European National Parks protect their surroundings but not everywhere: A study using land use/land cover dynamics derived from CORINE Land Cover data

Mingarro, Mario; Lobo, Jorge M.

doi:10.1016/j.landusepol.2022.106434

Cited by 17 publications

(6 citation statements)

References 53 publications

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“…CLC is the database of Copernicus Land-Monitoring Service (CLMS) and represents the European reference for land-cover and land-use inventory [46]. The CLC includes land-use/land-cover (LULC) status for European countries [47] and represents the spatial distribution of different types of physical coverage of the Earth's surface. For the sake of this work, the 44 standard thematic classes (CLC-2018) have been newly clusterized to match the L8 Ground Sample Distance (GSD) of the remote-sensed data used (90 × 90 m).…”

Section: Results Characterization By Using the Land Covermentioning

confidence: 99%

Satellite Time-Series Analysis for Thermal Anomaly Detection in the Naples Urban Area, Italy

Scalabrini,

Musacchio,

Silvestri

et al. 2024

Atmosphere

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Naples is the most densely populated Italian city (7744 inhabitants per km2). It is located in a particular geological context: the presence of Mt Vesuvius characterizes the eastern part, and the western part is characterized by the presence of the Phlegrean Fields, making Naples a high-geothermal-gradient region. This endogenous heat, combined with the anthropogenic heat due to intense urbanization, has defined Naples as an ideal location for Surface Urban Heat Island (SUHI) analysis. SUHI analysis was effectuated by acquiring the Land Surface Temperature (LST) over Naples municipality by processing Landsat 8 (L8) Thermal Infrared Sensor (TIRS) images in the 2013–2023 time series by employing Google Earth Engine (GEE). In GEE, two different approaches have been followed to analyze thermal images, starting from the Statistical Mono Window (SMW) algorithm, which computes the LST based on the brightness temperature (Tb), the emissivity value, and the atmospheric correction coefficients. The first one is used for the LST retrieval from daytime images; here, the emissivity component is derived using, firstly, the Normalized Difference Vegetation Index (NDVI) and then the Vegetation Cover Method (VCM), defining the Land Surface Emissivity (LSɛ), which considers solar radiation as the main source of energy. The second approach is used for the LST retrieval from nighttime images, where the emissivity is directly estimated from the Advance Spaceborne Thermal Emission Radiometer database (ASTER-GED), as, during nighttime without solar radiation, the main source of energy is the energy emitted by the Earth’s surface. From these two different algorithms, 123 usable daytime and nighttime LST images were downloaded from GEE and analyzed in Quantum GIS (QGIS). The results show that the SUHI is more concentrated in the eastern part, characterized by intense urbanization, as shown by the Corine Land Cover (CLC). At the same time, lower SUHI intensity is detected in the western part, defined by the Land Cover (LC) vegetated class. Also, in the analysis, we highlighted 40 spots (10 hotspots and 10 coldspots, both for daytime and nighttime collection) that present positive or negative temperature peaks for all the time series. Due to the huge amount of data, this work considered only the five representative spots that were most representative for SUHI analysis and determination of thermal anomalies in the urban environment.

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Section: Results Characterization By Using the Land Covermentioning

confidence: 99%

Satellite Time-Series Analysis for Thermal Anomaly Detection in the Naples Urban Area, Italy

Scalabrini,

Musacchio,

Silvestri

et al. 2024

Atmosphere

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“…This change can be attributed to the park's designation as a protected area, which restricted access to resources and allowed degraded fields to regenerate grasses and trees. Similarly [ 55 ], revealed that the designation of protected areas increases the naturalization of an area, thus providing beneficial effects on the surrounding environment. However [ 56 , 57 ], reported an expansion of bare lands in Baroiyadhala National Park, Bangladesh, and Awash National Park, Ethiopia, respectively, due to pronounced deforestation and degradation.…”

Section: Discussionmentioning

confidence: 99%

Impacts of Land use Land cover dynamics on Ecosystem services in maze national park and its environs, southwestern Ethiopia

Simeon,

Wana

2024

Heliyon

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“…PAs experience changes in Land Use and Land Cover (LULC), which diminish their resilience and affect the availability of ecosystem services, failing to meet their protection and conservation objectives. This scenario is observed in various PAs worldwide, including Brazil [7][8][9], Equador [10], the African continent [11,12], and the European continent [13,14].…”

Section: Introductionmentioning

confidence: 94%

A Framework Using Open-Source Software for Land Use Prediction and Climate Data Time Series Analysis in a Protected Area of Portugal: Alvão Natural Park

Folharini

Vieira

Bento‐Gonçalves

et al. 2023

Land

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Changes in land use and land cover (LULC) in protected areas can lead to an ecological imbalance in these territories. Temporal monitoring and predictive modeling are valuable tools for making decisions about conserving these areas and planning actions to reduce the pressure caused by activities such as agriculture. This study accordingly developed an LULC analysis framework based on open-source software (QGIS and R language) and predictive methodology using artificial neural networks in the Alvão Natural Park (PNA), a protected area in northern Portugal. The results show that in 2041, Agriculture and Open Space/Non-vegetation classes will evidence the greatest decrease, while Forest and Bushes will have expanded the most. Spatially, the areas to the west and northeast of the protected area will experience the most significant changes. The relationship of land use classes with data from the climate model HadGEM3-GC31-LL (CMIP6) utilizing scenarios RCP 4.5 and 8.5 demonstrates how through the period 2041–2060 there is a tendency for increased precipitation, which when combined with the dynamics of a retraction in classes such as agriculture, favors the advancement of natural classes such as bushes and forest; however, the subsequent climate data period (2061–2080) projects a decrease in precipitation volumes and an increase in the minimum and maximum temperatures, defining a new pattern with an extension of the period of drought and precipitation being concentrated in a short period of the year, which may result in a greater recurrence of extreme events, such as prolonged droughts that result in water shortages and fires.

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European National Parks protect their surroundings but not everywhere: A study using land use/land cover dynamics derived from CORINE Land Cover data

Cited by 17 publications

References 53 publications

Satellite Time-Series Analysis for Thermal Anomaly Detection in the Naples Urban Area, Italy

Satellite Time-Series Analysis for Thermal Anomaly Detection in the Naples Urban Area, Italy

Impacts of Land use Land cover dynamics on Ecosystem services in maze national park and its environs, southwestern Ethiopia

A Framework Using Open-Source Software for Land Use Prediction and Climate Data Time Series Analysis in a Protected Area of Portugal: Alvão Natural Park

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