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Remote sensing of environment 59건

  1. [해외논문]   Editorial Board   SCI SCIE


    Remote sensing of environment v.209 ,pp. ii - ii , 2018 , 0034-4257 ,

    초록

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  2. [해외논문]   Spectral matching based on discrete particle swarm optimization: A new method for terrestrial water body extraction using multi-temporal Landsat 8 images   SCI SCIE

    Jia, Kai (Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China ) , Jiang, Weiguo (Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China ) , Li, Jing (Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China ) , Tang, Zhenghong (Community and Regional Planning Program, College of Architecture, University of Nebraska-Lincoln, Lincoln, NE 68588-0105, USA)
    Remote sensing of environment v.209 ,pp. 1 - 18 , 2018 , 0034-4257 ,

    초록

    Abstract Terrestrial water, an important indicator of inland hydrological status, is sensitive to land use cover change, natural disaster and climate change. An accurate and robust water extraction method can determine the surface water distribution. In this paper, a new method, called the spectrum matching based on discrete particle swarm optimization (SMDPSO) is proposed to recognize water and nonwater in Landsat 8 Operational Land Imager (OLI) images. Only two parameters, the standard water spectrum and the tile size, are considered. These parameters are sufficiently stable so it is unnecessary to change their values for different conditions. By contrast, in supervised methods, samples are chosen based on conditions. Eight test sites covering various water types in different climate conditions are used to assess the performance relative to that of unsupervised and supervised methods in terms of overall accuracy (OA), kappa coefficients (KC), commission error (CE) and omission error (OE). The results show that: (1) SMDPSO achieves the highest accuracy and robustness; (2) SMDPSO has lower OE but higher CE than the supervised method, which means that SMDPSO is the least likely to misclassify water as nonwater, but is more likely to misclassify nonwater as water; (3) SMDPSO has advantages with respect to removing shallows and dark vegetation and preserving the real distribution of small ponds, but cannot recognize shadows, ice, or clouds without the help of other data such as DEM. In addition, a case of flooding in northeastern China is analyzed to demonstrate the applicability of SMDPSO in water inundation mapping. The findings of this study demonstrate a novel robust, low-cost water extraction method that satisfies the requirements of terrestrial water inundation mapping and management. Highlights A new method for water extraction called SMDPSO is proposed. SMDPSO has higher robustness and fewer parameters without manual intervention. SMDPSO has higher Overall Accuracy and Kappa Coefficient than supervised method. SMDPSO is applied to map flood inundation of Northeastern China 2013.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  3. [해외논문]   First hyperspectral imaging survey of the deep seafloor: High-resolution mapping of manganese nodules   SCI SCIE

    Dumke, Ines (Department of Marine Technology, Norwegian University of Science and Technology (NTNU), Otto Nielsens vei 10, 7491 Trondheim, Norway ) , Nornes, Stein M. (Department of Marine Technology, Norwegian University of Science and Technology (NTNU), Otto Nielsens vei 10, 7491 Trondheim, Norway ) , Purser, Autun (Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany ) , Marcon, Yann (Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany ) , Ludvigsen, Martin (Department of Marine Technology, Norwegian University of Science and Technology (NTNU), Otto Nielsens vei 10, 7491 Trondheim, Norway ) , Ellefmo, Steinar L. (Department of Geoscience and Petroleum, Norwegian University of Science and Technology (NTNU), Sem Sælands vei 1, 7491 Trondheim, Norway ) , Johnsen, Geir (Centre for Autonomous Marine Operations and Systems, Department of Biology, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway ) , Søreide, Fredrik (Department of Marine Technology, Norwegian Universit)
    Remote sensing of environment v.209 ,pp. 19 - 30 , 2018 , 0034-4257 ,

