- Dataset Availability
- 2006-01-24T00:00:00Z–2011-05-13T00:00:00Z
- Dataset Provider
- Conservation Science Partners
- Earth Engine Snippet
-
ee.Image("CSP/ERGo/1_0/Global/SRTM_mTPI") - Tags
Description
The mTPI distinguishes ridge from valley forms. It is calculated using elevation data for each location subtracted by the mean elevation within a neighborhood. mTPI uses moving windows of radius (km): 115.8, 89.9, 35.5, 13.1, 5.6, 2.8, and 1.2. It is based on the 30m SRTM DEM (available in EE as USGS/SRTMGL1_003).
The Conservation Science Partners (CSP) Ecologically Relevant Geomorphology (ERGo) Datasets, Landforms and Physiography contain detailed, multi-scale data on landforms and physiographic (aka land facet) patterns. Although there are many potential uses of these data, the original purpose for these data was to develop an ecologically relevant classification and map of landforms and physiographic classes that are suitable for climate adaptation planning. Because there is large uncertainty associated with future climate conditions and even more uncertainty around ecological responses, providing information about what is unlikely to change offers a strong foundation for managers to build robust climate adaptation plans. The quantification of these features of the landscape is sensitive to the resolution, so we provide the highest resolution possible given the extent and characteristics of a given index.
Bands
Resolution
270 meters
Bands
| Name | Units | Min | Max | Description |
|---|---|---|---|---|
elevation |
m | -8129* | 7905* | SRTM-derived mTPI ranging from negative (valleys) to positive (ridges) values |
Terms of Use
Terms of Use
Citations
Theobald, D. M., Harrison-Atlas, D., Monahan, W. B., & Albano, C. M. (2015). Ecologically-relevant maps of landforms and physiographic diversity for climate adaptation planning. PloS one, 10(12), e0143619
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.Image('CSP/ERGo/1_0/Global/SRTM_mTPI'); var srtmMtpi = dataset.select('elevation'); var srtmMtpiVis = { min: -200.0, max: 200.0, palette: ['0b1eff', '4be450', 'fffca4', 'ffa011', 'ff0000'], }; Map.setCenter(-105.8636, 40.3439, 11); Map.addLayer(srtmMtpi, srtmMtpiVis, 'SRTM mTPI');