التفاصيل البيبلوغرافية
| العنوان: |
AI4LUC: deep learning and automated mask labelling to support land use and land cover mapping in the Cerrado biome. |
| المؤلفون: |
de Souza Miranda, Mateus, de Santiago Júnior, Valdivino Alexandre, Körting, Thales Sehn, dos Santos Monteiro, Erison Carlos, Queiroz da Silva, Jadson |
| المصدر: |
Remote Sensing Letters; Aug2024, Vol. 15 Issue 8, p850-860, 11p |
| مصطلحات موضوعية: |
CONVOLUTIONAL neural networks, LAND use mapping, ZONING, ARTIFICIAL intelligence, LAND cover |
| مستخلص: |
Land use and land cover (LULC) mapping in the Brazilian Cerrado is challenging due to its vastness, seasonal vegetation changes, and spectral class confusion. Artificial intelligence, particularly deep learning (DL), offers promising solutions through semantic segmentation of Cerrado images, though it traditionally requires manual image annotation. This paper introduces the AI4LUC (Artificial Intelligence for Land Use and Land Cover Classification) method, leveraging DL and automated mask labeling to address LULC in the Brazilian Cerrado. AI4LUC includes pre-processing modules and the Smart Mask©Labelling (SML) module, which combines morphological operations with the CerraNetv3 deep convolutional neural network to automatically generate training masks for DL models like U-Net and DeepLabv3+. Additionally, we present the Cerrado Dataset (CerraData-v3), a high-resolution image dataset with 80,000 labeled samples. Our experiments show the SML module achieved an F1-score of 0.6647 and mIoU of 0.5068, demonstrating significant potential for automated semantic segmentation in this large biome. Furthermore, DeepLabv3+ outperformed U-Net by 69.86%. Source code and dataset: . [ABSTRACT FROM AUTHOR] |
|
Copyright of Remote Sensing Letters is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
PDF full text from Publisher 
Full Text Finder