    초록

    Abstract Hyperspectral seafloor surveys using airborne or spaceborne sensors are generally limited to shallow coastal areas, due to the requirement for target illumination by sunlight. Deeper marine environments devoid of sunlight cannot be imaged by conventional hyperspectral imagers. Instead, a close-range, sunlight-independent hyperspectral survey approach is required. In this study, we present the first hyperspectral image data from the deep seafloor. The data were acquired in approximately 4200 m water depth using a new Underwater Hyperspectral Imager (UHI) mounted on a remotely operated vehicle (ROV). UHI data were recorded for 112 spectral bands between 378 nm and 805 nm, with a high spectral (4 nm) and spatial resolution (1 mm per image pixel). The study area was located in a manganese nodule field in the Peru Basin (SE Pacific), close to the DISCOL (DISturbance and reCOLonization) experimental area. To test whether underwater hyperspectral imaging can be used for detection and mapping of mineral deposits in potential deep-sea mining areas, we compared two supervised classification methods, the Support Vector Machine (SVM) and the Spectral Angle Mapper (SAM). The results show that SVM is superior to SAM and is able to accurately detect nodule surfaces. The UHI therefore represents a promising tool for high-resolution seafloor exploration and characterisation prior to resource exploitation. Highlights We present the first hyperspectral image data from the deep seafloor. The data were acquired with a new UHI in 4200 m water depth. Supervised classification is able to detect manganese nodules and fauna. The UHI is a promising tool for high-resolution seafloor exploration and monitoring.

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  4. [해외논문]   How much can natural resource inventory benefit from finer resolution auxiliary data?   SCI SCIE

    Hou, Zhengyang (University of Nevada, Reno, Natural Resources & Environmental Science, Reno, NV 89667, United States ) , McRoberts, Ronald E. (Northern Research Station, U.S. Forest Service, Saint Paul, MN, United States ) , Stå (Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden ) , hl, Gö (University of Eastern Finland, Faculty of Science and Forestry, School of Forest Sciences, P.O. BOX 111, FI-80101 Joensuu, Finland ) , ran (University of Nevada, Reno, Natural Resources & Environmental Science, Reno, NV 89667, United States ) , Packalen, Petteri (University of Nevada, Reno, Natural Resources & Environmental Science, Reno, NV 89667, United States) , Greenberg, Jonathan A. , Xu, Qing
    Remote sensing of environment v.209 ,pp. 31 - 40 , 2018 , 0034-4257 ,

    초록

    Abstract For remote sensing-assisted natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the response variable of interest was firewood volume (m 3 /ha). A sample consisting of 160 field plots was selected from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, μ , and the variance of the estimator of the population mean, V μ ̂ , were estimated using two inferential frameworks, model-based and model-assisted, and compared. For each framework, V μ ̂ was estimated both analytically and empirically. Empirical variances were estimated using bootstrapping that accounted for the two-stage sampling. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributed to greater precision for estimators of population parameter, but despite the finer spatial resolution of RapidEye, the increase was only marginal, on the order of 10% for model-based variance estimators and 36% for model-assisted variance estimators; (2) subpixel information on texture was marginally beneficial for inference of large area population parameters; (3) RapidEye did not offer enough of an improvement to justify its cost relative to the free Landsat 8 imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) sampling distribution for the model-based V ̂ μ ̂ was more concentrated and smaller on the order of 42% to 59% than that for the model-assisted V ̂ μ ̂ , suggesting superior consistency and efficiency of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences. Highlights Analyses employ model-based, model-assisted inferences and two-stage sampling. Finer pixel size or subpixel information contributes little to population inferences. Compared with finer alternatives, pixel size similar to plot size is cost-effective. Model-based inference is superior to model-assisted in consistency and efficiency. Bootstrapping is an effective alternative to analytical variance estimators.

