Comparative Analysis of Potential Soil Degradation in the state of Sergipe

IF 0.1 Q4 GEOGRAPHY Geo UERJ Pub Date : 2023-06-09 DOI:10.12957/geouerj.2023.76860
Glauber Vinícius Pinto de Barros, Heliofábio Barros Gomes, Paulo Sergio De Rezende Nascimento, David Duarte Cavalcante Pinto, Fabrício Daniel dos Santos Silva, Rafaela Lisboa Costa
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Abstract

Performing field studies to assess soil degradation is expensive and time-consuming. Estimates made by numerical models are, therefore, usually preferred by many researchers and professionals that work on this subject. The present study primarily aims to assess the potential soil degradation (PSD) in the state of Sergipe, Brazil, in the years 2000 and 2019, by employing the fuzzy logic in a Geographic Information System (GIS) environment. The proposed model explores cause-effect relationships between specific variables that are known to affect the PSD, based on membership functions and the Fuzzy Gamma Operator (FGO) applied to data relative to geology, geomorphology, declivity, hypsometry, pedology, precipitation, erodibility, enhanced vegetation index (EVI) and land use. Our results show that, among these factors, the ones that most contributed to degradation were geology, geomorphology, pedology and precipitation. However, proper attention should be paid to variables susceptible to changes in the human timescale, such as precipitation, land use and cover and, consequently, the EVI, which were found to be important contributors to the observed increase in PSD along the studied timespan. Of those, especially, land use and cover, as it is a variable closely related to human activities. The cartographic products resulting from this work are also successful in indicating the regions that exhibit the most and the least important factors with respect to the influence on the processes that contribute to soil degradation, proving to be a valuable tool for decision-making in the planning of preventive and mitigating measures.
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Sergipe州潜在土壤退化的比较分析
进行实地研究以评估土壤退化既昂贵又费时。因此,许多研究这一课题的研究人员和专业人员通常更喜欢用数值模型进行估计。本研究主要目的是利用地理信息系统(GIS)环境中的模糊逻辑,对2000年和2019年巴西塞尔吉佩州的潜在土壤退化(PSD)进行评估。该模型基于隶属函数和模糊伽马算子(FGO),探讨了已知影响PSD的特定变量之间的因果关系,该算子应用于与地质、地貌、坡度、地形、土壤、降水、可蚀性、增强植被指数(EVI)和土地利用相关的数据。结果表明,在这些因素中,地质、地貌、土壤和降水对退化的影响最大。然而,应适当注意易受人类时间尺度变化影响的变量,如降水、土地利用和覆盖,以及因此而产生的EVI,它们被认为是在研究时间范围内观测到的PSD增加的重要因素。其中,特别是土地利用和覆盖,因为它是一个与人类活动密切相关的变量。这项工作所产生的制图产品也成功地指出了在对导致土壤退化的过程的影响方面表现出最重要和最不重要因素的区域,证明是规划预防和减轻措施的决策的宝贵工具。
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来源期刊
Geo UERJ
Geo UERJ GEOGRAPHY-
自引率
0.00%
发文量
28
审稿时长
8 weeks
期刊最新文献
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