Smits, P.C.,
Annoni, A.,
Updating Land-Cover Maps by Using Texture Information from Very
High-Resolution Space-Borne Imagery,
GeoRS(37), No. 3, May 1999, pp. 1244.
IEEE Top Reference.
BibRef
9905
Carvalho, S.[Sabrina],
Macel, M.[Mirka],
Schlerf, M.[Martin],
Moghaddam, F.E.[Fatemeh Eghbali],
Mulder, P.P.J.[Patrick P.J.],
Skidmore, A.K.[Andrew K.],
van der Putten, W.H.[Wim H.],
Changes in plant defense chemistry (pyrrolizidine alkaloids) revealed
through high-resolution spectroscopy,
PandRS(80), No. 1, June 2013, pp. 51-60.
Elsevier DOI
1305
Plant defense chemistry; Pyrrolizidine alkaloids; Spectroscopy; Senecio
erucifolius; Senecio inaequidens; Senecio jacobaea
BibRef
Bendig, J.[Juliane],
Bolten, A.[Andreas],
Bareth, G.[Georg],
UAV-based Imaging for Multi-Temporal, very high Resolution Crop Surface
Models to monitor Crop Growth Variability,
PFG(2013), No. 6, 2013, pp. 551-562.
DOI Link
1312
BibRef
Bisquert, M.[Mar],
Bordogna, G.[Gloria],
Bégué, A.[Agnčs],
Candiani, G.[Gabriele],
Teisseire, M.[Maguelonne],
Poncelet, P.[Pascal],
A Simple Fusion Method for Image Time Series Based on the Estimation
of Image Temporal Validity,
RS(7), No. 1, 2015, pp. 704-724.
DOI Link
1502
Combine low res, higher frequence visit with high res occasional view
images.
BibRef
Inglada, J.[Jordi],
Arias, M.[Marcela],
Tardy, B.[Benjamin],
Hagolle, O.[Olivier],
Valero, S.[Silvia],
Morin, D.[David],
Dedieu, G.[Gérard],
Sepulcre, G.[Guadalupe],
Bontemps, S.[Sophie],
Defourny, P.[Pierre],
Koetz, B.[Benjamin],
Assessment of an Operational System for Crop Type Map Production
Using High Temporal and Spatial Resolution Satellite Optical Imagery,
RS(7), No. 9, 2015, pp. 12356.
DOI Link
1511
BibRef
Valero, S.[Silvia],
Morin, D.[David],
Inglada, J.[Jordi],
Sepulcre, G.[Guadalupe],
Arias, M.[Marcela],
Hagolle, O.[Olivier],
Dedieu, G.[Gérard],
Bontemps, S.[Sophie],
Defourny, P.[Pierre],
Koetz, B.[Benjamin],
Production of a Dynamic Cropland Mask by Processing Remote Sensing
Image Series at High Temporal and Spatial Resolutions,
RS(8), No. 1, 2016, pp. 55.
DOI Link
1602
BibRef
Wang, J.[Jing],
Huang, B.[Bo],
A Rigorously-Weighted Spatiotemporal Fusion Model with Uncertainty
Analysis,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link
1711
High resolution, frequent coverage for temporal analysis.
BibRef
Lv, Z.Y.[Zhi-Yong],
Liu, T.F.[Tong-Fei],
Wan, Y.L.[Yi-Liang],
Benediktsson, J.A.[Jón Atli],
Zhang, X.K.[Xiao-Kang],
Post-Processing Approach for Refining Raw Land Cover Change Detection
of Very High-Resolution Remote Sensing Images,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Zhu, Y.P.[Yang-Peng],
Li, Q.Y.[Qian-Yu],
Lv, Z.Y.[Zhi-Yong],
Falco, N.[Nicola],
Novel Land Cover Change Detection Deep Learning Framework with Very
Small Initial Samples Using Heterogeneous Remote Sensing Images,
RS(15), No. 18, 2023, pp. 4609.
DOI Link
2310
BibRef
Lv, Z.Y.[Zhi-Yong],
Liu, T.F.[Tong-Fei],
Zhang, P.,
Benediktsson, J.A.[Jón Atli],
Lei, T.,
Zhang, X.K.[Xiao-Kang],
Novel Adaptive Histogram Trend Similarity Approach for Land Cover
Change Detection by Using Bitemporal Very-High-Resolution Remote
Sensing Images,
GeoRS(57), No. 12, December 2019, pp. 9554-9574.
