Mapping Caatinga vegetation using optical earth observation data – Opportunities and challenges

11Citations
Citations of this article
31Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The Caatinga biome represents around 10% of the Brazilian territory, and it has an estimated population of 28 million inhabitants. Its tree-shrub vegetation, adapted to semi-arid conditions, plays a fundamental role in maintaining the hydrological balance, feeding the energy matrix, and generating revenues for Brazil. Despite its importance, the Caatinga is one of the most neglected biomes by the scientific community. Therefore, this review article aims to present elements that contribute to updating the state-of-the-art on the use of optical Earth observation data in the conservation of Caatinga vegetation, based on the identification of mapping initiatives at different scales that consider the biome. To this end, this study carried out a systematic bibliographic review in which the main focus was the characterization of orbital sensors, image classification techniques, land-use and land-cover classes, validation strategies, and the time interval defined by each mapping initiative. This detailed overview allowed us to assess the degree of usability and reliability of the existing products. Therefore, this study looks to open up possibilities to fill current scientific gaps that need further investigation regarding the role of optical Earth observation data in mapping the vegetation of the Caatinga and subsidizing resources for new initiatives, restoration actions, and hence the improvement of public policies favoring the conservation and sustainable use of the Caatinga’s resources.

Cite

CITATION STYLE

APA

Ganem, K. A., Dutra, A. C., de Oliveira, M. T., de Freitas, R. M., Grecchi, R. C., da Silva Pinto Vieira, R. M., … Shimabukuro, Y. E. (2020). Mapping Caatinga vegetation using optical earth observation data – Opportunities and challenges. Revista Brasileira de Cartografia, 72, 829–854. https://doi.org/10.14393/RBCV72NESPECIAL50ANOS-56543

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free