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  5. [해외논문]   Glacial and tidal strain of landfast sea ice in Terra Nova Bay, East Antarctica, observed by interferometric SAR techniques   SCI SCIE

    Han, Hyangsun (Unit of Arctic Sea–Ice Prediction, Korea Polar Research Institute, Incheon 21990, Republic of Korea ) , Lee, Hoonyol (Division of Geology and Geophysics, Kangwon National University, Chuncheon, Kangwon–do 24341, Republic of Korea)
    Remote sensing of environment v.209 ,pp. 41 - 51 , 2018 , 0034-4257 ,

    초록

    Abstract The dynamics of landfast sea ice, also called fast ice for short, has a large influence on the variability of polynyas and marine ecosystems, and the logistics for research stations near the Antarctic coast. Therefore, it is important to accurately measure the strain of fast ice and its seasonal variations, and to identify the cause of stresses on the ice. In this paper, we separate the strains from glacial stress and tidal stress of fast ice near the Campbell Glacier Tongue (CGT) in Terra Nova Bay, East Antarctica. This was done using observations from a series of one-day tandem COSMO-SkyMed Interferometric Synthetic Aperture Radar (InSAR) images obtained from December 2010 to January 2012. Firstly, we discriminated fast ice from pack ice and open water by analyzing the interferometric coherence values. We then identified the characteristics of the strains by investigating the equi-displacement lines of fringes in weekly InSAR and double-differential InSAR (DDInSAR) images. The weekly InSAR images predominantly showed glacial shear strain of the fast ice with fringes parallel to the sides of the CGT. This was due to the cumulative flow of the CGT for a week, while oscillating tidal signals were relatively small. The DDInSAR images, which cancelled glacial strain rates in two one-day InSAR images, showed a deformation of the fast ice by tidal sea surface tilt, with the fringes parallel to the coastline. Based on the unique characteristics of these strains, we separated them from the one-day InSAR images by decomposing the fringe patterns into glacial and tidal strain. Glacial shear strain rates of fast ice attached to the east of the CGT decreased from May to August owing to ice thickening and then stabilized until December. Those to the west of the CGT increased from May to July. This was possibly due to bottom melting of the ice by the increased ocean circulation during the expansion period of the nearby polynya. The glacial strain then decreased until December because of reduced polynya activity. The fast ice near the Jang Bogo Station (JBS) only showed tidal strain as it was isolated from the CGT by cracks and leads. Tidal strain rates of the fast ice were strongly correlated with the magnitude of tidal variations in all these regions, which represents shows that the tidal strain represents tidal sea surface tilt. The tidal response of fast ice to the west of the CGT and near the JBS was stronger than that to the east of the CGT, probably owing to thinner ice thickness there. Highlights Glacial and tidal strain of fast ice near Campbell Glacier Tongue was investigated. Characteristics of the strains were identified from weekly InSAR and DDInSAR images. The strains were decomposed from one-day InSAR signals based on the characteristics. Glacial strain of fast ice varied seasonally due to the changes in ice thickness. Tidal strain representing tidal sea surface tilt was correlated with tide variations.

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    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  6. [해외논문]   Detecting and quantifying standing dead tree structural loss with reconstructed tree models using voxelized terrestrial lidar data   SCI SCIE

    Putman, Eric B. (Texas A&M University, Department of Ecosystem Science and Management, 534 John Kimbrough Blvd, WFES Building, Room 360, College Station, TX 77843, USA ) , Popescu, Sorin C. (Texas A&M University, Department of Ecosystem Science and Management, 534 John Kimbrough Blvd, WFES Building, Room 334, College Station, TX 77843, USA ) , Eriksson, Marian (Texas A&M University, Department of Ecosystem Science and Management, 534 John Kimbrough Blvd, WFES Building, Room 328, College Station, TX 77843, USA ) , Zhou, Tan (Texas A&M University, Department of Ecosystem Science and Management, 534 John Kimbrough Blvd, WFES Building, Room 360, College Station, TX 77843, USA ) , Klockow, Paul (Texas A&M University, Department of Ecosystem Science and Management, 474 Olsen Blvd, Kleberg Center, Room 318, College Station, TX 77843, USA ) , Vogel, Jason (University of Florida, School of Forest Resources and Conservation, PO Box 1100410, Gainesville, FL 32611, USA ) , Moore, Georgianne W. (Texas A&M University, Department of Ecosystem Science and Management, 459 Horticulture Road, HFSB Building, Room 302B, College Sta)
    Remote sensing of environment v.209 ,pp. 52 - 65 , 2018 , 0034-4257 ,

