22.1.4.1 Land Cover, Land Use, General Problems, Remote Sensing

Chapter Contents (Back)
Classification. Remote Sensing. Land Cover. Ground Cover. See also Object Based Land Cover, Region Based Land Cover, Land Use Analysis. See also LAI, Leaf Area Index, Land Cover Analysis. 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 Rice Crop Analysis, Production, Detection, Health, Change. For global scale analysis: See also Global-Scale Analysis, Global Land Cover Analysis.

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Integration of classification methods for improvement of land-cover map accuracy,
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Debeir, O.[Olivier], van den Steen, I.[Isabelle], Latinne, P.[Patrice], van Ham, P.[Philippe], Wolff, E.[Eléonore],
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PhEngRS(68), No. 6, June 2002, pp. 597.
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Improve the accuracy of land-cover clasification with textural, contextual, and multiple classifier system. BibRef

Hlavka, C.A., Dungan, J.L.,
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Huang, C., Davis, L.S., Townshend, J.R.G.,
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Shao, G.[Guofan], We, W.[Wenchun], Wu, G.[Gang], Zhou, X.H.[Xin-Hua], Wu, J.G.[Jian-Guo],
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PhEngRS(69), No. 8, August 2003, pp. 907-914.
WWW Link. 0401
The accuracy of cover class areas is not strongly related to conventional classification accuracy assessment indices, but can be assessed with a new index called Relative Errors of Area (REA). BibRef

Kempeneers, P., de Backer, S., Debruyn, W., Coppin, P., Scheunders, P.,
Generic Wavelet-Based Hyperspectral Classification Applied to Vegetation Stress Detection,
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de Backer, S.[Steve], Kempeneers, P.[Pieter], Debruyn, W.[Walter], Scheunders, P.[Paul],
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Tran, L.T.[Liem T.], Wickham, J.D.[James D.], Jarnagin, S.T.[S. Taylor], Knight, C.G.[C. Gregory],
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Li, X.Z.[Xiu-Zhen], He, H.S.[Hong S.], Bu, R.[Rencang], Wen, Q.C.[Qing-Chun], Chang, Y.[Yu], Hu, Y.M.[Yuan-Man], Li, Y.H.[Yue-Hui],
The adequacy of different landscape metrics for various landscape patterns,
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Elsevier DOI 0510
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Chen, L.[Li],
Nested Hyper-Rectangle Learning Model for Remote Sensing: Land Cover Classification,
PhEngRS(71), No. 3, March 2005, pp. 333. The NHLM learning model is presented and tested with SPOT data to illustrate an efficient and accurate supervised classification method.
WWW Link. 0509
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Herold, M., Woodcock, C., di Gregorio, A., Mayaux, P., Belward, A.S., Latham, J., Schmullius, C.C.,
A Joint Initiative for Harmonization and Validation of Land Cover Datasets,
GeoRS(44), No. 7, Part 1, July 2006, pp. 1719-1727.
IEEE DOI 0606
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Keramitsoglou, I.[Iphigenia], Sarimveis, H.[Haralambos], Kiranoudis, C.T.[Chris T.], Kontoes, C.C.[Charalambos C.], Sifakis, N.[Nicolaos], Fitoka, E.[Eleni],
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PandRS(60), No. 4, June 2006, pp. 225-238.
Elsevier DOI 0610
habitat classification; RBF neural networks; kernel based re-classification; support vector machines; EUNIS BibRef

Aitkenhead, M.J., Dyer, R.,
Improving Land-cover Classification Using Recognition Threshold Neural Networks,
PhEngRS(73), No. 4, April 2007, pp. 413-421.
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Saura, S.[Santiago], Castro, S.[Sandra],
Scaling functions for landscape pattern metrics derived from remotely sensed data: Are their subpixel estimates really accurate?,
PandRS(62), No. 3, August 2007, pp. 201-216.
Elsevier DOI 0709
Scale; Landscape pattern; Sensor spatial resolution; Spatial metrics; Landscape ecology; Land cover analysis BibRef

Makido, Y.[Yasuyo], Shortridge, A.[Ashton],
Weighting Function Alternatives for a Subpixel Allocation Model,
PhEngRS(73), No. 11, November 2007, pp. 1233-1240.
WWW Link. 0709
Properties of a pixel-swapping optimization algorithm for predicting subpixel land-cover distribution are investigated, and improvements to it are evaluated. BibRef

