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Time Series of Land Cover Mappings Can Allow the Evaluation of Grassland Protection Actions Estimated by Sustainable Development Goal 15.1.2 Indicator: The Case of Murgia Alta Protected Area

Academic Article
Publication Date:
2023
abstract:
Protected areas, or national parks, are established to preserve natural ecosystems; their effectiveness on the territory needs to be evaluated. We propose considering a time series of the SDG 15.1.2 indicator, "Proportion of important sites for terrestrial and freshwater biodiversity that are covered by protected areas, by ecosystem type", to quantify the presence over time of grassland ecosystem in Murgia Alta (southern Italy), within the Natura 2000 and national park boundaries. Time series of remote sensing imagery, freely available, were considered for extracting, by Support Vector Machine classifiers, a time series of grassland cover mappings from 1990 to 2021. This latter was, then, used for computing a time series of the SDG 15.1.2 indicator. A high reduction (about 15,000 ha) of grassland presence from 1990 to 2004, the foundation years of the national park, followed by the increasing stability up to nowadays, was evaluated. Furthermore, grassland presence was evaluated in a 5-km buffer area, surrounding Natura 2000 boundary, revealing a continuous loss from 1990 up to now (about 500 ha) in the absence of protection actions. This study represents the first long-term analysis for the grassland ecosystem in Murgia Alta and the first effort to analyze a time series of the SDG 15.1.2 indicator. The findings can provide inputs to governments in monitoring the effectiveness of protection actions.
Iris type:
01.01 Articolo in rivista
Keywords:
SDG 15.1.2; land cover time series; grassland ecosystem; spatio-temporal trend; protected area
List of contributors:
Aquilino, Mariella; Labadessa, Rocco; Adamo, Maria; Tarantino, Cristina
Authors of the University:
ADAMO MARIA
LABADESSA ROCCO
TARANTINO CRISTINA
Handle:
https://iris.cnr.it/handle/20.500.14243/445171
Published in:
REMOTE SENSING (BASEL)
Journal
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URL

https://doi.org/10.3390/rs15020505
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