Land Use Changes Monitoring with CORINE Land Cover Data

Cieślak, Iwona; Szuniewicz, Karol; Pawlewicz, Katarzyna; Czyża, Szymon

doi:10.1088/1757-899x/245/5/052049

Cited by 14 publications

(13 citation statements)

References 6 publications

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“…Land cover data are increasingly available from spatial databases and they can be rapidly processed with the use of GIS tools. These resources make analyses of urban sprawl less time consuming and they support analyses of a large number of cities, thus creating new sources of information for evaluating the extent and character of the evaluated phenomenon [56]. In this study, data for analysis were obtained from the CORINE Land Cover database.…”

Section: Methodsmentioning

confidence: 99%

The Use of the CORINE Land Cover (CLC) Database for Analyzing Urban Sprawl

2020

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Urban sprawl is generally defined as the urbanization of space adjacent to a city, which results from that city’s development. The discussed phenomenon involves land development, mainly agricultural land, in the proximity of cities, the development of infrastructure, and an increase in the number of residents who rely on urban services and commute to work in the city. Urban sprawl generates numerous problems which, in the broadest sense, result from the difficulty in identifying the boundaries of the central urban unit and the participation of local inhabitants, regardless of their actual place of residence, in that unit’s functional costs. These problems are associated not only with tax collection rights but with difficulties in measuring the extent of urban sprawl in research and local governance. The aim of this study was to analyze the applicability of the CORINE Land Cover (CLC) database for monitoring urbanization processes, including the dynamic process of urban sprawl. Polish cities with county rights, i.e., cities that implement independent spatial planning policies, were analyzed in the study to determine the pattern of urban sprawl in various types of cities. Buffer zones composed of municipalities that are directly adjacent to the central urban unit were mapped around the analyzed cities. The study proposes a novel method for measuring the extent of suburbanization with the use of the CLC database and Geographic Information System (GIS) tools. The developed method relies on the overgrowth of urbanization (OU) index calculated based on CLC data. The OU index revealed differences in the rate of urbanization in three groups of differently sized Polish cities. The analysis covered two periods: 2006–2012 and 2012–2018, and it revealed that urban sprawl in the examined cities proceeded in an unstable manner over time. The results of the present study indicate that the CLC database is a reliable source of information about urbanization processes.

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Section: Methodsmentioning

confidence: 99%

The Use of the CORINE Land Cover (CLC) Database for Analyzing Urban Sprawl

2020

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“…Over the past decades, several national and international agencies have developed remote sensing based land cover maps that report on the irrigated areas with global or regional coverages. Moderate Resolution Imaging Spectroradiometer (MODIS) sensor based land cover maps (MCD12Q1), CORINE land cover, Global Irrigated Area Mapping (GIAM), among others are widely used by researchers to understand the land cover land use changes at larger scales, including changes in agricultural systems [16][17][18][19][20]. Similarly, several agricultural monitoring systems have been developed at global and national scale.…”

Section: Introductionmentioning

confidence: 99%

Mapping Agricultural Landuse Patterns from Time Series of Landsat 8 Using Random Forest Based Hierarchial Approach

et al. 2019

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Increase in irrigated area, driven by demand for more food production, in the semi-arid regions of Asia and Africa is putting pressure on the already strained available water resources. To cope and manage this situation, monitoring spatial and temporal dynamics of the irrigated area land use at basin level is needed to ensure proper allocation of water. Publicly available satellite data at high spatial resolution and advances in remote sensing techniques offer a viable opportunity. In this study, we developed a new approach using time series of Landsat 8 (L8) data and Random Forest (RF) machine learning algorithm by introducing a hierarchical post-processing scheme to extract key Land Use Land Cover (LULC) types. We implemented this approach for Mashhad basin in Iran to develop a LULC map at 15 m spatial resolution with nine classes for the crop year 2015/2016. In addition, five irrigated land use types were extracted for three crop years—2013/2014, 2014/2015, and 2015/2016—using the RF models. The total irrigated area was estimated at 1796.16 km2, 1581.7 km2 and 1578.26 km2 for the cropping years 2013/2014, 2014/2015 and 2015/2016, respectively. The overall accuracy of the final LULC map was 87.2% with a kappa coefficient of 0.85. The methodology was implemented using open data and open source libraries. The ability of the RF models to extract key LULC types at basin level shows the usability of such approaches for operational near real time monitoring.

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“…The input data is derived from historical CLC data, and is compared against the latest CLC data from 2018. This dataset is a high-quality source for European land cover data and provides an opportunity for developing visualizations Cieślak et al (2017). For example, how to compare LC/LU data sets which have different nomenclatures and MMU/MMW (Minimum Mapping Units/Minimum Mapping Widths), and statistical graphics for the input data.…”

Section: Research Identificationmentioning

confidence: 99%

Testing approaches to visualize land cover/land use changes in time series with Web GIS microservice tools

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Jahnke

Walen

et al. 2021

Proc. Int. Cartogr. Assoc.

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Abstract. Web applications which are high functioning, efficient, and meet the performance demand of the client are essential in modern cartographic workflows. With more and more complex spatial data being integrated into web applications, such as time related features, it is essential to harmonize the means of data presentation so that the end product is aligned with the needs of the end-user. In this paper we present aWeb GIS application built as a microservice which displays various timeseries visualizations to the user to streamline intuitiveness and functionality. The prototype provides a solution which could help to understand various ways in which current web and spatial analysis methods can be combined to create visualizations that add value to existing spatial data for cartographic workflows.

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Land Use Changes Monitoring with CORINE Land Cover Data

Cited by 14 publications

References 6 publications

The Use of the CORINE Land Cover (CLC) Database for Analyzing Urban Sprawl

The Use of the CORINE Land Cover (CLC) Database for Analyzing Urban Sprawl

Mapping Agricultural Landuse Patterns from Time Series of Landsat 8 Using Random Forest Based Hierarchial Approach

Testing approaches to visualize land cover/land use changes in time series with Web GIS microservice tools

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