22.1.4.2 Object Based Land Cover, Region Based Land Cover, Land Use Analysis

Chapter Contents (Back)
Object-Based. Region-Based.

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 Link. 0610
Object-based classification applied in vegetation mapping at alliance level with 1-meter resolution airborne imagery compared with conventional pixel-based classification. 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 Link. 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

Rizvi, I.A., Mohan, B.K.,
Object-Based Image Analysis of High-Resolution Satellite Images Using Modified Cloud Basis Function Neural Network and Probabilistic Relaxation Labeling Process,
GeoRS(49), No. 12, December 2011, pp. 4815-4820.
IEEE DOI 1201
Classification of objects, not just pixels. BibRef

Xie, H.[Huan], Heipke, C.[Christian], Lohmann, P.[Peter], Soergel, U.[Uwe], Tong, X.H.[Xiao-Hua], Shi, W.Z.[Wen-Zhong],
A New Binary Encoding Algorithm for the Simultaneous Region-based Classification of Hyperspectral Data and Digital Surface Models,
PFG(2011), No. 1, 2011, pp. 17-33.
WWW Link. 1211
BibRef

Huth, J., Kuenzer, C., Wehrmann, T., Gebhardt, S., Tuan, V., Dech, S.,
Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification,
RS(4), No. 9, September 2012, pp. 2530-2553.
DOI Link 1210
BibRef

Wolf, N.[Nils],
Feature Evaluation for a Transferable Approach of Object-based Land Cover Classification Based on Ikonos and QuickBird Satellite Data,
PFG(2011), No. 3, 2011, pp. 135-144.
WWW Link. 1211
BibRef

Wolf, N.[Nils],
Object Features for Pixel-based Classi cation of Urban Areas Comparing Different Machine Learning Algorithms,
PFG(2013), No. 3, 2013, pp. 149-161.
DOI Link 1306
BibRef

Tang, H., Shen, L., Qi, Y., Chen, Y., Shu, Y., Li, J., Clausi, D.A.,
A Multiscale Latent Dirichlet Allocation Model for Object-Oriented Clustering of VHR Panchromatic Satellite Images,
GeoRS(51), No. 3, March 2013, pp. 1680-1692.
IEEE DOI 1303
semantic clustering of geo-objects. BibRef

Hu, Q.[Qiong], Wu, W.B.[Wen-Bin], Xia, T.[Tian], Yu, Q.Y.[Qiang-Yi], Yang, P.[Peng], Li, Z.G.[Zheng-Guo], Song, Q.[Qian],
Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping,
RS(5), No. 11, 2013, pp. 6026-6042.
DOI Link 1312
BibRef

Witharana, C.[Chandi], Lynch, H.J.[Heather J.],
An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images,
RS(8), No. 5, 2016, pp. 375.
DOI Link 1606
BibRef

Wang, M.[Min], Cui, Q.[Qi], Wang, J.[Jie], Ming, D.P.[Dong-Ping], Lv, G.[Guonian],
Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features,
PandRS(123), No. 1, 2017, pp. 104-113.
Elsevier DOI 1612
Region-line primitive association framework. Separate from water. BibRef

Wang, M.[Min], Cui, Q.[Qi], Sun, Y.[Yujie], Wang, Q.[Qiao],
Photovoltaic panel extraction from very high-resolution aerial imagery using region-line primitive association analysis and template matching,
PandRS(141), 2018, pp. 100-111.
Elsevier DOI 1806
Photovoltaic panel, Object-based image analysis, Region-line primitive association framework, High-resolution imagery BibRef

Lv, Z.Y.[Zhi-Yong], Shi, W.Z.[Wen-Zhong], Benediktsson, J.A.[Jón Atli], Ning, X.J.[Xiao-Juan],
Novel Object-Based Filter for Improving Land-Cover Classification of Aerial Imagery with Very High Spatial Resolution,
RS(8), No. 12, 2016, pp. 1023.
DOI Link 1612
BibRef

Lv, Z.Y.[Zhi-Yong], Shi, W.Z.[Wen-Zhong], Zhou, X.C.[Xiao-Cheng], Benediktsson, J.A.[Jón Atli],
Semi-Automatic System for Land Cover Change Detection Using Bi-Temporal Remote Sensing Images,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Lv, Z.Y.[Zhi-Yong], Liu, T.[Tongfei], Zhang, P.[Penglin], Benediktsson, J.A.[Jón Atli], Chen, Y.[Yixiang],
Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Chen, X.[Xi], Zhou, G.J.[Gong-Jian], Chen, Y.S.[Yu-Shi], Shao, G.F.[Guo-Fan], Gu, Y.F.[Yan-Feng],
Supervised Multiview Feature Selection Exploring Homogeneity and Heterogeneity With L_1,2-Norm and Automatic View Generation,
GeoRS(55), No. 4, April 2017, pp. 2074-2088.
IEEE DOI 1704
feature selection BibRef

