EVI: Malaria Atlas Project Gap-Filled Enhanced Vegetation Index (Monthly 1km)

  • This dataset, part of the Malaria Atlas Project Catalog, provides monthly 1km Enhanced Vegetation Index (EVI) data derived from gap-filled and BRDF-corrected MODIS imagery.

  • The data covers the period from February 2001 to December 2024 and has a spatial resolution of 5000 meters per pixel.

  • The single band available, Mean, represents the mean EVI value with estimated minimum and maximum values clipped to 0 and 1 respectively.

  • The dataset is available under the CC-BY-NC-SA-4.0 terms of use and should be cited using the provided publication by Weiss et al. (2014).

  • Users can explore this dataset within the Google Earth Engine platform, with sample code provided for visualization in the Code Editor.
projects/malariaatlasproject/assets/EVI_v061/1km/Monthly
info

This dataset is part of a Publisher Catalog, and not managed by Google Earth Engine. Contact The Malaria Atlas Project for bugs or view more datasets from the The Malaria Atlas Project Catalog. Learn more about Publisher datasets.

Catalog Owner
The Malaria Atlas Project
Dataset Availability
2001-02-01T00:00:00Z–2024-12-01T00:00:00Z
Dataset Provider
Contact
The Malaria Atlas Project
Earth Engine Snippet
ee.ImageCollection("projects/malariaatlasproject/assets/EVI_v061/1km/Monthly")
Cadence
1 Month
Tags
evi malariaatlasproject map publisher-dataset vegetation vegetation-indices

Description

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. After gap-filling the data was clipped to thresholds of [0, 1] to ensure valid values.

The gap-filled 8-daily ~1km outputs are then aggregated temporally to produce monthly and annual products.

Bands

Pixel Size
5000 meters

Bands

Name Min Max Pixel Size Description
Mean 0* 1* meters

The mean value of the Enhanced Vegetation Index for each aggregated pixel.
* estimated min or max value

Terms of Use

Terms of Use

CC-BY-NC-SA-4.0

Citations

Citations:

  • Weiss, D.J., P.M. Atkinson, S. Bhatt, B. Mappin, S.I. Hay & P.W. Gething (2014) An effective approach for gap-filling continental scale remotely sensed time-series. ISPRS Journal of Photogrammetry and Remote Sensing, 98, 106-118. doi:10.1016/j.isprsjprs.2014.10.001

Explore with Earth Engine

Code Editor (JavaScript)

var dataset = ee.ImageCollection('projects/malariaatlasproject/assets/EVI_v061/1km/Monthly')
                  .filter(ee.Filter.date('2022-01-01', '2022-12-31'));
var means = dataset.select('Mean');
var visParams = {
  min: 0.0,
  max: 1.0,
  palette: ['ffffff','fcd163','99b718','66a000','3e8601','207401','056201','004c00','011301'],
};
Map.setCenter(0, 0, 2);
Map.addLayer(means, visParams, 'Monthly EVI: Malaria Atlas Project Gap-Filled Enhanced Vegetation Index');
Open in Code Editor
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. After gap-filling the data was clipped to thresholds of [0, 1] to …
projects/malariaatlasproject/assets/EVI_v061/1km/Monthly, evi,malariaatlasproject,map,publisher-dataset,vegetation,vegetation-indices
2001-02-01T00:00:00Z/2024-12-01T00:00:00Z
-90 -180 90 180
Google Earth Engine