An integration of geospatial and fuzzy-logic techniques for flood-hazard mapping

IF 1.3 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Mausmi Gohil, Darshan Mehta, Mohamedmaroof Shaikh
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Abstract

A hazard is a natural occurrence that might harm humans, animals or the environment. It may cause loss of life, illness or other health consequences, property damage, social and economic crisis or environmental degradation. Various regions around the world are vulnerable to one or more types of disasters. Flooding is one of the worst environmental catastrophes that impacts both civilisation and the environment globally. Various datasets and methods, such as meteorological data, satellite images and GIS, were used to create the hazard assessment map. For a particular region, flood hazards can be developed by integrating an assessment map for several parameter categories. The aim of the study was to evaluate the hazard of flooding and map the areas that will be flooded in Gujarat. This study develops and tests flood-hazard maps to visualise the spatial variation of hazards in Gujarat, India. The parameters for flood-hazard assessment are mainly considered as elevation, slope, aspect, curvature, lithology, soil, land use/cover, drainage density and distance from the river, and rainfall to create a map in the context of a GIS. The acquired data was evaluated using ArcGIS and fuzzy-logic techniques to build a flood hazard map. Five categories have been assigned to the computed flood hazard map: very low, low, moderate, high, and very high. Engineers, planners and local governments may find this study useful in the future when it comes to land use planning and the control of hazards. Flood hazard potential mapping is necessary to manage and mitigate flooding.

Abstract Image

将地理空间技术与模糊逻辑技术相结合,用于洪水灾害绘图
危害是指可能对人类、动物或环境造成伤害的自然现象。它可能造成生命损失、疾病或其他健康后果、财产损失、社会和经济危机或环境退化。世界各地都容易遭受一种或多种类型的灾害。洪水是影响全球文明和环境的最严重的环境灾难之一。在绘制灾害评估地图时,我们使用了各种数据集和方法,如气象数据、卫星图像和地理信息系统。对于一个特定区域,可以通过整合多个参数类别的评估地图来制定洪水危害。这项研究的目的是评估古吉拉特邦的洪水灾害,并绘制将被洪水淹没的地区地图。本研究绘制并测试了洪水灾害地图,以直观显示印度古吉拉特邦灾害的空间变化。洪水灾害评估的参数主要包括海拔、坡度、坡向、曲率、岩性、土壤、土地利用/覆盖、排水密度和与河流的距离以及降雨量,以便在地理信息系统中绘制地图。利用 ArcGIS 和模糊逻辑技术对获取的数据进行评估,以绘制洪水灾害图。计算出的洪水灾害地图分为五个等级:极低、低、中、高和非常高。工程师、规划人员和地方政府可能会发现这项研究在未来的土地利用规划和灾害控制方面非常有用。绘制洪水灾害潜势图对于管理和减轻洪水灾害十分必要。
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来源期刊
Journal of Earth System Science
Journal of Earth System Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
3.20
自引率
5.30%
发文量
226
期刊介绍: The Journal of Earth System Science, an International Journal, was earlier a part of the Proceedings of the Indian Academy of Sciences – Section A begun in 1934, and later split in 1978 into theme journals. This journal was published as Proceedings – Earth and Planetary Sciences since 1978, and in 2005 was renamed ‘Journal of Earth System Science’. The journal is highly inter-disciplinary and publishes scholarly research – new data, ideas, and conceptual advances – in Earth System Science. The focus is on the evolution of the Earth as a system: manuscripts describing changes of anthropogenic origin in a limited region are not considered unless they go beyond describing the changes to include an analysis of earth-system processes. The journal''s scope includes the solid earth (geosphere), the atmosphere, the hydrosphere (including cryosphere), and the biosphere; it also addresses related aspects of planetary and space sciences. Contributions pertaining to the Indian sub- continent and the surrounding Indian-Ocean region are particularly welcome. Given that a large number of manuscripts report either observations or model results for a limited domain, manuscripts intended for publication in JESS are expected to fulfill at least one of the following three criteria. The data should be of relevance and should be of statistically significant size and from a region from where such data are sparse. If the data are from a well-sampled region, the data size should be considerable and advance our knowledge of the region. A model study is carried out to explain observations reported either in the same manuscript or in the literature. The analysis, whether of data or with models, is novel and the inferences advance the current knowledge.
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