Land Cover, General Problems, Remote Sensing

Chapter Contents (Back)
Classification. Remote Sensing. Land Cover. Ground Cover. The overlapping subset:
See also Land Use, General Problems.
See also Object Based Land Cover, Region Based Land Cover, Land Use Analysis.
See also LAI, Leaf Area Index, Land Cover Analysis.
See also Land Cover, Land Use, Very High Resolution, High Spatial Resolution.
See also Subpixel Target, Subpixel Land Use, Tiny Objects.
See also Surface Fractional Vegetation Cover.
See also Classification for Urban Area Land Cover, Remote Sensing.
See also Land Cover Analysis, Specific Location Applications, Site Analysis, Site Specific.
See also Sentinel-1, -2, -3 for Land Cover, Remote Sensing.
See also Rice Crop Analysis, Production, Detection, Health, Change. For global scale analysis:
See also Global-Scale Analysis, Global Land Cover Analysis.

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Chen, L.[Li],
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Bagan, H.[Hasi], Wang, Q.X.[Qin-Xue], Watanabe, M.[Masataka], Kameyama, S.[Satoshi], Bao, Y.H.[Yu-Hai],
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A land-cover classification methodology using ASTER VNIR, SWIR, and TIR band combinations based on wavelet fusion and SOM neural network methods, and classification accuracy of different band combinations. BibRef

Trias-Sanz, R.[Roger], Stamon, G.[Georges], Louchet, J.[Jean],
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Elsevier DOI 0803
Segmentation; Hierarchical; Colour; Cartography; Land cover BibRef

Tseng, M.H.[Ming-Hseng], Chen, S.J.[Sheng-Jhe], Hwang, G.H.[Gwo-Haur], Shen, M.Y.[Ming-Yu],
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feature extraction BibRef

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Liu, X., Li, X., Liu, L., He, J., Ai, B.,
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Lehner, P.E., Adelman, L., DiStasio, R.J., Erie, M.C., Mittel, J.S., Olson, S.L.,
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Tolpekin, V.A., Stein, A.,
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Congalton, R.G.[Russell G.], Green, K.[Kass],
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Baraldi, A., Gironda, M., Simonetti, D.,
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Forzieri, G., Castelli, F., Vivoni, E.R.,
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Elsevier DOI 1110
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Earlier: A1, A3, A2:
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HTML Version. 1307

Kasetkasem, T.[Teerasit], Rakwatin, P.[Preesan], Sirisommai, R.[Ratchawit], Eiumnoh, A.[Apisit],
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RS(8), No. 9, 2016, pp. 727.
DOI Link 1610

Gu, J.Y.[Jian-Yu], Congalton, R.G.[Russell G.], Pan, Y.Z.[Yao-Zhong],
The Impact of Positional Errors on Soft Classification Accuracy Assessment: A Simulation Analysis,
RS(7), No. 1, 2015, pp. 579-599.
DOI Link 1502

Chew, C.C., Small, E.E., Larson, K.M., Zavorotny, V.U.,
Vegetation Sensing Using GPS-Interferometric Reflectometry: Theoretical Effects of Canopy Parameters on Signal-to-Noise Ratio Data,
GeoRS(53), No. 5, May 2015, pp. 2755-2764.
Global Positioning System BibRef

Siegmann, B.[Bastian], Glässer, C.[Cornelia], Itzerott, S.[Sibylle], Neumann, C.[Carsten],
An Enhanced Classification Approach using Hyperspectral Image Data in Combination with in situ Spectral Measurements for the Mapping of Vegetation Communities,
PFG(2014), No. 6, 2014, pp. 523-533.
DOI Link 1503

Burai, P.[Péter], Deák, B.[Balázs], Valkó, O.[Orsolya], Tomor, T.[Tamás],
Classification of Herbaceous Vegetation Using Airborne Hyperspectral Imagery,
RS(7), No. 2, 2015, pp. 2046-2066.
DOI Link 1503

See, L.[Linda], Schepaschenko, D.[Dmitry], Lesiv, M.[Myroslava], McCallum, I.[Ian], Fritz, S.[Steffen], Comber, A.J.[Alexis J.], Perger, C.[Christoph], Schill, C.[Christian], Zhao, Y.Y.[Yuan-Yuan], Maus, V.[Victor], Siraj, M.A.[Muhammad Athar], Albrecht, F.[Franziska], Cipriani, A.[Anna], Vakolyuk, M.[Maryana], Garcia, A.[Alfredo], Rabia, A.H.[Ahmed H.], Singha, K.[Kuleswar], Marcarini, A.A.[Abel Alan], Kattenborn, T.[Teja], Hazarika, R.[Rubul], Schepaschenko, M.[Maria], van der Velde, M.[Marijn], Kraxner, F.[Florian], Obersteiner, M.[Michael],
Building a hybrid land cover map with crowdsourcing and geographically weighted regression,
PandRS(103), No. 1, 2015, pp. 48-56.
Elsevier DOI 1504
Land cover BibRef

