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Haralick, R.M.[Robert M.],
Hlavka, C.A.,
Carlyle, S.M., and
Yokoyama, R.,
The Discrimination of Winter Wheat Using a Growth-State Signature,
RSE(9), 1980, pp. 277-294.
BibRef
8000
Haralick, R.M.[Robert M.],
Hlavka, C.A.,
Yokoyama, R.,
Carlyle, S.M.,
Spectral-Temporal Classification Using Vegetation Phenology,
GeoRS(18), No. 2, April, 1980, pp. 167-174.
BibRef
8004
Ince, F.[Fuat],
The application of the coalescence clustering algorithm to remotely
sensed multispectral data,
PR(14), No. 1-6, 1981, pp. 121-126.
WWW Version.
0309
BibRef
Sawada, N.[Nobuo],
Numagami, H.[Hideo],
Shinoda, H.[Hidenori],
Kidode, M.[Masatsugu],
Watanabe, S.[Sadakazu],
Application of a parallel pattern processor to remote sensing,
PR(14), No. 1-6, 1981, pp. 331-343.
WWW Version.
0309
BibRef
Wharton, S.W.,
A Contextual Classification Method for Recognizing Land Use Patterns in
High Resolution Remotely Sensed Data,
PR(15), No. 4, 1982, pp. 317-324.
WWW Version.
BibRef
8200
Badhwar, G.D.,
Austin, W.W.,
Carnes, J.G.,
A semi-automatic technique for multitemporal classification of a given
crop within a landsat scene,
PR(15), No. 3, 1982, pp. 217-230.
WWW Version.
0309
BibRef
Davis, L.S.,
Wang, C.Y.,
Xie, H.C.,
An Experiment in Multispectral, Multitemporal Crop Classification
Using Relaxation Techniques,
CVGIP(23), No. 2, August 1983, pp. 227-235.
WWW Version.
BibRef
8308
Shoshany, M.,
Kutiel, P.,
Lavee, H.,
Eichler, M.,
Remote-Sensing of Vegetation Cover Along A Climatological Gradient,
PandRS(49), No. 4, August 1994, pp. 2-10.
BibRef
9408
Skirvin, S.M.,
Dryden, G.,
Classification of LANDSAT Thematic Mapper Image Data,
Chiricahua National Monument, Arizona,
AIApp(11), No. 3, 1997, pp. 90-98.
9802
BibRef
Heikkonen, J.,
Varfis, A.,
Land Cover Land Use Classification of Urban Areas:
A Remote-Sensing Approach,
PRAI(12), No. 4, June 1998, pp. 475-489.
9808
BibRef
Heikkonen, J.[Jukka],
Varfis, A.[Aristide], and
Kanellopoulos, I.[Ioannis],
A Method for Remote Sensing Based Classification of Urban Areas,
SCIA97(xx-yy)
9705
HTML Version.
BibRef
Lobo, A.,
Image Segmentation and Discriminant-Analysis for the Identification of
Land-Cover Units in Ecology,
GeoRS(35), No. 5, September 1997, pp. 1136-1145.
IEEE Top Reference.
9710
BibRef
Bischof, H.[Horst],
Schneider, W.[Werner],
Pinz, A.[Axel],
Multispectral Classification of Landsat Images Using Neural Networks,
GeoRS(30), No. 3, 1992, pp. 482-490.
BibRef
9200
Bischof, H.[Horst],
Leonardis, A.[Ales],
Finding Optimal Neural Networks for Land Use Classification,
GeoRS(36), No. 1, 1998, pp. 337-341.
BibRef
9800
Stoms, D.M.,
Bueno, M.J.,
Davis, F.W.,
Cassidy, K.M.,
Driese, K.L.,
Kagan, J.S.,
Map Guided Classification of Regional Land Cover with
Multitemporal AVHRR Data,
PhEngRS(64), No. 8, August 1998, pp. 831-838.
9808
BibRef
Kavzoglu, T.,
Mather, P.M.,
Pruning artificial neural networks: an example using land cover
classification of multi-sensor images,
JRS(20), No. 14, September 1999, pp. 2787.
BibRef
9909
Kavzoglu, T.,
Mather, P.M.,
The role of feature selection in artificial neural network applications,
JRS(23), No. 15, August 2002, pp. 2919-2937.
0211
BibRef
Defries, R.S.,
Chan, J.C.W.[Jonathan Cheung-Wai],
Multiple Criteria for Evaluating Machine Learning Algorithms for Land
Cover Classification from Satellite Data,
RSE(74), No. 3, 2000, pp. 503-515.
0102
BibRef
Steele, B.M.[Brian M.],
Combining Multiple Classifiers. An Application Using Spatial and
Remotely Sensed Information for Land Cover Type Mapping,
RSE(74), No. 3, 2000, pp. 545- 556.
0102
BibRef
Ji, C.Y.,
Land-Use Classification of Remotely Sensed Data Using Kohonen
Self-Organizing Feature Map Neural Networks,
PhEngRS(66), No. 12, December 2000, pp. 1451-1460.
Results are compared to those of the maximum-likelihood method and of
the BP neural networks.
0101
BibRef
Webb, E.L.[Edward L.],
Evangelista, M.A.[Ma. Arlene],
Robinson, J.A.[Julie A.],
Digital Land-Use Classification Using Space-Shuttle-Acquired Orbital
Photographs: A Quantitative Comparison with Landsat TM Imagery of a
Coastal Environment, Chanthaburi, Thailand,
PhEngRS(66), No. 12, December 2000, pp. 1439-1450.
0101
Evaluation, Classifiers.
BibRef
Liu, X.H.[Xue-Hua],
Skidmore, A.K.,
van Oosten, H.,
Integration of classification methods for improvement of land-cover map
accuracy,
PandRS(56), No. 4, July 2002, pp. 257-268.
HTML Version.
0207
BibRef
Debeir, O.[Olivier],
van den Steen, I.[Isabelle],
Latinne, P.[Patrice],
van Ham, P.[Philippe],
Wolff, E.[Eléonore],
Textural and Contextual Land-Cover Classification Using Single and
Multiple Classifier Systems,
PhEngRS(68), No. 6, June 2002, pp. 597.
