Faten Nahas , Islam Hamdi , Mohamed Hereher , Martina Zelenakova , Ahmed M. El Kenawy
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Ordinary least squares (OLS) regression method was used to calculate the trend for each pixel and the Mann-Kendall test was used to assess the statistical significance of the trend at 95% confidence level (p < 0.05). The central and southern regions of the delta experienced significant LST increases, highlighting the risk of warming due to vegetation degradation. Specifically, the diurnal LST trend ranged from −0.46 °C to 0.34 °C/year, while the nocturnal trend ranged from −0.12 °C to 0.26 °C/year. Spatially, the study also indicates cooling trends in coastal cities such as Port Said, New Damietta and Alexandria due to the moderate influence of the Mediterranean Sea. In contrast, the inland and southern Delta cities are warming rapidly. The relationship between diurnal UHI average and the NDVI showed a modest negative correlation (R = −0.31, p < 0.0001). This association was much stronger at night, with a negative correlation of (R = −0.71, P < 0.0001) A strong negative correlation between diurnal UHI trend and NDVI (R = −0.68, p < 0.0001). The relationship between nocturnal UHI trend and NDVI is negative (R = −0.61, p < 0.0001). The analysis reveals that 13 cities exhibited significant warming during the daytime, compared to 35 cities at night. The results highlight the importance of pixel-level data to accurately assess environmental changes and inform urban planning strategies to mitigate the effects of warming on the Nile Delta.</div></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"37 ","pages":"Article 101408"},"PeriodicalIF":3.8000,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Warming trends in the Nile Delta: A high-resolution Spatial statistical approach\",\"authors\":\"Faten Nahas , Islam Hamdi , Mohamed Hereher , Martina Zelenakova , Ahmed M. El Kenawy\",\"doi\":\"10.1016/j.rsase.2024.101408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The Nile Delta, a region of historical significance, is facing significant environmental changes driven by climate change. This study employs a novel pixel-level spatial statistical analysis to assess the intensity and trends in the daytime and nighttime urban heat island (UHI) from 2003 to 2021. We employed high-resolution data from the Global Artificial Impermeable Area (GAIA) dataset (30 m), land surface temperature (LST) from the MODIS Aqua satellite 1000 m, and the MOD13A3 Normalized Difference Vegetation Index (NDVI) (1000 m). Bivariate choropleth maps were used to illustrate the spatial relationships between daytime and nighttime LST and NDVI. Ordinary least squares (OLS) regression method was used to calculate the trend for each pixel and the Mann-Kendall test was used to assess the statistical significance of the trend at 95% confidence level (p < 0.05). The central and southern regions of the delta experienced significant LST increases, highlighting the risk of warming due to vegetation degradation. Specifically, the diurnal LST trend ranged from −0.46 °C to 0.34 °C/year, while the nocturnal trend ranged from −0.12 °C to 0.26 °C/year. Spatially, the study also indicates cooling trends in coastal cities such as Port Said, New Damietta and Alexandria due to the moderate influence of the Mediterranean Sea. In contrast, the inland and southern Delta cities are warming rapidly. The relationship between diurnal UHI average and the NDVI showed a modest negative correlation (R = −0.31, p < 0.0001). This association was much stronger at night, with a negative correlation of (R = −0.71, P < 0.0001) A strong negative correlation between diurnal UHI trend and NDVI (R = −0.68, p < 0.0001). The relationship between nocturnal UHI trend and NDVI is negative (R = −0.61, p < 0.0001). The analysis reveals that 13 cities exhibited significant warming during the daytime, compared to 35 cities at night. 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引用次数: 0
摘要
尼罗河三角洲是一个具有历史意义的地区,在气候变化的推动下,它正面临着重大的环境变化。本研究采用一种新颖的像素级空间统计分析方法,对2003 - 2021年中国城市白天和夜间热岛强度及其变化趋势进行了评估。利用全球人工不透水面积(GAIA)数据集(30 m)的高分辨率数据、MODIS Aqua卫星(1000 m)的陆地表面温度(LST)数据和MOD13A3归一化植被指数(NDVI)数据(1000 m),利用二元地形图分析昼夜地表温度与NDVI的空间关系。使用普通最小二乘(OLS)回归方法计算每个像素点的趋势,并使用Mann-Kendall检验在95%置信水平上评估趋势的统计学显著性(p <;0.05)。三角洲中部和南部地区地表温度显著升高,突出了植被退化导致的变暖风险。其中,日变化趋势为- 0.46°C ~ 0.34°C/年,夜变化趋势为- 0.12°C ~ 0.26°C/年。从空间上看,该研究还表明,由于地中海的适度影响,塞得港、新达米埃塔和亚历山大等沿海城市也出现了降温趋势。相比之下,内陆和南部三角洲城市正在迅速变暖。日平均热岛指数与NDVI呈适度负相关(R = - 0.31, p <;0.0001)。这种关联在夜间更为强烈,呈负相关(R = - 0.71, P <;0.0001)日UHI趋势与NDVI呈显著负相关(R = - 0.68, p <;0.0001)。夜间UHI趋势与NDVI呈负相关(R = - 0.61, p <;0.0001)。分析显示,13个城市在白天表现出明显的变暖,而35个城市在夜间表现出明显的变暖。研究结果强调了像素级数据对准确评估环境变化的重要性,并为城市规划策略提供信息,以减轻气候变暖对尼罗河三角洲的影响。
Warming trends in the Nile Delta: A high-resolution Spatial statistical approach
The Nile Delta, a region of historical significance, is facing significant environmental changes driven by climate change. This study employs a novel pixel-level spatial statistical analysis to assess the intensity and trends in the daytime and nighttime urban heat island (UHI) from 2003 to 2021. We employed high-resolution data from the Global Artificial Impermeable Area (GAIA) dataset (30 m), land surface temperature (LST) from the MODIS Aqua satellite 1000 m, and the MOD13A3 Normalized Difference Vegetation Index (NDVI) (1000 m). Bivariate choropleth maps were used to illustrate the spatial relationships between daytime and nighttime LST and NDVI. Ordinary least squares (OLS) regression method was used to calculate the trend for each pixel and the Mann-Kendall test was used to assess the statistical significance of the trend at 95% confidence level (p < 0.05). The central and southern regions of the delta experienced significant LST increases, highlighting the risk of warming due to vegetation degradation. Specifically, the diurnal LST trend ranged from −0.46 °C to 0.34 °C/year, while the nocturnal trend ranged from −0.12 °C to 0.26 °C/year. Spatially, the study also indicates cooling trends in coastal cities such as Port Said, New Damietta and Alexandria due to the moderate influence of the Mediterranean Sea. In contrast, the inland and southern Delta cities are warming rapidly. The relationship between diurnal UHI average and the NDVI showed a modest negative correlation (R = −0.31, p < 0.0001). This association was much stronger at night, with a negative correlation of (R = −0.71, P < 0.0001) A strong negative correlation between diurnal UHI trend and NDVI (R = −0.68, p < 0.0001). The relationship between nocturnal UHI trend and NDVI is negative (R = −0.61, p < 0.0001). The analysis reveals that 13 cities exhibited significant warming during the daytime, compared to 35 cities at night. The results highlight the importance of pixel-level data to accurately assess environmental changes and inform urban planning strategies to mitigate the effects of warming on the Nile Delta.
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