Wu, X.C.[Xiao-Cui], Ju, W.M.[Wei-Min], Zhou, Y.[Yanlian], He, M.Z.[Ming-Zhu], Law, B.E.[Beverly E.], Black, T.A.[T. Andrew], Margolis, H.A.[Hank A.], Cescatti, A.[Alessandro], Gu, L.H.[Lian-Hong], Montagnani, L.[Leonardo], Noormets, A.[Asko], Griffis, T.J.[Timothy J.], Pilegaard, K.[Kim], Varlagin, A.[Andrej], Valentini, R.[Riccardo], Blanken, P.D.[Peter D.], Wang, S.Q.[Shao-Qiang], Wang, H.M.[Hui-Min], Han, S.J.[Shi-Jie], Yan, J.H.[Jun-Hua], Li, Y.N.[Ying-Nian], Zhou, B.B.[Bing-Bing], Liu, Y.[Yibo],
Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales,
RS(7), No. 3, 2015, pp. 2238-2278.
DOI Link 1504
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Hou, D.Y.[Dong-Yang], Chen, J.[Jun], Wu, H.[Hao], Li, S.N.[Song-Nian], Chen, F.[Fei], Zhang, W.W.[Wei-Wei],
Active Collection of Land Cover Sample Data from Geo-Tagged Web Texts,
RS(7), No. 5, 2015, pp. 5805-5827.
DOI Link 1506

Xing, H.Q.[Hua-Qiao], Chen, J.[Jun], Wu, H.[Hao], Hou, D.Y.[Dong-Yang],
A Web Service-Oriented Geoprocessing System for Supporting Intelligent Land Cover Change Detection,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901

Yan, S.[Shuang], Jiang, L.M.[Ling-Mei], Chai, L.[Linna], Yang, J.T.[Jun-Tao], Kou, X.K.[Xiao-Kang],
Calibration of the L-MEB Model for Croplands in HiWATER Using PLMR Observation,
RS(7), No. 8, 2015, pp. 10878.
DOI Link 1509

Bachmann, M.[Martin], Makarau, A.[Aliaksei], Segl, K.[Karl], Richter, R.[Rudolf],
Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products: Examples for Ground Reflectance Retrieval and Vegetation Indices,
RS(7), No. 8, 2015, pp. 10689.
DOI Link 1509

Ishihara, M.[Mitsunori], Inoue, Y.[Yoshio], Ono, K.[Keisuke], Shimizu, M.[Mariko], Matsuura, S.[Shoji],
The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands: Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements,
RS(7), No. 10, 2015, pp. 14079.
DOI Link 1511

Zhao, F.[Feng], Guo, Y.Q.[Yi-Qing], Huang, Y.B.[Yan-Bo], Verhoef, W.[Wout], van der Tol, C.[Christiaan], Dai, B.[Bo], Liu, L.Y.[Liang-Yun], Zhao, H.[Huijie], Liu, G.[Guang],
Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion,
RS(7), No. 10, 2015, pp. 14179.
DOI Link 1511

Bue, B.D.[Brian D.], Thompson, D.R.[David R.], Sellar, R.G.[R. Glenn], Podest, E.V.[Erika V.], Eastwood, M.L.[Michael L.], Helmlinger, M.C.[Mark C.], McCubbin, I.B.[Ian B.], Morgan, J.D.[John D.],
Leveraging in-scene spectra for vegetation species discrimination with MESMA-MDA,
PandRS(108), No. 1, 2015, pp. 33-48.
Elsevier DOI 1511
Hyperspectral BibRef

Szulkin, M.[Marta], Zelazowski, P.[Przemyslaw], Marrot, P.[Pascal], Charmantier, A.[Anne],
Application of High Resolution Satellite Imagery to Characterize Individual-Based Environmental Heterogeneity in a Wild Blue Tit Population,
RS(7), No. 10, 2015, pp. 13319.
DOI Link 1511

Xie, Y.H.[Yan-Hui], Shi, J.C.[Jian-Cheng], Lei, Y.H.[Yong-Hui], Li, Y.Q.[Yun-Qing],
Modeling Microwave Emission from Short Vegetation-Covered Surfaces,
RS(7), No. 10, 2015, pp. 14099.
DOI Link 1511

Peng, J.J.[Jing-Jing], Fan, W.J.[Wen-Jie], Xu, X.[Xiru], Wang, L.Z.[Li-Zhao], Liu, Q.H.[Qin-Huo], Li, J.[Jvcai], Zhao, P.[Peng],
Estimating Crop Albedo in the Application of a Physical Model Based on the Law of Energy Conservation and Spectral Invariants,
RS(7), No. 11, 2015, pp. 15536.
DOI Link 1512

Wu, X.D.[Xiao-Dan], Xiao, Q.[Qing], Wen, J.G.[Jian-Guang], Liu, Q.A.[Qi-Ang], You, D.Q.[Dong-Qin], Dou, B.[Baocheng], Tang, Y.[Yong], Li, X.[Xiaowen],
Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe,
RS(7), No. 11, 2015, pp. 14757.
DOI Link 1512

Sweeney, S.[Sean], Ruseva, T.[Tatyana], Estes, L.[Lyndon], Evans, T.[Tom],
Mapping Cropland in Smallholder-Dominated Savannas: Integrating Remote Sensing Techniques and Probabilistic Modeling,
RS(7), No. 11, 2015, pp. 15295.
DOI Link 1512

Huang, Y., Walker, J.P., Gao, Y., Wu, X., Monerris, A.,
Estimation of Vegetation Water Content From the Radar Vegetation Index at L-Band,
GeoRS(54), No. 2, February 2016, pp. 981-989.
Backscatter BibRef

Atoum, Y.[Yousef], Afridi, M.J.[Muhammad Jamal], Liu, X.M.[Xiao-Ming], McGrath, J.M.[J. Mitchell], Hanson, L.E.[Linda E.],
On developing and enhancing plant-level disease rating systems in real fields,
PR(53), No. 1, 2016, pp. 287-299.
Elsevier DOI 1602
CLS Rater BibRef