Lv, Z.Y.[Zhi-Yong], Zhang, P.L.[Peng-Lin], Benediktsson, J.A.[Jón Atli],
Automatic Object-Oriented, Spectral-Spatial Feature Extraction Driven by Tobler's First Law of Geography for Very High Resolution Aerial Imagery Classification,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Lu, L.[Lizhen], Huang, Y.L.[Yan-Lin], Di, L.P.[Li-Ping], Hang, D.[Danwei],
A New Spatial Attraction Model for Improving Subpixel Land Cover Classification,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Gu, H.Y.[Hai-Yan], Li, H.T.[Hai-Tao], Yan, L.[Li], Liu, Z.J.[Zheng-Jun], Blaschke, T.[Thomas], Soergel, U.[Uwe],
An Object-Based Semantic Classification Method for High Resolution Remote Sensing Imagery Using Ontology,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Yang, B.[Bin], Liu, Z.J.[Zheng-Jun], Xing, Y.[Ying], Luo, C.F.[Cheng-Feng],
Remote Sensing Image Classification Based on Improved BP Neural Network,
ISIDF11(1-4).
IEEE DOI 1111
BibRef

Gerçek, D.[Deniz],
A Conceptual Model for Delineating Land Management Units (LMUs) Using Geographical Object-Based Image Analysis,
IJGI(6), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Gerçek, D.[Deniz], Zeydanl, U.[Ugur],
Object-Based Classification of Landscape into Land Management Units (LMUs),
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Xu, Y.[Yan], Du, Q.[Qian], Li, W.[Wei], Chen, C.[Chen], Younan, N.H.[Nicolas H.],
Nonlinear Classification of Multispectral Imagery Using Representation-Based Classifiers,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Zhang, X.L.[Xue-Liang], Xiao, P.[Pengfeng], Feng, X.Z.[Xue-Zhi],
Toward combining thematic information with hierarchical multiscale segmentations using tree Markov random field model,
PandRS(131), No. 1, 2017, pp. 134-146.
Elsevier DOI 1709
High-spatial resolution remote sensing image BibRef

Cheng, X.J.[Xiao-Juan], Lu, J.W.[Ji-Wen], Feng, J.J.[Jian-Jiang], Yuan, B.[Bo], Zhou, J.[Jie],
Scene recognition with objectness,
PR(74), No. 1, 2018, pp. 474-487.
Elsevier DOI 1711
Scene recognition BibRef

Huang, Y.H.[Yao-Huan], Zhao, C.P.[Chuan-Peng], Yang, H.J.[Hai-Jun], Song, X.Y.[Xiao-Yang], Chen, J.[Jie], Li, Z.H.[Zhong-Hua],
Feature Selection Solution with High Dimensionality and Low-Sample Size for Land Cover Classification in Object-Based Image Analysis,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Balasubramaniam, R., Namboodiri, S., Nidamanuri, R.R., Gorthi, R.K.S.S.[R. K. S. S.],
Active Learning-Based Optimized Training Library Generation for Object-Oriented Image Classification,
GeoRS(56), No. 1, January 2018, pp. 575-585.
IEEE DOI 1801
Databases, Detectors, Entropy, Hyperspectral imaging, Libraries, Training, Active learning (AL), multiclassifier systems, training library BibRef

Yu, L.L.[Long-Long], Su, J.[Jinhe], Li, C.[Chun], Wang, L.[Le], Luo, Z.[Ze], Yan, B.P.[Bao-Ping],
Improvement of Moderate Resolution Land Use and Land Cover Classification by Introducing Adjacent Region Features,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Georganos, S.[Stefanos], Lennert, M.[Moritz], Grippa, T.[Tais], Vanhuysse, S.[Sabine], Johnson, B.[Brian], Wolff, E.[Eléonore],
Normalization in Unsupervised Segmentation Parameter Optimization: A Solution Based on Local Regression Trend Analysis,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Gong, X.[Xi], Xie, Z.[Zhong], Liu, Y.Y.[Yuan-Yuan], Shi, X.[Xuguo], Zheng, Z.[Zhuo],
Deep Salient Feature Based Anti-Noise Transfer Network for Scene Classification of Remote Sensing Imagery,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
Find higher-level features for low quality data. BibRef

