Google Earth Engine ——数据全解析专辑(US NED CHILI /Landforms/Topographic Diversity)美国DEM地形10米分辨率数据集

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简介: Google Earth Engine ——数据全解析专辑(US NED CHILI /Landforms/Topographic Diversity)美国DEM地形10米分辨率数据集

本次介绍三个数据集


CHILI

CHILI is a surrogate for effects of insolation and topographic shading on evapotranspiration represented by calculating insolation at early afternoon, sun altitude equivalent to equinox. It is based on the USGS's 10m NED DEM (available in EE as USGS/NED).

The ALOS Landform dataset provides landform classes created by combining the Continuous Heat-Insolation Load Index (CHILI) and the multi-scale Topographic Position Index (mTPI) datasets. It is based on the USGS's 10m NED DEM (available in EE as USGS/NED).


Topographic diversity (D) is a surrogate variable that represents the variety of temperature and moisture conditions available to species as local habitats. It expresses the logic that a higher variety of topo-climate niches should support higher diversity (especially plant) and support species persistence given climatic change.

To calculate D, the multi-scale Topographic Position Index (mTPI), being a dominant control of soil moisture (T), was used for measuring hillslope position. The mTPI was combined with the square-root transform for mTPI>0 (T’) and with the standard deviation of the Continuous Heat-Insolation Load Index (CHILI), calculated at multiple scales (C’) as: D = 1 – ((1-T’) * (1-C’). 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.


CHILI是日照和地形遮挡对蒸发量影响的替代物,通过计算下午早期的日照,太阳高度相当于赤道。它基于美国地质调查局的10米NED DEM(在EE中可作为USGS/NED)。

ALOS地貌数据集提供了通过结合连续热-日照负荷指数(CHILI)和多尺度地形位置指数(mTPI)数据集创建的地貌类别。它是基于美国地质调查局的10米NED DEM(在EE中以USGS/NED的形式提供)。


地形多样性(D)是一个替代变量,代表了物种作为当地栖息地可用的各种温度和湿度条件。它所表达的逻辑是,较多的地形气候龛位应支持较高的多样性(尤其是植物),并在气候变化的情况下支持物种的持续存在。


为了计算D,多尺度地形位置指数(mTPI),作为土壤水分(T)的主要控制因素,被用于测量山坡位置。mTPI与mTPI>0时的方根变换(T')和连续热阻负荷指数(CHILI)的标准差相结合,在多尺度下计算(C')。D=1-((1-T')*(1-C')。它是基于美国地质调查局的10米NED DEM(在EE中以USGS/NED的名义提供)。


保护科学伙伴(CSP)的生态相关地貌(ERGo)数据集、地貌和地形学包含详细的、多尺度的地貌和地形学(又称土地面)模式数据。尽管这些数据有许多潜在的用途,但这些数据的最初目的是开发适合气候适应规划的生态相关的地貌和自然地理类别的分类和地图。因为未来的气候条件有很大的不确定性,围绕生态反应的不确定性甚至更大,提供有关不太可能改变的信息,为管理者建立强大的气候适应计划提供了坚实的基础。景观的这些特征的量化对分辨率很敏感,所以我们在给定指数的范围和特征的情况下,提供尽可能高的分辨率。


US NED CHILI (Continuous Heat-Insolation Load Index)

Dataset Availability

2006-01-24T00:00:00 - 2011-05-13T00:00:00

Dataset Provider

Conservation Science Partners

Collection Snippet

ee.Image("CSP/ERGo/1_0/US/CHILI")

Resolution

10 meters

Bands Table

Name Description Min Max
constant NED-derived CHILI index ranging from 0 (very cool) to 255 (very warm). This was rescaled from the [0,1] range in the publication. 0 255

var dataset = ee.Image('CSP/ERGo/1_0/US/CHILI');
var usChili = dataset.select('constant');
var usChiliVis = {
  min: 0.0,
  max: 255.0,
};
Map.setCenter(-105.8636, 40.3439, 11);
Map.addLayer(usChili, usChiliVis, 'US CHILI');

US NED Landforms

Dataset Availability

2006-01-24T00:00:00 - 2011-05-13T00:00:00

Dataset Provider

Conservation Science Partners

Collection Snippet

Copied

ee.Image("CSP/ERGo/1_0/US/landforms")

Resolution

10 meters

Bands Table

Name Description
constant NED-derived landform classes

Class Table: constant

Value Color Color Value Description
11 #141414 Peak/ridge (warm)
12 #383838 Peak/ridge
13 #808080 Peak/ridge (cool)
14 #EBEB8F Mountain/divide
15 #F7D311 Cliff
21 #AA0000 Upper slope (warm)
22 #D89382 Upper slope
23 #DDC9C9 Upper slope (cool)
24 #DCCDCE Upper slope (flat)
31 #1C6330 Lower slope (warm)
32 #68AA63 Lower slope
33 #B5C98E Lower slope (cool)
34 #E1F0E5 Lower slope (flat)
41 #a975ba Valley
42 #6f198c Valley (narrow)
var dataset = ee.Image('CSP/ERGo/1_0/US/landforms');
var landforms = dataset.select('constant');
var landformsVis = {
  min: 11.0,
  max: 42.0,
  palette: [
    '141414', '383838', '808080', 'EBEB8F', 'F7D311', 'AA0000', 'D89382',
    'DDC9C9', 'DCCDCE', '1C6330', '68AA63', 'B5C98E', 'E1F0E5', 'a975ba',
    '6f198c'
  ],
};
Map.setCenter(-105.58, 40.5498, 11);
Map.addLayer(landforms, landformsVis, 'Landforms');


US NED Topographic Diversity

Dataset Availability

2006-01-24T00:00:00 - 2011-05-13T00:00:00

var dataset = ee.Image('CSP/ERGo/1_0/US/lithology');
var lithology = dataset.select('b1');
var lithologyVis = {
  min: 0.0,
  max: 20.0,
  palette: [
    '356EFF', 'ACB6DA', 'D6B879', '313131', 'EDA800', '616161', 'D6D6D6',
    'D0DDAE', 'B8D279', 'D5D378', '141414', '6DB155', '9B6D55', 'FEEEC9',
    'D6B879', '00B7EC', 'FFDA90', 'F8B28C'
  ],
};
Map.setCenter(-105.8636, 40.3439, 11);
Map.addLayer(lithology, lithologyVis, 'Lithology');

Dataset Provider

Conservation Science Partners

Collection Snippet

ee.Image("CSP/ERGo/1_0/US/topoDiversity")

Resolution

90 meters

Bands Table

Name Description Min* Max*
constant NED-derived topographic diversity 0 1

* = Values are estimated


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