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Academic Journal

Multi-Temporal Data for Land Use Change Analysis Using a Machine Learning Approach (Google Earth Engine).

Authors : Aji, A.¹ ; Husna, V. N.¹; Purnama, S. M.²

Source: International Journal of Geoinformatics. Apr2024, Vol. 20 Issue 4, p19-28. 10p.

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Academic Journal

A mosaic method for multi-temporal data registration by using convolutional neural networks for forestry remote sensing applications.

Authors : Zeng, Yi¹ (AUTHOR); Ning, Zihan¹ (AUTHOR); Liu, Peng² (AUTHOR)

Source: Computing. Mar2020, Vol. 102 Issue 3, p795-811. 17p.

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Academic Journal

Research on A Special Hyper-Pixel for SAR Radiometric Monitoring.

Authors : Shangguan, Songtao^1,2,3 (AUTHOR) ; Qiu, Xiaolan^1,2,3 (AUTHOR) ; Fu, Kun^1,2,3 (AUTHOR)

Source: Remote Sensing. Apr2023, Vol. 15 Issue 8, p2175. 18p.

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Academic Journal

Synergistic Use of Multi-Temporal Radar and Optical Remote Sensing for Soil Organic Carbon Prediction.

Authors : Dahhani, Sara¹ (AUTHOR) ; Raji, Mohamed¹ (AUTHOR); Bouslihim, Yassine² (AUTHOR)

Source: Remote Sensing. Jun2024, Vol. 16 Issue 11, p1871. 18p.

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Academic Journal

Farm-Scale Crop Yield Prediction from Multi-Temporal Data Using Deep Hybrid Neural Networks.

Authors : Engen, Martin¹ (AUTHOR) ; Sandø, Erik¹ (AUTHOR) ; Sjølander, Benjamin Lucas Oscar¹ (AUTHOR)

Source: Agronomy. Dec2021, Vol. 11 Issue 12, p2576-2576. 1p.

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Academic Journal

Effect of Using Different Amounts of Multi-Temporal Data on the Accuracy: A Case of Land Cover Mapping of Parts of Africa Using FengYun-3C Data.

Authors : Adugna, Tesfaye^1,2,3 (AUTHOR) ; Xu, Wenbo^1,2 (AUTHOR); Fan, Jinlong⁴ (AUTHOR)

Source: Remote Sensing. Nov2021, Vol. 13 Issue 21, p4461. 1p.

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Academic Journal

Mapping Rice Paddy Based on Machine Learning with Sentinel-2 Multi-Temporal Data: Model Comparison and Transferability.

Authors : Zhang, Weichun¹ (AUTHOR) ; Liu, Hongbin¹ (AUTHOR) ; Wu, Wei² (AUTHOR)

Source: Remote Sensing. 5/15/2020, Vol. 12 Issue 10, p1620-1620. 1p.

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Academic Journal

Dominant Tree Species Mapping Using Machine Learning Based on Multi-Temporal and Multi-Source Data.

Authors : Guo, Heyi^1,2 (AUTHOR) ; Boonprong, Sornkitja³ (AUTHOR) ; Wang, Shaohua¹ (AUTHOR)

Source: Remote Sensing. Dec2024, Vol. 16 Issue 24, p4674. 19p.

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Academic Journal

On-Orbit Geometric Calibration and Accuracy Validation of the Jilin1-KF01B Wide-Field Camera.

Authors : Wu, Hongyu^1,2,3 (AUTHOR) ; Chen, Guanzhou⁴ (AUTHOR) ; Bai, Yang³ (AUTHOR)

Source: Remote Sensing. Oct2024, Vol. 16 Issue 20, p3893. 32p.

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Academic Journal

A Framework for Subregion Ensemble Learning Mapping of Land Use/Land Cover at the Watershed Scale.

Authors : Li, Runxiang^1,2,3 (AUTHOR) ; Gao, Xiaohong^1,2,3 (AUTHOR) ; Shi, Feifei^1,2,3 (AUTHOR)

Source: Remote Sensing. Oct2024, Vol. 16 Issue 20, p3855. 24p.

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فلترة النتائج

Multi-Temporal Data for Land Use Change Analysis Using a Machine Learning Approach (Google Earth Engine).

A mosaic method for multi-temporal data registration by using convolutional neural networks for forestry remote sensing applications.

Research on A Special Hyper-Pixel for SAR Radiometric Monitoring.

Synergistic Use of Multi-Temporal Radar and Optical Remote Sensing for Soil Organic Carbon Prediction.

Farm-Scale Crop Yield Prediction from Multi-Temporal Data Using Deep Hybrid Neural Networks.

Effect of Using Different Amounts of Multi-Temporal Data on the Accuracy: A Case of Land Cover Mapping of Parts of Africa Using FengYun-3C Data.

Mapping Rice Paddy Based on Machine Learning with Sentinel-2 Multi-Temporal Data: Model Comparison and Transferability.

Dominant Tree Species Mapping Using Machine Learning Based on Multi-Temporal and Multi-Source Data.

On-Orbit Geometric Calibration and Accuracy Validation of the Jilin1-KF01B Wide-Field Camera.

A Framework for Subregion Ensemble Learning Mapping of Land Use/Land Cover at the Watershed Scale.

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