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Monitoring land degradation at national level using satellite Earth Observation time-series data to support SDG15 – exploring the potential of data cube

Authors :
Gregory Giuliani
Bruno Chatenoux
Antonio Benvenuti
Pierre Lacroix
Mattia Santoro
Paolo Mazzetti
Source :
Big Earth Data, Vol 4, Iss 1, Pp 3-22 (2020)
Publication Year :
2020
Publisher :
Taylor & Francis Group, 2020.

Abstract

Avoiding, reducing, and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth. To halt and reverse the current trends in land degradation, there is an immediate need to enhance national capacities to undertake quantitative assessments and mapping of their degraded lands, as required by the Sustainable Development Goals (SDGs), in particular, the SDG indicator 15.3.1 (“proportion of land that is degraded over total land area”). Earth Observations (EO) can play an important role both for generating this indicator as well as complementing or enhancing national official data sources. Implementations like Trends.Earth to monitor land degradation in accordance with the SDG15.3.1 rely on default datasets of coarse spatial resolution provided by MODIS or AVHRR. Consequently, there is a need to develop methodologies to benefit from medium to high-resolution satellite EO data (e.g. Landsat or Sentinels). In response to this issue, this paper presents an initial overview of an innovative approach to monitor land degradation at the national scale in compliance with the SDG15.3.1 indicator using Landsat observations using a data cube but further work is required to improve the calculation of the three sub-indicators.

Details

Language :
English
ISSN :
20964471 and 25745417
Volume :
4
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Big Earth Data
Publication Type :
Academic Journal
Accession number :
edsdoj.34b73a3632d94e31bbeb42190c795ce3
Document Type :
article
Full Text :
https://doi.org/10.1080/20964471.2020.1711633