• Title/Summary/Keyword: VEGETATION Sensor

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Analysis of Optimal Pathways for Terrestrial LiDAR Scanning for the Establishment of Digital Inventory of Forest Resources (디지털 산림자원정보 구축을 위한 최적의 지상LiDAR 스캔 경로 분석)

  • Ko, Chi-Ung;Yim, Jong-Su;Kim, Dong-Geun;Kang, Jin-Taek
    • Korean Journal of Remote Sensing
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    • v.37 no.2
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    • pp.245-256
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    • 2021
  • This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

Effect of Red-edge Band to Estimate Leaf Area Index in Close Canopy Forest (울폐산림의 엽면적지수 추정을 위한 적색경계 밴드의 효과)

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.571-585
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    • 2017
  • The number of spaceborne optical sensors including red-edge band has been increasing since red-edge band is known to be effective to enhance the information content on biophysical characteristics of vegetation. Considering that the Agriculture and Forestry Satellite is planning to carry an imaging sensor having red-edge band, we tried to analyze the current status and potential of red-edge band. As a case study, we analyzed the effect of using red-edge band and tried to find the optimum band width and wavelength region of the red-edge band to estimate leaf area index (LAI) of very dense tree canopy. Field spectral measurements were conducted from April to October over two tree species (white oak and pitch pine) having high LAI. Using the spectral measurement data, total 355 red-edge bands reflectance were simulated by varying five band width (10 nm, 20 nm, 30 nm, 40 nm, 50 nm) and 71 central wavelength. Two red-edge based spectral indices(NDRE, CIRE) were derived using the simulated red-edge band and compared with the LAI of two tree species. Both NDRE and CIRE showed higher correlation coefficients with the LAI than NDVI. This would be an alternative to overcome the limitation of the NDVI saturation problem that NDVI has not been effective to estimate LAI over very dense canopy situation. There was no significant difference among five band widths of red-edge band in relation to LAI. The highest correlation coefficients were obtained at the red-edge band of center wavelength near the 720 nm for the white oak and 710 nm for the pitch pine. To select the optimum band width and wavelength region of the red-edge band, further studies are necessary to examine the relationship with other biophysical variables, such as chlorophyll, nitrogen, water content, and biomass.

A Study on the Calculation of Evapotranspiration Crop Coefficient in the Cheongmi-cheon Paddy Field (청미천 논지에서의 증발산량 작물계수 산정에 관한 연구)

  • Kim, Kiyoung;Lee, Yongjun;Jung, Sungwon;Lee, Yeongil
    • Korean Journal of Remote Sensing
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    • v.35 no.6_1
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    • pp.883-893
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    • 2019
  • In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS Kc and SM&VI Kc, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS Kc and SM&VI Kc in specific period was performed according to the growth phase of the crop. The result shows that GLDAS Kc was better in the early and mid-phase of the crop growth, and SM&VI Kc was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.

Validation of Surface Reflectance Product of KOMPSAT-3A Image Data Using RadCalNet Data (RadCalNet 자료를 이용한 다목적실용위성 3A 영상 자료의 지표 반사도 성과 검증)

  • Lee, Kiwon;Kim, Kwangseob
    • Korean Journal of Remote Sensing
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    • v.36 no.2_1
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    • pp.167-178
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    • 2020
  • KOMPSAT-3A images have been used in various kinds of applications, since its launch in 2015. However, there were limits to scientific analysis and application extensions of these data, such as vegetation index estimation, because no tool was developed to obtain the surface reflectance required for analysis of the actual land environment. The surface reflectance is a product of performing an absolute atmospheric correction or calibration. The objective of this study is to quantitatively verify the accuracy of top-of-atmosphere reflectance and surface reflectance of KOMPSAT-3A images produced from the OTB open-source extension program, performing the cross-validation with those provided by a site measurement data of RadCalNet, an international Calibration/Validation (Cal/Val) portal. Besides, surface reflectance was obtained from Landsat-8 OLI images in the same site and applied together to the cross-validation process. According to the experiment, it is proven that the top-of-atmosphere reflectance of KOMPSAT-3A images differs by up to ± 0.02 in the range of 0.00 to 1.00 compared to the mean value of the RadCalNet data corresponding to the same spectral band. Surface reflectance in KOMPSAT-3A images also showed a high degree of consistency with RadCalNet data representing the difference of 0.02 to 0.04. These results are expected to be applicable to generate the value-added products of KOMPSAT-3A images as analysisready data (ARD). The tools applied in thisstudy and the research scheme can be extended as the new implementation of each sensor model to new types of multispectral images of compact advanced satellites (CAS) for land, agriculture, and forestry and the verification method, respectively.

A Study on the Land Surface Emissivity (LSE) Distribution of Mid-wavelength Infrared (MWIR) over the Korean Peninsula (한반도 중파장적외선 지표 복사율 분포 연구)

  • Sun, Jongsun;Park, Wook;Won, Joong-sun
    • Korean Journal of Remote Sensing
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    • v.32 no.5
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    • pp.423-434
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    • 2016
  • Surface emissivity and its background values according to each sensor are mandatorily necessary for Mid-Wavelength Infrared (MWIR) remote sensing to retrieve surface temperature and temporal variation. This study presents the methods and results of Land Surface Emissivity (LSE) of the MWIR according to land cover over the Korean Peninsula. The MWIR emissivity was estimated by applying the Temperature Independent Spectral Indices (TISI) method to the Visible Infrared Imaging Radiometer Suite (VIIRS) band 4 Day/Night images ($3.74{\mu}m$ in center wavelength). The obtained values were classified according to land-cover types, and the obtained emissivity was then compared with those calculated from a standard Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) spectral library. The annual means of MWIR emissivity of Deciduous Broadleaf Forest (0.958) and Mixed Forest (0.935) are higher than those of Croplands (0.925) and Natural Vegetation Mosaics (0.935) by about 2-3%. The annual mean of Urban area is the lowest (0.914) with an annual variation of about 2% which is by larger than those (1%) of other land-covers. The TISI and VIIRS based emissivity is slightly lower than the ASTER spectral library by about 2-3% supposedly due to various reasons such as lack of land cover homogeneity. The results will be used to understand the MWIR emissivity properties of the Korean Peninsula and to examine the seasonal and other environmental changes using MWIR images.