Luo, H.[Heng], Li, L.[Lin], Zhu, H.H.[Hai-Hong], Kuai, X.[Xi], Zhang, Z.J.[Zhi-Jun], Liu, Y.[Yu],
Land Cover Extraction from High Resolution ZY-3 Satellite Imagery Using Ontology-Based Method,
IJGI(5), No. 3, 2016, pp. 31.
DOI Link 1604

Sawada, Y., Tsutsui, H., Koike, T., Rasmy, M., Seto, R., Fujii, H.,
A Field Verification of an Algorithm for Retrieving Vegetation Water Content From Passive Microwave Observations,
GeoRS(54), No. 4, April 2016, pp. 2082-2095.
Land surface BibRef

Chang, T.[Tommy], Comandur, B.[Bharath], Park, J.[Johnny], Kak, A.C.[Avinash C.],
A variance-based Bayesian framework for improving Land-Cover classification through wide-area learning from large geographic regions,
CVIU(147), No. 1, 2016, pp. 3-22.
Elsevier DOI 1605

Sicre, C.M.[Claire Marais], Inglada, J.[Jordi], Fieuzal, R.[Rémy], Baup, F.[Frédéric], Valero, S.[Silvia], Cros, J.[Jérôme], Huc, M.[Mireille], Demarez, V.[Valérie],
Early Detection of Summer Crops Using High Spatial Resolution Optical Image Time Series,
RS(8), No. 7, 2016, pp. 591.
DOI Link 1608

Chen, Y.Y.[Yuan-Yuan], Wang, Q.F.[Quan-Fang], Wang, Y.L.[Yan-Long], Duan, S.B.[Si-Bo], Xu, M.Z.[Miao-Zhong], Li, Z.L.[Zhao-Liang],
A Spectral Signature Shape-Based Algorithm for Landsat Image Classification,
IJGI(5), No. 9, 2016, pp. 154.
DOI Link 1610
More than just the value at the point. BibRef

Wang, H.S.[He-Song], Jia, G.S.[Gen-Suo], Zhang, A.Z.[An-Zhi], Miao, C.[Chen],
Assessment of Spatial Representativeness of Eddy Covariance Flux Data from Flux Tower to Regional Grid,
RS(8), No. 9, 2016, pp. 742.
DOI Link 1610

Block, S.[Sebastián], González, E.J.[Edgar J.], Gallardo-Cruz, J.A.[J. Alberto], Fernández, A.[Ana], Solórzano, J.V.[Jonathan V.], Meave, J.A.[Jorge A.],
Using Google Earth Surface Metrics to Predict Plant Species Richness in a Complex Landscape,
RS(8), No. 10, 2016, pp. 865.
DOI Link 1609

Grebby, S.[Stephen], Field, E.[Elena], Tansey, K.[Kevin],
Evaluating the Use of an Object-Based Approach to Lithological Mapping in Vegetated Terrain,
RS(8), No. 10, 2016, pp. 843.
DOI Link 1609

Connette, K.J.L.[Katherine J. LaJeunesse], Connette, G.[Grant], Bernd, A.[Asja], Phyo, P.[Paing], Aung, K.H.[Kyaw Htet], Tun, Y.L.[Ye Lin], Thein, Z.M.[Zaw Min], Horning, N.[Ned], Leimgruber, P.[Peter], Songer, M.[Melissa],
Assessment of Mining Extent and Expansion in Myanmar Based on Freely-Available Satellite Imagery,
RS(8), No. 11, 2016, pp. 912.
DOI Link 1612

Volpi, M., Tuia, D.[Devis],
Dense Semantic Labeling of Subdecimeter Resolution Images With Convolutional Neural Networks,
GeoRS(55), No. 2, February 2017, pp. 881-893.
geophysical image processing BibRef

Tan, Q.Y.[Qiao-Yu], Liu, Y.[Yezi], Chen, X.[Xia], Yu, G.X.[Guo-Xian],
Multi-Label Classification Based on Low Rank Representation for Image Annotation,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703

Yan, L.[Li], Zhu, R.X.[Rui-Xi], Mo, N.[Nan], Liu, Y.[Yi],
Improved Class-Specific Codebook with Two-Step Classification for Scene-Level Classification of High Resolution Remote Sensing Images,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704

Yan, L.[Li], Zhu, R.X.[Rui-Xi], Liu, Y.[Yi], Mo, N.[Nan],
Scene Capture and Selected Codebook-Based Refined Fuzzy Classification of Large High-Resolution Images,
GeoRS(56), No. 7, July 2018, pp. 4178-4192.
feature extraction, fuzzy set theory, image classification, image representation, image resolution, image segmentation, selection of representative vocabularies BibRef

Wang, Y.[Yexin], Di, K.C.[Kai-Chang], Xin, X.[Xin], Wan, W.H.[Wen-Hui],
Automatic detection of Martian dark slope streaks by machine learning using HiRISE images,
PandRS(129), No. 1, 2017, pp. 12-20.
Elsevier DOI 1706
Dark slope streak. BibRef

Rozenstein, O.[Offer], Adamowski, J.[Jan],
Linking Spaceborne and Ground Observations of Autumn Foliage Senescence in Southern Québec, Canada,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706

Lu, X., Zheng, X., Yuan, Y.,
Remote Sensing Scene Classification by Unsupervised Representation Learning,
GeoRS(55), No. 9, September 2017, pp. 5148-5157.
spatial pyramid model, weighted deconvolution model, BibRef