Bagan, H.[Hasi], Wang, Q.X.[Qin-Xue], Watanabe, M.[Masataka], Kameyama, S.[Satoshi], Bao, Y.H.[Yu-Hai],
Land-cover Classification Using ASTER Multi-band Combinations Based on Wavelet Fusion and SOM Neural Network,
PhEngRS(74), No. 3, March 2008, pp. 333-342.
WWW Link. 0803
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],
Using colour, texture, and hierarchial segmentation for high-resolution remote sensing,
PandRS(63), No. 2, March 2008, pp. 156-168.
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],
A genetic algorithm rule-based approach for land-cover classification,
PandRS(63), No. 2, March 2008, pp. 202-212.
Elsevier DOI 0803
Classification; Land-cover; Rule-based; Genetic algorithm; Knowledge rules BibRef

Mitrakis, N.E., Topaloglou, C.A., Alexandridis, T.K., Theocharis, J.B., Zalidis, G.C.,
Decision Fusion of GA Self-Organizing Neuro-Fuzzy Multilayered Classifiers for Land Cover Classification Using Textural and Spectral Features,
GeoRS(46), No. 7, July 2008, pp. 2137-2152.
IEEE DOI 0806
BibRef

Stavrakoudis, D.G., Theocharis, J.B., Zalidis, G.C.,
A Boosted Genetic Fuzzy Classifier for land cover classification of remote sensing imagery,
PandRS(66), No. 4, July 2011, pp. 529-544.
Elsevier DOI 1107
AdaBoost; Genetic fuzzy rule-based classification systems (GFRBCS); Local feature selection; Textural and spatial features; Multispectral image classification BibRef

Stavrakoudis, D.G., Galidaki, G.N., Gitas, I.Z., Theocharis, J.B.,
A Genetic Fuzzy-Rule-Based Classifier for Land Cover Classification From Hyperspectral Imagery,
GeoRS(50), No. 1, January 2012, pp. 130-148.
IEEE DOI 1201
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Mylonas, S.K.[Stelios K.], Stavrakoudis, D.G.[Dimitris G.], Theocharis, J.B.[John B.], Mastorocostas, P.A.[Paris A.],
A Region-Based GeneSIS Segmentation Algorithm for the Classification of Remotely Sensed Images,
RS(7), No. 3, 2015, pp. 2474-2508.
DOI Link 1504
BibRef

Mylonas, S.K.[Stelios K.], Stavrakoudis, D.G.[Dimitris G.], Theocharis, J.B.[John B.], Mastorocostas, P.A.[Paris A.],
Classification of Remotely Sensed Images Using the GeneSIS Fuzzy Segmentation Algorithm,
GeoRS(53), No. 10, October 2015, pp. 5352-5376.
IEEE DOI 1509
feature extraction BibRef

Smikrud, K.M.[Kathy M.], Prakash, A.[Anupma], Nichols, J.V.[Jeff V.],
Decision-based Fusion for Improved Fluvial Landscape Classification Using Digital Aerial Photographs and Forward Looking Infrared Images,
PhEngRS(74), No. 7, July 2008, pp. 903-912.
WWW Link. 0804
Comparing different image processing routines to classify macro fish habitat indicators in a large river floodplain using digital aerial photographs and forward looking infrared images leading to a decision-based fusion strategy to provide the best results. BibRef

Duca, R., Del Frate, F.,
Hyperspectral and Multiangle CHRIS-PROBA Images for the Generation of Land Cover Maps,
GeoRS(46), No. 10, October 2008, pp. 2857-2866.
IEEE DOI 0810
BibRef

Li, Z.[Zhe],
Fuzzy ARTMAP-based Neurocomputational Spatial Uncertainty Measures,
PhEngRS(74), No. 12, December 2008, pp. 1573-1584.
WWW Link. 0804
Non-parametric Commitment and Typicality measures for the fuzzy ARTMAP computational neural network to handle spatial uncertainty in remotely sensed imagery classification. BibRef

Carrer, D., Roujean, J.L., Meurey, C.,
Comparing Operational MSG/SEVIRI Land Surface Albedo Products From Land SAF With Ground Measurements and MODIS,
GeoRS(48), No. 4, April 2010, pp. 1714-1728.
IEEE DOI 1003
BibRef

Liu, X., Li, X., Liu, L., He, J., Ai, B.,
An Innovative Method to Classify Remote-Sensing Images Using Ant Colony Optimization,
GeoRS(46), No. 12, December 2008, pp. 4198-4208.
IEEE DOI 0812
BibRef

Lehner, P.E., Adelman, L., DiStasio, R.J., Erie, M.C., Mittel, J.S., Olson, S.L.,
Confirmation Bias in the Analysis of Remote Sensing Data,
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IEEE DOI 0901
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Wuest, B.[Ben], Zhang, Y.[Yun],
Region based segmentation of QuickBird multispectral imagery through band ratios and fuzzy comparison,
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Elsevier DOI 0804
Remote sensing; Segmentation; QuickBird; Algorithms; Land cover BibRef

