scholarly journals EFFECTS OF GEOSPATIAL DATA SOURCES ON THE IDENTIFICATION AND CHARACTERIZATION OF BURNT AREAS IN PORTUGAL

2021 ◽  
Vol V-4-2021 ◽  
pp. 49-54
Author(s):  
C. C. Fonte ◽  
J. Patriarca ◽  
D. Duarte
Keyword(s):  
Land Cover ◽  
Data Sources ◽  
Land Use Land Cover ◽  
Burnt Area ◽  
Corine Land Cover ◽  
Levels Of Detail ◽  
Large Level ◽  
European Forest ◽  
Burnt Areas

Abstract. The work presented in this paper compares the burnt areas in continental Portugal in 2017 and 2018 mapped by three initiatives, namely the Portuguese Institute of Nature and Forests Conservation (ICNF), the Corine Land Cover (CLC) inventory of the Copernicus programme and the European Forest Fire Information System (EFFIS). Then, the Land Use Land Cover (LULC) classes affected by the 2017 burnt areas mapped by ICNF are analysed considering CLC 2018 and the 2018 LULC map produced by the Portuguese National Mapping Agency (Direção Geral do Território) – “Carta de Ocupação do Solo” (COS 2018). To enable a comparison between the classes of both LULC products, a nomenclature was selected and both CLC 2018 and COS 2018 were mapped into the chosen classes. The comparison of the burnt area’s extent showed that there are large differences in both area and levels of detail between the analysed data sources. The results regarding the LULC classes affected by the 2017 fires mapped by ICNF show large differences in terms of burnt area in each class as well as the proportion of the burnt areas associated to the classes. This analysis shows that very different results may be reached if different products are used, and therefore a large level of uncertainty is associated with the conclusions achieved with these products.

Wildfires in Europe: the role of land use/land cover changes

2020 ◽  
Author(s):  
Joana Parente ◽  
Marj Tonini ◽  
Zoi Stamou ◽  
Nikos Koutsias ◽  
Mário Pereira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Methodological Approach ◽  
Environmental Drivers ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Climate Conditions ◽  
European Forest ◽  
Burnt Areas ◽  
Land Cover Maps

<p>Wildfire (WF) has the potential to occur in more than 30% of the worldwide land area, in many different biomes/ecosystems/land cover types, where it is controlled mainly by the environmental drivers such as vegetation structure, meteorological/climate conditions, and human activities. On the other hand, land use/land cover changes (LULCC) are one of the most important global alterations of the environment. In the last decades, Europe registered significant-high fire incidence and LULCC between all land cover classes. In the 2000 – 2018 period, according to the European Forest Fire Information System (EFFIS), Europe was affected by 18 882 WFs which burned 6 887,713 ha. According to CORINE land cover maps, the observed LULCC area in Europe for the same period was of 23,510,075 ha. Recent studies suggested that regional LULCC in the last decades promoted the occurrence of more and larger WF, in some European regions. Therefore, the main objectives of this study were to assessed the LULCC in and around burnt areas (BAs) during the 2000–2018 period. This study benefits from the use of reliable CORINE inventories and EFFIS BA product. A geospatial methodological approach was implemented to identify and quantify LULCC and to characterize the relationship between LULCC and WFs in Europe. This research provides a detailed characterization of the LULCC in and around BAs in Europe, and attempts to contribute to a better management of the landscape, urbanization and wildland-urban interface to reduce related losses in the natural and human system including losses of life, property and assets.</p>

scholarly journals Cropland Abandonment in Slovakia: Analysis and Comparison of Different Data Sources

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Juraj Lieskovský ◽  
Dana Lieskovská
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Data ◽  
Data Sources ◽  
Communist Regime ◽  
Corine Land Cover ◽  
Cropland Area ◽  
Cropland Abandonment ◽  
Multi Temporal

This study compares different nationwide multi-temporal spatial data sources and analyzes the cropland area, cropland abandonment rates and transformation of cropland to other land cover/land use categories in Slovakia. Four multi-temporal land cover/land use data sources were used: The Historic Land Dynamics Assessment (HILDA), the Carpathian Historical Land Use Dataset (CHLUD), CORINE Land Cover (CLC) data and Landsat images classification. We hypothesized that because of the different spatial, temporal and thematic resolution of the datasets, there would be differences in the resulting cropland abandonment rates. We validated the datasets, compared the differences, interpreted the results and combined the information from the different datasets to form an overall picture of long-term cropland abandonment in Slovakia. The cropland area increased until the Second World War, but then decreased after transition to the communist regime and sharply declined following the 1989 transition to an open market economy. A total of 49% of cropland area has been transformed to grassland, 34% to forest and 15% to urban areas. The Historical Carpathian dataset is the more reliable long-term dataset, and it records 19.65 km2/year average cropland abandonment for 1836–1937, 154.44 km2/year for 1938–1955 and 140.21 km2/year for 1956–2012. In comparison, the Landsat, as a recent data source, records 142.02 km2/year abandonment for 1985–2000 and 89.42 km2/year for 2000–2010. These rates, however, would be higher if the dataset contained urbanisation data and more precise information on afforestation. The CORINE Land Cover reflects changes larger than 5 ha, and therefore the reported cropland abandonment rates are lower.