Santara, A., Mani, K., Hatwar, P., Singh, A., Garg, A., Padia, K., Mitra, P.,
BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification,
GeoRS(55), No. 9, September 2017, pp. 5293-5301.
deep learning based land cover classification algorithms, BibRef

Marinoni, A., Iannelli, G.C., Gamba, P.,
An Information Theory-Based Scheme for Efficient Classification of Remote Sensing Data,
GeoRS(55), No. 10, October 2017, pp. 5864-5876.
feature extraction, remote sensing, BibRef

Ye, B.[Bei], Tian, S.F.[Shu-Fang], Ge, J.[Jia], Sun, Y.[Yaqin],
Assessment of WorldView-3 Data for Lithological Mapping,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712

Liu, Q., Hang, R., Song, H., Li, Z.,
Learning Multiscale Deep Features for High-Resolution Satellite Image Scene Classification,
GeoRS(56), No. 1, January 2018, pp. 117-126.
Feature extraction, Histograms, Learning systems, Satellites, Spatial resolution, Training, Visualization, spatial pyramid pooling BibRef

Chen, W.[Weitao], Li, X.J.[Xian-Ju], He, H.X.[Hai-Xia], Wang, L.Z.[Li-Zhe],
Assessing Different Feature Sets' Effects on Land Cover Classification in Complex Surface-Mined Landscapes by ZiYuan-3 Satellite Imagery,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802

Svendsen, D.H.[Daniel H.], Martino, L.[Luca], Campos-Taberner, M.[Manuel], Garcia-Haro, F.J., Camps-Valls, G.[Gustau],
Joint Gaussian Processes for Biophysical Parameter Retrieval,
GeoRS(56), No. 3, March 2018, pp. 1718-1727.
Gaussian processes, geophysical image processing, inverse problems, learning (artificial intelligence), vegetation monitoring BibRef

Camps-Valls, G.[Gustau], Svendsen, D.H.[Daniel H.], Martino, L.[Luca], Muńoz-Marí, J.[Jordi], Laparra, V.[Valero], Campos-Taberner, M.[Manuel], Luengo, D.[David],
Physics-Aware Gaussian Processes for Earth Observation,
SCIA17(II: 205-217).
Springer DOI 1706

Zhang, X.N.[Xiao-Ning], Jiao, Z.[Ziti], Dong, Y.D.[Ya-Dong], Zhang, H.[Hu], Li, Y.[Yang], He, D.[Dandan], Ding, A.X.[An-Xin], Yin, S.[Siyang], Cui, L.[Lei], Chang, Y.X.[Ya-Xuan],
Potential Investigation of Linking PROSAIL with the Ross-Li BRDF Model for Vegetation Characterization,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804

Guo, R.[Rui], Liu, J.B.[Jian-Bo], Li, N.[Na], Liu, S.[Shibin], Chen, F.[Fu], Cheng, B.[Bo], Duan, J.B.[Jian-Bo], Li, X.[Xinpeng], Ma, C.[Caihong],
Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks,
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804

Xia, W.[Wei], Ma, C.H.[Cai-Hong], Liu, J.B.[Jian-Bo], Liu, S.B.[Shi-Bin], Chen, F.[Fu], Yang, Z.[Zhi], Duan, J.B.[Jian-Bo],
High-Resolution Remote Sensing Imagery Classification of Imbalanced Data Using Multistage Sampling Method and Deep Neural Networks,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911

Wen, J.G.[Jian-Guang], Liu, Q.A.[Qi-Ang], Xiao, Q.[Qing], Liu, Q.H.[Qin-Huo], You, D.Q.[Dong-Qin], Hao, D.L.[Da-Lei], Wu, S.B.[Sheng-Biao], Lin, X.W.[Xing-Wen],
Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804

Hao, D.L.[Da-Lei], Wen, J.G.[Jian-Guang], Xiao, Q.[Qing], Wu, S.B.[Sheng-Biao], Lin, X.W.[Xing-Wen], Dou, B.C.[Bao-Cheng], You, D.Q.[Dong-Qin], Tang, Y.[Yong],
Simulation and Analysis of the Topographic Effects on Snow-Free Albedo over Rugged Terrain,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804

Wu, S.B.[Sheng-Biao], Wen, J.G.[Jian-Guang], Lin, X.W.[Xing-Wen], Hao, D.L.[Da-Lei], You, D.Q.[Dong-Qin], Xiao, Q.[Qing], Liu, Q.H.[Qin-Huo], Yin, T.G.[Tian-Gang],
Modeling Discrete Forest Anisotropic Reflectance Over a Sloped Surface With an Extended GOMS and SAIL Model,
GeoRS(57), No. 2, February 2019, pp. 944-957.
Surface topography, Atmospheric modeling, Forestry, Vegetation, Scattering, Remote sensing, Canopy reflectance, sloped surface BibRef

Marcinkowska-Ochtyra, A.[Adriana], Zagajewski, B.[Bogdan], Raczko, E.[Edwin], Ochtyra, A.[Adrian], Jarocinska, A.[Anna],
Classification of High-Mountain Vegetation Communities within a Diverse Giant Mountains Ecosystem Using Airborne APEX Hyperspectral Imagery,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805

