scholarly journals Apports de l'imagerie Pléiades à la Gestion Intégrée des Zones Côtières - Application au territoire de Thau -

Author(s):  
Claire Dupaquier ◽  
Annie Desbrosse ◽  
Pierre Maurel ◽  
Laure-Elise Ruoso ◽  
Roelof Plant ◽  
...  

Dans le contexte actuel de gestion intégrée du littoral, la croissance démographique et l'augmentation de la pression foncière sur le bassin de Thau font de ce territoire un enjeu important, se répercutant sur l'occupation du sol. Pour faire face à ces enjeux, les collectivités territoriales du territoire de Thau ont confié au SMBT à partir de 2006 l'élaboration conjointe de plusieurs instruments de planification afin de mener une approche intégrée du développement territorial au travers du SCoT, du SAGE et d'une procédure Natura 2000. L'objectif de cette contribution est de présenter la méthodologie opérationnelle développée pour cartographier l'occupation du sol initiale 2012/2013 à partir d'images Pléiades sur le bassin de Thau. Cette cartographie constituera une donnée d'entrée pour nourrir l'observatoire du territoire de Thau et sera adaptée à la mise en œuvre des instruments de planification. La méthodologie a été scindée en deux parties, une première partie de photo-interprétation pour cartographier les espaces artificialisés et leurs évolutions sur plusieurs années et une seconde partie sur une approche par télédétection avec la réalisation d'une classification orientée-objet sur les espaces agricoles et les milieux naturels. La démarche procure un état actualisé de l'occupation du sol selon une typologie à 4 niveaux adaptée de Corine Land Cover et sera mise à jour tous les deux ans pour produire des indicateurs de suivi et d'évaluation du territoire de Thau.

2020 ◽  
Vol 12 (13) ◽  
pp. 2075 ◽  
Author(s):  
Adrian Ursu ◽  
Cristian Constantin Stoleriu ◽  
Constantin Ion ◽  
Vasile Jitariu ◽  
Andrei Enea

The present paper aims to evaluate if the Natura 2000 sites in Romania are placed over dynamic areas from a land cover changes perspective, or if they are placed in areas with low human interest and what the impact of these changes are. The effectiveness of conservation measures was addressed by analyzing the number of land cover changes and their areas in Natura 2000 sites, before and after declaring them as protected areas. Corine Land Cover (CLC) data were used as a tool to identify threats and pressures from each Natura 2000 site, and also assess whether land cover changes are more frequent in sites with a high biodiversity index, compared to those with low diversity, in order to estimate the conservation status. Changes in the land cover during 1990–2018 are characterized by three types of events, from 1990 to 2000 with most changes recorded, followed by a relative period of stability from 2000 to 2012; the most dynamic period is from 2012 to 2018. The main changes are due to deforestation. Only 29.7% ROSCI (Romanian Sites of Community Importance) and 36.5% ROSPA (Romanian Special Protected Areas) sites are characterized by a good degree of conservation without or with low modifications regarding the land cover. The most frequent threats and pressures that were found through CLC changes in the ROSCIs in Romania are related to forestry, grazing, the extent of the urbanized environment and those related to agriculture. The correspondence between Corine Land Cover and Natura 2000 specific threats and pressures emphasizes new guidelines for the Corine Land Cover program; therefore, this correspondence can be a potential tool to get more information for Natura 2000 sites.


Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Juraj Lieskovský ◽  
Dana Lieskovská

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.


2021 ◽  
Vol 13 (6) ◽  
pp. 1060
Author(s):  
Luc Baudoux ◽  
Jordi Inglada ◽  
Clément Mallet

CORINE Land-Cover (CLC) and its by-products are considered as a reference baseline for land-cover mapping over Europe and subsequent applications. CLC is currently tediously produced each six years from both the visual interpretation and the automatic analysis of a large amount of remote sensing images. Observing that various European countries regularly produce in parallel their own land-cover country-scaled maps with their own specifications, we propose to directly infer CORINE Land-Cover from an existing map, therefore steadily decreasing the updating time-frame. No additional remote sensing image is required. In this paper, we focus more specifically on translating a country-scale remote sensed map, OSO (France), into CORINE Land Cover, in a supervised way. OSO and CLC not only differ in nomenclature but also in spatial resolution. We jointly harmonize both dimensions using a contextual and asymmetrical Convolution Neural Network with positional encoding. We show for various use cases that our method achieves a superior performance than the traditional semantic-based translation approach, achieving an 81% accuracy over all of France, close to the targeted 85% accuracy of CLC.