    초록

    Abstract The structural loss rates of standing dead trees (SDTs) affect a variety of processes of interest to ecologists and foresters, yet the decomposition of SDTs has been traditionally characterized by qualitative decay classes, reductions in wood density as decay progresses, and sampling schemes focused on estimating snag longevity. By establishing a methodology to accurately and efficiently quantify SDT structural loss over time, these estimated structural loss rates would improve the performance of a variety of models and potentially provide new insight as to the manner in which SDTs undergo degradation in various conditions. The specific objective of this study were: 1) utilize the TreeVolX algorithm to estimate the volume of 29 SDTs scanned with terrestrial lidar; 2) develop a novel, voxel-based change detection algorithm capable of providing automated structural loss estimates with multitemporal terrestrial lidar observations; and 3) estimate and characterize the structural loss rates of Pinus taeda and Quercus stellata in southeastern Texas. A voxel-based change detection methodology was developed to accurately detect and quantify structural losses and incorporated several methods to mitigate the challenges presented by shifting tree and branch positions as SDT decay progresses. The volume and structural loss of 29 SDTs, composed of Pinus taeda and Quercus stellata , were successfully estimated using multitemporal terrestrial lidar observations over elapsed times ranging from 71 to 753 days. Pine and oak structural loss rates were characterized by estimating the amount of volumetric loss occurring in 20 equal-interval height bins of each SDT. Results showed that large pine snags exhibited more rapid structural loss in comparison to medium-sized oak snags in southeastern Texas. Highlights A voxel-based change detection algorithm successfully detected snag degradation. The algorithm can quantify structural loss and identify lost branches. Structural loss rates were estimated with repeated terrestrial lidar observations. Large pine snags were found to degrade more quickly than medium-sized oak snags. Height bins offer a unique three-dimensional perspective of structural loss rates.

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  7. [해외논문]   Evaluation and modification of the Drought Severity Index (DSI) in East Asia   SCI SCIE

    Um, Myoung-Jin (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea ) , Kim, Yeonjoo (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea ) , Park, Daeryong (Department of Civil, Environmental, and Plant Engineering, Konkuk University, Seoul 05029, Republic of Korea)
    Remote sensing of environment v.209 ,pp. 66 - 76 , 2018 , 0034-4257 ,

    초록

    Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Drought Severity Index (DSI) can be produced at a 1-km spatial resolution and can be used for a wide range of water-resource and ecological applications. This study aims to understand the robustness and sensitivity of the DSI in East Asia, and we investigate the performance of the annual DSI using different Normalized Difference Vegetation Index (NDVI) datasets. Additionally, the MODIS-based DSI is compared to other drought indices, including the DSI with Advanced Very High Resolution Radiometer (AVHRR) NDVI (DSI AVHRR ) and the Standardized Precipitation Evapotranspiration Index (SPEI) with the Climate Research Unit (CRU) dataset. Three different drought indices are estimated in East Asia from 2000 to 2013 and compared via a correlation analysis based on a 5° × 5° grid. Specifically, the correlation between the DSI and DSI AVHRR is relatively high (0.796), which suggests the potential use of the DSI based on combined products that include parameters such as the NDVI, although the DSI originally used only MODIS-based products. Characteristics such as the frequency and spatial extent of droughts based on the DSI are compared to those based on the SPEI using the drought classification schemes that were originally proposed for the SPEI and DSI, including mild, moderate, severe and extremely dry classes. Based on the results, we suggest a revised classification according to a comparison of the DSI and SPEI. The frequency and spatial extent results of the SPEI and DSI exhibit good agreement when using this classification. Moreover, the DSI from the revised classification is used to evaluate drought events in East Asia in 2003, 2006, 2008 and 2009. Overall, this study shows the potential of using the DSI with datasets that differ from the originally suggested datasets; however, caution must be taken when classifying and identifying drought events. Highlights The robustness and sensitivity of the DSI is evaluated in East Asia. A revised classification based on a comparison of the DSI and SPEI is suggested. Potential of using the DSI with datasets that differ from those originally suggested.