Improve the accuracy of land-cover clasification with textural, contextual, and multiple classifier system.
WWW Version.
0207
BibRef
Hlavka, C.A.,
Dungan, J.L.,
Areal Estimates of Fragmented Land Cover:
Effects of Pixel Size and Model-Based Corrections,
JRS(23), No. 4, February 2002, pp. 711-724.
0202
BibRef
King, R.B.,
Land cover mapping principles: a return to interpretation fundamentals,
JRS(23), No. 18, September 2002, pp. 3525-3545.
WWW Version.
0211
BibRef
Huang, C.,
Davis, L.S.,
Townshend, J.R.G.,
An assessment of support vector machines for land cover classification,
JRS(23), No. 4, February 2002, pp. 725-749.
0202
BibRef
Sun, W.X.[Wan-Xiao],
Heidt, V.,
Gong, P.[Peng],
Xu, G.[Gang],
Information fusion for rural land-use classification with
high-resolution satellite imagery,
GeoRS(41), No. 4, April 2003, pp. 883-890.
IEEE Abstract.
0307
BibRef
Rogan, J.[John],
Miller, J.[Jennifer],
Stow, D.[Doug],
Franklin, J.[Janet],
Levien, L.[Lisa],
Fischer, C.[Chris],
Land-Cover Change Monitoring with Classification Trees Using Landsat TM
and Ancillary Data,
PhEngRS(69), No. 7, July 2003, pp. 793-804.
Overall accuracies of the land-cover change maps ranged between 72 percent and 92 percent, with ancillary variables
playing an important discriminatory role in the most detailed level of land-cover change.
WWW Version.
0307
BibRef
Shao, G.[Guofan],
We, W.[Wenchun],
Wu, G.[Gang],
Zhou, X.H.[Xin-Hua],
Wu, J.G.[Jian-Guo],
An Explicit Index for Assessing the Accuracy of Cover-Class Areas,
PhEngRS(69), No. 8, August 2003, pp. 907-914.
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).
WWW Version.
0401
BibRef
Özkan, C.[Coskun],
Erbek, F.S.[Filiz Sunar],
A Comparison of Activation Functions for Multispectral Landsat TM Image
Classification,
PhEngRS(69), No. 11, November 2003, pp. 1225-1234.
Compare linear, sigmoid, and tangent hyperbolic activation functions through
the one- and two-hidden layered MLP neural network structures trained
with the scaled conjugate gradient learning
algorithm, and evaluate their perfornances for a multispectral Landsat
TM imagery hard classification problem.
WWW Version.
0401
BibRef
Wade, T.G.[Timothy G.],
Wickham, J.D.[James D.],
Nash, M.S.[Maliha S.],
Neale, A.C.[Anne C.],
Riitters, K.H.[Kurt H.],
Jones, K.B.[K. Bruce],
A Comparison of Vector and Raster GIS Methods for Calculating Landscape
Metrics Used in Environmental Assessments,
PhEngRS(69), No. 12, December 2003, pp. 1399-1405.
A statistical analysis of the potential impact of processing methodology on environmental assessment results is
presented.
WWW Version.
0401
BibRef
Aplin, P.[Paul],
Atkinson, P.M.[Peter M.],
Predicting Missing Field Boundaries to Increase Per-Field
Classification Accuracy,
PhEngRS(70), No. 1, January 2004, pp. 141-150.
WWW Version. Missing field boundaries were predicted by comparing the within-field modal land-cover proportion and local variance to increase the accuracy of per-field classification.
0403
See also Super-resolution target identification from remotely sensed images using a Hopfield neural network.
BibRef
Kempeneers, P.,
de Backer, S.,
Debruyn, W.,
Coppin, P.,
Scheunders, P.,
Generic Wavelet-Based Hyperspectral Classification Applied to
Vegetation Stress Detection,
GeoRS(43), No. 3, March 2005, pp. 610-614.
IEEE Abstract.
0501
BibRef
Somers, B.[Ben],
Delalieux, S.[Stephanie],
Verstraeten, W.W.[Willem W.],
Coppin, P.[Pol],
A Conceptual Framework for the Simultaneous Extraction of Sub-pixel
Spatial Extent and Spectral Characteristics of Crops,
PhEngRS(75), No. 1, January 2009, pp. 57-68.
WWW Version.
0902
BibRef
de Backer, S.[Steve],
Kempeneers, P.[Pieter],
Debruyn, W.[Walter],
Scheunders, P.[Paul],
Classification of Dune Vegetation from Remotely Sensed Hyperspectral
Images,
ICIAR04(II: 497-503).
WWW Version.
0409
BibRef
Li, X.[Xia],
A Four-Component Efficiency Index for Assessing Land Development Using
Remote Sensing and GIS,
PhEngRS(71), No. 1, January 2005, pp. 47-58.
This paper derives the indicators of quantity, quality, location, and
morphology to access land development based on the integration of
remote sensing and GIS.
WWW Version.
0509
BibRef
Islam, Z.,
Metternicht, G.,
The Performance of Fuzzy Operators on Fuzzy Classification of Urban
Land Covers,
PhEngRS(71), No. 1, January 2005, pp. 59-68.
Evaluation of the performance of fuzzy operators for integrating fuzzy
membership values associated with multiple spectral bands for mapping
urban land covers.
WWW Version.
0509
BibRef
Tran, L.T.[Liem T.],
Wickham, J.D.[James D.],
Jarnagin, S.T.[S. Taylor],
Knight, C.G.[C. Gregory],
Mapping Spatial Thematic Accuracy with Fuzzy Sets,
PhEngRS(71), No. 1, January 2005, pp. 29-36.
WWW Version.
0509
BibRef
Pearlstine, L.[Leonard],
Portier, K.M.[Kenneth M.],
Smith, S.E.[Scot E.],
Textural Discrimination of an Invasive Plant, Schinus terebinthifolius,
from Low Altitude Aerial Digital Imagery,
PhEngRS(71), No. 3, March 2005, pp. 289-298.