Liu, T.[Tao], Abd-Elrahman, A.[Amr],
An Object-Based Image Analysis Method for Enhancing Classification of Land Covers Using Fully Convolutional Networks and Multi-View Images of Small Unmanned Aerial System,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Qiu, S.H.[Shao-Hua], Wen, G.[Gongjian], Liu, J.[Jia], Deng, Z.P.[Zhi-Peng], Fan, Y.[Yaxiang],
Unified Partial Configuration Model Framework for Fast Partially Occluded Object Detection in High-Resolution Remote Sensing Images,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Tang, Y.[Yunwei], Zhang, J.[Jingxiong], Jing, L.[Linhai], Gao, H.[Han],
Geostatistical modelling of spatial dependence in area-class occurrences for improved object-based classifications of remote-sensing images,
PandRS(141), 2018, pp. 219-236.
Elsevier DOI 1806
GEOBIA, Geostatistics, Spatial structural modelling, Change-of-support, Area-class, Image segmentation, Image classification BibRef

Aguilar, R.[Rosa], Zurita-Milla, R.[Raul], Izquierdo-Verdiguier, E.[Emma], A. de By, R.[Rolf],
A Cloud-Based Multi-Temporal Ensemble Classifier to Map Smallholder Farming Systems,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
The regions are small. Worldview-2 images. BibRef

Zeng, D.[Dan], Chen, S.J.[Shuai-Jun], Chen, B.Y.[Bo-Yang], Li, S.Y.[Shu-Ying],
Improving Remote Sensing Scene Classification by Integrating Global-Context and Local-Object Features,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Sitokonstantinou, V.[Vasileios], Papoutsis, I.[Ioannis], Kontoes, C.[Charalampos], Arnal, A.L.[Alberto Lafarga], Andrés, A.P.A.[Ana Pilar Armesto], Zurbano, J.A.G.[José Angel Garraza],
Scalable Parcel-Based Crop Identification Scheme Using Sentinel-2 Data Time-Series for the Monitoring of the Common Agricultural Policy,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Li, P.[Peng], Ren, P.[Peng], Zhang, X.[Xiaoyu], Wang, Q.[Qian], Zhu, X.O.[Xia-Obin], Wang, L.[Lei],
Region-Wise Deep Feature Representation for Remote Sensing Images,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Arief, H.A.[Hasan Asyari], Strand, G.H.[Geir-Harald], Tveite, H.[Hĺvard], Indahl, U.G.[Ulf Geir],
Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Zanotta, D.C.[Daniel Capella], Zortea, M.[Maciel], Ferreira, M.P.[Matheus Pinheiro],
A supervised approach for simultaneous segmentation and classification of remote sensing images,
PandRS(142), 2018, pp. 162-173.
Elsevier DOI 1807
Object-based image analysis, Segmentation, Supervised classification, Multispectral imaging BibRef


Zaouali, M.[Mariem], Bouzidi, S.[Sonia], Zagrouba, E.[Ezzeddine],
Shearlet-Based Region Map Guidance for Improving Hyperspectral Image Classification,
ACIVS17(191-202).
Springer DOI 1712
BibRef

Blaschke, T., Lang, S., Tiede, D., Papadakis, M., Györi, A.,
Object-based Image Analysis Beyond Remote Sensing: The Human Perspective,
ISPRS16(B7: 879-882).
DOI Link 1610
BibRef

Kupidura, P., Osinska-Skotak, K., Pluto-Kossakowska, J.,
Automatic Approach to VHR Satellite Image Classification,
ISPRS16(B7: 277-282).
DOI Link 1610
Spectral and texture measures. BibRef

Wu, L.[Linmei], Shen, L.[Li], Li, Z.P.[Zhi-Peng],
A Kernel Method Based On Topic Model For Very High Spatial Resolution (VHSR) Remote Sensing Image Classification,
ISPRS16(B7: 399-403).
DOI Link 1610
BibRef

Cui, W.H.[Wei-Hong], Wang, G.[Guofeng], Feng, C.[Chenyi], Zheng, Y.[Yiwei], Li, J.[Jonathan], Zhang, Y.[Yi],
SPMK and Grabcut Based Target Extraction From High Resolution Remote Sensing Images,
ISPRS16(B7: 195-203).
DOI Link 1610
BibRef

Hingee, K.L.,
Statistics For Patch Observations,
ISPRS16(B6: 235-242).
DOI Link 1610
BibRef

Kamiya, K., Fuse, T., Takahashi, M.,
Applicability Evaluation Of Object Detection Method To Satellite And Aerial Imageries,
ISPRS16(B7: 229-234).
DOI Link 1610
BibRef