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

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  8. [해외논문]   Validation of Jason-3 tracking modes over French rivers   SCI SCIE

    Biancamaria, Sylvain (LEGOS, Université) , Schaedele, Thomas (de Toulouse, CNES, CNRS, IRD, UPS, 14 avenue Edouard Belin, 31400 Toulouse, France ) , Blumstein, Denis (LEGOS, Université) , Frappart, Fré (de Toulouse, CNES, CNRS, IRD, UPS, 14 avenue Edouard Belin, 31400 Toulouse, France ) , dé (LEGOS, Université) , ric (de Toulouse, CNES, CNRS, IRD, UPS, 14 avenue Edouard Belin, 31400 Toulouse, France ) , Boy, Franç (LEGOS, Université) , ois (de Toulouse, CNES, CNRS, IRD, UPS, 14 avenue Edouard Belin, 31400 Toulouse, France ) , Desjonquè (CNES, 18 avenue Edouard Belin, 31401 Toulouse Cedex, France ) , res, Jean-Damien (CNES, 18 avenue Edouard Belin, 31401 Toulouse Cedex, France ) , Pottier, Claire (CNES, 18 avenue Edouard Belin, 31401 Toulouse Cedex, France ) , Blarel, Fabien (LEGOS, Université) , Niñ (de Toulouse, CNES, CNRS, IRD, UPS, 14 avenue Edouard Belin, 31400 Toulouse, France ) , o, Fernando (LEGOS, Université)
    Remote sensing of environment v.209 ,pp. 77 - 89 , 2018 , 0034-4257 ,

    초록

    Abstract Satellite nadir radar altimeters have been widely used to measure river and lake surface water elevations. They can now retrieve the elevations of some rivers The Jason-3 altimetry mission, launched in January 2016, has an alternative instrument operation mode, the so called Open-Loop (OL) or Digital Elevation Model (DEM) tracking mode. This mode is intended to help overcome this issue, by using an on-board DEM. However it was not used in 2016 as the operational mode because of difficulties in defining an accurate on-board global-scale DEM. Mainland France has been chosen to test the OL tracking mode, as water masks and DEMs of sufficient accuracy are available. Following the launch of Jason-3, Jason-2 (its predecessor) was maintained on the same nominal orbit as its follow-on, for more than 6 months. During this tandem period, data from the first 10 Jason-3 cycles (a Jason-2/-3 cycle corresponds to 10 days) were acquired in the traditional Closed-Loop (CL) tracking mode. Jason-3 data from the last 13 cycles were acquired in OL tracking mode. Jason-2 was always in CL tracking mode. Compared to nearby in situ gages and for river wider than 100 m, Jason-3 water elevation anomalies have a RMSE between 0.20 and 0.30 m for most reaches. Jason-3 performance over narrow rivers is similar to that of Jason-2. In CL tracking mode, Jason-3 altimeter tends to be locked over the surrounding topography more frequently than Jason-2 (due to the specific post-launch Jason-2 altimeter tuning). This study shows that Jason-2 observed 60% of river reaches studied (48 of 86 reaches), whereas Jason-3 in OL tracking mode was able to measure all river reaches for every cycle. This result clearly highlights the significant advantages of the OL tracking mode for observation of steep-sided rivers. However, further investigations are required to compute an accurate on-board global-scale DEM and to determine those locations where the use of OL tracking mode is or is not appropriate. Highlights Validation of the newly launched Jason-3 altimetry mission Jason-3 detects rivers wider than 100 m, with RMSE from 20 to 30 cm in most cases Some rivers with width as small as 40 m have been observed, but with higher error. Jason-3's open-loop tracking mode measures steep-sided rivers, unlike Jason-2. Open-loop tracking mode yields better results, but needs an accurate onboard DEM.

