The underlying dataset for this Enhanced Vegetation Index (EVI) product is MODIS BRDF-corrected imagery (MCD43B4), which was gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by factors such as cloud cover. Gap-free outputs were then aggregated temporally and …
The underlying dataset for this landcover product is the IGBP layer found within the MODIS annual landcover product (MCD12Q1). This data was converted from its categorical format, which has a ≈500 meter resolution, to a fractional product indicating the integer percentage (0-100) of the output …
The underlying dataset for this daytime product is MODIS land surface temperature data (MOD11A2), which was gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by factors such as cloud cover. Gap-free outputs were then aggregated temporally and spatially …
The underlying dataset for this nighttime product is MODIS land surface temperature data (MOD11A2), which was gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by factors such as cloud cover. Gap-free outputs were then aggregated temporally and spatially …
This gap-filled Tasseled Cap Brightness (TCB) dataset was created by applying the tasseled-cap equations defined in Lobser and Cohen (2007) to MODIS BRDF-corrected imagery (MCD43B4). The resulting data were gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by …
This gap-filled Tasseled Cap Wetness (TCW) dataset was created by applying the tasseled-cap equations defined in Lobser and Cohen (2007) to MODIS BRDF-corrected imagery (MCD43B4). The resulting data were gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by …
This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometer or …
This global accessibility map enumerates land-based travel time (in minutes) to the nearest hospital or clinic for all areas between 85 degrees north and 60 degrees south for a nominal year 2019. It also includes "walking-only" travel time, using non-motorized means of transportation only. Major …
This global friction surface enumerates land-based travel speed for all land pixels between 85 degrees north and 60 degrees south for a nominal year 2019. It also includes "walking-only" travel speed, using non-motorized means of transportation only. This map was produced through a collaboration between …
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["This collection provides various gap-filled environmental datasets, including EVI, LST, TCB, and TCW, derived from MODIS imagery and processed using the approach outlined in Weiss et al.(2014)."],["It includes a fractional landcover product based on the IGBP layer from MODIS annual landcover data (MCD12Q1), representing the percentage of land cover types within each pixel."],["Additionally, it offers global accessibility maps for cities and healthcare facilities, indicating travel time to these locations based on land-based travel speed data."],["The datasets were developed by the Malaria Atlas Project (MAP) and are intended for research and analysis related to environmental monitoring, malaria epidemiology, and accessibility studies."]]],["The content describes various datasets from the Oxford Malaria Atlas Project (MAP). These datasets include: Enhanced Vegetation Index (EVI), Fractional Landcover, Daytime and Nighttime Land Surface Temperature (LST), Tasseled Cap Brightness (TCB), and Tasseled Cap Wetness (TCW). Each dataset was created using MODIS imagery and gap-filled to eliminate missing data. Also, accessibility data for travel time to cities (2015) and healthcare (2019), as well as a global friction surface map (2019), are presented.\n"]]