Advanced search
Start date

Automatic segmentation of landslide scars in remote sensing imagery with deep learning

Grant number: 19/17555-1
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): December 01, 2019
Effective date (End): November 30, 2021
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Geology
Principal Investigator:Carlos Henrique Grohmann de Carvalho
Grantee:Lucas Pedrosa Soares
Host Institution: Instituto de Geociências (IGC). Universidade de São Paulo (USP). São Paulo , SP, Brazil


The global number of landslides cases has increased due to greater urbanization and land use, as well as higher frequency of extreme climatic events. Since these events have strong social and economic impacts on Brazil and worldwide, they are considered one obstacle for the sustainable development according to the United Nations (UN). Studies conducted to date aim to find landslide prone areas, nevertheless, few studies address automatic methodologies for systematic monitoring of these areas. Thus, the main objective of this study is to use deep learning with convolution neural networks (CNN) in order to automate the segmentation of landslide scars on remote sensing imagery. The automation of this process is relevant to reduce the social and economic impacts since it allows constant monitoring of landslide susceptible areas, moreover, it is important for the validation of predictive models. The methodology that will be used, aiming to achieve the expected results, addresses aspects related to the database, architecture, hyperparameters, validation and result metrics of the model. The CNN will be constructed with the Python libraries: Keras and TensorFlow. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
Articles published in other media outlets (0 total):
More itemsLess items

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
XU, GUOSEN; WANG, YI; WANG, LIZHE; SOARES, LUCAS PEDROSA; GROHMANN, CARLOS H.. Feature-Based Constraint Deep CNN Method for Mapping Rainfall-Induced Landslides in Remote Regions With Mountainous Terrain: An Application to Brazil. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, v. 15, p. 16-pg., . (19/17555-1, 16/06628-0)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
SOARES, Lucas Pedrosa. Segmentação automática de cicatrizes de deslizamento de terra em imagens de sensores remotos utilizando aprendizagem profunda de máquina (Deep Learning). 2022. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Geociências (IG/BT) São Paulo.

Please report errors in scientific publications list using this form.