Environmental Evaluation for Determining the Potential Lands for Agriculture and Pasturage in Neyshabour County
The aim of the present study is to identify the most suitable land uses with the highest efficiency and least vulnerability at the lowest costs. Among various land uses, due to the direct connection between agricultural land uses and environment, environmental evaluation become very sensitive. And i...
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Veröffentlicht in: | Faṣlnāmah-i pizhūhishʹhā-yi rūstāyī 2020-08, Vol.11 (2), p.366-383 |
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Zusammenfassung: | The aim of the present study is to identify the most suitable land uses with the highest efficiency and least vulnerability at the lowest costs. Among various land uses, due to the direct connection between agricultural land uses and environment, environmental evaluation become very sensitive. And in fact, when the potentials of the natural environment are identified, we can expect to achieve sustainable agriculture. The present study is aimed at environmental evaluation for determining potential lands for agriculture and pasturage in Neyshabour County to achieve sustainable agriculture. Therefore, systematic research method was used, and at the first stage, environmental potentials and resources were identified in the region. Then, the collected information was analyzed and combined based on the systematic approach, and finally was organized in the form of information layers. The environmental potential was determined by the measurement of extracted units with ecological criteria. And finally, the spatial correlation of distribution of villages in high potential lands for agriculture and pasturage was determined by the Moran index. The results of the research showed that the region enjoys high potential for class 3 agriculture and pasturage, and then for class 1 and 2. It was also shown that the region has the least potential for class 4 agriculture. It also identified an impressive level of area for irrigated farming, gardening, animal husbandry, aviculture, and beekeeping. The results of the Moran index indicate that spatial distribution of villages is cluster one type, with the Moran index of 0.244 and confidence level of 99 percent. |
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ISSN: | 2008-7373 2423-7787 |
DOI: | 10.22059/jrur.2020.293501.1428 |