US NED mTPI (Multi-Scale Topographic Position Index)

CSP/ERGo/1_0/US/mTPI
Dataset Availability
2006-01-24T00:00:00Z–2011-05-13T00:00:00Z
Dataset Provider
Earth Engine Snippet
ee.Image("CSP/ERGo/1_0/US/mTPI")

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 USGS's 10m NED DEM (available in EE as USGS/NED).

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 -378 493

NED-derived mTPI ranging from negative (valleys) to positive (ridges) values

Terms of Use

Terms of Use

CC-BY-NC-SA-4.0

Citations

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/US/mTPI');
var usMtpi = dataset.select('elevation');
var usMtpiVis = {
  min: -200.0,
  max: 200.0,
  palette: ['0b1eff', '4be450', 'fffca4', 'ffa011', 'ff0000'],
};
Map.setCenter(-105.8636, 40.3439, 11);
Map.addLayer(usMtpi, usMtpiVis, 'US mTPI');
Open in Code Editor