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
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
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
Lu, L.Z.[Li-Zhen],
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
Zhu, P.P.[Pan-Pan],
Zhang, L.Q.[Li-Qiang],
Wang, Y.B.[Yue-Bin],
Mei, J.[Jie],
Zhou, G.Q.[Guo-Qing],
Liu, F.Y.[Fang-Yu],
Liu, W.W.[Wei-Wei],
Mathiopoulos, P.T.[P. Takis],
Projection learning with local and global consistency constraints for
scene classification,
PandRS(144), 2018, pp. 202-216.
Elsevier DOI
1809
Scene classification, Projection learning,
Manifold regularization, Label consistency, Classification error
BibRef
Ventura, D.[Daniele],
Bonifazi, A.[Andrea],
Gravina, M.F.[Maria Flavia],
Belluscio, A.[Andrea],
Ardizzone, G.[Giandomenico],
Mapping and Classification of Ecologically Sensitive Marine Habitats
Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image
Analysis (OBIA),
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Liu, S.[Shuo],
Ding, W.R.[Wen-Rui],
Liu, C.H.[Chun-Hui],
Liu, Y.[Yu],
Wang, Y.F.[Yu-Feng],
Li, H.G.[Hong-Guang],
ERN: Edge Loss Reinforced Semantic Segmentation Network for Remote
Sensing Images,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Peng, J.J.[Jing-Jing],
Fan, W.J.[Wen-Jie],
Wang, L.Z.[Li-Zhao],
Xu, X.[Xiru],
Li, J.[Jvcai],
Zhang, B.T.[Bei-Tong],
Tian, D.F.[Ding-Fang],
Modeling the Directional Clumping Index of Crop and Forest,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link
1811
Depending on the angle, objects (i.e. trees) have very different
spatial properties, cover more of the scene.
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
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.,
Otir, K.,
Application of Object Based Approach to Heterogeneous Land Cover/Use,
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
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
Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Irrigation Monitoring, Irrigated Field Detection, Land Use Analysis .