Costa, H.[Hugo], Almeida, D.[Diana], Vala, F.[Francisco], Marcelino, F.[Filipe], Caetano, M.[Mário],
Land Cover Mapping from Remotely Sensed and Auxiliary Data for Harmonized Official Statistics,
IJGI(7), No. 4, 2018, pp. xx-yy.
DOI Link 1805

Mutowo, G.[Godfrey], Mutanga, O.[Onisimo], Masocha, M.[Mhosisi],
Evaluating the Applications of the Near-Infrared Region in Mapping Foliar N in the Miombo Woodlands,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
Nitrogen in leaves. BibRef

Hao, Y.L.[Yan-Ling], Cui, T.W.[Ting-Wei], Singh, V.P.[Vijay P.], Zhang, J.[Jie], Yu, R.H.[Rui-Hong], Zhao, W.J.[Wen-Jing],
Diurnal Variation of Light Absorption in the Yellow River Estuary,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805

McRoberts, R.E.[Ronald E.], Stehman, S.V.[Stephen V.], Liknes, G.C.[Greg C.], Nćsset, E.[Erik], Sannier, C.[Christophe], Walters, B.F.[Brian F.],
The effects of imperfect reference data on remote sensing-assisted estimators of land cover class proportions,
PandRS(142), 2018, pp. 292-300.
Elsevier DOI 1807
Intepreter error, Bias, Precision, Greenhouse gas inventory, Gain-loss method BibRef

Mahdianpari, M.[Masoud], Salehi, B.[Bahram], Rezaee, M.[Mohammad], Mohammadimanesh, F.[Fariba], Zhang, Y.[Yun],
Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808

Yang, G., Shen, H., Sun, W., Li, J., Diao, N., He, Z.,
On the Generation of Gapless and Seamless Daily Surface Reflectance Data,
GeoRS(56), No. 8, August 2018, pp. 4289-4306.
geophysical image processing, image reconstruction, land cover, remote sensing, time series, time series BibRef

Ottinger, M.[Marco], Clauss, K.[Kersten], Kuenzer, C.[Claudia],
Opportunities and Challenges for the Estimation of Aquaculture Production Based on Earth Observation Data,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808

Yu, Y.L.[Yun-Long], Liu, F.X.[Fu-Xian],
Dense Connectivity Based Two-Stream Deep Feature Fusion Framework for Aerial Scene Classification,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808

Levy, C.R.[Charlotte R.], Burakowski, E.[Elizabeth], Richardson, A.D.[Andrew D.],
Novel Measurements of Fine-Scale Albedo: Using a Commercial Quadcopter to Measure Radiation Fluxes,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809

Sun, H.[Hua], Wang, Q.[Qing], Wang, G.X.[Guang-Xing], Lin, H.[Hui], Luo, P.[Peng], Li, J.P.[Ji-Ping], Zeng, S.[Siqi], Xu, X.Y.[Xiao-Yu], Ren, L.X.[Lan-Xiang],
Optimizing kNN for Mapping Vegetation Cover of Arid and Semi-Arid Areas Using Landsat Images,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809

Garcia-Salgado, B.P.[Beatriz P.], Ponomaryov, V.I.[Volodymyr I.], Sadovnychiy, S.[Sergiy], Robles-Gonzalez, M.[Marco],
Parallel supervised land-cover classification system for hyperspectral and multispectral images,
RealTimeIP(14), No. 3, October 2018, pp. 687-704.
Springer DOI 1811

Zeng, Y.[Yelu], Xu, B.D.[Bao-Dong], Yin, G.F.[Gao-Fei], Wu, S.B.[Sheng-Biao], Hu, G.Q.[Guo-Qing], Yan, K.[Kai], Yang, B.[Bin], Song, W.J.[Wan-Juan], Li, J.[Jing],
Spectral Invariant Provides a Practical Modeling Approach for Future Biophysical Variable Estimations,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811

Campos, J.C.[Joăo Carlos], Brito, J.C.[José Carlos],
Mapping underrepresented land cover heterogeneity in arid regions: The Sahara-Sahel example,
PandRS(146), 2018, pp. 211-220.
Elsevier DOI 1812
Arid regions, Ecoregions, Landsat, Remote sensing, Supervised classification BibRef

Zhao, W.Z.[Wen-Zhi], Emery, W.J.[William J.], Bo, Y.C.[Yan-Chen], Chen, J.[Jiage],
Land Cover Mapping with Higher Order Graph-Based Co-Occurrence Model,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Gaetano, R.[Raffaele], Ienco, D.[Dino], Ose, K.[Kenji], Cresson, R.[Remi],
A Two-Branch CNN Architecture for Land Cover Classification of PAN and MS Imagery,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Chen, D.[Di], Lu, M.[Miao], Zhou, Q.[Qingbo], Xiao, J.F.[Jing-Feng], Ru, Y.T.[Ya-Ting], Wei, Y.B.[Yan-Bing], Wu, W.B.[Wen-Bin],
Comparison of Two Synergy Approaches for Hybrid Cropland Mapping,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902

Zhang, W.[Wei], Tang, P.[Ping], Zhao, L.J.[Li-Jun],
Remote Sensing Image Scene Classification Using CNN-CapsNet,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903

Du, Z.R.[Zhen-Rong], Yang, J.Y.[Jian-Yu], Ou, C.[Cong], Zhang, T.T.[Ting-Ting],
Smallholder Crop Area Mapped with a Semantic Segmentation Deep Learning Method,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904