Texture features derived from first and second order statistics and
edge components in high-resolution digital color infrared images were
tested for their ability to discriminate Schinus terebinthifolius in
multiple linear logistic regressions.
WWW Version.
0509
BibRef
Ramsey, III, E.[Elijah],
Rangoonwala, A.[Amina],
Leaf Optical Property Changes Associated with the Occurrence of
Spartina alterniflora Dieback in Coastal Louisiana Related to Remote
Sensing Mapping,
PhEngRS(71), No. 3, March 2005, pp. 299-312.
Determining optimal reflectance bands for detecting march impact with
hyperspectral leaf optical analysis.
WWW Version.
0509
BibRef
Sohn, Y.S.[Young-Sinn],
Qi, J.G.[Jia-Guo],
Mapping Detailed Biotic Communities in the Upper San Pedro Valley of
Southeastern Arizona using Landsat 7 ETM+ Data and Supervised Spectral
Angle Classifier,
PhEngRS(71), No. 6, June 2005, pp. 709-718.
Detailed biotic communities were mapped with high accuracy using the
Supervised Spectral Angle Classifier and Landsat-7 EMT+ imagery.
WWW Version.
0509
BibRef
Pozzi, F.[Francesca],
Small, C.[Christopher],
Analysis of Urban Land Cover and Population Density in the United
States,
PhEngRS(71), No. 6, June 2005, pp. 719-726.
Analysis of population density and vegetation distribution for several
cities shows a strong correspondence in cities with high population
density but considerable regional variability that precludes simple
spectral classifications of land cover.
WWW Version.
0509
BibRef
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,
PR(38), No. 12, December 2005, pp. 2626-2638.
WWW Version.
0510
BibRef
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 Version.
0509
BibRef
Sun, W.,
Cetin, M.,
Thacker, W.C.,
Chin, T.M.,
Willsky, A.S.,
Variational Approaches on Discontinuity Localization and Field
Estimation in Sea Surface Temperature and Soil Moisture,
GeoRS(44), No. 2, February 2006, pp. 336-350.
IEEE DOI Link
0602
BibRef
Fieguth, P.W.,
Willsky, A.S.,
Menemenlis, D.,
Wunsch, C.I.,
A general multiresolution approach to the estimation of dense fields in
remote sensing,
ICIP96(II: 609-612).
IEEE DOI Link
9610
BibRef
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 Link
0606
BibRef
Mayaux, P.,
Eva, H.,
Gallego, J.,
Strahler, A.H.,
Herold, M.,
Agrawal, S.,
Naumov, S.,
DeMiranda, E.E.,
DiBella, C.M.,
Ordoyne, C.,
Kopin, I.,
Roy, P.S.,
Validation of the Global Land Cover 2000 Map,
GeoRS(44), No. 7, Part 1, July 2006, pp. 1728-1739.
IEEE DOI Link
0606
BibRef
Abuelgasim, A.A.,
Fernandes, R.A.,
Leblanc, S.G.,
Evaluation of National and Global LAI Products Derived From Optical
Remote Sensing Instruments Over Canada,
GeoRS(44), No. 7, Part 1, July 2006, pp. 1872-1884.
Leaf Area Index
IEEE DOI Link
0606
BibRef
Deng, F.,
Chen, J.M.,
Plummer, S.,
Chen, M.,
Pisek, J.,
Algorithm for Global Leaf Area Index Retrieval Using Satellite Imagery,
GeoRS(44), No. 8, August 2006, pp. 2219-2229.
IEEE DOI Link
0608
BibRef
Chen, J.M.,
Deng, F.,
Chen, M.,
Locally Adjusted Cubic-Spline Capping for Reconstructing Seasonal
Trajectories of a Satellite-Derived Surface Parameter,
GeoRS(44), No. 8, August 2006, pp. 2230-2238.
IEEE DOI Link
0608
BibRef
Zhang, L.P.[Liang-Pei],
Huang, X.,
Huang, B.[Bo],
Li, P.X.[Ping-Xiang],
A Pixel Shape Index Coupled With Spectral Information for
Classification of High Spatial Resolution Remotely Sensed Imagery,
GeoRS(44), No. 10, October 2006, pp. 2950-2961.
IEEE DOI Link
0609
BibRef
Huang, X.[Xin],
Zhang, L.P.[Liang-Pei],
Li, P.X.[Ping-Xiang],
Classification of Very High Spatial Resolution Imagery Based on the
Fusion of Edge and Multispectral Information,
PhEngRS(74), No. 12, December 2008, pp. 1585-1597.
WWW Version.
0804
A new algorithm to classify high spatial resolution remotely sensed
imagery by integrating fuzzy edge information and multispectral
features.
BibRef
Huang, X.[Xin],
Zhang, L.P.[Liang-Pei],
An Adaptive Mean-Shift Analysis Approach for Object Extraction and
Classification From Urban Hyperspectral Imagery,
GeoRS(46), No. 12, December 2008, pp. 4173-4185.
IEEE DOI Link
0812
BibRef
Zhao, Y.[Yindi],
Zhang, L.P.[Liang-Pei],
Li, P.X.[Ping-Xiang],
Huang, B.[Bo],
Classification of High Spatial Resolution Imagery Using Improved
Gaussian Markov Random-Field-Based Texture Features,
GeoRS(45), No. 5, May 2007, pp. 1458-1468.
IEEE DOI Link
0704
BibRef
Zhang, L.P.[Liang-Pei],
Zhao, Y.D.[Yin-Di],
Huang, B.[Bo],
Li, P.X.[Ping-Xiang],
Texture Feature Fusion with Neighborhood-Oscillating Tabu Search for
High Resolution Image Classification,
PhEngRS(74), No. 3, March 2008, pp. 323-332.
WWW Version.
0803
Neighborhood-Oscillating tabu search integrates different types of
texture features to improve classifi cation performance of
high-resolution imagery.
BibRef
Lathrop, R.G.[Richard G.],
Montesano, P.[Paul],
Haag, S.[Scott],
A Multi-scale Segmentation Approach to Mapping Seagrass Habitats Using
Airborne Digital Camera Imagery,
PhEngRS(72), No. 6, June 2006, pp. 665-676.
