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2017.tif
Jan 1, 2022 - Global urban entities (2000–2024): A novel perspective to delineate urban entities based on consistent nighttime light data
TIFF Image - 10.8 MB - MD5: 36746fcf9938e0a00b5d80a4139b6757
2018.tif
Jan 1, 2022 - Global urban entities (2000–2024): A novel perspective to delineate urban entities based on consistent nighttime light data
TIFF Image - 10.8 MB - MD5: 132bc9940a28ded560e5dd3fe5130e96
2019.tif
Jan 1, 2022 - Global urban entities (2000–2024): A novel perspective to delineate urban entities based on consistent nighttime light data
TIFF Image - 10.9 MB - MD5: acd93f45eac7c3ab5a986fba7521d6d2
2020.tif
Jan 1, 2022 - Global urban entities (2000–2024): A novel perspective to delineate urban entities based on consistent nighttime light data
TIFF Image - 10.9 MB - MD5: 07268c38dbf46ee9e3cf7dba21683b42
COVID-19 geovisualizations understanding survey
Jan 1, 2022
Rezk, Ahmed, 2022, "COVID-19 geovisualizations understanding survey", https://doi.org/10.7910/DVN/UBEYLR, Harvard Dataverse, V1
A survey conducted to assess users understanding of four COVID-19 geovisualizations. Map 1: Bing covid tracker Map 2: ECDC covid map Map 3: Johns Hopkins CSSE covid dashboard Map 4: WHO covid dashboard
DATA_COVID-19 geovisualizations.xlsx
Jan 1, 2022 - COVID-19 geovisualizations understanding survey
MS Excel Spreadsheet - 96.9 KB - MD5: b91decc504c450da9ccd8fe48cc38683
readme.pdf
readme.pdf
Dec 21, 2021 - Replication Data for: Measuring Misperceptions?
Adobe PDF - 79.7 KB - MD5: 6712f20c5573753d2128c22dcccec64d
Describes contents of replication file.zip
replication file.zip
Dec 21, 2021 - Replication Data for: Measuring Misperceptions?
ZIP Archive - 2.2 MB - MD5: 73ec8a22f2a6aff14168a3a737adcce1
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