Shen, Z.Q.[Zhang-Quan], Qi, J.G.[Jia-Guo], Wang, K.[Ke],
Modification of Pixel-swapping Algorithm with Initialization from a Sub-pixel/pixel Spatial Attraction Model,
PhEngRS(75), No. 5, May 2009, pp. 557-568.
WWW Link. 0904
Based on the pixel-swapping algorithm, its initialization process is replaced by a sub-pixel mapping approach with a subpixel/ pixel spatial attraction model; the modified algorithm can improve sub-pixel mapping accuracy and computation efficiency. BibRef

Ge, Y., Li, S., Lakhan, V.C.,
Development and Testing of a Subpixel Mapping Algorithm,
GeoRS(47), No. 7, July 2009, pp. 2155-2164.
IEEE DOI 0906
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Tolpekin, V.A., Stein, A.,
Quantification of the Effects of Land-Cover-Class Spectral Separability on the Accuracy of Markov-Random-Field-Based Superresolution Mapping,
GeoRS(47), No. 9, September 2009, pp. 3283-3297.
IEEE DOI 0909
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Borengasser, M.[Marcus], Hungate, W.S.[William S.], Watkins, R.[Russell],
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CRC PressDecember, 2007, ISBN: 9781566706544
WWW Link. Buy this book: Hyperspectral Remote Sensing 0910
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Mather, P.[Paul], Tso, B.[Brandt], Bie-Tou,
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CRC PressMay 2009, ISBN: 9781420090727. Second Edition.
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CRC PressDecember, 2008, ISBN: 9781420055122
WWW Link. Buy this book: Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition (Mapping Science) 0910
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Serra, P., Moré, G., Pons, X.,
Thematic Accuracy Consequences in Cadastre Landcover Enrichment from a Pixel and from a Polygon Perspective,
PhEngRS(75), No. 12, December 2009, pp. 1441-1450.
WWW Link. 1001
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Baraldi, A., Gironda, M., Simonetti, D.,
Operational Two-Stage Stratified Topographic Correction of Spaceborne Multispectral Imagery Employing an Automatic Spectral-Rule-Based Decision-Tree Preliminary Classifier,
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IEEE DOI 1001
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Forzieri, G., Castelli, F., Vivoni, E.R.,
A Predictive Multidimensional Model for Vegetation Anomalies Derived From Remote-Sensing Observations,
GeoRS(48), No. 4, April 2010, pp. 1729-1741.
IEEE DOI 1003
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Xie, Y.C.[Yi-Chun], Sha, Z.Y.[Zong-Yao], Bai, Y.F.[Yong-Fei],
Classifying historical remotely sensed imagery using a tempo-spatial feature evolution (T-SFE) model,
PandRS(65), No. 2, March 2010, pp. 182-190.
Elsevier DOI 1003
Classification; GIS; History; Landsat; Vegetation BibRef

Salberg, A.B.[Arnt-Břrre],
Land Cover Classification of Cloud-Contaminated Multitemporal High-Resolution Images,
GeoRS(49), No. 1, January 2011, pp. 377-387.
IEEE DOI 1101
BibRef

Liu, K.[Kimfung], Shi, W.Z.[Wen-Zhong], Zhang, H.[Hua],
A fuzzy topology-based maximum likelihood classification,
PandRS(66), No. 1, January 2011, pp. 103-114.
Elsevier DOI 1101
Fuzzy topology; Maximum likelihood classification (MLC); Thresholding; Remote sensing; Land cover mapping BibRef

Li, W., Guo, Q., Elkan, C.,
A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote-Sensing Data,
GeoRS(49), No. 2, February 2011, pp. 717-725.
IEEE DOI 1102
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Li, W., Guo, Q.,
A New Accuracy Assessment Method for One-Class Remote Sensing Classification,
GeoRS(52), No. 8, August 2014, pp. 4621-4632.
IEEE DOI 1403
Accuracy BibRef

Baek, J., Kim, J.W., Lim, G.J., Lee, D.C.,
Electromagnetic Land Surface Classification Through Integration of Optical and Radar Remote Sensing Data,
GeoRS(49), No. 4, April 2011, pp. 1214-1222.
IEEE DOI 1104
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Jun, G., Ghosh, J.,
Spatially Adaptive Classification of Land Cover With Remote Sensing Data,
GeoRS(49), No. 7, July 2011, pp. 2662-2673.
IEEE DOI 1107
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Jun, G., Ghosh, J.,
Semisupervised Learning of Hyperspectral Data With Unknown Land-Cover Classes,
GeoRS(51), No. 1, January 2013, pp. 273-282.
IEEE DOI 1301
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Li, W.D.[Wei-Dong], Zhang, C.R.[Chuan-Rong],
A Markov Chain Geostatistical Framework for Land-Cover Classification With Uncertainty Assessment Based on Expert-Interpreted Pixels From Remotely Sensed Imagery,
GeoRS(49), No. 8, August 2011, pp. 2983-2992.
IEEE DOI 1108
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Nidamanuri, R.R.[Rama Rao], Zbell, B.[Bernd],
Use of field reflectance data for crop mapping using airborne hyperspectral image,
PandRS(66), No. 5, September 2011, pp. 683-691.
Elsevier DOI 1110
Field spectrometry; HyMAP; Hyperspectral remote sensing; Crop classification; Spectral library BibRef