WWW Version.
0610
BibRef
Yu, Q.[Qian],
Gong, P.[Peng],
Clinton, N.[Nick],
Biging, G.[Greg],
Kelly, M.[Maggi],
Schirokauer, D.[Dave],
Object-based Detailed Vegetation Classification with Airborne High
Spatial Resolution Remote Sensing Imagery,
PhEngRS(72), No. 7, July 2006, pp. 799-812.
WWW Version.
0610
Object-based classification applied in vegetation mapping at alliance level
with 1-meter resolution airborne imagery compared with conventional
pixel-based classification.
BibRef
Wu, S.S.[Shuo-Sheng],
Xu, B.[Bing],
Wang, L.[Le],
Urban Land-use Classification Using Variogram-based Analysis with an
Aerial Photograph,
PhEngRS(72), No. 7, July 2006, pp. 813-822.
WWW Version.
0610
A variogram-based texture analysis was tested for classifying detailed urban
land-use classes, such as mobile home, singlefamily house,
multi-family house, industrial, and commercial, from a digital color
infrared aerial photograph.
BibRef
Keramitsoglou, I.[Iphigenia],
Sarimveis, H.[Haralambos],
Kiranoudis, C.T.[Chris T.],
Kontoes, C.[Charalambos],
Sifakis, N.[Nicolaos],
Fitoka, E.[Eleni],
The performance of pixel window algorithms in the classification of
habitats using VHSR imagery,
PandRS(60), No. 4, June 2006, pp. 225-238.
WWW Version.
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.
WWW Version.
0704
Improving land-cover classification from remote sensing imagery with neural
networks using a threshold of recognition below which the recognition system
applies additional bootstrapped information to classify pixels.
BibRef
Huang, H.[Heng],
Legarsky, J.[Justin],
Othman, M.[Maslina],
Land-cover Classification Using Radarsat and Landsat Imagery for St.
Louis, Missouri,
PhEngRS(73), No. 1, January 2007, pp. 37-44.
WWW Version.
0704
An investigation of the classification accuracy of merging satellite
imagery from Radarsat and Landsat missions.
BibRef
Sanchez-Hernandez, C.[Carolina],
Boyd, D.S.[Doreen S.],
Foody, G.M.[Giles M.],
One-Class Classification for Mapping a Specific Land-Cover Class:
SVDD Classification of Fenland,
GeoRS(45), No. 4, April 2007, pp. 1061-1073.
IEEE DOI Link
0704
BibRef
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.
WWW Version.
0709
Scale; Landscape pattern; Sensor spatial resolution; Spatial metrics;
Landscape ecology; Land cover analysis
BibRef
Lucas, R.[Richard],
Rowlands, A.[Aled],
Brown, A.[Alan],
Keyworth, S.[Steve],
Bunting, P.[Peter],
Rule-based classification of multi-temporal satellite imagery for
habitat and agricultural land cover mapping,
PandRS(62), No. 3, August 2007, pp. 165-185.
WWW Version.
0709
Time-series imagery; Landsat; Segmentation; Decision rules; Fuzzy membership
BibRef
Yang, P.,
Shibasaki, R.,
Wu, W.,
Zhou, Q.,
Chen, Z.,
Zha, Y.,
Shi, Y.,
Tang, H.,
Evaluation of MODIS Land Cover and LAI Products in Cropland of North
China Plain Using In Situ Measurements and Landsat TM Images,
GeoRS(45), No. 10, October 2007, pp. 3087-3097.
IEEE DOI Link
0711
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 Version.
0709
Properties of a pixel-swapping optimization algorithm for predicting subpixel
land-cover distribution are investigated, and improvements to it are evaluated.
BibRef
Van de Voorde, T.[Tim],
de Genst, W.[William],
Canters, F.[Frank],
Improving Pixel-based VHR Land-cover Classifications of Urban Areas
with Post-classification Techniques,
PhEngRS(73), No. 9, September 2007, pp. 1017-1028.
WWW Version.
0709
Three post-classification techniques were applied to improve the accuracy
and the structural coherence of an urban land-cover map derived
from a soft pixel-based classification.
BibRef
Bellens, R.,
Gautama, S.,
Martinez-Fonte, L.,
Philips, W.,
Chan, J.C.W.,
Canters, F.[Frank],
Improved Classification of VHR Images of Urban Areas Using Directional
Morphological Profiles,
GeoRS(46), No. 10, October 2008, pp. 2803-2813.
IEEE DOI Link
0810
BibRef
Chan, J.C.W.[Jonathan Cheung-Wai],
Bellens, R.[Rik],
Canters, F.[Frank],
Gautama, S.[Sidharta],
An Assessment of Geometric Activity Features for Per-pixel
Classification of Urban Man-made Objects using Very High Resolution
Satellite Imagery,
PhEngRS(75), No. 4, April 2009, pp. 397-412.
WWW Version.
0903
The results of using geometric activity features based on ridge-based
modeling and morphological profi les for the classification of urban
man-made objects from an Ikonos image.
BibRef
Xu, B.[Bing],
Gong, P.[Peng],
Land-use/Land-cover Classification with Multispectral and Hyperspectral
EO-1 Data,
PhEngRS(73), No. 8, August 2007, pp. 955-965.
WWW Version.
0709
Land-use and land-cover classification in an urban rural fringe
of the San Francisco Bay Area using EO-1 Hyperion imagery is compared
with that using EO-1 ALI imagery, and the application of a computationally
efficient segmentation-based feature reduction approach.
BibRef
Makido, Y.[Yasuyo],
Shortridge, A.[Ashton],
Messina, J.P.[Joseph P.],
Assessing Alternatives for Modeling the Spatial Distribution of
Multiple Land-cover Classes at Sub-pixel Scales,
PhEngRS(73), No. 8, August 2007, pp. 935-944.
WWW Version.
0709
Evaluating three methods for modeling the spatial distribution of
multiple land cover classes at sub-pixel scales.
