A large-scale VHR parcel dataset and a novel hierarchical semantic boundary-guided network for agricultural parcel delineation

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2025, Номер 221, С. 1 - 19

Опубликована: Фев. 3, 2025

Язык: Английский

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Unveiling grain production patterns in China (2005–2020) towards targeted sustainable intensification

Agricultural Systems, Год журнала: 2024, Номер 216, С. 103878 - 103878

Опубликована: Фев. 2, 2024

Язык: Английский

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Performance of GEDI data combined with Sentinel-2 images for automatic labelling of wall-to-wall corn mapping

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 127, С. 103643 - 103643

Опубликована: Янв. 9, 2024

Corn is the dominant crop planted in Northeast China, and its accurate timely mapping important for food security agricultural management China. However, absence of enough labels challenging corn a regional area using machine learning methods or deep methods. In this study, an efficient way automatic labelling areas by combining Global Ecosystem Dynamics Investigation (GEDI) data Sentinel-2 images proposed. We explore height vertical structure differences between other crops derived from GEDI features generate automatically referencing type products transferring models historical years. The trained networks points decision trees Random Forest (RF) classifier can be transferred to arbitrary target are combined perform wall-to-wall random forest algorithm GEDI-based labels. This approach used map China 2019 2022, classification results validated independent collected field campaigns 2023, published maps, official statistics. Our reveal that our proposed method achieves high accuracy robustness with average overall 0.91 testing spatial-type stratified sampling. correlation coefficient (R2) classified result statistical reach 0.96 0.98, respectively. These demonstrate potential label collection vegetation difference provide new on large-scale.

Язык: Английский

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STFCropNet: A Spatio-Temporal Fusion Network for Crop Classification in Multi-Resolution Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2025, Номер 18, С. 4736 - 4750

Опубликована: Янв. 1, 2025

Язык: Английский

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Artificial Intelligence Enhances Food Testing Process: A Comprehensive Review

Food Bioscience, Год журнала: 2025, Номер unknown, С. 106404 - 106404

Опубликована: Март 1, 2025

Язык: Английский

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Deep learning in cropland field identification: A review

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 222, С. 109042 - 109042

Опубликована: Май 17, 2024

Язык: Английский

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An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping

Remote Sensing of Environment, Год журнала: 2024, Номер 314, С. 114387 - 114387

Опубликована: Авг. 28, 2024

Язык: Английский

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Spatiotemporal expansion and methane emissions of rice-crayfish farming systems in Jianghan Plain, China

Agricultural and Forest Meteorology, Год журнала: 2024, Номер 347, С. 109908 - 109908

Опубликована: Янв. 29, 2024

Язык: Английский

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A refined edge-aware convolutional neural networks for agricultural parcel delineation

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 133, С. 104084 - 104084

Опубликована: Авг. 16, 2024

Язык: Английский

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Understanding the potentials of early-season crop type mapping by using Landsat-8, Sentinel-1/2, and GF-1/6 data

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 224, С. 109239 - 109239

Опубликована: Июль 15, 2024

Язык: Английский

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