IEEE DOI
1912
Remote sensing, Histograms, Market research, Shape, Level set,
Usability, Terrain factors, urban remote sensing
BibRef
Lv, Z.Y.[Zhi-Yong],
Liu, T.F.[Tong-Fei],
Benediktsson, J.A.[Jón Atli],
Lei, T.[Tao],
Wan, Y.L.[Yi-Liang],
Multi-Scale Object Histogram Distance for LCCD Using Bi-Temporal
Very-High-Resolution Remote Sensing Images,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Cui, G.Q.[Guo-Qing],
Lv, Z.Y.[Zhi-Yong],
Li, G.F.[Guang-Fei],
Benediktsson, J.A.[Jón Atli],
Lu, Y.D.[Yu-Dong],
Refining Land Cover Classification Maps Based on Dual-Adaptive
Majority Voting Strategy for Very High Resolution Remote Sensing
Images,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link
1809
BibRef
Peng, D.F.[Dai-Feng],
Zhang, Y.J.[Yong-Jun],
Guan, H.Y.[Hai-Yan],
End-to-End Change Detection for High Resolution Satellite Images
Using Improved UNet++,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Nascimento, F.S.[Filipe Silveira],
Gastauer, M.[Markus],
Souza-Filho, P.W.M.[Pedro Walfir M.],
Nascimento, W.R.[Wilson R.],
Santos, D.C.[Diogo C.],
Costa, M.F.[Marlene F.],
Land Cover Changes in Open-Cast Mining Complexes Based on
High-Resolution Remote Sensing Data,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Zhang, C.X.[Chen-Xiao],
Yue, P.[Peng],
Tapete, D.[Deodato],
Jiang, L.C.[Liang-Cun],
Shangguan, B.Y.[Bo-Yi],
Huang, L.[Li],
Liu, G.C.[Guang-Chao],
A Deeply Supervised Image Fusion Network for Change Detection in High
Resolution Bi-Temporal Remote Sensing Images,
PandRS(166), 2020, pp. 183-200.
Elsevier DOI
2007
Change detection, Deep supervision network, Image fusion,
High resolution remote sensing image, Image difference discrimination
BibRef
Lv, Z.,
Liu, T.,
Benediktsson, J.A.,
Object-Oriented Key Point Vector Distance for Binary Land Cover
Change Detection Using VHR Remote Sensing Images,
GeoRS(58), No. 9, September 2020, pp. 6524-6533.
IEEE DOI
2008
Remote sensing, Image segmentation, Area measurement, Shape, Sensors,
Level set, Feature extraction, Key point vector distance (KPVD),
very high-resolution (VHR) remote sensing image
BibRef
Wu, T.J.[Tian-Jun],
Luo, J.C.[Jian-Cheng],
Zhou, Y.N.[Ya-Nan],
Wang, C.P.[Chang-Peng],
Xi, J.B.[Jiang-Bo],
Fang, J.[Jianwu],
Geo-Object-Based Land Cover Map Update for High-Spatial-Resolution
Remote Sensing Images via Change Detection and Label Transfer,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Chen, H.R.X.[Hong-Rui-Xuan],
Wu, C.[Chen],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
Wang, L.[Le],
Change Detection in Multisource VHR Images via Deep Siamese
Convolutional Multiple-Layers Recurrent Neural Network,
GeoRS(58), No. 4, April 2020, pp. 2848-2864.
IEEE DOI
2004
Change detection (CD),
deep siamese convolutional multiple-layers recurrent neural network,
very-high-resolution (VHR) images
BibRef
Song, A.[Ahram],
Kim, Y.[Yongil],
Han, Y.K.[You-Kyung],
Uncertainty Analysis for Object-Based Change Detection in Very
High-Resolution Satellite Images Using Deep Learning Network,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Qian, Y.G.[Yu-Guo],
Zhou, W.Q.[Wei-Qi],
Yu, W.J.[Wen-Juan],
Han, L.J.[Li-Jian],
Li, W.F.[Wei-Feng],
Zhao, W.H.[Wen-Hui],
Integrating Backdating and Transfer Learning in an Object-Based
Framework for High Resolution Image Classification and Change
Analysis,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Chen, P.[Pan],
Zhang, B.[Bing],
Hong, D.F.[Dan-Feng],
Chen, Z.C.[Zheng-Chao],
Yang, X.[Xuan],
Li, B.P.[Bai-Peng],
FCCDN: Feature constraint network for VHR image change detection,
PandRS(187), 2022, pp. 101-119.