BibRef
Budreski, K.A.[Katherine A.],
Wynne, R.H.[Randolph H.],
Browder, J.O.[John O.],
Campbell, J.B.[James B.],
Comparison of Segment and Pixel-based Non-parametric Land Cover
Classification in the Brazilian Amazon Using Multi-temporal Landsat
TM/ETM+ Imagery,
PhEngRS(73), No. 7, July 2007, pp. 813-828.
WWW Version.
0709
Accurate land-cover maps were produced using inter-annual,
multi-temporal Landsat TM/EMT+ imagery and pixel-based kNN and
CART®; segmentation proved unnecessary.
BibRef
Addink, E.A.[Elisabeth A.],
de Jong, S.M.[Steven M.],
Pebesma, E.J.[Edzer J.],
The Importance of Scale in Object-based Mapping of Vegetation
Parameters with Hyperspectral Imagery,
PhEngRS(73), No. 8, August 2007, pp. 905-912.
WWW Version.
0709
An investigation of optimal object definition for prediction of
biomass and leaf area index.
BibRef
Mahtab, A.,
Sridhar, V.N.,
Navalgund, R.R.,
Impact of Surface Anisotropy on Classification Accuracy of Selected
Vegetation Classes: An Evaluation Using Multidate Multiangular MISR
Data Over Parts of Madhya Pradesh, India,
GeoRS(46), No. 1, January 2008, pp. 250-258.
IEEE DOI Link
0712
BibRef
Myint, S.W.[Soe W.],
Wentz, E.A.[Elizabeth A.],
Purkis, S.J.[Sam J.],
Employing Spatial Metrics in Urban Land-use/Landcover Mapping:
Comparing the Getis and Geary Indices,
PhEngRS(73), No. 12, December 2007, pp. 1403-1417.
WWW Version.
0712
The effectiveness of Getis index (Gi) in comparison to a measure of
spatial autocorrelation (Geary's C) in classifying landuse /
land-cover classes in a high resolution imagery and the impact of
distance threshold used in Getis index with regards to the
classification accuracy.
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 Version.
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
Chastain Jr., R.A.[Robert A.],
Struckhoff, M.A.[Matthew A.],
He, H.[Hong],
Larsen, D.R.[David R.],
Mapping Vegetation Communities Using Statistical Data Fusion in the
Ozark National Scenic Riverways, Missouri, USA,
PhEngRS(74), No. 2, February 2008, pp. 247-264.
WWW Version.
0803
A vegetation community map was produced for the Ozark National Scenic
Riverways using a discriminant analysis statistical approach combined
with photointerpretation to exploit a large set of input variables
obtained from remote sensing and topographic data.
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.
WWW Version.
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.
WWW Version.
0803
Classification; Land-cover; Rule-based; Genetic algorithm; Knowledge rules
BibRef
Karjalainen, M.[Mika],
Kaartinen, H.[Harri],
Hyyppä, J.[Juha],
Agricultural Monitoring Using Envisat Alternating Polarization SAR
Images,
PhEngRS(74), No. 1, January 2008, pp. 117-128
WWW Version.
0803
Satellite images will improve yield estimation in the future because
they can provide objective information about crop growth over large
areas; in this context SAR images are extremely useful due to their
high revisit imaging capability.
BibRef
Chen, D.M.[Dong-Mei],
A Standardized Probability Comparison Approach for Evaluating and
Combining Pixel-based Classification Procedures,
PhEngRS(74), No. 5, May 2008, pp. 601-610.
WWW Version.
0804
An objective approach to evaluate pixel labeling confidence in a
classification and to combine classified maps generated from different
classification procedures.
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 Link
0806
BibRef
Yu, Q.[Qian],
Gong, P.[Peng],
Tian, Y.Q.[Yong Q.],
Pu, R.L.[Rui-Liang],
Yang, J.[Jun],
Factors Affecting Spatial Variation of Classification Uncertainty in an
Image Object-based Vegetation Mapping,
PhEngRS(74), No. 8, August 2008, pp. 1007-1018.
WWW Version.
0804
A mixed linear model to examine the effect of six categories of
factors on classification uncertainty in an object-based vegetation
mapping, including general membership, topography, sample object
density, spatial composition, sample object reliability and object
features.
BibRef
Aitkenhead, M.J.,
Flaherty, S.,
Cutler, M.E.J.,
Evaluating Neural Networks and Evidence Pooling for Land Cover Mapping,
PhEngRS(74), No. 8, August 2008, pp. 1019-1032.
WWW Version.
0804
Integrating evidence from a range of data sources was to produce land
cover mapping based on neural networks trained to identify specific
land cover classes.
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 Version.
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 Link
0810
BibRef
Freitas, C.C.,
Soler, L.S.,
Sant'Anna, S.J.S.,
Dutra, L.V.,
dos Santos, J.R.,
Mura, J.C.,
Correia, A.H.,
Land Use and Land Cover Mapping in the Brazilian Amazon Using
Polarimetric Airborne P-Band SAR Data,
GeoRS(46), No. 10, October 2008, pp. 2956-2970.
IEEE DOI Link
0810
BibRef
Aguera, F.[Francisco],
Aguilar, F.J.[Fernando J.],
Aguilar, M.A.[Manuel A.],
Using texture analysis to improve per-pixel classification of very high
resolution images for mapping plastic greenhouses,
PandRS(63), No. 6, November 2008, pp. 635-646.
WWW Version.
0811
QuickBird; IKONOS; Texture; Land use
BibRef
Carvajal, F.,
Crisanto, E.,
Aguilar, F.J.,
Aguera, F.,
Aguilar, M.A.,
Greenhouses Detection Using an Artificial Neural Network with a Very
High Resolution Satellite Image,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
Aguilar, M.A.[Manuel A.],
Aguilar, F.J.[Fernando J.],
Agüera, F.[Francisco],
Assessing Geometric Reliability of Corrected Images from Very High
Resolution Satellites,
PhEngRS(74), No. 12, December 2008, pp. 1551-1560.
WWW Version.
0804
Validation of two theoretical models for estimating the reliability of
geometric accuracies measured as Root Mean Square Error over corrected
single images from QuickBird and Ikonos imagery.