scholarly journals Environmental Aftermath of the 2019 Stromboli Eruption

2020 ◽  
Vol 12 (6) ◽  
pp. 994 ◽  
Author(s):  
Agnese Turchi ◽  
Federico Di Traglia ◽  
Tania Luti ◽  
Davide Olori ◽  
Iacopo Zetti ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landscape Patterns ◽  
Corine Land Cover ◽  
Field Surveys ◽  
Multi Temporal ◽  
Olive Trees ◽  
Normalized Burn Ratio ◽  
Burnt Areas ◽  
Vegetation Loss

This study focuses on the July-August 2019 eruption-induced wildfires at the Stromboli island (Italy). The analysis of land cover (LC) and land use (LU) changes has been crucial to describe the environmental impacts concerning endemic vegetation loss, damages to agricultural heritage, and transformations to landscape patterns. Moreover, a survey was useful to collect eyewitness accounts aimed to define the LU and to obtain detailed information about eruption-induced damages. Detection of burnt areas was based on PLÉIADES-1 and Sentinel-2 satellite imagery, and field surveys. Normalized Burn Ratio (NBR) and Relativized Burn Ratio (RBR) allowed mapping areas impacted by fires. LC and LU classification involved the detection of new classes, following the environmental units of landscape, being the result of the intersection between CORINE Land Cover project (CLC) and local landscape patterns. The results of multi-temporal comparison show that fire-damaged areas amount to 39% of the total area of the island, mainly affecting agricultural and semi-natural vegetated areas, being composed by endemic Aeolian species and abandoned olive trees that were cultivated by exploiting terraces up to high altitudes. LC and LU analysis has shown the strong correlation between land use management, wildfire severity, and eruption-induced damages on the island.

scholarly journals Is there Urban Landscape in Metropolitan Areas? An Unobvious Answer Based on Corine Land Cover Analyses

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 51
Author(s):  
Urszula Myga-Piątek ◽  
Anna Żemła-Siesicka ◽  
Katarzyna Pukowiec-Kurda ◽  
Michał Sobala ◽  
Jerzy Nita
Keyword(s):  
Land Cover ◽  
Metropolitan Area ◽  
Urban Areas ◽  
Spatial Organization ◽  
Urban Landscape ◽  
Metropolitan Areas ◽  
Urban Landscapes ◽  
Corine Land Cover ◽  
Levels Of Detail ◽  
Landscape Factors

The recent increase in urban areas has stimulated landscape urbanization. One of the ways to study this process is an analysis based on the structure of land cover. The aim of this paper is to assess the intensity of the urban landscape on the basis of the CORINE in the seven largest metropolitan areas in Poland and in the Ruhr Metropolis in Germany. To this end, an urban landscape intensity indicator (ULII) was used based on Corine Land Cover at three levels of detail: the metropolitan area, municipalities and hexagons. There are similarities in landscape structure in areas with similar origin (industrial function) and spatial organization (mono- and polycentric agglomerations). The landscape of the Upper Silesia-Zagłębie Metropolis differs from the landscape of other metropolitan areas in Poland and simultaneously shows similarities to the landscape of the Ruhr Metropolis. The results of the ULII also revealed a dependency: the dominance of rural and transitional landscapes in a majority of the study areas. Urban landscapes occur only in the central zones of the metropolitan areas. This proves that determining the range of a metropolitan area in terms of landscape factors is different from doing it with formal or legal ones.

scholarly journals Data Fusion and Accuracy Analysis of Multi-Source Land Use/Land Cover Datasets along Coastal Areas of the Maritime Silk Road

2019 ◽  
Vol 8 (12) ◽  
pp. 557 ◽  
Author(s):  
Wan Hou ◽  
Xiyong Hou
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Input Data ◽  
Coastal Areas ◽  
Kappa Coefficient ◽  
Silk Road ◽  
Data Sources ◽  
Land Use Land Cover ◽  
Fusion Data ◽  
Maritime Silk Road

