23.2.2.2.1 Agricultural Field Extraction

Chapter Contents (Back)
Agricultural Field. Field Extraction. Region-Based.
See also Irrigation Monitoring, Irrigated Field Detection, Land Use Analysis.
See also Rice Crop Analysis, Production, Detection, Health, Change.
See also Smallholder Analysis.

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

Gundermann, N.[Niels], Lowe, W.[Welf], Fransson, J.E.S.[Johan E. S.], Olofsson, E.[Erika], Wehrenpfennig, A.[Andreas],
Object Identification in Land Parcels Using a Machine Learning Approach,
RS(16), No. 7, 2024, pp. 1143.
DOI Link 2404
BibRef


Seedz, R.F.R.[Rodrigo Fill Rangel], Gaivota, V.N.L.[Vítor Nascimento Lourenço], Seedz, L.V.O.[Lucas Volochen Oldoni], Seedz, A.F.C.B.[Ana Flavia Carrara Bonamigo], Gaivota, W.S.[Wallas Santos], Seedz, B.S.O.[Bruno Silva Oliveira], Seedz, M.N.B.[Mateus Neves Barreto],
A Unified Framework for Cropland Field Boundary Detection and Segmentation,
Pretrain24(636-644)
IEEE DOI 2404
Measurement, Image segmentation, Filtering, Pipelines, Neural networks BibRef

Meyer, L., Lemarchand, F., Sidiropoulos, P.,
A Deep Learning Architecture for Batch-mode Fully Automated Field Boundary Detection,
ISPRS20(B3:1009-1016).
DOI Link 2012
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 .


Last update:May 6, 2024 at 15:50:14