Elsevier DOI
2205
Change detection, Deep learning, Feature constraint
BibRef
Wang, C.C.[Cong-Cong],
Sun, W.B.[Wen-Bin],
Fan, D.Q.[De-Qin],
Liu, X.D.[Xiao-Ding],
Zhang, Z.[Zhi],
Adaptive Feature Weighted Fusion Nested U-Net with Discrete Wavelet
Transform for Change Detection of High-Resolution Remote Sensing
Images,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Chen, P.[Pan],
Li, C.[Cong],
Zhang, B.[Bing],
Chen, Z.C.[Zheng-Chao],
Yang, X.[Xuan],
Lu, K.X.[Kai-Xuan],
Zhuang, L.[Lina],
A Region-Based Feature Fusion Network for VHR Image Change Detection,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Sun, C.Z.[Cheng-Zhe],
Wu, J.J.[Jiang-Jiang],
Chen, H.[Hao],
Du, C.[Chun],
SemiSANet: A Semi-Supervised High-Resolution Remote Sensing Image
Change Detection Model Using Siamese Networks with Graph Attention,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Ge, C.T.[Chu-Ting],
Ding, H.Y.[Hai-Yong],
Molina, I.[Inigo],
He, Y.J.[Yong-Jian],
Peng, D.F.[Dai-Feng],
Object-Oriented Change Detection Method Based on
Spectral-Spatial-Saliency Change Information and Fuzzy
Integral Decision Fusion for HR Remote Sensing Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Tian, S.Q.[Shi-Qi],
Zhong, Y.F.[Yan-Fei],
Zheng, Z.[Zhuo],
Ma, A.L.[Ai-Long],
Tan, X.C.[Xi-Cheng],
Zhang, L.P.[Liang-Pei],
Large-Scale Deep Learning Based Binary and Semantic Change Detection
in Ultra High Resolution Remote Sensing Imagery: From Benchmark
Datasets to Urban Application,
PandRS(193), 2022, pp. 164-186.
Elsevier DOI
2210
Ultra high resolution, Semantic change detection, Deep learning, Remote sensing
BibRef
Wu, C.[Chen],
Chen, H.R.X.[Hong-Rui-Xuan],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
Unsupervised Change Detection in Multitemporal VHR Images Based on
Deep Kernel PCA Convolutional Mapping Network,
Cyber(52), No. 11, November 2022, pp. 12084-12098.
IEEE DOI
2211
Feature extraction, Principal component analysis, Kernel,
Convolution, Remote sensing, Training, Task analysis,
very-high-resolution (VHR) images
BibRef
Jiang, Z.R.[Zhuo-Ran],
Zhou, X.X.[Xin-Xin],
Cao, W.[Wei],
Sun, Z.H.[Zai-Hong],
Wu, C.B.[Chang-Bin],
ICD: VHR-Oriented Interactive Change-Detection Algorithm,
IJGI(11), No. 10, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Ling, J.[Jie],
Hu, L.[Lei],
Cheng, L.[Lang],
Chen, M.H.[Ming-Hui],
Yang, X.[Xin],
IRA-MRSNet: A Network Model for Change Detection in High-Resolution
Remote Sensing Images,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Rommel, E.[Edvinas],
Giese, L.[Laura],
Fricke, K.[Katharina],
Kathöfer, F.[Frederik],
Heuner, M.[Maike],
Mölter, T.[Tina],
Deffert, P.[Paul],
Asgari, M.[Maryam],
Näthe, P.[Paul],
Dzunic, F.[Filip],
Rock, G.[Gilles],
Bongartz, J.[Jens],
Burkart, A.[Andreas],
Quick, I.[Ina],
Schröder, U.[Uwe],
Baschek, B.[Björn],
Very High-Resolution Imagery and Machine Learning for Detailed
Mapping of Riparian Vegetation and Substrate Types,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Li, J.K.[Jian-Kang],
Zhu, S.Y.[Shan-You],
Gao, Y.Y.[Yi-Yao],
Zhang, G.X.[Gui-Xin],
Xu, Y.M.[Yong-Ming],
Change Detection for High-Resolution Remote Sensing Images Based on a
Multi-Scale Attention Siamese Network,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Pan, F.[Fei],
Wu, Z.B.[Ze-Bin],
Jia, X.P.[Xiu-Ping],
Liu, Q.[Qian],
Xu, Y.[Yang],
Wei, Z.H.[Zhi-Hui],
A Temporal-Reliable Method for Change Detection in High-Resolution
Bi-Temporal Remote Sensing Images,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Zhang, R.Q.[Rui-Qian],
Zhang, H.C.[Han-Chao],
Ning, X.G.[Xiao-Gang],
Huang, X.[Xiao],
Wang, J.M.[Jia-Ming],
Cui, W.[Wei],
Global-aware siamese network for change detection on remote sensing
images,
PandRS(199), 2023, pp. 61-72.