BibRef
Walton, J.T.[Jeffrey T.],
Subpixel Urban Land Cover Estimation:
Comparing Cubist, Random Forests, and Support Vector Regression,
PhEngRS(74), No. 10, October 2008, pp. 1213-1222.
WWW Version.
0804
Three machine learning subpixel estimation methods were applied to
estimate urban cover and the resulting predictions were compared based
on accuracy.
BibRef
Stehman, S.V.[Stephen V.],
Wickham, J.D.[James D.],
Wade, T.G.[Timothy G.],
Smith, J.D.[Jonathan D.],
Designing a Multi-Objective, Multi-Support Accuracy Assessment of the
2001 National Land Cover Data (NLCD 2001) of the Conterminous United
States,
PhEngRS(74), No. 12, December 2008, pp. 1561-1572.
WWW Version.
0804
A framework for designing accuracy assessments of largearea land-cover
maps developed and applied to the 2001 National Land Cover Data.
BibRef
Li, Z.[Zhe],
Fuzzy ARTMAP-based Neurocomputational Spatial Uncertainty Measures,
PhEngRS(74), No. 12, December 2008, pp. 1573-1584.
WWW Version.
0804
Non-parametric Commitment and Typicality measures for the fuzzy ARTMAP
computational neural network to handle spatial uncertainty in remotely
sensed imagery classification.
BibRef
Geiger, B.,
Carrer, D.,
Franchistéguy, L.,
Roujean, J.L.,
Meurey, C.,
Land Surface Albedo Derived on a Daily Basis From Meteosat Second
Generation Observations,
GeoRS(46), No. 11, November 2008, pp. 3841-3856.
IEEE DOI Link
0812
BibRef
Johnson, D.M.[David M.],
A Comparison of Coincident Landsat-5 TM and Resourcesat-1 AWiFS Imagery
for Classifying Croplands,
PhEngRS(74), No. 11, November 2008, pp. 1413-1424.
WWW Version.
0804
Testing the suitability of AWiFS imagery with TM as a benchmark for
deriving row crop focused cover type maps over highly cultivated
regions of the central U.S.
BibRef
Lowry, Jr., J.H.[John H.],
Ramsey, R.D.[R. Douglas],
Stoner, L.L.[Lisa Langs],
Kirby, J.[Jessica],
Schulz, K.[Keith],
An Ecological Framework for Evaluating Map Errors Using Fuzzy Sets,
PhEngRS(74), No. 12, December 2008, pp. 1509-1520.
WWW Version.
0804
Using an ecological context to define varying levels of landcover
class similarity, a decision framework guides map experts' decisions
and provides a more meaningful assessment of map errors using fuzzy
sets.
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 Link
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,
SMC-A(39), No. 1, January 2009, pp. 218-226.
IEEE DOI Link
0901
BibRef
Wuest, B.[Ben],
Zhang, Y.[Yun],
Region based segmentation of QuickBird multispectral imagery through
band ratios and fuzzy comparison,
PandRS(64), No. 1, January 2009, pp. 55-64.
Elsevier DOI Link
WWW Version.
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 Version.
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
Nichol, J.[Janet],
An Emissivity Modulation Method for Spatial Enhancement of Thermal
Satellite Images in Urban Heat Island Analysis,
PhEngRS(75), No. 5, May 2009, pp. 547-556.
WWW Version.
0904
A methodology using ancillary land-cover information to enhance the
spatial resolution of thermal satellite images for detailed studies of
land surface temperature, such as in urban heat island analysis.
BibRef
Alvarez, G.A.,
Salinas, R.A.,
Malthus, T.J.,
Integrating CFD modelling, neural networks and remote sensing:
controlled prediction of chlorophyll-a concentration in the Mejillones
of South Bay,
IET-CV(1), No. 2, June 2007, pp. 55-65.
WWW Version.
0905
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 Link
0906
BibRef
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 Link
0909
BibRef
Jimenez Berni, J.A.,
Zarco-Tejada, P.J.,
Suárez, L.,
Fereres, E.,
Thermal and narrow-band multispectral remote sensing
for vegetation monitoring from an unmanned aerial vehicle,
GeoRS(47), No. 3, March 2009, pp. 722-738.
BibRef
0903
Jimenez Berni, J.A.,
Zarco-Tejada, P.J.,
Suárez, L.,
González-Dugo, V.,
Fereres, E.,
Remote sensing of vegetation from UAV platforms using lightweight
multispectral and thermal imaging sensors,
HighRes09(xx-yy).
PDF Version.
0906
BibRef
Waske, B.[Bjorn],
Braun, M.[Matthias],
Classifier ensembles for land cover mapping using multitemporal SAR
imagery,
PandRS(64), No. 5, September 2009, pp. 450-457,.
Elsevier DOI Link
WWW Version.
0910
Decision tree; Random forests; Boosting; Multitemporal SAR data; Land
cover classification
BibRef
Silva, W.F.[Wagner F.],
Rudorff, B.F.T.[Bernardo F.T.],
Formaggio, A.R.[Antonio R.],
Paradella, W.R.[Waldir R.],
Mura, J.C.[Jose C.],
Discrimination of agricultural crops in a tropical semi-arid region of
Brazil based on L-band polarimetric airborne SAR data,
PandRS(64), No. 5, September 2009, pp. 458-463,.
Elsevier DOI Link
WWW Version.
0910
Remote sensing; Classification; Multi-polarization; Contextual
classifier; Image classification
BibRef
Canty, M.J.[Morton J.],
Image Analysis, Classification and Change Detection in Remote Sensing:
With Algorithms for ENVI/IDL,
Second Edition:
CRC PressDecember 2009, ISBN: 9781420087130
Buy this book: Image Analysis, Classification, and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL, Second Edition
WWW Version.
Code, Image Processing.
0910
BibRef
Chen, C.H., (Ed.)
Image Processing for Remote Sensing,
CRC PressOctober, 2007, ISBN: 9781420066647
WWW Version.
Buy this book: Image Processing for Remote Sensing
BibRef
Borengasser, M.[Marcus],
Hungate, W.S.[William S.],
Watkins, R.[Russell],
Hyperspectral Remote Sensing: Principles and Applications,
CRC PressDecember, 2007, ISBN: 9781566706544
WWW Version.
