{"title":"基于热遥感估算住宅用水空间格局的简化方法评价,加沙地带汗尤尼斯省","authors":"Wiesam Essa, O. Batelaan","doi":"10.52865/omtu9489","DOIUrl":null,"url":null,"abstract":"Background: Water consumption (WC) data is critical for managing water crises in water-scarce countries, especially in those countries that are lagging behind technical advancement for collecting accurate WC data at the household level. There is a lack of methods for estimating WC. Method: Here, we introduce a simplified method for estimating WC data based on regression analysis of satellite Land Surface Temperature (LST) data for the Khan-Younis Governorate, Gaza Strip, for the year 2017. We demonstrate the potential for using WC-LST models with and without low-resolution population data to estimate residential WC for two spatial resolutions: Landsat TIR moderate resolution (100 m), and MODIS TIR low resolution (1000 m). Residential WC data is measured based on readings from water meters of 28,000 individual houses. Results: The method performs better without the low-spatial resolution population data. The use of similar spatial resolution data or higher to Landsat 8 TIR (100 m) is a prerequisite for robust WC estimation. Although the method can easily be modified and applied in areas where no estimated water consumption data is available, using the regression equation might result in a poor result due to the use of different water supply sources as demonstrated for the periphery of Khan Younis city.","PeriodicalId":223912,"journal":{"name":"Israa University Journal for Applied Science","volume":"126 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of a simplified method for estimating spatial patterns of residential water use based on thermal remote sensing, Khan-Younis Governorate, Gaza Strip\",\"authors\":\"Wiesam Essa, O. Batelaan\",\"doi\":\"10.52865/omtu9489\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Water consumption (WC) data is critical for managing water crises in water-scarce countries, especially in those countries that are lagging behind technical advancement for collecting accurate WC data at the household level. There is a lack of methods for estimating WC. Method: Here, we introduce a simplified method for estimating WC data based on regression analysis of satellite Land Surface Temperature (LST) data for the Khan-Younis Governorate, Gaza Strip, for the year 2017. We demonstrate the potential for using WC-LST models with and without low-resolution population data to estimate residential WC for two spatial resolutions: Landsat TIR moderate resolution (100 m), and MODIS TIR low resolution (1000 m). Residential WC data is measured based on readings from water meters of 28,000 individual houses. Results: The method performs better without the low-spatial resolution population data. The use of similar spatial resolution data or higher to Landsat 8 TIR (100 m) is a prerequisite for robust WC estimation. Although the method can easily be modified and applied in areas where no estimated water consumption data is available, using the regression equation might result in a poor result due to the use of different water supply sources as demonstrated for the periphery of Khan Younis city.\",\"PeriodicalId\":223912,\"journal\":{\"name\":\"Israa University Journal for Applied Science\",\"volume\":\"126 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Israa University Journal for Applied Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52865/omtu9489\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Israa University Journal for Applied Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52865/omtu9489","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
背景:水资源消耗(WC)数据对于管理缺水国家的水危机至关重要,特别是在那些在收集家庭层面准确的WC数据方面技术进步滞后的国家。目前还缺乏估算用水量的方法。方法:本文介绍了一种基于2017年加沙地带Khan-Younis省卫星地表温度(LST)数据回归分析的简化估算用水量的方法。我们展示了在两种空间分辨率下使用WC- lst模型估算住宅用水量的潜力:Landsat TIR中等分辨率(100米)和MODIS TIR低分辨率(1000米)。住宅用水量数据是基于28,000个独立住宅的水表读数测量的。结果:在没有低空间分辨率人口数据的情况下,该方法具有更好的性能。使用与Landsat 8 TIR (100 m)相似或更高的空间分辨率数据是稳健估计WC的先决条件。虽然该方法可以很容易地修改并应用于没有估计用水量数据的地区,但使用回归方程可能会导致结果不佳,因为使用了不同的供水来源,如汗尤尼斯市外围所示。
Evaluation of a simplified method for estimating spatial patterns of residential water use based on thermal remote sensing, Khan-Younis Governorate, Gaza Strip
Background: Water consumption (WC) data is critical for managing water crises in water-scarce countries, especially in those countries that are lagging behind technical advancement for collecting accurate WC data at the household level. There is a lack of methods for estimating WC. Method: Here, we introduce a simplified method for estimating WC data based on regression analysis of satellite Land Surface Temperature (LST) data for the Khan-Younis Governorate, Gaza Strip, for the year 2017. We demonstrate the potential for using WC-LST models with and without low-resolution population data to estimate residential WC for two spatial resolutions: Landsat TIR moderate resolution (100 m), and MODIS TIR low resolution (1000 m). Residential WC data is measured based on readings from water meters of 28,000 individual houses. Results: The method performs better without the low-spatial resolution population data. The use of similar spatial resolution data or higher to Landsat 8 TIR (100 m) is a prerequisite for robust WC estimation. Although the method can easily be modified and applied in areas where no estimated water consumption data is available, using the regression equation might result in a poor result due to the use of different water supply sources as demonstrated for the periphery of Khan Younis city.