Rodriguez-Galiano, V.F., Ghimire, B., Rogan, J., Chica-Olmo, M., Rigol-Sanchez, J.P.,
An assessment of the effectiveness of a random forest classifier for land-cover classification,
PandRS(67), No. 1, January 2012, pp. 93-104.
Elsevier DOI 1202
Remote sensing; Machine learning; Classification; Random forest; Land-cover; Landsat Thematic Mapper BibRef

Li, A.[Ainong], Jiang, J.G.[Jin-Gang], Bian, J.[Jinhu], Deng, W.[Wei],
Combining the matter element model with the associated function of probability transformation for multi-source remote sensing data classification in mountainous regions,
PandRS(67), No. 1, January 2012, pp. 80-92.
Elsevier DOI 1202
Remote sensing; Classification; Matter element model; Associated function; Mountainous region. Land cover integrating constraints and remote sensing information. BibRef

Yuan, H., van der Wiele, C., Khorram, S.,
An Automated Artificial Neural Network System for Land Use/Land Cover Classification from Landsat TM Imagery,
RS(1), No. 3, September 2009, pp. 243-265.
DOI Link 1203
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Manandhar, R., Odeh, I., Ancev, T.,
Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data Using Post-Classification Enhancement,
RS(1), No. 3, September 2009, pp. 330-344.
DOI Link 1203
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Yoshioka, H., Miura, T., Obata, K.,
Derivation of Relationships between Spectral Vegetation Indices from Multiple Sensors Based on Vegetation Isolines,
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Clark, M., Aide, T.,
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Pervez, M., Brown, J.,
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Dandois, J., Ellis, E.,
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Motohka, T., Nasahara, K., Oguma, H., Tsuchida, S.,
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Neugebauer, N.[Nikolaus], Vuolo, F.[Francesco],
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PFG(2014), No. 5, 2014, pp. 369-381.
DOI Link 1411
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Martínez, S., Mollicone, D.,
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RS(4), No. 4, April 2012, pp. 1024-1045.
DOI Link 1202
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Roscher, R.[Ribana], Förstner, W.[Wolfgang], Waske, B.[Björn],
I2VM: Incremental import vector machines,
IVC(30), No. 4-5, May 2012, pp. 263-278.
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Incremental import vector machines for large area land cover classification,
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Import vector machines; Incremental learning; Concept-drifts BibRef

Roscher, R.[Ribana], Wenzel, S., Waske, B.[Björn],
Discriminative archetypal self-taught learning for multispectral landcover classification,
PRRS16(1-5)
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Roscher, R.[Ribana], Waske, B.[Björn],
Shapelet-Based Sparse Representation for Landcover Classification of Hyperspectral Images,
GeoRS(54), No. 3, March 2016, pp. 1623-1634.
IEEE DOI 1603
Dictionaries BibRef

Shao, Y.[Yang], Lunetta, R.S.[Ross S.],
Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points,
PandRS(70), No. 1, June 2012, pp. 78-87.
Elsevier DOI 1206
Land-cover mapping; Support vector machine; Accuracy assessment BibRef

Kitada, K., Fukuyama, K.,
Land-Use and Land-Cover Mapping Using a Gradable Classification Method,
RS(4), No. 6, June 2012, pp. 1544-1558.
DOI Link 1208
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Jiao, L.M.[Li-Min], Liu, Y.L.[Yao-Lin], Li, H.L.[Hong-Liang],
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PandRS(72), No. 1, August 2012, pp. 46-55.
Elsevier DOI 1209
Land-use; Image segmentation; Landscape metrics; Shape metrics; Image classification BibRef

Jiao, L.M., Liu, Y.L.,
Analyzing the Shape Characteristics of Land Use Classes in Remote Sensing Imagery,
AnnalsPRS(I-7), No. 2012, pp. 135-140.
HTML Version. 1209
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Yang, J.X.[Jing-Xue], Wang, Y.P.[Yun-Peng],
Classification of 10m-resolution SPOT data using a combined Bayesian Network Classifier-shape adaptive neighborhood method,
PandRS(72), No. 1, August 2012, pp. 36-45.
Elsevier DOI 1209
Bayesian Network Classifier; Shape adaptive neighborhood; Fisher optimal division; Maximum Likelihood Classifier; Remote sensing; Classification BibRef

