively correlated with canopy reflectance indices measured at each growth stage (P<0.01). The regression of GNDVI by spectroradiometer on yield showed positively quadratic curve and explained about 90% for the variability of measured yield. The sufficiency index (SI) calculated from data/maximum value of GNDVI at the $40^{th}$ DAT ranged from 0.72 to 1.0 and showed the same positively quadratic regression with N application rate explaining 84% for the variability of N rate. These results suggest that use of reflectance indices measured with ground-based remote sensors may assist in determining application rate of fertilizer N at the critical season and estimating yield in mid-season.

• 상하수도학회지
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• 제31권3호
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• pp.197-204
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• 2017

This study was carried out to apply the UAV(Unmanned Aerial Vehicle) coupled with Multispectral sensor for the algae bloom monitoring in river. The study acquired remote sensing data using UAV on the midstream area of Gum River, one of four major rivers in South Korea. Normalized difference vegetation index (NDVI) is used for monitoring algae change. This study conducted water sampling and analysis in the field for correlating with NDVI values. Among the samples analyzed, the chlorophyll concentration exhibited strong and significant linear relationships with NDVI, and thus NDVI was chosen for algae bloom index to identify emergence aspect of phytoplankton in river. Aerial remote sensing technology can provide more accurate, flexible, cheaper, and faster monitoring methods of detecting and predicting eutrophication and therefore cyanobacteria bloom in water reservoirs compared to currently used technology. As a result, there was high level of correlation in chlorophyll-a and NDVI. It is expected that when this remote water quality and pollution monitoring technology is applied in the field, it would be able to improve capabilities to deal with the river water quality and pollution at the early stage.

• 한국작물학회지
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• 제64권2호
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• pp.159-164
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• 2019

Weed control is a crucial practice not only in organic farming, but also in modern agriculture because it can lead to loss in crop yield. In general, weed is distributed in patches heterogeneously in the field. These patches vary in size, shape, and density. Thus, it would be efficient if chemicals are sprayed on these patches rather than spraying uniformly in the field, which can pollute the environment and be cost prohibitive. In this sense, weed detection could be beneficial for sustainable agriculture. Studies have been conducted to detect weed patches in the field using remote sensing technologies, which can be classified into a method using image segmentation based on morphology and a method with vegetative indices based on the wavelength of light. In this study, the latter methodology has been used to detect the weed patches. As a result, it was found that the vegetative indices were easier to operate as it did not need any sophisticated algorithm for differentiating weeds from crop and soil as compared to the former method. Consequently, we demonstrated that the current method of using vegetative index is accurate enough to detect weed patches, and will be useful for farmers to control weeds with minimal use of chemicals and in a more precise manner.