Depicting impervious surfaces as a continuous variable: estimates and uncertainties using lnear spectral mixture analysis and random forest

• Grant number: 16/17698-9
• Support Opportunities: Regular Research Grants
• Start date: May 01, 2017
• End date: April 30, 2019
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Physical Geography
• Principal Investigator: Fernando Shinji Kawakubo
• Grantee: Fernando Shinji Kawakubo
• Host Institution: Faculdade de Filosofia, Letras e Ciências Humanas (FFLCH). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• City of the host institution: São Paulo
• Associated researchers: Reinaldo Paul Pérez Machado ; Rúbia Gomes Morato

Abstract

Impervious surfaces correspond to the areas where soil water infiltration is impeded due to the paving of roads, sidewalks, parking lots, buildings, roofs, etc. Impervious surface area (ISA) constitutes a major human alteration of the land surface, playing important impact on the deterioration of environmental quality. Because of its relevance, this project aims at mapping ISA in the metropolitan region of Sao Paulo by using remotely sensed dataset and image processing techniques. To this end, the methodology explores the synergism of the detailed land information obtained from the high-resolution aerial photography and the broad coverage of the multispectral images (in terms of area and frequency) generated by the OLI instrument, onboard the Landsat-8 satellite. Owing to the great diversity of material presented in the urban plot, which may hamper an accurate classification, this study treats ISA as a continuous variable of soil impermeability. We will test two techniques for estimating ISA: the linear spectral mixture model and the random forest algorithm. The first model is well known in remote sensing applications, but it is still little used for mapping impervious areas. Random forest, in turn, is the state-of-the-art of the predictive modelling, and study addressed to mapping water percolation at the intra-pixel scale is lacking. (AU)

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

KAWAKUBO, FERNANDO; MORATO, RUBIA; MARTINS, MARCOS; MATAVELI, GUILHERME; NEPOMUCENO, PABLO; MARTINES, MARCOS. Quantification and Analysis of Impervious Surface Area in the Metropolitan Region of SAo Paulo, Brazil. REMOTE SENSING, v. 11, n. 8, APR 2 2019. (16/17698-9)