Kavzoglu, T., Erdemir, M.Y.[M. Yildiz], Tonbul, H.,
A Region-based Multi-scale Approach For Object-based Image Analysis,
ISPRS16(B7: 241-247).
DOI Link 1610
BibRef

Li, C.K., Fang, W., Dong, X.J.,
Research on the Classification of High Resolution Image Based on Object-oriented and Class Rule,
IWIDF15(75-80).
DOI Link 1508
BibRef

Wang, G., Liu, J., He, G.,
Object-Based Land Cover Classification for ALOS Image Combining TM Spectral,
SSG13(263-266).
DOI Link 1402
BibRef

Djerriri, K., Malki, M.,
Data Mining for Knowledge Discovery from Object-Based Segmentation of VHR Remotely Sensed Imagery,
Hannover13(87-92).
DOI Link 1308
Region based analysis BibRef

Firat, O.[Orhan], Can, G.[Gulcan], Vural, F.T.Y.[Fatos Tunay Yarman],
Representation Learning for Contextual Object and Region Detection in Remote Sensing,
ICPR14(3708-3713)
IEEE DOI 1412
BibRef
And: A2, A1, Only:
Conditional Random Fields for Land Use/Land Cover Classification and Complex Region Detection,
SSSPR12(216-224).
Springer DOI 1211
Airplanes BibRef

Kanjir, U., Veljanovski, T., Marsetic, A., Oštir, K.,
Application of Object Based Approach to Heterogeneous Land Cover/Use,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Arroyo, L.A.[Lara A.], Johansen, K.[Kasper], Phinn, S.R.[Stuart R.],
Mapping Land Cover Types from Very High Spatial Resolution Imagery: Automatic Application of an Object Based Classification Scheme,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Lizarazo, I.[Ivan],
Fuzzy Image Regions for Quantitative Land Cover Analysis,
GEOBIA10(xx-yy).
WWW Link. 1007
BibRef

Malinverni, E.S., Tassetti, A.N., Bernardini, A.,
Automatic Land Use/Land Cover Classification System with Rules Based Both on Objects Attributes and Landscape Indicators,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Ons, G.[Ghariani], Tebourbi, R.[Riadh],
Object oriented hierarchical classification of high resolution remote sensing images,
ICIP09(1681-1684).
IEEE DOI 0911
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 0904
BibRef

Argany, M., Amini, J.,
Artificial neural networks for improvement of classification accuracy in Landsat ETM+ images,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Jia, Z., Liu, X.,
Study and application of a multi-resolution hierarchy remote sensing image classification,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Corcoran, P., Winstanley, A.,
Using texture to tackle the problem of scale in land-cover classification,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Chmiel, J.,
Example of object based approach in land cover classification of VHR satellite image for agricultural areas,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Delenne, C., Rabatel, G., Agurto, V., Deshayes, M.,
Vine plot detection in aerial images using Fourier analysis,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Tarantino, E., Caprioli, M.,
Multiscale representation of brownfield sites with IKONOS imagery,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Preiner, M., Weinke, E., Lang, S.,
Two structure-related strategies for automatically delineating and classifying habitats in an alpine environment,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Urbanski, J.A.,
Using ArcGIS Model Builder for object-based image classification of seagrass meadows,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Carleer, A.P., Wolff, E.,
Region-based classification potential for land-cover classification with very high spatial resolution satellite data,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Kamagata, N., Hara, K., Mori, M., Akamatsu, Y., Li, Y., Hoshino, Y.,
A new method of vegetation mapping by object-based classification using high resolution satellite data,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Luscier, J.D., Thompson, W.L., Wilson, J.M., Gorham, B.E., Dragut, L.D.,
Using digital photographs and object-based image analysis to estimate percent ground cover in vegetation plots,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Müterthies, M., Buck, O.,
DeCOVER: Developing a methodology to update land cover data for public authorities in Germany,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Lück, W.,
An object oriented data model for a high end land cover classification product,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Lübker, T., Schaab, G.,
Optimization of Parameter Settings for Multilevel Image Segmentation in GEOBIA,
HighRes09(xx-yy).
PDF File. 0906
GEOBIA: GEOgraphic Object-Based Image Analysis. BibRef

Lübker, T., Schaab, G.,
A Work-Flow Design for Large-Area Multilevel Geobia: Integrating Statistical Measures and Expert Knowledge,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
LAI, Leaf Area Index, Land Cover Analysis .


Last update:Aug 16, 2018 at 18:22:30