Huo, H., Qing, J., Fang, T., Li, N.,
Land Cover Classification Using Local Softened Affine Hull,
GeoRS(50), No. 11, November 2012, pp. 4369-4383.
IEEE DOI 1210
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Vuolo, F., Atzberger, C.,
Exploiting the Classification Performance of Support Vector Machines with Multi-Temporal Moderate-Resolution Imaging Spectroradiometer (MODIS) Data in Areas of Agreement and Disagreement of Existing Land Cover Products,
RS(4), No. 10, October 2012, pp. 3143-3167.
DOI Link 1210
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Verrelst, J., Romijn, E., Kooistra, L.,
Mapping Vegetation Density in a Heterogeneous River Floodplain Ecosystem Using Pointable CHRIS/PROBA Data,
RS(4), No. 9, September 2012, pp. 2866-2889.
DOI Link 1210
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Pan, Y., Hu, T., Zhu, X., Zhang, J., Wang, X.,
Mapping Cropland Distributions Using a Hard and Soft Classification Model,
GeoRS(50), No. 11, November 2012, pp. 4301-4312.
IEEE DOI 1210
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Arnold, S.[Stephan],
Integration of remote sensing data in national and European spatial data infrastructures derivation of CORINE Land Cover data from the DLM-DE,
PFG(2009), No. 2, 2009, pp. 129-141.
WWW Link. 1211
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Arnold, S.,
Digital Landscape Model DLM-DE: Deriving land cover information by integration of topographic reference data with remote sensing data,
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PDF File. 0906
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Waser, L.T.[Lars T.], Klonus, S.[Sascha], Ehlers, M.[Manfred], Küchler, M.[Meinrad], Jung, A.[András],
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PFG(2010), No. 2, 2010, pp. 141-156.
WWW Link. 1211
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Jung, A.[András], Götze, C.[Christian], Glässer, C.[Cornelia],
Overview of Experimental Setups in Spectroscopic Laboratory Measurements: The SpecTour Project,
PFG(2012), No. 4, 2012, pp. 433-442.
WWW Link. 1211
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Buck, O.[Oliver], Peter, B.[Benedikt], Büker, C.[Cordt],
Zwei-skaliger Ansatz zur Aktualisierung landwirtschaftlicher Referenzkulissen (LPIS),
PFG(2011), No. 5, 2011, pp. 339-348.
WWW Link. 1211
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Kersten, J.[Jens], Gähler, M.[Monika], Voigt, S.[Stefan],
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Xie, H.[Huan], Heipke, C.[Christian], Lohmann, P.[Peter], Soergel, U.[Uwe], Tong, X.H.[Xiao-Hua], Shi, W.Z.[Wen-Zhong],
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WWW Link. 1211
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Pérez-Hoyos, A., García-Haro, F.J., San-Miguel-Ayanz, J.,
Conventional and fuzzy comparisons of large scale land cover products: Application to CORINE, GLC2000, MODIS and GlobCover in Europe,
PandRS(74), No. 1, November 2012, pp. 185-201.
Elsevier DOI 1212
GlobCover; Fuzzy comparison; LCCS; CORINE; GLC2000; MODISLC BibRef

Moser, G., Serpico, S.B., Benediktsson, J.A.,
Land-Cover Mapping by Markov Modeling of Spatial-Contextual Information in Very-High-Resolution Remote Sensing Images,
PIEEE(100), No. 3, March 2013, pp. 631-651.
IEEE DOI 1303
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Moser, G., De Giorgi, A., Serpico, S.B.,
Multiresolution Supervised Classification of Panchromatic and Multispectral Images by Markov Random Fields and Graph Cuts,
GeoRS(54), No. 9, September 2016, pp. 5054-5070.
IEEE DOI 1609
Markov processes BibRef

Barb, A.[Adrian], Kilicay-Ergin, N.[Nil],
Genetic Optimization for Associative Semantic Ranking Models of Satellite Images by Land Cover,
IJGI(2), No. 2, 2013, pp. 531-552.
DOI Link 1307
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Erasmi, S.[Stefan],
Habitat Mapping from Optical and SAR Satellite Data: Implications of Synergy and Uncertainty for Landscape Analysis,
PFG(2013), No. 3, 2013, pp. 139-148.
DOI Link 1306
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Hu, F.[Fan], Yang, W.[Wen], Chen, J.[Jiayu], Sun, H.[Hong],
Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field,
RS(5), No. 5, 2013, pp. 2275-2291.
DOI Link 1307
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Xu, J.B.[Jian Bo], Song, L.S.[Li Sheng], Zhong, D.F.[De Fu], Zhao, Z.Z.[Zhi Zhong], Zhao, K.[Kai],
Remote Sensing Image Classification Based on a Modified Self-organizing Neural Network with a Priori Knowledge,
Sensors(153), No. 6, June 2013, pp. 29-36.
HTML Version. 1307
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Chen, Y.[Yanlei], Gong, P.[Peng],
Clustering based on eigenspace transformation: CBEST for efficient classification,
PandRS(83), No. 1, 2013, pp. 64-80.
Elsevier DOI 1308
Land cover/use mapping BibRef