Da Re, D.[Daniele], de Clercq, E.M.[Eva M.], Tordoni, E.[Enrico], Madder, M.[Maxime], Rousseau, R.[Raphaël], Vanwambeke, S.O.[Sophie O.],
Looking for Ticks from Space: Using Remotely Sensed Spectral Diversity to Assess Amblyomma and Hyalomma Tick Abundance,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904

Park, S.E.[Sang-Eun], Jung, Y.T.[Yoon Taek], Cho, J.H.[Jae-Hyoung], Moon, H.[Hyoi], Han, S.H.[Seung-Hoon],
Theoretical Evaluation of Water Cloud Model Vegetation Parameters,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
For scattering. BibRef

Muhammad, U.[Usman], Wang, W.Q.A.[Wei-Qi-Ang], Hadid, A.[Abdenour], Pervez, S.[Shahbaz],
Bag of words KAZE (BoWK) with two-step classification for high-resolution remote sensing images,
IET-CV(13), No. 4, June 2019, pp. 395-403.
DOI Link 1906

See also KAZE Features. BibRef

Ratajczak, R., Crispim-Junior, C.F., Faure, E., Fervers, B., Tougne, L.,
Automatic Land Cover Reconstruction From Historical Aerial Images: An Evaluation of Features Extraction and Classification Algorithms,
IP(28), No. 7, July 2019, pp. 3357-3371.
computer vision, convolutional neural nets, feature extraction, filtering theory, geophysical image processing, historical aerial images BibRef

Hu, P.C.[Peng-Cheng], Guo, W.[Wei], Chapman, S.C.[Scott C.], Guo, Y.[Yan], Zheng, B.Y.[Bang-You],
Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breeding,
PandRS(154), 2019, pp. 1-9.
Elsevier DOI 1907
Plant phenotyping, Ground coverage, Remote sensing, Pixel size, UAV BibRef

Yuan, Q.Q.[Qiang-Qiang], Li, S.[Shuwen], Yue, L.W.[Lin-Wei], Li, T.W.[Tong-Wen], Shen, H.F.[Huan-Feng], Zhang, L.P.[Liang-Pei],
Monitoring the Variation of Vegetation Water Content with Machine Learning Methods: Point-Surface Fusion of MODIS Products and GNSS-IR Observations,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907

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Where's the Rock: Using Convolutional Neural Networks to Improve Land Cover Classification,
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Fang, J.[Jie], Yuan, Y.[Yuan], Lu, X.Q.[Xiao-Qiang], Feng, Y.C.[Ya-Chuang],
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Yoo, C.[Cheolhee], Han, D.[Daehyeon], Im, J.[Jungho], Bechtel, B.[Benjamin],
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Elsevier DOI 1911
Local climate zone, Convolutional neural networks, Random forest, Urban climate, Landsat BibRef

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DOI Link 1911

Chen, Y.[Yushi], Huang, L.[Lingbo], Zhu, L.[Lin], Yokoya, N.[Naoto], Jia, X.P.[Xiu-Ping],
Fine-Grained Classification of Hyperspectral Imagery Based on Deep Learning,
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Zhao, N.[Nan], Ma, A.[Ailong], Zhong, Y.F.[Yan-Fei], Zhao, J.[Ji], Cao, L.Q.[Li-Qin],
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Ma, A.[Ailong], Wan, Y.T.[Yu-Ting], Zhong, Y.F.[Yan-Fei], Wang, J.J.[Jun-Jue], Zhang, L.P.[Liang-Pei],
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Spectral Diversity Successfully Estimates the a-Diversity of Biocrust-Forming Lichens,
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DOI Link 1912

Alonso-Sarria, F.[Francisco], Valdivieso-Ros, C.[Carmen], Gomariz-Castillo, F.[Francisco],
Isolation Forests to Evaluate Class Separability and the Representativeness of Training and Validation Areas in Land Cover Classification,
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Li, X.D.[Xiao-Dong], Chen, R.[Rui], Foody, G.M.[Giles M.], Wang, L.H.[Li-Hui], Yang, X.H.[Xiao-Hong], Du, Y.[Yun], Ling, F.[Feng],
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Lei, G.B.[Guang-Bin], Li, A.N.[Ai-Nong], Bian, J.H.[Jin-Hu], Yan, H.[He], Zhang, L.[Lulu], Zhang, Z.J.[Zheng-Jian], Nan, X.[Xi],
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Wang, M.J.[Meng-Jia], Sun, R.[Rui], Zhu, A.[Anran], Xiao, Z.Q.[Zhi-Qiang],
Evaluation and Comparison of Light Use Efficiency and Gross Primary Productivity Using Three Different Approaches,
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Hou, W.J.[Wen-Juan], Gao, J.B.[Jiang-Bo],
Spatially Variable Relationships between Karst Landscape Pattern and Vegetation Activities,
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Laamrani, A.[Ahmed], Joosse, P.[Pamela], McNairn, H.[Heather], Berg, A.A.[Aaron A.], Hagerman, J.[Jennifer], Powell, K.[Kathryn], Berry, M.[Mark],
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Chen, C.P.J.[Chun-Peng James], Zhang, Z.W.[Zhi-Wu],
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Sakuma, A.[Asahi], Yamano, H.[Hiroya],
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Blanco, S.R.[Sergio R.], Heras, D.B.[Dora B.], Argüello, F.[Francisco],
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Samarinas, N.[Nikiforos], Tziolas, N.[Nikolaos], Zalidis, G.[George],
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DOI Link 2010

