AI4LUC: deep learning and automated mask labelling to support land use and land cover mapping in the <i>Cerrado</i> biome-Reference-Cited by-同舟云学术

AI4LUC: deep learning and automated mask labelling to support land use and land cover mapping in the Cerrado biome

Published:2024-08 Issue:8 Volume:15 Page:850-860
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

de Souza Miranda Mateus¹^ORCID,de Santiago Júnior Valdivino Alexandre¹^ORCID,Körting Thales Sehn¹^ORCID,dos Santos Monteiro Erison Carlos¹²^ORCID,Queiroz da Silva Jadson¹²^ORCID

Affiliation:

1. Laboratório de Inteligência Artificial para Aplicações Aeroespaciais e Ambientais (LIAREA), Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, Brazil

2. Instituto Nacional de Pesquisas Espaciais (INPE), Deutsche Gesellschaft für Internationale Zusammenarbeit(GIZ), Brasília, Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2024.2382845

Reference11 articles.

1. Incorporating DeepLabv3+ and object-based image analysis for semantic segmentation of very high resolution remote sensing images

2. Pattern Recognition and Remote Sensing techniques applied to Land Use and Land Cover mapping in the Brazilian Savannah

3. INPE. 2019. “Metodologia Utilizada nos Projetos PRODES e DETER.” Programa de Monitoramento da Amazônia e Demais Biomas. CoordenaÃ§ão Geral de ObservaÃ§ão da Terra Instituto Nacional de Pesquisas Espaciais. http://www.obt.inpe.br/OBT/assuntos/programas/amazonia/prodes.

4. Deep learning in remote sensing applications: A meta-analysis and review

5. Deep Convolutional Neural Network for Classifying Satellite Images with Heterogeneous Spatial Resolutions