Elsevier DOI
2305
Change detection, Remote sensing, High-resolution images,
Global attention, Foreground awareness
BibRef
Zhang, C.[Chong],
Zhang, Y.H.[Yong-Hong],
Lin, H.F.[Hai-Feng],
Multi-Scale Feature Interaction Network for Remote Sensing Change
Detection,
RS(15), No. 11, 2023, pp. 2880.
DOI Link
2306
BibRef
Ma, C.[Chong],
Yin, H.Y.[Hong-Yang],
Weng, L.G.[Li-Guo],
Xia, M.[Min],
Lin, H.F.[Hai-Feng],
DAFNet: A Novel Change-Detection Model for High-Resolution
Remote-Sensing Imagery Based on Feature Difference and Attention
Mechanism,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link
2308
BibRef
Lin, M.[Manhui],
Yang, G.Y.[Guang-Yi],
Zhang, H.Y.[Hong-Yan],
Transition Is a Process: Pair-to-Video Change Detection Networks for
Very High Resolution Remote Sensing Images,
IP(32), 2023, pp. 57-71.
IEEE DOI
2301
Task analysis, Couplings, Spatiotemporal phenomena, Decoding,
Computational modeling, Training, very high resolution image
BibRef
Zhang, M.Y.[Ming-Yang],
Zheng, H.H.[Han-Hong],
Gong, M.[Maoguo],
Wu, Y.[Yue],
Li, H.[Hao],
Jiang, X.M.[Xiang-Ming],
Self-structured pyramid network with parallel spatial-channel
attention for change detection in VHR remote sensed imagery,
PR(138), 2023, pp. 109354.
Elsevier DOI
2303
Change detection, VHR remote sensing images, Feature pyramids,
Attention mechanisms, Deep learning
BibRef
Luo, J.H.[Jian-Hui],
Chen, Q.[Qiang],
Wang, L.[Lei],
Huang, Y.X.[Yi-Xiao],
Multi-Difference Image Fusion Change Detection Using a Visual
Attention Model on VHR Satellite Data,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link
2308
BibRef
Wang, B.[Biao],
He, A.[Ao],
Wang, C.L.[Chun-Lin],
Xu, X.[Xiao],
Yang, H.[Hui],
Wu, Y.[Yanlan],
A Heterogeneity-Enhancement and Homogeneity-Restraint Network
(HEHRNet) for Change Detection from Very High-Resolution Remote
Sensing Imagery,
RS(15), No. 22, 2023, pp. 5425.
DOI Link
2311
BibRef
Lin, H.[Haihan],
Wang, X.Q.[Xiao-Qin],
Li, M.M.[Meng-Meng],
Huang, D.H.[De-Hua],
Wu, R.[Ruijiao],
A Multi-Task Consistency Enhancement Network for Semantic Change
Detection in HR Remote Sensing Images and Application of
Non-Agriculturalization,
RS(15), No. 21, 2023, pp. 5106.
DOI Link
2311
BibRef
Ning, X.G.[Xiao-Gang],
Zhang, H.[Hanchao],
Zhang, R.Q.[Rui-Qian],
Huang, X.[Xiao],
Multi-Stage Progressive Change Detection on High Resolution Remote
Sensing Imagery,
PandRS(207), 2024, pp. 231-244.
Elsevier DOI
2401
Change detection, Remote sensing images,
Stage progressive change detection, Coarse to fine detection,
Knowledge distillation
BibRef
Gao, G.,
Zhang, M.,
Gu, Y.,
Object Manifold Alignment for Multi-temporal High Resolution Remote
Sensing Images Classification,
Hannover17(325-332).
DOI Link
1805
BibRef
Lavender, S.J.,
Monitoring Land Cover Dynamics At Varying Spatial Scales Using High To
Very High Resolution Optical Imagery,
ISPRS16(B8: 937-939).
DOI Link
1610
BibRef
Bryson, M.,
Johnson-roberson, M.,
Murphy, R.,
Low-cost, Ultra-high Spatial And Temporal Resolution Mapping Of
Intertidal Rock Platforms,
ISPRS12(XXXIX-B8:243-248).
DOI Link
1209
BibRef
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Land Cover Change Analysis Using Learning, Neural Nets .