Thomas, N.[Nathan], Neigh, C.S.R.[Christopher S. R.], Carroll, M.L.[Mark L.], McCarty, J.L.[Jessica L.], Bunting, P.[Pete],
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DOI Link 2010

Gudmann, A.[András], Csikós, N.[Nándor], Szilassi, P.[Péter], Mucsi, L.[László],
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Radke, D.[David], Radke, D.[Daniel], Radke, J.[John],
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Yin, G., Ma, L., Zhao, W., Zeng, Y., Xu, B., Wu, S.,
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Earth, Remote sensing, Artificial satellites, Vegetation mapping, Surface topography, Scattering, Soil, Explicit method (EM), topographic correction BibRef

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DOI Link 2104

Minghelli, A.[Audrey], Chevalier, C.[Cristele], Descloitres, J.[Jacques], Berline, L.[Léo], Blanc, P.[Philippe], Chami, M.[Malik],
Synergy between Low Earth Orbit (LEO): MODIS and Geostationary Earth Orbit (GEO): GOES Sensors for Sargassum Monitoring in the Atlantic Ocean,
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Ji, S.P.[Shun-Ping], Wang, D.P.[Ding-Pan], Luo, M.Y.[Mu-Ying],
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Image segmentation, Remote sensing, Training, Decoding, Generative adversarial networks, Feature extraction, remote sensing BibRef

Li, X.[Xiao], Lei, L.[Lin], Sun, Y.[Yuli], Li, M.[Ming], Kuang, G.Y.[Guang-Yao],
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Optical imaging, Feature extraction, Logic gates, Nonlinear optics, Synthetic aperture radar, Collaboration, Optical sensors, land cover classification BibRef

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How Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology?,
Springer DOI 2103

Zhang, Q., Zhang, Y., Yang, P., Meng, Y., Zhuo, S., Yang, Z.,
The Land Cover Classification Using A Feature Pyramid Networks Architecture From Satellite Imagery,
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Zhang, K., Yang, H.,
Semi-Supervised Multi-Spectral Land Cover Classification With Multi-Attention and Adaptive Kernel,
Feature extraction, Kernel, Remote sensing, Training, Generators, Convolution, Agriculture, Multi-Spectral, Multi-Attention BibRef

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Springer DOI 2010

Rußwurm, M., Wang, S., Körner, M., Lobell, D.,
Meta-Learning for Few-Shot Land Cover Classification,
Task analysis, Adaptation models, Remote sensing, Data models, Image segmentation, Laser radar, Satellites BibRef

Artemeva, O.V., Zareie, S., Elhaei, Y., Pozdnyakova, N.A., Vasilev, N.D.,
Using Remote Sensing Data to Create Maps of Vegetation and Relief For Natural Resource Management of a Large Administrative Region,
DOI Link 1912

Abujayyab, S.K.M., Karas, I.R.,
Geospatial Machine Learning Datasets Structuring and Classification Tool: Case Study for Mapping LULC From Rasat Satellite Images,
DOI Link 1912

Yao, Y., Zhao, H., Huang, D., Tan, Q.,
Remote Sensing Scene Classification Using Multiple Pyramid Pooling,
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Rakhlin, A., Davydow, A., Nikolenko, S.,
Land Cover Classification from Satellite Imagery with U-Net and Lovász-Softmax Loss,
Image segmentation, Satellites, Computer architecture, Training, Task analysis, Computer vision, Stochastic processes BibRef

Li, T., Comer, M., Zerubia, J.,
A Connected-Tube MPP Model for Object Detection with Application to Materials and Remotely-Sensed Images,
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Wolfe, J., Jin, X., Bahr, T., Holzer, N.,
Application of Softmax Regression And Its Validation for Spectral-based Land Cover Mapping,
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Workman, S., Zhai, M., Crandall, D.J.[David J.], Jacobs, N.,
A Unified Model for Near and Remote Sensing,
feature extraction, feedforward neural nets, geophysical image processing, image resolution, land cover, Remote sensing BibRef

Khawaja, H.A.[Hassan A.],
Solution of Pure Scattering Radiation Transport Equation (RTE) Using Finite Difference Method (FDM),
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Wirth, E., Szabó, G., Czinkóczky, A.,
Measure Landscape Diversity With Logical Scout Agents,
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Hosni, I., Bennaceur Farah, L., Naceur, M.S., Farah, I.R.,
Estimation Of Physical Parameters Of A Multilayered Multi-scale Vegetated Surface,
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Niederheiser, R.[Robert], Rutzinger, M.[Martin], Lamprecht, A.[Andrea], Steinbauer, K.[Klaus], Winkler, M.[Manuela], Pauli, H.[Harald],
Mapping Alpine Vegetation Location Properties By Dense Matching,
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Müllerová, J.[Jana], Bruna, J.[Josef], Dvorák, P.[Petr], Bartaloš, T.[Tomáš], Vítková, M.[Michaela],
Does The Data Resolution/origin Matter? Satellite, Airborne And UAV Imagery To Tackle Plant Invasions,
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Wu, H.[Hao], Chen, J.[Jun], Xing, H.[Huaqiao], Li, S.[Songnian], Hu, J.[Juju],
Pragmatics Driven Land Cover Service Composition Utilizing Behavior-intention Model,
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Aswatha, S.M., Mukhopadhyay, J., Biswas, P.K.,
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Jay, S., Bendoula, R., Hadoux, X., Gorretta, N.,
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Star: A Contextual Description of Superpixels for Remote Sensing Image Classification,
Springer DOI 1703

de Andrade, Jr., E.F.[Edemir Ferreira], de Albuquerque Araújo, A.[Arnaldo], dos Santos, J.A.[Jefersson A.],
A Multiclass Approach for Land-Cover Mapping by Using Multiple Data Sensors,
Springer DOI 1511

