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The Impact of Urbanization on Water ...
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Kamau, Lucy N.,
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The Impact of Urbanization on Water Scarcity and Waterborne Diseases in Eastern Africa: A Case Study of Nairobi /
Record Type:
Electronic resources : Monograph/item
Title/Author:
The Impact of Urbanization on Water Scarcity and Waterborne Diseases in Eastern Africa: A Case Study of Nairobi // Lucy N Kamau.
Author:
Kamau, Lucy N.,
Description:
1 electronic resource (98 pages)
Notes:
Source: Masters Abstracts International, Volume: 86-11.
Contained By:
Masters Abstracts International86-11.
Subject:
Environmental engineering. -
Online resource:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31997106
ISBN:
9798315747598
The Impact of Urbanization on Water Scarcity and Waterborne Diseases in Eastern Africa: A Case Study of Nairobi /
Kamau, Lucy N.,
The Impact of Urbanization on Water Scarcity and Waterborne Diseases in Eastern Africa: A Case Study of Nairobi /
Lucy N Kamau. - 1 electronic resource (98 pages)
Source: Masters Abstracts International, Volume: 86-11.
Urbanization in Eastern African cities has rapidly accelerated, placing immense strain on existing water infrastructure and sanitation systems. In Nairobi, this has resulted in spatial disparities in access to clean water and heightened vulnerability to waterborne disease risks. The study aimed to (1) assess the impact of urbanization on water scarcity and waterborne diseases in Nairobi using geospatial analysis and remote sensing (2) quantify urbanization trends 1999-2024 (3) identify spatio-temporal water scarcity hotspots for the years 2019 and 2024 (4) model waterborne disease risk maps for 2019 and 2024 (5) Overlay disease risk map with hospitals. To quantify urbanization for the years 1999-2014, LULC was classified using Random Forest classification in GEE from Landsat imagery. Water scarcity was mapped using a weighted overlay of normalized indicators, including population density, water access, LULC, and the VIIRS socioeconomic vulnerability proxy. Seasonal waterborne disease risk was modeled by integrating precipitation, land surface temperature, and water scarcity layers. Spatial overlay was performed in ArcGIS Pro to assess the proximity of healthcare amenities to high-risk zones. Results show that built-up area expanded by over 180% between 1999 and 2024, replacing forests and grasslands/bare soils. Water scarcity intensified with over 2.3 million people living in 'Severe' and 'Extreme' scarcity zones by 2024, a significant rise from 1.9 million in 2019. High disease risk areas during the dry season increased by over 800,000 people (a 43.45% rise), exceeding 2.6 million by 2024. During the wet season, localized flooding and sewer overflows contributed to a 36.94% rise in high-risk population, highlighting how seasonal extremes amplify disease vulnerability in Nairobi. Spatial overlay revealed that while health facilities are geographically present in high-risk zones, access remains inequitable due to congestion, resource constraints, and affordability barriers. Rapid urbanization in Nairobi has intensified water scarcity and waterborne disease risks, especially in informal settlements/low-income communities where water infrastructure lags behind population growth. These findings reinforce the value of GIS and remote sensing in supporting routine-based monitoring of water scarcity and disease risk, enabling public health interventions in rapidly urbanizing cities like Nairobi.
English
ISBN: 9798315747598Subjects--Topical Terms:
548583
Environmental engineering.
Subjects--Index Terms:
Nairobi
The Impact of Urbanization on Water Scarcity and Waterborne Diseases in Eastern Africa: A Case Study of Nairobi /
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Urbanization in Eastern African cities has rapidly accelerated, placing immense strain on existing water infrastructure and sanitation systems. In Nairobi, this has resulted in spatial disparities in access to clean water and heightened vulnerability to waterborne disease risks. The study aimed to (1) assess the impact of urbanization on water scarcity and waterborne diseases in Nairobi using geospatial analysis and remote sensing (2) quantify urbanization trends 1999-2024 (3) identify spatio-temporal water scarcity hotspots for the years 2019 and 2024 (4) model waterborne disease risk maps for 2019 and 2024 (5) Overlay disease risk map with hospitals. To quantify urbanization for the years 1999-2014, LULC was classified using Random Forest classification in GEE from Landsat imagery. Water scarcity was mapped using a weighted overlay of normalized indicators, including population density, water access, LULC, and the VIIRS socioeconomic vulnerability proxy. Seasonal waterborne disease risk was modeled by integrating precipitation, land surface temperature, and water scarcity layers. Spatial overlay was performed in ArcGIS Pro to assess the proximity of healthcare amenities to high-risk zones. Results show that built-up area expanded by over 180% between 1999 and 2024, replacing forests and grasslands/bare soils. Water scarcity intensified with over 2.3 million people living in 'Severe' and 'Extreme' scarcity zones by 2024, a significant rise from 1.9 million in 2019. High disease risk areas during the dry season increased by over 800,000 people (a 43.45% rise), exceeding 2.6 million by 2024. During the wet season, localized flooding and sewer overflows contributed to a 36.94% rise in high-risk population, highlighting how seasonal extremes amplify disease vulnerability in Nairobi. Spatial overlay revealed that while health facilities are geographically present in high-risk zones, access remains inequitable due to congestion, resource constraints, and affordability barriers. Rapid urbanization in Nairobi has intensified water scarcity and waterborne disease risks, especially in informal settlements/low-income communities where water infrastructure lags behind population growth. These findings reinforce the value of GIS and remote sensing in supporting routine-based monitoring of water scarcity and disease risk, enabling public health interventions in rapidly urbanizing cities like Nairobi.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31997106
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