000025540 001__ 25540
000025540 005__ 20220518110448.0
000025540 0410_ $$aeng
000025540 100__ $$aGiuliania, Gregory et al.
000025540 245__ $$aKnowledge generation using satellite earth observations to support sustainable development goals (SDG): A use case on Land degradation
000025540 260__ $$c2020
000025540 269__ $$cimprint
000025540 520__ $$aLand degradation is a critical issue globally requiring immediate actions for protecting biodiversity and associated services provided by ecosystems that are supporting human quality of life. The latest Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services Landmark Assessment Report highlighted that human activities are considerably degrading land and threating the well-being of approximately 3.2 billion people. In order to reduce and ideally reverse this prevailing situation, national capacities should be strengthened to enable effective assessments and mapping of their degraded lands as recommended by the United Nations Sustainable Development Goals (SDGs). The indicator 15.3.1 (“proportion of land that is degraded over total land area”) requires regular data production by countries to inform and assess it through space and time. Earth Observations (EO) can play an important role both for generating the indicator in countries where it is missing, as well complementing or enhancing national official data sources. In response to this issue, this paper presents an innovative, scalable and flexible approach to monitor land degradation at various scales (e.g., national, regional, global) using various components of the Global Earth Observation System of Systems (GEOSS) platform to leverage EO resources for informing SDG 15.3.1. The proposed approach follows the Data-Information-Knowledge pattern using the Trends.Earth model (http:// trends.earth) and various data sources to generate the indicator. It also implements additional components for model execution and orchestration, knowledge management, and visualization. The proposed approach has been successfully applied at global, regional and national scales and advances the vision of (1) establishing data analytics platforms that can potentially support countries to discover, access and use the necessary datasets to assess land degradation; and (2) developing new capacities to effectively and efficiently use EO-based resources.
000025540 6531_ $$aEarth observations$$aKnowledge$$aSustainable development goal$$aLand degradation
000025540 773__ $$aInt J Appl Earth Obs Geoinformation$$gVol. 88, 12 p.
000025540 8564_ $$uhttps://invenio.unidep.org/invenio//record/25540/files/1-s2.0-S0303243419311869-main.pdf
000025540 8564_ $$uhttps://invenio.unidep.org/invenio//record/25540/files/1-s2.0-S0303243419311869-main.gif?subformat=icon$$xicon
000025540 8564_ $$uhttps://invenio.unidep.org/invenio//record/25540/files/1-s2.0-S0303243419311869-main.gif?subformat=icon-700$$xicon-700
000025540 8564_ $$uhttps://invenio.unidep.org/invenio//record/25540/files/1-s2.0-S0303243419311869-main.pdf?subformat=pdfa$$xpdfa
000025540 980__ $$aEBOOK$$aARTICLE