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 spatially to produce the monthly ≈5km product.
This dataset was produced by Harry Gibson and Daniel Weiss of the Malaria Atlas Project (Big Data Institute, University of Oxford, United Kingdom, [http://www.map.ox.ac.uk/] (http://www.map.ox.ac.uk/)).
该增强植被指数（EVI）产品的基础数据集是MODIS BRDF校正图像（MCD43B4），使用Weiss等人（2014）中概述的方法填补了该图像的缺口，以消除由云层等因素造成的数据缺失。然后将无间隙输出在时间和空间上进行汇总，产生每月的≈5公里产品。
该数据集由Malaria Atlas项目的Harry Gibson和Daniel Weiss制作（英国牛津大学大数据研究所，[http://www.map.ox.ac.uk/] （http://www.map.ox.ac.uk/））。
Dataset Availability
2001-02-01T00:00:00 - 2015-06-01T00:00:00
Dataset Provider
Oxford Malaria Atlas Project
Collection Snippet
ee.ImageCollection("Oxford/MAP/EVI_5km_Monthly")
Resolution
5000 meters
Bands Table
| Name | Description | Min* | Max* | Units |
|---|---|---|---|---|
| Mean | The mean value of the Enhanced Vegetation Index for each aggregated pixel. | 0 | 1 | |
| FilledProportion | A quality control band that indicates the percentage of each resulting pixel that was comprised of raw data (as opposed to gap-filled estimates). | 0 | 100 | % |
* = Values are estimated
数据引用：
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.
代码：
var dataset = ee.ImageCollection('Oxford/MAP/EVI_5km_Monthly')
.filter(ee.Filter.date('2015-01-01', '2015-12-31'));
var evi = dataset.select('Mean');
var eviVis = {
min: 0.0,
max: 1.0,
palette: [
'ffffff', 'fcd163', '99b718', '66a000', '3e8601', '207401', '056201',
'004c00', '011301'
],
};
Map.setCenter(-60.5, -20.0, 2);
Map.addLayer(evi, eviVis, 'EVI');