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  9. [해외논문]   Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and lidar plots   SCI SCIE

    Matasci, Giona (Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada ) , Hermosilla, Txomin (Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada ) , Wulder, Michael A. (Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada ) , White, Joanne C. (Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada ) , Coops, Nicholas C. (Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada ) , Hobart, Geordie W. (Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada ) , Zald, Harold S.J. (Department of Forestry and Wildland Resources, Humboldt State University, 1 Harpst St., Arcata, CA 95521, USA)
    Remote sensing of environment v.209 ,pp. 90 - 106 , 2018 , 0034-4257 ,

    초록

    Abstract Passive optical remotely sensed images such as those from the Landsat satellites enable the development of spatially comprehensive, well-calibrated reflectance measures that support large-area mapping. In recent years, as an alternative to field plot data, the use of Light Detection and Ranging (lidar) acquisitions for calibration and validation purposes in combination with such satellite reflectance data to model a range of forest structural response variables has become well established. In this research, we use a predictive modeling approach to map forest structural attributes over the ~552millionha boreal forest of Canada. For model calibration and independent validation we utilize airborne lidar-derived measurements of forest vertical structure (known as lidar plots) obtained in 2010 via a >25,000km transect-based national survey. Models were developed linking the lidar plot structural variables to wall-to-wall 30-m spatial resolution surface reflectance composites derived from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery. Spectral indices extracted from the composites, disturbance information (years since disturbance and type), as well as geographic position and topographic variables (i.e., elevation, slope, radiation, etc.) were considered as predictor variables. A nearest neighbor imputation approach based on the Random Forest framework was used to predict a total of 10 forest structural attributes. The model was developed and validated on >80,000 lidar plots, with R 2 values ranging from 0.49 to 0.61 for key response variables such as canopy cover, stand height, basal area, stem volume, and aboveground biomass. Additionally, a predictor variable importance analysis confirmed that spectral indices, elevation, and geographic coordinates were key sources of information, ultimately offering an improved understanding of the driving variables for large-area forest structure modeling. This study demonstrates the integration of airborne lidar and Landsat-derived reflectance products to generate detailed and spatially extensive maps of forest structure. The methods are portable to map other attributes of interest (based upon calibration data) through access to Landsat or other appropriate optical remotely-sensed data sources, thereby offering unique opportunities for science, monitoring, and reporting programs. Highlights Framework for large-area mapping of forest structural attributes Landsat pixel composites and LiDAR plots data combined with an imputation model R 2 in 0.49–0.61 for key forest attributes when validating on >20,000 lidar plots. 30m resolution forest attributes maps generated for Canadian boreal zone. Relevance of the predictors provided insights on key model drivers.

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  10. [해외논문]   Characterization of vegetation and soil scattering mechanisms across different biomes using P-band SAR polarimetry   SCI SCIE

    Alemohammad, Seyed Hamed (Corresponding author at: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, United States.) , Konings, Alexandra G. , Jagdhuber, Thomas , Moghaddam, Mahta , Entekhabi, Dara
    Remote sensing of environment v.209 ,pp. 107 - 117 , 2018 , 0034-4257 ,

    초록

    Abstract Understanding the scattering mechanisms from the ground surface in the presence of different vegetation densities is necessary for the interpretation of P-band Synthetic Aperture Radar (SAR) observations and for the design of geophysical retrieval algorithms. In this study, a quantitative analysis of vegetation and soil scattering mechanisms estimated from the observations of an airborne P-band SAR instrument across nine different biomes in North America is presented. The goal is to apply a hybrid (model- and eigen-based) three component decomposition approach to separate the contributions of surface, double-bounce and vegetation volume scattering across a wide range of biome conditions. The decomposition makes no prior assumptions about vegetation structure. We characterize the dynamics of the decomposition across different North American biomes and assess their characteristic range. Impacts of vegetation cover seasonality and soil surface roughness on the contributions of each scattering mechanism are also investigated. Observations used here are part of the NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission and data have been collected between 2013 and 2015. Highlights A hybrid decomposition approach is applied to fully polarimetric P-band SAR observations. Contributions of surface, vegetation, and double-bounce scattering are separated. Decomposition results from 10 campaign sites across North America are presented. Impacts of surface roughness and seasonal vegetation characteristics are explored.

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