A comparative analysis to assess the efficiency of lineament extraction utilizing satellite imagery from Landsat-8, Sentinel-2B, and Sentinel-1A: A case study around suez canal zone, Egypt

IF 3.8 Q2 ENVIRONMENTAL SCIENCES

Remote Sensing Applications-Society and Environment Pub Date : 2024-07-27 DOI:10.1016/j.rsase.2024.101312

Hadeer Ahmed Desoky , Mohamed Abd El-Dayem , Mahmoud Abd El-Rahman Hegab

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引用次数: 0

Abstract

Satellite remote sensing data has been extensively utilized in various fields, for example topography, geology, and hydrogeology, to extract lineament information. With notable advancements in remote sensing techniques, the process of lineament extraction and identification can now be performed in a more efficient and accurate manner, surpassing traditional manual methods. This study presents a comparative analysis utilizing Landsat-8, Sentinel-2B, and Sentinel-1A data to automatically extract lineaments. The approach includes ground truth data, an existing geological map, and a Digital Elevation Model (DEM) in addition to the data on satellite images. Through the use of a semi-totally automatic method that combines a line-linking algorithm and an edge-line detection technique, within the study area, we have determined the optimal parameters for automated lineament extraction. It has been demonstrated through further comparison and assessment of the data that using Sentinel-1A data resulted in more efficient restitution of lineaments. This demonstrates how well radar data performs in this kind of investigation when compared to optical data.

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利用 Landsat-8、Sentinel-2B 和 Sentinel-1A 卫星图像评估线状提取效率的比较分析：埃及苏伊士运河区周边案例研究

卫星遥感数据已被广泛应用于各个领域，如地形学、地质学和水文地质学，以提取线状信息。随着遥感技术的显著进步，线状物的提取和识别过程现在可以更高效、更准确地进行，超越了传统的人工方法。本研究利用 Landsat-8、Sentinel-2B 和 Sentinel-1A 数据进行比较分析，以自动提取线状物。除卫星图像数据外，该方法还包括地面实况数据、现有地质图和数字高程模型（DEM）。通过在研究区域内使用一种结合了线连接算法和边缘线检测技术的半自动方法，我们确定了自动提取线状物的最佳参数。通过对数据的进一步比较和评估证明，使用 Sentinel-1A 数据能更有效地还原线状线。这表明，与光学数据相比，雷达数据在此类调查中的表现非常出色。

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来源期刊

Remote Sensing Applications-Society and Environment Multiple-

CiteScore

8.00

自引率

8.50%

发文量

204

审稿时长

65 days

期刊介绍： The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems