Yan, F.Q.[Feng-Qin],
Yu, L.X.[Ling-Xue],
Yang, C.B.[Chao-Bin],
Zhang, S.W.[Shu-Wen],
Paddy Field Expansion and Aggregation Since the Mid-1950s in a Cold
Region and Its Possible Causes,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Wagner, M.P.[Matthias P.],
Oppelt, N.[Natascha],
Deep Learning and Adaptive Graph-Based Growing Contours for
Agricultural Field Extraction,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Vlachopoulos, O.[Odysseas],
Leblon, B.[Brigitte],
Wang, J.F.[Jin-Fei],
Haddadi, A.[Ataollah],
LaRocque, A.[Armand],
Patterson, G.[Greg],
Delineation of Crop Field Areas and Boundaries from UAS Imagery Using
PBIA and GEOBIA with Random Forest Classification,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link
2008
BibRef
Liu, J.[Jin],
Zheng, H.[Haokun],
EFN: Field-Based Object Detection for Aerial Images,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Chang, L.[Lena],
Chen, Y.T.[Yi-Ting],
Wang, J.H.[Jung-Hua],
Chang, Y.L.[Yang-Lang],
Rice-Field Mapping with Sentinel-1A SAR Time-Series Data,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Gilcher, M.[Mario],
Udelhoven, T.[Thomas],
Field Geometry and the Spatial and Temporal Generalization of Crop
Classification Algorithms: A Randomized Approach to Compare Pixel
Based and Convolution Based Methods,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Taravat, A.[Alireza],
Wagner, M.P.[Matthias P.],
Bonifacio, R.[Rogerio],
Petit, D.[David],
Advanced Fully Convolutional Networks for Agricultural Field Boundary
Detection,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Waldner, F.[François],
Diakogiannis, F.I.[Foivos I.],
Batchelor, K.[Kathryn],
Ciccotosto-Camp, M.[Michael],
Cooper-Williams, E.[Elizabeth],
Herrmann, C.[Chris],
Mata, G.[Gonzalo],
Toovey, A.[Andrew],
Detect, Consolidate, Delineate: Scalable Mapping of Field Boundaries
Using Satellite Images,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Wen, C.Y.[Cai-Yun],
Lu, M.[Miao],
Bi, Y.[Ying],
Zhang, S.N.[Sheng-Nan],
Xue, B.[Bing],
Zhang, M.J.[Meng-Jie],
Zhou, Q.B.[Qing-Bo],
Wu, W.B.[Wen-Bin],
An Object-Based Genetic Programming Approach for Cropland Field
Extraction,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
See also New Genetic Programming-Based Approach to Object Detection in Mussel Farm Images, A.
BibRef
Li, T.[Ting],
Johansen, K.[Kasper],
McCabe, M.F.[Matthew F.],
A machine learning approach for identifying and delineating
agricultural fields and their multi-temporal dynamics using three
decades of Landsat data,
PandRS(186), 2022, pp. 83-101.
Elsevier DOI
2203
Center-pivot field, Delineation, DBSCAN,
Convolution neural networks, Spectral clustering, Random forest
BibRef
Lu, R.[Rui],
Wang, N.[Nan],
Zhang, Y.B.[Yan-Bin],
Lin, Y.N.[Ye-Neng],
Wu, W.Q.[Wen-Qiang],
Shi, Z.[Zhou],
Extraction of Agricultural Fields via DASFNet with Dual Attention
Mechanism and Multi-scale Feature Fusion in South Xinjiang, China,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Zhang, Z.Q.[Zhi-Qi],
Lu, W.[Wen],
Cao, J.S.[Jin-Shan],
Xie, G.Q.[Guang-Qi],
MKANet: An Efficient Network with Sobel Boundary Loss for Land-Cover
Classification of Satellite Remote Sensing Imagery,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Ge, J.[Ji],
Zhang, H.[Hong],
Xu, L.[Lu],
Sun, C.L.[Chun-Ling],
Duan, H.X.[Hao-Xuan],
Guo, Z.H.[Zi-Huan],
Wang, C.[Chao],
A Physically Interpretable Rice Field Extraction Model for PolSAR
Imagery,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Liu, X.C.[Xiang-Chen],
Shao, Y.[Yun],
Li, K.[Kun],
Liu, Z.[Zhiqu],
Liu, L.[Long],
Xiao, X.[Xiulai],
Backscattering Statistics of Indoor Full-Polarization Scatterometric
and Synthetic Aperture Radar Measurements of a Rice Field,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Xu, Y.[Yang],
Xue, X.Y.[Xin-Yu],
Sun, Z.[Zhu],
Gu, W.[Wei],
Cui, L.F.[Long-Fei],
Jin, Y.[Yongkui],
Lan, Y.[Yubin],
Deriving Agricultural Field Boundaries for Crop Management from
Satellite Images Using Semantic Feature Pyramid Network,
RS(15), No. 11, 2023, pp. 2937.
DOI Link
2306
BibRef
Li, M.M.[Meng-Meng],
Long, J.[Jiang],
Stein, A.[Alfred],
Wang, X.Q.[Xiao-Qin],
Using a semantic edge-aware multi-task neural network to delineate
agricultural parcels from remote sensing images,
PandRS(200), 2023, pp. 24-40.
Elsevier DOI
2306
Agricultural parcel delineation, SEANet,
Multi-task neural networks, Semantic edge-aware detection,
Uncertainty weighted loss
BibRef
Chen, L.[Long],
Song, W.L.[Wen-Long],
Sun, T.[Tao],
Lu, Y.Z.[Yi-Zhu],
Jiang, W.[Wei],
Liu, J.[Jun],
Liu, H.J.[Hong-Jie],
Feng, T.S.[Tian-Shi],
Gui, R.J.[Rong-Jie],
Abbas, H.[Haider],
Meng, L.W.[Ling-Wei],
Lin, S.J.[Sheng-Jie],
He, Q.[Qian],
Field Patch Extraction Based on High-Resolution Imaging and U2-Net++
Convolutional Neural Networks,
RS(15), No. 20, 2023, pp. 4900.
DOI Link
2310
BibRef
Awad, B.[Bahaa],
Erer, I.[Isin],
FAUNet: Frequency Attention U-Net for Parcel Boundary Delineation in
Satellite Images,
RS(15), No. 21, 2023, pp. 5123.
DOI Link
2311
BibRef
Cai, Z.W.[Zhi-Wen],
Hu, Q.[Qiong],
Zhang, X.Y.[Xin-Yu],
Yang, J.Y.[Jing-Ya],
Wei, H.D.[Hao-Dong],
Wang, J.[Jiayue],
Zeng, Y.[Yelu],
Yin, G.F.[Gao-Fei],
Li, W.J.[Wen-Juan],
You, L.Z.[Liang-Zhi],
Xu, B.D.[Bao-Dong],
Shi, Z.H.[Zhi-Hua],
Improving agricultural field parcel delineation with a dual branch
spatiotemporal fusion network by integrating multimodal satellite
data,
PandRS(205), 2023, pp. 34-49.
Elsevier DOI
2311
Agricultural field parcel delineation, Deep learning,
Multimodal satellite data, Spatiotemporal fusion, Spatial transferability
BibRef
Liu, L.[Lei],
Li, G.[Guorun],
Du, Y.F.[Yue-Feng],
Li, X.Y.[Xiao-Yu],
Wu, X.[Xiuheng],
Qiao, Z.[Zhi],
Wang, T.Y.[Tian-Yi],
CS-net: Conv-simpleformer network for agricultural image segmentation,
PR(147), 2024, pp. 110140.
Elsevier DOI
2312
Semantic segmentation, CS-net, Agricultural image, CNNs,
Transformers, Simple-attention
BibRef
Qi, L.[Liang],
Zuo, D.F.[Dan-Feng],
Wang, Y.R.[Yi-Rong],
Tao, Y.[Ye],
Tang, R.[Runkang],
Shi, J.[Jiayu],
Gong, J.J.[Jia-Jun],
Li, B.[Bangyu],
Convolutional Neural Network-Based Method for Agriculture Plot
Segmentation in Remote Sensing Images,
RS(16), No. 2, 2024, pp. 346.
DOI Link
2402
BibRef
Nair, S.[Shruti],
Sharifzadeh, S.[Sara],
Palade, V.[Vasile],
Farmland Segmentation in Landsat 8 Satellite Images Using Deep
Learning and Conditional Generative Adversarial Networks,
RS(16), No. 5, 2024, pp. 823.
DOI Link
2403
BibRef
Chen, G.[Gang],
Hammelman, C.[Colleen],
Anantsuksomsri, S.[Sutee],
Tontisirin, N.[Nij],
Todd, A.R.[Amelia R.],
Hicks, W.W.[William W.],
Robinson, H.M.[Harris M.],
Calloway, M.G.[Miles G.],
Bell, G.M.[Grace M.],
Kinsey, J.E.[John E.],
Fine-Scale (10 m) Dynamics of Smallholder Farming through COVID-19 in
Eastern Thailand,
RS(16), No. 6, 2024, pp. 1035.
DOI Link
2403
BibRef
Wakabayashi, H.,
Motohashi, K.,
Kitagami, T.,
Tjahjono, B.,
Dewayani, S.,
Hidayat, D.,
Hongo, C.,
Flooded Area Extraction of Rice Paddy Field in Indonesia Using
Sentinel-1 Sar Data,
Environmental19(73-76).
DOI Link
1904
BibRef
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Smallholder Analysis .