Dhawale, N.M., Adamchuk, V.I., Prasher, S.O., Dutilleul, P.R.L., Ferguson, R.B.,
Spatially Constrained Geospatial Data Clustering for Multilayer Sensor-Based Measurements,
DOI Link 1411

Ustuner, M., Sanli, F.B., Abdikan, S., Esetlili, M.T., Kurucu, Y.,
Crop Type Classification Using Vegetation Indices of RapidEye Imagery,
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Brocks, S., Bareth, G.,
Evaluating the potential of consumer-grade smart cameras for low-cost stereo-photogrammetric Crop-Surface Monitoring,
DOI Link 1404

Jia, Y., Li, H.T., Gu, H.Y., Han, Y.S.,
Study on the Technology and Method of Land Cover Classification for Geographic National Conditions Surveying,
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Hu, B., Li, P.,
A Comparative Study Between Pair-Point Clique and Multi-Point Clique Markov Random Field Models for Land Cover Classification,
HTML Version. 1311

Bradbury, G.[Gwyneth], Mitchell, K.[Kenny], Weyrich, T.[Tim],
Multi-spectral Material Classification in Landscape Scenes Using Commodity Hardware,
Springer DOI 1311

Moody, D.I., Bauer, D.E., Brumby, S.P., Chisolm, E.D., Warren, M.S., Skillman, S.W., Keisler, R.,
Land cover classification in fused multisensor multispectral satellite imagery,
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Moody, D.I., Brumby, S.P., Rowland, J.C., Altmann, G.L., Larson, A.E.,
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Warren, M.S., Brumby, S.P., Skillman, S.W., Kelton, T., Wohlberg, B., Mathis, M., Chartrand, R., Keisler, R., Johnson, M.,
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Moody, D.I., Wozniak, P.R., Brumby, S.P.,
Automated variability selection in time-domain imaging surveys using sparse representations with learned dictionaries,
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Moody, D.I., Brumby, S.P., Rowland, J.C., Gangodagamage, C.,
Unsupervised land cover classification in multispectral imagery with sparse representations on learned dictionaries,
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Region-Based Classification of PolSAR Data Through Kernel Methods and Stochastic Distances,
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Negri, R.G.[Rogério G.], Dutra, L.V.[Luciano V.], Sant'Anna, S.J.S.[Sidnei J.S.],
Stochastic Approaches of Minimum Distance Method for Region Based Classification,
Springer DOI 1209

Niroumand Jadidi, M., Safdarinezhad, A.R., Sahebi, M.R., Mokhtarzade, M.,
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Mccamley, G., Grant, I., Jones, S., Bellman, C.,
Characterising Vegetated Surfaces Using Modis Multiangular Satellite Data,
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Handique, B.K.,
A Class of Regression-cum-ratio Estimators In Two-phase Sampling For Utilizing Information From High Resolution Satellite Data,
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Büschenfeld, T., Ostermann, J.,
Automatic Refinement of Training Data for Classification of Satellite Imagery,
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Improvement Of Thermal Estimation At Land Cover Boundary By Using Quantile,
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Zhai, L., Sun, J., Sang, H., Yang, G., Jia, Y.,
Large Area Land Cover Classification With Landsat Etm+ Images Based On Decision Tree,
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Nilsen, A.B., Bjřrkelo, K.,
National Land Cover And Resource Statistics,
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Fadaei, H., Suzuki, R., Sakai, T., Torii, K.,
A Proposed New Vegetation Index, The Total Ratio Vegetation Index (trvi), For Arid And Semi-arid Regions,
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Bareth, G., Waldhoff, G.,
Regionalization of Agricultural Management by Using the Multi-Data Approach (MDA),
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Springer DOI 0812

Alonso, M.C.[María C.], Sanz, M.A.[María A.], Malpica, J.A.[José A.],
Classification of High Resolution Satellite Images Using Texture from the Panchromatic Band,
ISVC07(II: 499-508).
Springer DOI 0711

Jones, S.D., Ferwerda, J.G., Reinke, K.J.,
Scaling the Walls of History: The Perils and Pitfalls of Multi-Scale Land Cover Comparison,
PDF File. 0607

Shkvarko, Y.V.[Yuriy V.], Villalon-Turrubiates, I.E.[Ivan E.],
Remote Sensing Imagery and Signature Fields Reconstruction Via Aggregation of Robust Regularization with Neural Computing,
Springer DOI 0708

Ferreiro-Armán, M.[Marcos], Bandeira, L.P.C.[Lourenço P. C.], Martín-Herrero, J.[Julio], Pina, P.[Pedro],
Classifiers for Vegetation and Forest Mapping with Low Resolution Multiespectral Imagery,
IbPRIA07(I: 177-184).
Springer DOI 0706

Yang, Y.F.[Yeh Fen], Lohmann, P.[Peter], Heipke, C.[Christian],
Genetic Algorithms for the Unsupervised Classification of Satellite Images,
PDF File. 0609

Ohkubo, A.[Akito], Niijima, K.[Koichi],
New Supervised Learning of Neural Networks for satellite image classification,
IEEE DOI Land Cover Classification BibRef 9900

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Land Use, General Problems .

Last update:May 2, 2021 at 12:04:43