Oxford MAP: Malaria Atlas Project Fractional International Geosphere-Biosphere Programme Landcover

  • This dataset, derived from the MODIS MCD12Q1 product, provides fractional landcover data at 5km resolution.

  • It offers percentage coverage for 17 landcover classes, including an overall dominant class.

  • The data is available annually from 2001 to 2013.

  • This product was created by the Malaria Atlas Project at the University of Oxford.
Oxford/MAP/IGBP_Fractional_Landcover_5km_Annual
Dataset Availability
2001-01-01T00:00:00Z–2013-01-01T00:00:00Z
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("Oxford/MAP/IGBP_Fractional_Landcover_5km_Annual")
Cadence
1 Year
Tags
landcover landuse-landcover map oxford
igbp

Description

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 pixel covered by each of the 17 landcover classes (1 per band).

This dataset was produced by Harry Gibson and Daniel Weiss of the Malaria Atlas Project (Big Data Institute, University of Oxford, United Kingdom, https://malariaatlas.org/).

Bands

Pixel Size
5000 meters

Bands

Name Units Min Max Pixel Size Description
Overall_Class 0 17 meters

Dominant class of each resulting pixel
Water % 0 100 meters

Percentage of water
Evergreen_Needleleaf_Forest % 0 100 meters

Percentage of evergreen needleleaf forest
Evergreen_Broadleaf_Forest % 0 100 meters

Percentage of evergreen broadleaf forest
Deciduous_Needleleaf_Forest % 0 100 meters

Percentage of deciduous needleleaf forest
Deciduous_Broadleaf_Forest % 0 100 meters

Percentage of deciduous broadleaf forest
Mixed_Forest % 0 100 meters

Percentage of mixed forest
Closed_Shrublands % 0 100 meters

Percentage of closed shrublands
Open_Shrublands % 0 100 meters

Percentage of open shrublands
Woody_Savannas % 0 100 meters

Percentage of woody savannas
Savannas % 0 100 meters

Percentage of savannas
Grasslands % 0 100 meters

Percentage of grasslands
Permanent_Wetlands % 0 100 meters

Percentage of permanent wetlands
Croplands % 0 100 meters

Percentage of croplands
Urban_And_Built_Up % 0 100 meters

Percentage of urban and built up
Cropland_Natural_Vegetation_Mosaic % 0 100 meters

Percentage of cropland natural vegetation mosaic
Snow_And_Ice % 0 100 meters

Percentage of snow and ice
Barren_Or_Sparsely_Populated % 0 100 meters

Percentage of barren or sparsely populated
Unclassified % 0 100 meters

Percentage of unclassified
No_Data % 0 100 meters

Percentage of no data

Overall_Class Class Table

Value Color Description
0 #032f7e

Water
1 #02740b

Evergreen_Needleleaf_Fores
2 #02740b

Evergreen_Broadleaf_Forest
3 #8cf502

Deciduous_Needleleaf_Forest
4 #8cf502

Deciduous_Broadleaf_Forest
5 #a4da01

Mixed_Forest
6 #ffbd05

Closed_Shrublands
7 #ffbd05

Open_Shrublands
8 #7a5a02

Woody_Savannas
9 #f0ff0f

Savannas
10 #869b36

Grasslands
11 #6091b4

Permanent_Wetlands
12 #ff4e4e

Croplands
13 #999999

Urban_and_Built-up
14 #ff4e4e

Cropland_Natural_Vegetation_Mosaic
15 #ffffff

Snow_and_Ice
16 #feffc0

Barren_Or_Sparsely_Vegetated
17 #020202

Unclassified

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.

Explore with Earth Engine

Code Editor (JavaScript)

var dataset =
    ee.ImageCollection('Oxford/MAP/IGBP_Fractional_Landcover_5km_Annual')
        .filter(ee.Filter.date('2012-01-01', '2012-12-31'));
var landcover = dataset.select('Overall_Class');
var landcoverVis = {
  min: 1.0,
  max: 19.0,
  palette: [
    '032f7e', '02740b', '02740b', '8cf502', '8cf502', 'a4da01', 'ffbd05',
    'ffbd05', '7a5a02', 'f0ff0f', '869b36', '6091b4', '999999', 'ff4e4e',
    'ff4e4e', 'ffffff', 'feffc0', '020202', '020202'
  ],
};
Map.setCenter(-88.6, 26.4, 1);
Map.addLayer(landcover, landcoverVis, 'Landcover');
Open in Code Editor
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 pixel covered by each of …
Oxford/MAP/IGBP_Fractional_Landcover_5km_Annual, landcover,landuse-landcover,map,oxford
2001-01-01T00:00:00Z/2013-01-01T00:00:00Z
-90 -180 90 180
Google Earth Engine