Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria
Lagos, Nigeria, is considered a rapidly growing urban hub. This study focuses on an urban development characterization with remote sensing-based variables for Lagos as well as understanding spatio-temporal precipitation responses to the changing intensity of urban development. Initially, a harmonic...
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MDPI AG
2022-06-01
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Series: | Urban Science |
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Online Access: | https://www.mdpi.com/2413-8851/6/2/40 |
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author | Alamin Molla Liping Di Liying Guo Chen Zhang Fei Chen |
author_facet | Alamin Molla Liping Di Liying Guo Chen Zhang Fei Chen |
author_sort | Alamin Molla |
collection | DOAJ |
description | Lagos, Nigeria, is considered a rapidly growing urban hub. This study focuses on an urban development characterization with remote sensing-based variables for Lagos as well as understanding spatio-temporal precipitation responses to the changing intensity of urban development. Initially, a harmonic analysis showed an increase in yearly precipitation of about 3 mm from 1992 to 2018 for the lower bound of the fitted curve and about 2 mm for the upper bound. The yearly total precipitation revealed no significant trend based on the Mann–Kendall trend test. Subsequent analyses first involved characterizing urbanization based on nighttime light and population density data and then combined them together for the final analysis. Each time, the study area was subdivided into four zones: Zone 0, Zone 1, Zone 2, and Zone 3, which refer to non-urbanized, low-urbanized, mid-urbanized, and highly urbanized regions, respectively. The results from the Google Earth Engine-based analysis uncovered that only Zone 1 has a statistical monotonic increasing precipitation trend (Tau 0.29) with a 0.03 significance level when the combined criteria were applied. There is about a 200 mm precipitation increase in Zone 1. Insignificant patterns for the other three zones (Zone 2, Zone 3, and Zone 4) indicate that these trends are not consistent, they might change over time, and fluctuate heavily. |
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issn | 2413-8851 |
language | English |
last_indexed | 2024-03-09T22:18:25Z |
publishDate | 2022-06-01 |
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series | Urban Science |
spelling | doaj.art-a1e23de34b3f4359b786f9ba31c0fd5b2023-11-23T19:19:45ZengMDPI AGUrban Science2413-88512022-06-01624010.3390/urbansci6020040Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, NigeriaAlamin Molla0Liping Di1Liying Guo2Chen Zhang3Fei Chen4Center for Spatial Information Science and System (CSISS), George Mason University, Fairfax, VA 22030, USACenter for Spatial Information Science and System (CSISS), George Mason University, Fairfax, VA 22030, USACenter for Spatial Information Science and System (CSISS), George Mason University, Fairfax, VA 22030, USACenter for Spatial Information Science and System (CSISS), George Mason University, Fairfax, VA 22030, USANational Center for Atmospheric Research (NCAR), Boulder, CO 80307, USALagos, Nigeria, is considered a rapidly growing urban hub. This study focuses on an urban development characterization with remote sensing-based variables for Lagos as well as understanding spatio-temporal precipitation responses to the changing intensity of urban development. Initially, a harmonic analysis showed an increase in yearly precipitation of about 3 mm from 1992 to 2018 for the lower bound of the fitted curve and about 2 mm for the upper bound. The yearly total precipitation revealed no significant trend based on the Mann–Kendall trend test. Subsequent analyses first involved characterizing urbanization based on nighttime light and population density data and then combined them together for the final analysis. Each time, the study area was subdivided into four zones: Zone 0, Zone 1, Zone 2, and Zone 3, which refer to non-urbanized, low-urbanized, mid-urbanized, and highly urbanized regions, respectively. The results from the Google Earth Engine-based analysis uncovered that only Zone 1 has a statistical monotonic increasing precipitation trend (Tau 0.29) with a 0.03 significance level when the combined criteria were applied. There is about a 200 mm precipitation increase in Zone 1. Insignificant patterns for the other three zones (Zone 2, Zone 3, and Zone 4) indicate that these trends are not consistent, they might change over time, and fluctuate heavily.https://www.mdpi.com/2413-8851/6/2/40urbanizationnighttime lightpopulation densityCHIRPS precipitationGoogle Earth EngineMann–Kendall trend test |
spellingShingle | Alamin Molla Liping Di Liying Guo Chen Zhang Fei Chen Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria Urban Science urbanization nighttime light population density CHIRPS precipitation Google Earth Engine Mann–Kendall trend test |
title | Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria |
title_full | Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria |
title_fullStr | Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria |
title_full_unstemmed | Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria |
title_short | Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria |
title_sort | spatio temporal responses of precipitation to urbanization with google earth engine a case study for lagos nigeria |
topic | urbanization nighttime light population density CHIRPS precipitation Google Earth Engine Mann–Kendall trend test |
url | https://www.mdpi.com/2413-8851/6/2/40 |
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