Grains play a significant role in meeting the nutritional needs of the increasing world population. Consequently, the need for new studies on agricultural production and land suitability assessments has increased. The present paper aims to perform agricultural land suitability assessment to evaluate agricultural productivity in Tekirdağ province to determine precise productive agricultural areas. This study combines a variety of datasets to develop a dynamic model using GIS-based multi-criteria decision analysis for land suitability assessment and agricultural productivity. The datasets used in this study are supported by terrestrial samples and processed with spatial technologies. The results of the study indicate that the agricultural potential of the provincial lands is quite high. It reveals that 65.7% of province lands are suitable for agricultural production. Of the remaining lands, 20.3% is marginally suitable while only 8% of the land is unsuitable for agricultural production. In the northwestern part, suitable land for agricultural productivity is higher compared to other parts of the study area. This part also corresponds to the areas where industrial activities are marginal. The results also imply that agricultural activities in grain production areas must be reconsidered and replanned according to the new classification of land suitability assessment. In this respect, our study suggests that the policymakers and the government should take necessary steps to ensure the protection and sustainability of agricultural lands while planning for the industrial and settlement development in grain production areas.
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http://dx.doi.org/10.1007/s10661-021-09663-1 | DOI Listing |
PLoS One
December 2024
Department of Pediatrics, College of Medicine and King Khalid University Hospital, King Saud University, Medical City, Riyadh, Saudi Arabia.
The habitat suitability of Salvadora oleoides and Tamarix aphylla can be one of the most significant steps towards conserving these tree species. Habitat loss presents a critical threat to the existence of S. oleoides and T.
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December 2024
School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China.
Drawing from the United Nations Sustainable Development Goals (SDGs), this study offers a framework for optimizing rail transit routes, balancing economic benefits with environmental preservation. Using the Bivariate Choropleth-Multi-Criteria Decision Analysis (BC-MCDA) model, we categorize global regions into economic benefit, environmental conservation, high-conflict, and low-conflict zones. Specifically, 7.
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December 2024
Programa de Pós-Graduação em Ecologia, Instituto de Ciência Biológicas, Universidade Federal do Pará, Belém, Brazil.
The negative effects of land-use changes on biodiversity significantly contribute to climate change. Primates are among the animals most affected by these changes, because of their high dependence on forest cover where a lack of forest connectivity can limit their dispersal and segregate their populations. In this sense, protected areas (PAs) are crucial for conserving endangered primates, especially endemic species.
View Article and Find Full Text PDFEnviron Manage
December 2024
Departamento de Ciencias de la Vida - UD Ecología, Edificio de Ciencias, Universidad de Alcalá, E-28805, Alcalá de Henares, Spain.
Deforestation and forest degradation are key drivers of biodiversity loss and global environmental change. Ecosystem restoration is recognized as a global priority to counter these processes. Forest restoration efforts have commonly adopted a predominantly ecological approach, without including broader socioeconomic variables and the characteristics of the rural context.
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December 2024
School of Geological Engineering and Geomatics, Chang'an University, Xi'an, 710054, China.
The array of wildfire activities instigated by human endeavors has emerged as a significant source of atmospheric pollution, posing considerable risks to both public health and property safety. This study harnesses Sentinel-2 satellite data, employing a variety of methods including spectral index methods, thresholding, and the Random Forest (RF) model for active fire spot detection. The research encompasses a wide range of land cover types across various Chinese regions.
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