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Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China
المؤلفون المشاركون
Wang, Jun
He, Qian
Zhou, Ping
Gong, Qinghua
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-11-11
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
The main purposes of the study were to test the performance of the Revised Universal Soil Loss Equation (RUSLE) and to understand the key factors responsible for generating soil erosion in the Nanling National Nature Reserve (NNNR), South China, where soil erosion has become a very serious ecological and environmental problem.
By combining the RUSLE and geographic information system (GIS) data, we first produced a map of soil erosion risk at 30 m-resolution pixel level with predicted factors.
We then used consecutive Landsat 8 satellite images to obtain the spatial distribution of four types of soil erosion and carried out ground truth checking of the RUSLE.
On this basis, we innovatively developed a probability model to explore the relationship between four types of soil erosion and the key influencing factors, identify high erosion area, and analyze the reason for the differences derived from the RUSLE.
The results showed that the overall accuracy of image interpretation was acceptable, which could be used to represent the currently actual spatial distribution of soil erosion.
Ground truth checking indicated some differences between the spatial distribution and class of soil erosion derived from the RUSLE and the actual situation.
The performance of the RUSLE was unsatisfactory, producing differences and even some errors when used to estimate the ecological risks posed by soil erosion within the NNNR.
We finally produced a probability table revealing the degree of influence of each factor on different types of soil erosion and quantitatively elucidated the reason for generating these differences.
We suggested that soil erosion type and the key influencing factors should be identified prior to soil erosion risk assessment in a region.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Jun& He, Qian& Zhou, Ping& Gong, Qinghua. 2019. Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China. Advances in Civil Engineering،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1116961
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Jun…[et al.]. Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China. Advances in Civil Engineering No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1116961
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Jun& He, Qian& Zhou, Ping& Gong, Qinghua. Test of the RUSLE and Key Influencing Factors Using GIS and Probability Methods: A Case Study in Nanling National Nature Reserve, South China. Advances in Civil Engineering. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1116961
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1116961
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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