Regional Variations of Land-Use Development and Land-Use/Cover Change Dynamics: A Case Study of Turkey

Ustaoglu, Eda; Aydınoğlu, Arif Çağdaş

doi:10.3390/rs11070885

Cited by 30 publications

(14 citation statements)

References 72 publications

(82 reference statements)

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“…In this case, numerous policymakers will eventually use CLC just as an informative base of interpretation and not as an analytical frame. At the NUTS3 scale, the CLC dataset overlaps national or regional statistical information that, in some conditions, creates data redundancy or impossible comparisons (mainly in the case of the artificial surfaces) [15].…”

Section: Introductionmentioning

confidence: 99%

Structural Changes in the Romanian Economy Reflected through Corine Land Cover Datasets

et al. 2020

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During the last 30 years, the Romanian economy has faced different challenges due to structural readjustments, overcoming crisis and globalization. The share of primary and secondary sectors in the gross domestic product have strongly decreased, while the services have taken off. The main objective for this study is to observe how these economic readjustments can be assessed and measured using the Corine Land Cover datasets from 1990, 2000, 2006, 2012 and 2018 (with special observation on the range 2006 and 2018, after Romania was included in European Union). Despite some of the methodological limitations (like the minimum surface change), the Corine Land Cover turned out to be a powerful tool and it allowed us to detect an intense correlation between the socioeconomic and the structural trends in land use, in specific spatial contexts. The artificial surfaces are constantly increasing and this trend is rather visible as a distance function to the major Romanian cities. The most interesting changes occurred in the case of the agricultural polygons. The main trend emphasized by our analysis regards the redeployment of large farms in areas of agronomic and environmental territorial optimum. Such is the case for vineyards (after a decline during 2000–2006) and for annual cultures. All these changes in land-use patterns are too complex to be encompassed by a single methodology, which is why we used different tools, ranging from spatial analysis to geo-economic modeling, in order to detect how the Corine Land Cover datasets might be used for a better understanding of the Romanian economic readjustments.

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Section: Introductionmentioning

confidence: 99%

Structural Changes in the Romanian Economy Reflected through Corine Land Cover Datasets

et al. 2020

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“…They are currently being reflected in various regional and national evaluations. Their interpretations can be used to assess ecosystem services [43][44][45][46], biomass [47], the impact of EU subsidies [48], regional development [49][50][51][52][53][54][55][56], urbanization [57], the impact of climate change on the landscape [58], landscape protection [59][60][61][62][63][64], and many others. Our results are consistent with detailed mapping and comparisons in other European countries.…”

Section: Discussionmentioning

confidence: 99%

Comparison of CORINE Land Cover Data with National Statistics and the Possibility to Record This Data on a Local Scale—Case Studies from Slovakia

et al. 2020

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Monitoring of land cover (LC) provides important information of actual land use (LU) and landscape dynamics. LC research results depend on the size of the area, purpose and applied methodology. CORINE Land Cover (CLC) data is one of the most important sources of LU data from a European perspective. Our research compares official CLC data (third hierarchical level of nomenclature at a scale of 1:100,000) and national statistics (NS) of LU in Slovakia between 2000 and 2018 at national, county, and local levels. The most significant differences occurred in arable land and permanent grassland, which is also related to the recording method and the development of agricultural land management. Due to the abandonment of agricultural areas, a real recorded increase in forest cover due to forest succession was not introduced in the official records of Land register. New modification of CLC methodology for identifying LC classes at a scale of 1:10,000 and fifth hierarchical level of CLC is firstly applied for local case studies representing lowland, basin, and mountain landscape. The size of the least identified and simultaneously recorded area was established at 0.1 ha the minimum width of a polygon was established at 10 m, the minimum recorded width of linear elements such as communications was established at 2 m. The use of the fifth CLC level in the case studies areas generated average boundary density 17.2 km/km2, comparing to the 2.6 km/km2 of the third level. Therefore, when measuring the density of spatial information by the polygon boundary lengths, the fifth level carries 6.6 times more information than the third level. Detailed investigation of LU affords better verification of national statistics data at a local level. This study also contributes to a more detailed recording of the current state of the Central European landscape and its changes.

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“…The economic factor was not included due to the unavailability of this data. Several researchers have proposed the economic factor in their land cover change model [11,61,62]. For further research, the economic factor should be selected into the model.…”

Section: Discussionmentioning

confidence: 99%

Predicting Land Cover Change in the Mamminasata Area, Indonesia, to Evaluate the Spatial Plan

Hakim

Matsuoka

Baja

et al. 2020

IJGI

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The spatial plan program for Makassar City and the surrounding area called Mamminasata (Makassar, Maros, Sungguminasa, and Takalar) was created by the Indonesian Government. The program regulates the proportion of land cover, but predictions about land cover changes were not considered. Therefore, in this study, we predict what the land cover may be in 2031 using the multi-layer perceptron neural network and the Markov chain methods. For this purpose, image composite, support vector machine classifier, and change detection were applied to a time series of satellite data. Visual validation showed the hot-spots of land cover changes related to population density, and statistical validation scored 0.99 and 0.78 in no information kappa and grid-cell level location kappa, respectively. The model was performed to predict land cover in 2031, and the predicted result was then compared with the spatial plan using an overlapping method. The results showed that built-up area, dryland agriculture, and wetland agriculture occupied two, twenty, and eight percent of the protected zone, respectively. Meanwhile, fifteen percent of the development zone was covered by forest, mainly in the eastern part of Mamminasata. The result can be used to help the Government decide future plans for the Mamminasata area.

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Regional Variations of Land-Use Development and Land-Use/Cover Change Dynamics: A Case Study of Turkey

Cited by 30 publications

References 72 publications

Structural Changes in the Romanian Economy Reflected through Corine Land Cover Datasets

Structural Changes in the Romanian Economy Reflected through Corine Land Cover Datasets

Comparison of CORINE Land Cover Data with National Statistics and the Possibility to Record This Data on a Local Scale—Case Studies from Slovakia

Predicting Land Cover Change in the Mamminasata Area, Indonesia, to Evaluate the Spatial Plan

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