High-precision land use/land cover classification mapping derived from remote sensing supplies essential datasets for scientific research on environmental assessment, climate change simulation, geographic condition monitoring, and environmental management at global and regional scales. It is an important issue in the study of earth system science, and the coastal area is a hot spot region in this field. In this paper, the coastal areas of the Maritime Silk Road were used as the research object and a fusion method based on agreement analysis and fuzzy-set theory was adopted to achieve the fusion of three land use/land cover datasets: MCD12Q1-2010, CCI-LC2010, and GlobeLand30-2010. The accuracy of the fusion results was analyzed using an error matrix, spatial confusion, average overall consistency, and average type-specific consistency. The main findings were as follows. (1) After the establishment of reference data based on Google Earth, both the producer accuracy and user accuracy of the fusion data were improved when compared with those of the three input data sources, and the fusion data had the highest overall accuracy and Kappa coefficient, with values of 90.37% and 0.8617, respectively. (2) Various input data sources differed in terms of the correctly classified contributions and misclassified influences of different land use/land cover types in the fusion data; furthermore, the overall accuracy and Kappa coefficient between the fusion data and any one of the input data sources were far higher than those between any two of the input data sources. (3) The average overall consistency of the fusion data was the highest at 89.29%, which was approximately 5% higher than that of the input data sources. (4) The average type-specific consistencies of cropland, forest, grassland, shrubland, wetland, artificial surfaces, bare land, and permanent snow and ice in the fusion data were the highest, with values of 69.95%, 74.41%, 21.24%, 34.22%, 97.62%, 51.83%, 84.39%, and 2.46%, respectively; compared with the input data sources, the average type-specific consistencies of the fusion data were 0.61–20.32% higher. This paper provides information and suggestions for the development and accuracy evaluation of future land use/land cover data in global and regional coastal areas.

scholarly journals Assessing Anthropogenic Dynamics in Megacities from the Characterization of Land Use/Land Cover Changes: The Bogotá Study Case

2020 ◽  
Vol 12 (9) ◽  
pp. 3884
Author(s):  
Claudia P. Romero ◽  
Alicia García-Arias ◽  
Celine Dondeynaz ◽  
Félix Francés
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Sustainable Management ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Study Case ◽  
The City

Usually, megacities expand without proper planning in a context of demographic growth and are increasingly dependent on the natural resources related to the occupied area. This is a major challenge for the sustainable management of these territories, justifying the need for a better knowledge of land use/land cover (LULC) distribution and characteristics to observe spatial anthropogenic dynamics. In this study, the Bogotá river basin and the Bogotá megacity were analyzed as a case study. The main objective of this work was to analyze the historical LULC dynamics from 1985 to 2014. Reliable forecasting scenarios were developed using the Land Change Modeler to support sustainable management and planning. Results show an expansion of the Bogotá megacity toward the Northeast and an increase of urban areas within the basin. These changes implied a loss of 58% of forest surface, a strategic ecosystem, from 1985 to 2014. This dynamic is expected to continue, with a 50% increase of urban areas between 2012 to 2050, thus the megacity and neighbor cities potentially become an “urban continuum”. A replacement of crop and pasture lands near the city is expected, even though Bogotá lands are among the best agricultural lands in the Andean region of Colombia.

scholarly journals A Comparative Review of Manifold Learning Techniques for Hyperspectral and Polarimetric SAR Image Fusion

2019 ◽  
Vol 11 (6) ◽  
pp. 681 ◽  
Author(s):  
Jingliang Hu ◽  
Danfeng Hong ◽  
Yuanyuan Wang ◽  
Xiao Zhu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Manifold Learning ◽  
Land Cover Classification ◽  
Data Availability ◽  
Data Sources ◽  
Land Use Land Cover ◽  
Data Alignment ◽  
Comparative Review ◽  
Manifold Alignment

In remote sensing, hyperspectral and polarimetric synthetic aperture radar (PolSAR) images are the two most versatile data sources for a wide range of applications such as land use land cover classification. However, the fusion of these two data sources receive less attention than many other, because of their scarce data availability, and relatively challenging fusion task caused by their distinct imaging geometries. Among the existing fusion methods, including manifold learning-based, kernel-based, ensemble-based, and matrix factorization, manifold learning is one of most celebrated techniques for the fusion of heterogeneous data. Therefore, this paper aims to promote the research in hyperspectral and PolSAR data fusion, by providing a comprehensive comparison between existing manifold learning-based fusion algorithms. We conducted experiments on 16 state-of-the-art manifold learning algorithms that embrace two important research questions in manifold learning-based fusion of hyperspectral and PolSAR data: (1) in which domain should the data be aligned—the data domain or the manifold domain; and (2) how to make use of existing labeled data when formulating a graph to represent a manifold—supervised, semi-supervised, or unsupervised. The performance of the algorithms were evaluated via multiple accuracy metrics of land use land cover classification over two data sets. Results show that the algorithms based on manifold alignment generally outperform those based on data alignment (data concatenation). Semi-supervised manifold alignment fusion algorithms performs the best among all. Experiments using multiple classifiers show that they outperform the benchmark data alignment-based algorithms by ca. 3% in terms of the overall classification accuracy.

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