2020 ◽  
Vol 12 (13) ◽  
pp. 2137 ◽  
Author(s):  
Ilinca-Valentina Stoica ◽  
Marina Vîrghileanu ◽  
Daniela Zamfir ◽  
Bogdan-Andrei Mihai ◽  
Ionuț Săvulescu

Monitoring uncontained built-up area expansion remains a complex challenge for the development and implementation of a sustainable planning system. In this regard, proper planning requires accurate monitoring tools and up-to-date information on rapid territorial transformations. The purpose of the study was to assess built-up area expansion, comparing two freely available and widely used datasets, respectively, Corine Land Cover and Landsat, to each other, as well as the ground truth, with the goal of identifying the most cost-effective and reliable tool. The analysis was based on the largest post-socialist city in the European Union, the capital of Romania, Bucharest, and its neighboring Ilfov County, from 1990 to 2018. This study generally represents a new approach to measuring the process of urban expansion, offering insights about the strengths and limitations of the two datasets through a multi-level territorial perspective. The results point out discrepancies between the datasets, both at the macro-scale level and at the administrative unit’s level. On the macro-scale level, despite the noticeable differences, the two datasets revealed the spatiotemporal magnitude of the expansion of the built-up area and can be a useful tool for supporting the decision-making process. On the smaller territorial scale, detailed comparative analyses through five case-studies were conducted, indicating that, if used alone, limitations on the information that can be derived from the datasets would lead to inaccuracies, thus significantly limiting their potential to be used in the development of enforceable regulation in urban planning.


2021 ◽  
Vol 13 (9) ◽  
pp. 1743
Author(s):  
Daniel Paluba ◽  
Josef Laštovička ◽  
Antonios Mouratidis ◽  
Přemysl Štych

This study deals with a local incidence angle correction method, i.e., the land cover-specific local incidence angle correction (LC-SLIAC), based on the linear relationship between the backscatter values and the local incidence angle (LIA) for a given land cover type in the monitored area. Using the combination of CORINE Land Cover and Hansen et al.’s Global Forest Change databases, a wide range of different LIAs for a specific forest type can be generated for each scene. The algorithm was developed and tested in the cloud-based platform Google Earth Engine (GEE) using Sentinel-1 open access data, Shuttle Radar Topography Mission (SRTM) digital elevation model, and CORINE Land Cover and Hansen et al.’s Global Forest Change databases. The developed method was created primarily for time-series analyses of forests in mountainous areas. LC-SLIAC was tested in 16 study areas over several protected areas in Central Europe. The results after correction by LC-SLIAC showed a reduction of variance and range of backscatter values. Statistically significant reduction in variance (of more than 40%) was achieved in areas with LIA range >50° and LIA interquartile range (IQR) >12°, while in areas with low LIA range and LIA IQR, the decrease in variance was very low and statistically not significant. Six case studies with different LIA ranges were further analyzed in pre- and post-correction time series. Time-series after the correction showed a reduced fluctuation of backscatter values caused by different LIAs in each acquisition path. This reduction was statistically significant (with up to 95% reduction of variance) in areas with a difference in LIA greater than or equal to 27°. LC-SLIAC is freely available on GitHub and GEE, making the method accessible to the wide remote sensing community.


2016 ◽  
pp. 111-116 ◽  
Author(s):  
Tomas Soukup ◽  
György Büttner ◽  
Jan Feranec ◽  
Gerard Hazeu ◽  
Gabriel Jaffrain ◽  
...  
Keyword(s):  

2016 ◽  
pp. 69-78
Author(s):  
Tomas Soukup ◽  
Jan Feranec ◽  
Gerard Hazeu ◽  
Gabriel Jaffrain ◽  
Marketa Jindrova ◽  
...  
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document