Kasetkasem, T.[Teerasit], Rakwatin, P.[Preesan], Sirisommai, R.[Ratchawit], Eiumnoh, A.[Apisit],
A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model,
RS(5), No. 10, 2013, pp. 5089-5121.
DOI Link 1311
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Cernicharo, J.[Jesus], Verger, A.[Aleixandre], Camacho, F.[Fernando],
Empirical and Physical Estimation of Canopy Water Content from CHRIS/PROBA Data,
RS(5), No. 10, 2013, pp. 5265-5284.
DOI Link 1311
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Baraldi, A., Boschetti, L., Humber, M.L.,
Probability Sampling Protocol for Thematic and Spatial Quality Assessment of Classification Maps Generated From Spaceborne/Airborne Very High Resolution Images,
GeoRS(52), No. 1, January 2014, pp. 701-760.
IEEE DOI 1402
decision trees BibRef

Wang, D.D.[Dong-Dong], Liang, S.L.[Shun-Lin], He, T.[Tao], Cao, Y.F.[Yun-Feng], Jiang, B.[Bo],
Surface Shortwave Net Radiation Estimation from FengYun-3 MERSI Data,
RS(7), No. 5, 2015, pp. 6224-6239.
DOI Link 1506
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Wang, D.D.[Dong-Dong], Liang, S.L.[Shun-Lin], He, T.[Tao], Shi, Q.Q.[Qin-Qing],
Estimation of Daily Surface Shortwave Net Radiation From the Combined MODIS Data,
GeoRS(53), No. 10, October 2015, pp. 5519-5529.
IEEE DOI 1509
atmospheric radiation BibRef

Wang, D.D.[Dong-Dong], Liang, S.L.[Shun-Lin],
Estimating Top-of-Atmosphere Daily Reflected Shortwave Radiation Flux Over Land From MODIS Data,
GeoRS(55), No. 7, July 2017, pp. 4022-4031.
IEEE DOI 1706
Atmospheric modeling, Clouds, Earth, MODIS, Satellites, Sensors, Clouds and the Earth's Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), radiation budget, shortwave radiation, top-of-atmosphere, (TOA), flux See also Direct Estimation of Land Surface Albedo From Simultaneous MISR Data. BibRef

Li, P.[Peng], Jiang, L.G.[Lu-Guang], Feng, Z.M.[Zhi-Ming],
Cross-Comparison of Vegetation Indices Derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) Sensors,
RS(6), No. 1, 2013, pp. 310-329.
DOI Link 1402
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Cheng, J.[Jie], Liang, S.L.[Shun-Lin], Yao, Y.J.[Yun-Jun], Ren, B.Y.[Bai-Yang], Shi, L.P.[Lin-Peng], Liu, H.[Hao],
A Comparative Study of Three Land Surface Broadband Emissivity Datasets from Satellite Data,
RS(6), No. 1, 2013, pp. 111-134.
DOI Link 1402
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Zhu, X.L.[Xiao-Lin], Liu, D.[Desheng],
MAP-MRF Approach to Landsat ETM+ SLC-Off Image Classification,
GeoRS(52), No. 2, February 2014, pp. 1131-1141.
IEEE DOI 1402
geophysical image processing BibRef

Luo, W.[Wang], Li, H.L.[Hong-Liang], Liu, G.H.[Guang-Hui], Zeng, L.Y.[Liao-Yuan],
Semantic Annotation of Satellite Images Using Author-Genre-Topic Model,
GeoRS(52), No. 2, February 2014, pp. 1356-1368.
IEEE DOI 1402
feature extraction BibRef

Luo, B.[Bin], Zhang, L.P.[Liang-Pei],
Robust Autodual Morphological Profiles for the Classification of High-Resolution Satellite Images,
GeoRS(52), No. 2, February 2014, pp. 1451-1462.
IEEE DOI 1402
artificial satellites BibRef

Case, J.L., LaFontaine, F.J., Bell, J.R., Jedlovec, G.J., Kumar, S.V., Peters-Lidard, C.D.,
A Real-Time MODIS Vegetation Product for Land Surface and Numerical Weather Prediction Models,
GeoRS(52), No. 3, March 2014, pp. 1772-1786.
IEEE DOI 1403
atmospheric boundary layer BibRef

