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Monitoring Sustainable Development Goal Indicator 15.3.1 on Land Degradation Using SEPAL: Examples, Challenges and Prospects.

Authors :
Ghosh, Amit
Rambaud, Pierrick
Finegold, Yelena
Jonckheere, Inge
Martin-Ortega, Pablo
Jalal, Rashed
Adebayo, Adebowale Daniel
Alvarez, Ana
Borretti, Martin
Caela, Jose
Ghosh, Tuhin
Lindquist, Erik
Henry, Matieu
Source :
Land (2012); Jul2024, Vol. 13 Issue 7, p1027, 16p
Publication Year :
2024

Abstract

A third of the world's ecosystems are considered degraded, and there is an urgent need for protection and restoration to make the planet healthier. The Sustainable Development Goals (SDGs) target 15.3 aims at protecting and restoring the terrestrial ecosystem to achieve a land degradation-neutral world by 2030. Land restoration through inclusive and productive growth is indispensable to promote sustainable development by fostering climate change-resistant, poverty-alleviating, and environmentally protective economic growth. The SDG Indicator 15.3.1 is used to measure progress towards a land degradation-neutral world. Earth observation datasets are the primary data sources for deriving the three sub-indicators of indicator 15.3.1. It requires selecting, querying, and processing a substantial historical archive of data. To reduce the complexities, make the calculation user-friendly, and adapt it to in-country applications, a module on the FAO's SEPAL platform has been developed in compliance with the UNCCD Good Practice Guidance (GPG v2) to derive the necessary statistics and maps for monitoring and reporting land degradation. The module uses satellite data from Landsat, Sentinel 2, and MODIS sensors for primary productivity assessment, along with other datasets enabling high-resolution to large-scale assessment of land degradation. The use of an in-country land cover transition matrix along with in-country land cover data enables a more accurate assessment of land cover changes over time. Four different case studies from Bangladesh, Nigeria, Uruguay, and Angola are presented to highlight the prospect and challenges of monitoring land degradation using various datasets, including LCML-based national land cover legend and land cover data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2073445X
Volume :
13
Issue :
7
Database :
Complementary Index
Journal :
Land (2012)
Publication Type :
Academic Journal
Accession number :
178694109
Full Text :
https://doi.org/10.3390/land13071027