Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia
Despite the sparse distribution of meteorological stations and issues with missing data, vector-borne disease studies in Ethiopia have been commonly conducted based on the relationships between these diseases and ground-based in situ measurements of climate variation. High temporal and spatial resol...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/5/1316 |
| _version_ | 1798039383426727936 |
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| author | Woubet G. Alemu Michael C. Wimberly |
| author_facet | Woubet G. Alemu Michael C. Wimberly |
| author_sort | Woubet G. Alemu |
| collection | DOAJ |
| description | Despite the sparse distribution of meteorological stations and issues with missing data, vector-borne disease studies in Ethiopia have been commonly conducted based on the relationships between these diseases and ground-based in situ measurements of climate variation. High temporal and spatial resolution satellite-based remote-sensing data is a potential alternative to address this problem. In this study, we evaluated the accuracy of daily gridded temperature and rainfall datasets obtained from satellite remote sensing or spatial interpolation of ground-based observations in relation to data from 22 meteorological stations in Amhara Region, Ethiopia, for 2003−2016. Famine Early Warning Systems Network (FEWS-Net) Land Data Assimilation System (FLDAS) interpolated temperature showed the lowest bias (mean error (ME) ≈ 1−3 °C), and error (mean absolute error (MAE) ≈ 1−3 °C), and the highest correlation with day-to-day variability of station temperature (COR ≈ 0.7−0.8). In contrast, temperature retrievals from the blended Advanced Microwave Scanning Radiometer on Earth Observing Satellite (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) passive microwave and Moderate-resolution Imaging Spectroradiometer (MODIS) land-surface temperature data had higher bias and error. Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) rainfall showed the least bias and error (ME ≈ −0.2−0.2 mm, MAE ≈ 0.5−2 mm), and the best agreement (COR ≈ 0.8), with station rainfall data. In contrast FLDAS had the higher bias and error and the lowest agreement and Global Precipitation Mission/Tropical Rainfall Measurement Mission (GPM/TRMM) data were intermediate. This information can inform the selection of geospatial data products for use in climate and disease research and applications. |
| first_indexed | 2024-04-11T21:53:08Z |
| format | Article |
| id | doaj.art-446c4f2ea76f4d948475854218706519 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:53:08Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-446c4f2ea76f4d9484758542187065192022-12-22T04:01:11ZengMDPI AGSensors1424-82202020-02-01205131610.3390/s20051316s20051316Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, EthiopiaWoubet G. Alemu0Michael C. Wimberly1Department of Earth and Environment, Florida International University, Miami, FL 33199, USADepartment of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK 73019, USADespite the sparse distribution of meteorological stations and issues with missing data, vector-borne disease studies in Ethiopia have been commonly conducted based on the relationships between these diseases and ground-based in situ measurements of climate variation. High temporal and spatial resolution satellite-based remote-sensing data is a potential alternative to address this problem. In this study, we evaluated the accuracy of daily gridded temperature and rainfall datasets obtained from satellite remote sensing or spatial interpolation of ground-based observations in relation to data from 22 meteorological stations in Amhara Region, Ethiopia, for 2003−2016. Famine Early Warning Systems Network (FEWS-Net) Land Data Assimilation System (FLDAS) interpolated temperature showed the lowest bias (mean error (ME) ≈ 1−3 °C), and error (mean absolute error (MAE) ≈ 1−3 °C), and the highest correlation with day-to-day variability of station temperature (COR ≈ 0.7−0.8). In contrast, temperature retrievals from the blended Advanced Microwave Scanning Radiometer on Earth Observing Satellite (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) passive microwave and Moderate-resolution Imaging Spectroradiometer (MODIS) land-surface temperature data had higher bias and error. Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) rainfall showed the least bias and error (ME ≈ −0.2−0.2 mm, MAE ≈ 0.5−2 mm), and the best agreement (COR ≈ 0.8), with station rainfall data. In contrast FLDAS had the higher bias and error and the lowest agreement and Global Precipitation Mission/Tropical Rainfall Measurement Mission (GPM/TRMM) data were intermediate. This information can inform the selection of geospatial data products for use in climate and disease research and applications.https://www.mdpi.com/1424-8220/20/5/1316accuracy assessmentenvironmental dataepidemiaamsr-eamsr2fldasmodistrmm/gpmchirpsepidemiological data |
| spellingShingle | Woubet G. Alemu Michael C. Wimberly Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia Sensors accuracy assessment environmental data epidemia amsr-e amsr2 fldas modis trmm/gpm chirps epidemiological data |
| title | Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia |
| title_full | Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia |
| title_fullStr | Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia |
| title_full_unstemmed | Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia |
| title_short | Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia |
| title_sort | evaluation of remotely sensed and interpolated environmental datasets for vector borne disease monitoring using in situ observations over the amhara region ethiopia |
| topic | accuracy assessment environmental data epidemia amsr-e amsr2 fldas modis trmm/gpm chirps epidemiological data |
| url | https://www.mdpi.com/1424-8220/20/5/1316 |
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