Understory Evapotranspiration Measured by Eddy-Covariance in Gwangneung Deciduous and Coniferous Forests (광릉 활엽수림과 침엽수림에서 에디공분산으로 관측한 하부 군락의 증발산)

  • Kang, Min-Seok;Kwon, Hyo-Jung;Lim, Jong-Hwan;Kim, Joon
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.11 no.4
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    • pp.233-246
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    • 2009
  • The partitioning of evapotranspiration (ET) into evaporation (E) and transpiration (T) is critical in understanding the water cycle and the couplings between the cycles of energy, water, and carbon. In forests, the total ET measured above the canopy consists of T from both overstory and understory vegetation, and E from soil and the intercepted precipitation. To quantify their relative contributions, we have measured ET from the floors of deciduous and coniferous forests in Gwangneung using eddy covariance technique from 1 June 2008 to 31 May 2009. Due to smaller eddies that contribute to turbulent transfer near the ground, we performed a spectrum analysis and found that the errors associated with sensor separation were <10%. The annual sum of the understory ET was 59 mm (16% of total ET) in the deciduous forest and 43 mm (~7%) in the coniferous forest. Overall, the understory ET was not negligible except during the summer season when the plant area index was near its maximum. In both forest canopies, the decoupling factor ($\Omega$) was about ~0.15, indicating that the understory ET was controlled mainly by vapor pressure deficit and soil moisture content. The differences in the understory ET between the two forest canopies were due to different environmental conditions within the canopies, particularly the contrasting air humidity and soil water content. The non-negligible understory ET in the Gwangneung forests suggests that the dual source or multi-level models are required for the interpretation and modeling of surface exchange of mass and energy in these forests.

Current Status of Hyperspectral Remote Sensing: Principle, Data Processing Techniques, and Applications (초분광 원격탐사의 특성, 처리기법 및 활용 현용)

  • Kim Sun-Hwa;Ma Jung-Rim;Kook Min-Jung;Lee Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.21 no.4
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    • pp.341-369
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    • 2005
  • Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.

Application of Atmospheric Correction to KOMPSAT for Agriculture Monitoring (농경지 관측을 위한 KOMPSAT 대기보정 적용 및 평가)

  • Ahn, Ho-yong;Ryu, Jae-Hyun;Na, Sang-il;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.37 no.6_3
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    • pp.1951-1963
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    • 2021
  • Remote sensing data using earth observation satellites in agricultural environment monitoring has many advantages over other methods in terms of time, space, and efficiency. Since the sensor mounted on the satellite measures the energy that sunlight is reflected back to the ground, noise is generated in the process of being scattered, absorbed, and reflected by the Earth's atmosphere. Therefore, in order to accurately measure the energy reflected on the ground (radiance), atmospheric correction, which must remove noise caused by the effect of the atmosphere, should be preceded. In this study, atmospheric correction sensitivity analysis, inter-satellite cross-analysis, and comparative analysis with ground observation data were performed to evaluate the application of KOMPSAT-3 satellite's atmospheric correction for agricultural application. As a result, in all cases, the surface reflectance after atmospheric correction showed a higher mutual agreement than the TOA reflectance before atmospheric correction, and it is possible to produce the time series vegetation index of the same standard. However, additional research is needed for quantitative analysis of the sensitivity of atmospheric input parameters and the tilt angle.

Estimation of Benthic Microalgae Chlorophyll-a Concentration in Mudflat Surfaces of Geunso Bay Using Ground-based Hyperspectral Data (지상 초분광자료를 이용한 근소만 갯벌표층에서 저서성 미세조류의 엽록소-a 공간분포 추정)

  • Koh, Sooyoon;Noh, Jaehoon;Baek, Seungil;Lee, Howon;Won, Jongseok;Kim, Wonkook
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1111-1124
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    • 2021
  • Mudflats are crucial for understanding the ecological structure and biological function of coastal ecosystem because of its high primary production by microalgae. There have been many studies on measuring primary productivity of tidal flats for the estimation of organic carbon abundance, but it is relatively recent that optical remote sensing technique, particularly hyperspectral sensing, was used for it. This study investigates hyperspectral sensing of chlorophyll concentration on a tidal flat surface, which is a key variable in deriving primary productivity. The study site is a mudflat in Geunso bay, South Korea and field campaigns were conducted at ebb tide in April and June 2021. Hyperspectral reflectance of the mudflat surfaces was measured with two types of hyperspectral sensors; TriOS RAMSES (directionalsensor) and the Specim-IQ (camera sensor), and Normal Differenced Vegetation Index (NDVI) and Contiuum Removal Depth (CRD) were used to estimate Chl-a from the optical measurements. The validation performed against independent field measurements of Chl-a showed that both CRD and NDVI can retrieve surface Chl-a with R2 around 0.7 for the Chl-a range of 0~150 mg/m2 tested in this study.

Selection on Optimal Bands to EstimateYield of the Chinese Cabbage Using Drone-based Hyperspectral Image (드론 기반 초분광 영상을 이용한 배추 단수 추정의 최적밴드 선정)

  • Na, Sang-il;Park, Chan-won;So, Kyu-ho;Ahn, Ho-yong;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.35 no.3
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    • pp.375-387
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    • 2019
  • The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.