Buy this book: Hyperspectral Remote Sensing
BibRef
Mather, P.[Paul],
Tso, B.[Brandt],
Bie-Tou,
Classification Methods for Remotely Sensed Data,
CRC PressMay 2009, ISBN: 9781420090727.
Second Edition.
WWW Version.
Buy this book: Classification Methods for Remotely Sensed Data, Second Edition
BibRef
Congalton, R.G.[Russell G.],
Green, K.[Kass],
Assessing the Accuracy of Remotely Sensed Data:
Principles and Practices,
CRC PressDecember, 2008, ISBN: 9781420055122
WWW Version.
Buy this book: Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition (Mapping Science)
BibRef
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 Version.
1001
An analysis of thematic accuracy consequences of being more or less
restrictive at the classification stage and of applying different mode
restrictions in polygon enrichment.
BibRef
Davies, W.H.,
North, P.R.J.,
Grey, W.M.F.,
Barnsley, M.J.,
Improvements in Aerosol Optical Depth Estimation Using Multiangle
CHRIS/PROBA Images,
GeoRS(48), No. 1, January 2010, pp. 18-24.
IEEE DOI Link
1001
BibRef
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,
GeoRS(48), No. 1, January 2010, pp. 112-146.
IEEE DOI Link
1001
BibRef
Velpuri, N.M.,
Thenkabail, P.S.,
Gumma, M.K.,
Biradar, C.,
Dheeravath, V.,
Noojipady, P.,
Yuanjie, L.,
Influence of Resolution in Irrigated Area Mapping and Area Estimation,
PhEngRS(75), No. 12, December 2009, pp. 1383-1396.
WWW Version.
1001
A comparison of irrigated areas derived from four different spatial
resolutions is performed to ascertain the influence of resolution on
irrigated area mapping and area estimation.
BibRef
Long, Z.Y.[Zhi-Yong],
He, M.[Mingyuan],
Shi, H.Q.[Han-Qing],
Rao, R.[Ruoyu],
Study on Water Bodies Extraction with FY3A Satellite Image,
CISP09(1-5).
IEEE DOI Link
0910
BibRef
Cui, H.S.[Hai-Shan],
Qian, H.S.[Huai-Sui],
Qian, L.X.[Le-Xiang],
Li, Y.[Ying],
Remote Sensing Experts Classification System Applying in the Land Use
Classification in Guangzhou City,
CISP09(1-4).
IEEE DOI Link
0910
BibRef
Liu, M.[Min],
Huang, F.[Fang],
Zhang, H.[Hannv],
Wang, P.[Ping],
Vegetation Canopy Water Content Estimation Using GVMI and EWT Model
from MODIS Data,
CISP09(1-4).
IEEE DOI Link
0910
BibRef
Fang, L.[Lei],
Jiang, T.[Tao],
Shan, C.Z.[Chun-Zhi],
Li, H.W.[Hai-Wei],
A Per-Pixel Stratified Classification Methodology for Land Cover
Mapping Based on Medium-Resolution Satellite Imagery,
CISP09(1-5).
IEEE DOI Link
0910
BibRef
Huang, Y.[Ying],
Zhou, Y.X.[Yun-Xuan],
Li, X.[Xing],
Kuang, R.Y.[Run-Yuan],
Zheng, Z.S.[Zong-Sheng],
Two Strategies for Remote Sensing Classification Accuracy Improvement
of Salt Marsh Vegetation: A Case Study in Chongming Dongtan,
CISP09(1-7).
IEEE DOI Link
0910
BibRef
Qian, Y.R.[Yu Rong],
Yang, F.[Feng],
Li, J.L.[Jian Long],
Wavelet-Based Feature Extraction for Retrieval of Photosynthetic
Pigment Concentrations from Hyperspectral Reflectance,
CISP09(1-5).
IEEE DOI Link
0910
BibRef
Liu, D.Z.[Da-Zhao],
Chen, C.Q.[Chu-Qun],
Gong, J.Q.[Jie-Qiong],
Fu, D.Y.[Dong-Yang],
Retrieval of Colored Dissolved Organic Matter in Pearl River Estuary
Using MODIS Data,
CISP09(1-3).
IEEE DOI Link
0910
BibRef
Giguere, P.[Philippe],
Dudek, G.[Gregory],
Prahacs, C.[Christopher],
Plamondon, N.[Nicolas],
Turgeon, K.[Katrine],
Unsupervised Learning of Terrain Appearance for Automated Coral Reef
Exploration,
CRV09(268-275).
IEEE DOI Link
0905
BibRef
Lohmann, P.[Peter],
Soergel, U.,
Tavakkoli, M.,
Farghaly, D.,
Multi-temporal Classification for Crop Discrimination using TerraSAR-X
Spotlight images,
HighRes09(xx-yy).
PDF Version.
0906
BibRef
Le Bris, A.,
Robert-Sainte, P.,
Classification of Roof Materials for Rainwater Pollution Modelization,
HighRes09(xx-yy).
PDF Version.
0906
BibRef
Arnold, S.,
Digital Landscape Model DLM-DE: Deriving land cover information by
integration of topographic reference data with remote sensing data,
HighRes09(xx-yy).
PDF Version.
0906
BibRef
Hefnawy, A.A.,
A High Accuracy Land Use/Cover Retrieval System,
HighRes09(xx-yy).
PDF Version.
0906
BibRef
Helmholz, P.,
Rottensteiner, F.,
Automatic Verification of Agricultural Areas using IKONOS Satellite
Images,
HighRes09(xx-yy).
PDF Version.
0906
BibRef
Zingaretti, P.[Primo],
Frontoni, E.[Emanuele],
Malinverni, E.S.[Eva Savina],
Mancini, A.[Adriano],
A Hybrid Approach to Land Cover Classification from Multi Spectral
Images,
CIAP09(500-508).
Springer DOI Link
0909
BibRef
Wang, O.[Oliver],
Gunawardane, P.[Prabath],
Scher, S.[Steve],
Davis, J.[James],
Material classification using BRDF slices,
CVPR09(2805-2811).