Wu, W.C.[Wei-Cheng],
The Generalized Difference Vegetation Index (GDVI) for Dryland Characterization,
RS(6), No. 2, 2014, pp. 1211-1233.
DOI Link 1403
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Marconcini, M., Fernandez-Prieto, D., Buchholz, T.,
Targeted Land-Cover Classification,
GeoRS(52), No. 7, July 2014, pp. 4173-4193.
IEEE DOI 1403
Accuracy BibRef

Chiang, J.L., Liou, J.J., Wei, C., Cheng, K.S.,
A Feature-Space Indicator Kriging Approach for Remote Sensing Image Classification,
GeoRS(52), No. 7, July 2014, pp. 4046-4055.
IEEE DOI 1403
Accuracy BibRef

Liu, M.W., Ozdogan, M., Zhu, X.,
Crop Type Classification by Simultaneous Use of Satellite Images of Different Resolutions,
GeoRS(52), No. 6, June 2014, pp. 3637-3649.
IEEE DOI 1403
Agriculture BibRef

Voisin, A., Krylov, V.A., Moser, G., Serpico, S.B., Zerubia, J.B.,
Supervised Classification of Multisensor and Multiresolution Remote Sensing Images With a Hierarchical Copula-Based Approach,
GeoRS(52), No. 6, June 2014, pp. 3346-3358.
IEEE DOI 1403
Data models BibRef

Wang, Q.M.[Qun-Ming], Shi, W.Z.[Wen-Zhong], Wang, L.,
Allocating Classes for Soft-Then-Hard Subpixel Mapping Algorithms in Units of Class,
GeoRS(52), No. 5, May 2014, pp. 2940-2959.
IEEE DOI 1403
Mathematical model. Subpixel mapping. See also Spatiotemporal Subpixel Mapping of Time-Series Images. BibRef

Wawrzaszek, A.[Anna], Aleksandrowicz, S.[Sebastian], Krupiski, M.[Michal], Drzewiecki, W.[Wojciech],
Influence of Image Filtering on Land Cover Classification when using Fractal and Multifractal Features,
PFG(2014), No. 2, April 2014, pp. 101-115.
DOI Link 1405
BibRef

Tran, T.V.[Trung V.], Julian, J.P.[Jason P.], de Beurs, K.M.[Kirsten M.],
Land Cover Heterogeneity Effects on Sub-Pixel and Per-Pixel Classifications,
IJGI(3), No. 2, 2014, pp. 540-553.
DOI Link 1405
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Ullah, S.[Saleem], Skidmore, A.K.[Andrew K.], Ramoelo, A.[Abel], Groen, T.A.[Thomas A.], Naeem, M.[Mohammad], Ali, A.[Asad],
Retrieval of leaf water content spanning the visible to thermal infrared spectra,
PandRS(93), No. 1, 2014, pp. 56-64.
Elsevier DOI 1407
Water stress BibRef

Jones, E.[Eriita], Caprarelli, G.[Graziella], Mills, F.P.[Franklin P.], Doran, B.[Bruce], Clarke, J.[Jonathan],
An Alternative Approach to Mapping Thermophysical Units from Martian Thermal Inertia and Albedo Data Using a Combination of Unsupervised Classification Techniques,
RS(6), No. 6, 2014, pp. 5184-5237.
DOI Link 1407
Surface material on Mars. BibRef

Li, Y.Z.[Yi-Zhan], Zhu, X.F.[Xiu-Fang], Pan, Y.Z.[Yao-Zhong], Gu, J.Y.[Jian-Yu], Zhao, A.Z.[An-Zhou], Liu, X.F.[Xian-Feng],
A Comparison of Model-Assisted Estimators to Infer Land Cover/Use Class Area Using Satellite Imagery,
RS(6), No. 9, 2014, pp. 8904-8922.
DOI Link 1410
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Ji, L.[Lei], Zhang, L.[Li], Rover, J.[Jennifer], Wylie, B.K.[Bruce K.], Chen, X.[Xuexia],
Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices,
PandRS(96), No. 1, 2014, pp. 20-27.
Elsevier DOI 1410
Geostatistics BibRef

Gao, B.[Bo], Jia, L.[Li], Wang, T.X.[Tian-Xing],
Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products,
RS(6), No. 9, 2014, pp. 8966-8985.
DOI Link 1410
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Gao, B.[Bo], Gong, H.[Huili], Wang, T.X.[Tian-Xing],
A Method for Retrieving Daily Land Surface Albedo from Space at 30-m Resolution,
RS(7), No. 8, 2015, pp. 10951.
DOI Link 1509
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Gao, B.[Bo], Gong, H.[Huili], Wang, T.X.[Tian-Xing], Jia, L.[Li],
Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition,
RS(8), No. 9, 2016, pp. 727.
DOI Link 1610
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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
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Chen, S.Z.[Shi-Zhi], Tian, Y.L.[Ying-Li],
Pyramid of Spatial Relatons for Scene-Level Land Use Classification,
GeoRS(53), No. 4, April 2015, pp. 1947-1957.
IEEE DOI 1502
data structures BibRef