IEEE DOI Link
0906
Bidirectional Reflectance Distribution Function
BibRef
Yu, H.Y.[Hai-Yang],
Gan, F.P.[Fu-Ping],
Object recognition of high resolution remote sensing image based on
PSWT,
IASP09(52-56).
IEEE DOI Link
0904
BibRef
Besbes, O.[Olfa],
Boujemaa, N.[Nozha],
Belhadj, Z.[Ziad],
Cue Integration for Urban Area Extraction in Remote Sensing Images,
ICIAR09(248-257).
Springer DOI Link
0907
BibRef
And:
Contextual classification of high-resolution satellite images,
CIIP09(41-47).
IEEE DOI Link
0903
BibRef
McNeill, S.J.,
Pairman, D.,
Belliss, S.E.,
Dalley, D.,
Dynes, R.,
Estimation of pasture biomass using dual-polarisation radar imagery:
A preliminary study,
IVCNZ08(1-6).
IEEE DOI Link
0811
BibRef
Borkowski, A.,
Józków, G.,
Airborne Laser Scanning Data Filtering Using Flakes,
ISPRS08(B3b: 179 ff).
PDF Version.
0807
BibRef
Tymkow, P.,
Borkowski, A.,
Land Cover Classification Using Airborne Laser Scanning Data and
Photographs,
ISPRS08(B3b: 185 ff).
PDF Version.
0807
BibRef
Silva, S.[Sara],
Tseng, Y.T.[Yao-Ting],
Classification of Seafloor Habitats Using Genetic Programming,
EvoIASP08(xx-yy).
Springer DOI Link
0804
BibRef
López, A.A.[Adrian A.],
Malpica, J.A.[José A.],
High Resolution Satellite Classification with Graph Cut Algorithms,
ISVC08(II: 105-112).
Springer DOI Link
0812
BibRef
Alonso, M.C.[María C.],
Malpica, J.A.[José A.],
Classification of Multispectral High-Resolution Satellite Imagery Using
LIDAR Elevation Data,
ISVC08(II: 85-94).
Springer DOI Link
0812
BibRef
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 Link
0711
BibRef
Le Bris, A.,
Boldo, D.,
Extraction of Landcover Themes out of Aerial Orthoimages in Mountainous
Areas Using External Information,
PIA07(123).
PDF Version.
0711
BibRef
Helmholz, P.,
Gerke, M.,
Heipke, C.,
Automatic Discrimination of Farmland Types Using IKONOS Imagery,
PIA07(81).
PDF Version.
0711
BibRef
Brzank, A.,
Heipke, C.,
Supervised Classification of Water Regions from Lidar Data in the
Wadden Sea Using a Fuzzy Logic Concept,
Laser07(90).
PDF Version.
0709
BibRef
Ratanopad, S.,
Kainz, W.,
Land Cover Classification and Monitoring in Northeast Thailand Using
Landsat 5 TM Data,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
Jones, S.D.,
Ferwerda, J.G.,
Reinke, K.J.,
Scaling the Walls of History: The Perils and Pitfalls of Multi-Scale
Land Cover Comparison,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
Lacerda, M.P.C.,
Barbosa, I.O.,
Alves, H.M.R.,
Vieira, T.G.C.,
Menezes, P.R.,
The Use of Soil-Landscape Relationships Modelling and Geotechnologies
for Detailing the Soil Map Of Distrito Federal in Brazil,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
Carvalho, F.A.,
Lacerda, M.P.C.,
Monitoring Environmental Impact of Land Use:
Evaluating an Agricultural Area of Distrito Federal, Brazil,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
Vieira, T.G.C.,
Alves, H.M.R.,
Souza, V.C.O.,
Bernardes, T.,
Lacerda, M.P.C.,
Assessing and Mapping Changes, in Space and Time, of Coffee Lands of
the State of Minas Gerais in Brazil,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
Alves, H.M.R.,
Vieira, T.G.C.,
Souza, V.C.O.,
Bertoldo, M.A.,
Lacerda, M.P.C.,
Andrade, H.,
Bernardes, N.,
Monitoring the Relationships between Environment and Coffee Production
in Agroecosytems of the State of Minas Gerais in Brazil,
IfromI06(xx-yy).
PDF Version.
0607
BibRef
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,
ACIVS07(865-876).
Springer DOI Link
0708
BibRef
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 Link
0706
BibRef
Yang, Y.F.[Yeh Fen],
Lohmann, P.[Peter],
Heipke, C.[Christian],
Genetic Algorithms for the Unsupervised Classification of Satellite
Images,
PCV06(xx-yy).
PDF Version.
0609
BibRef
Argany, M.,
Amini, J.,
Artificial neural networks for improvement of classification accuracy
in Landsat ETM+ images,
OBIA06(xx-yy).
PDF Version.
0607
BibRef
Jia, Z.,
Liu, X.,
Study and application of a multi-resolution hierarchy remote sensing
image classification,
OBIA06(xx-yy).
PDF Version.
0607
BibRef
Corcoran, P.,
Winstanley, A.,
Using texture to tackle the problem of scale in land-cover
classification,
OBIA06(xx-yy).
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Chmiel, J.,
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Delenne, C.,
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Field-based classification of agricultural crops using multi-scale
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Developing an integrated system for the extraction of sub-fields within
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Preiner, M.,
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Lang, S.,
Two structure-related strategies for automatically delineating and
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Urbanski, J.,
Using ArcGIS Model Builder for object-based image classification of
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Torra, R.,
Application of Landsat TM 5 images to supervised and non-supervised
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Carleer, A.P.,
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Müterthies, M.,
Buck, O.,
DeCOVER: Developing a methodology to update land cover data for public
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Riedel, T.,
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Smith, G.,
The development of integrated object-based analysis of EO data within
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Levick, S.,
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LiDAR and object-based image analysis as tools for monitoring the
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Grenier, M.,
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Kelly, M.,
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Integrating Lidar and CIR imagery for mapping tidal wetlands: an
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Yokota, S.,
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Study on the relationship between landscape characteristics of
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Kux, H.,
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Multi-temporal object-oriented classifications and analysis of
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Kux, H.,
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