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.
IEEE DOI 1502
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
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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
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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
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Phompila, C.[Chittana], Lewis, M.[Megan], Ostendorf, B.[Bertram], Clarke, K.[Kenneth],
MODIS EVI and LST Temporal Response for Discrimination of Tropical Land Covers,
RS(7), No. 5, 2015, pp. 6026-6040.
DOI Link 1506
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Rivera, J.P.[Juan Pablo], Verrelst, J.[Jochem], Gómez-Dans, J.[Jose], Muńoz-Marí, J.[Jordi], Moreno, J.[José], Camps-Valls, G.[Gustau],
An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning,
RS(7), No. 7, 2015, pp. 9347.
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Martino, L.[Luca], Vicent, J.[Jorge], Camps-Valls, G.[Gustau],
Automatic Emulation by Adaptive Relevance Vector Machines,
SCIA17(I: 443-454).
Springer DOI 1706
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Verrelst, J.[Jochem], Sabater, N.[Neus], Rivera, J.P.[Juan Pablo], Muńoz-Marí, J.[Jordi], Vicent, J.[Jorge], Camps-Valls, G.[Gustau], Moreno, J.[José],
Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis,
RS(8), No. 8, 2016, pp. 673.
DOI Link 1609
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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
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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
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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.
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Zhao, F.[Feng], Guo, Y.Q.[Yi-Qing], Huang, Y.[Yanbo], Verhoef, W.[Wout], van der Tol, C.[Christiaan], Dai, B.[Bo], Liu, L.[Liangyun], 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
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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.
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Xie, Y.H.[Yan-Hui], Shi, J.C.[Jian-Cheng], Lei, Y.[Yonghui], Li, Y.Q.[Yun-Qing],
Modeling Microwave Emission from Short Vegetation-Covered Surfaces,
RS(7), No. 10, 2015, pp. 14099.
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Peng, J.J.[Jing-Jing], Fan, W.J.[Wen-Jie], Xu, X.[Xiru], Wang, L.[Lizhao], 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
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Wu, X.[Xiaodan], 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,
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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.
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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.
IEEE DOI 1601
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
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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.
IEEE DOI 1604
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
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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
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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.[Hesong], Jia, G.[Gensuo], Zhang, A.[Anzhi], 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
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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
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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.
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Pereira, D.R.[Danillo Roberto], Papa, J.P.[Joăo Paulo],
A new approach to contextual learning using interval arithmetic and its applications for land-use classification,
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Elsevier DOI 1609
Sliding Window BibRef

Lv, Z.Y.[Zhi-Yong], He, H.Q.[Hai-Qing], Benediktsson, J.A.[Jón Atli], Huang, H.[Hong],
A Generalized Image Scene Decomposition-Based System for Supervised Classification of Very High Resolution Remote Sensing Imagery,
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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,
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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.
IEEE DOI 1702
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,
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Fan, J., Chen, T., Lu, S.,
Unsupervised Feature Learning for Land-Use Scene Recognition,
GeoRS(55), No. 4, April 2017, pp. 2250-2261.
IEEE DOI 1704
geophysical techniques BibRef

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,
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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,
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Chance, E.W.[Eric W.], Cobourn, K.M.[Kelly M.], Thomas, V.A.[Valerie A.], Dawson, B.C.[Blaine C.], Flores, A.N.[Alejandro N.],
Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Composting Algorithms, Spectral Indices, and Sensors,
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Rozenstein, O.[Offer], Adamowski, J.[Jan],
Linking Spaceborne and Ground Observations of Autumn Foliage Senescence in Southern Québec, Canada,
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Sawada, Y.[Yohei], Tsutsui, H.[Hiroyuki], Koike, T.[Toshio],
Ground Truth of Passive Microwave Radiative Transfer on Vegetated Land Surfaces,
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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
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Khawaja, H.A.[Hassan A.],
Solution of Pure Scattering Radiation Transport Equation (RTE) Using Finite Difference Method (FDM),
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Springer DOI 1706
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Wirth, E., Szabó, G., Czinkóczky, A.,
Measure Landscape Diversity With Logical Scout Agents,
ISPRS16(B2: 491-495).
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Chapter on Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR continues in
Object Based Land Cover, Region Based Land Cover, Land Use Analysis .


Last update:Sep 18, 2017 at 11:34:11