多分辨率量化全球生境的空间异质性数据集

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此星光明 发表于 2023/05/28 17:32:36 2023/05/28
【摘要】 全球栖息地异质性这些数据集包含14个指标，根据中分辨率成像分光仪（MODIS）获取的增强植被指数（EVI）图像的纹理特征，以多种分辨率量化全球生境的空间异质性。关于这些指标的更多信息以及对其在生物多样性建模中的效用的评价。该数据集以1公里、5公里和25公里的分辨率生成，这里只列出了1公里的资产，只需根据需要用_5公里和_25公里替换_1公里。数据集细节在30角秒（赤道约1公里）、2.5角分（...

全球栖息地异质性
这些数据集包含14个指标，根据中分辨率成像分光仪（MODIS）获取的增强植被指数（EVI）图像的纹理特征，以多种分辨率量化全球生境的空间异质性。关于这些指标的更多信息以及对其在生物多样性建模中的效用的评价。该数据集以1公里、5公里和25公里的分辨率生成，这里只列出了1公里的资产，只需根据需要用_5公里和_25公里替换_1公里。

数据集细节
在30角秒（赤道约1公里）、2.5角分（约5公里）和12.5角分（约25公里）的分辨率下，有6个一阶和8个二阶纹理测量。一阶纹理测量是描述EVI值频率分布的统计数据，测量一个地区内EVI的组成变化。二阶纹理测量是一个区域内像素对之间不同EVI组合的出现概率的统计，因此也反映了EVI值的空间排列和依赖性。

First-order texture measures

Metric Measure Value Range Expected Relationship with Heterogeneity
Coefficient of variation Normalized dispersion of EVI >=0 Positive
Evenness Evenness of EVI >=0; <=1 Positive
Range Range of EVI >=0 Positive
Shannon Diversity of EVI >=0; <=ln(max # of different EVI) Positive
Simpson Diversity of EVI >=0; <=1-1/(max # of different EVI) Positive
Standard deviation Dispersion of EVI >=0 Positive

Second-order texture measures

Metric Measure Value Range Expected Relationship with Heterogeneity
Contrast Exponentially weighted difference in EVI between adjacent pixels >=0 Positive
Correlation Linear dependency of EVI on adjacent pixels >=-1; <=1 Nonlinear
Dissimilarity Difference in EVI between adjacent pixels >=0 Positive
Entropy Disorderliness of EVI >=0 Positive
Homogeneity Similarity of EVI between adjacent pixels >=0; <=1 Negative
Maximum Dominance of EVI combinations between adjacent pixels >=0; <=1 Negative
Uniformity Orderliness of EVI >=0; <=1 Negative
Variance Dispersion of EVI combinations between adjacent pixels >=0 Positive

All data layers are in WGS84 projection and have a spatial extent from 85ºN - 60ºS and from 180ºW - 180ºE. The pixel values of the data layers should be mulitplied by 0.0001 to obtain the actual values of the metrics.

Dataset Citation

Tuanmu, M.-N. and W. Jetz. (2015) A global, remote sensing-based characterization of terrestrial habitat heterogeneity
for biodiversity and ecosystem modeling. Global Ecology and Biogeography. DOI: 10.1111/geb.12365.

Project Website: Global 1-km Consensus Land Cover - EarthEnv

App Website: App link here

Curated by: Samapriya Roy

Keywords: Earthenv, habitat heterogeneity, shannon, simpson, pielou, dissimilarity, homogeneity, variance, contrast

Last updated: 2021-05-09

Paper Citation

Tuanmu, M.-N. and W. Jetz. (2015) A global, remote sensing-based characterization of terrestrial habitat heterogeneity
for biodiversity and ecosystem modeling. Global Ecology and Biogeography. DOI: 10.1111/geb.12365.

Earth Engine Snippet

var cov = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/coefficient_of_variation_1km");
var contrast = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/contrast_1km");
var corr = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/correlation_1km");
var dissimilarity = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/dissimilarity_1km");
var entropy = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/entropy_1km");
var homogeneity = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/homogeneity_1km");
var maximum = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/maximum_1km");
var mean = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/mean_1km");
var pielou = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/pielou_1km");
var range = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/range_1km");
var shannon = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/shannon_1km");
var simpson = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/simpson_1km");
var sd = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/standard_deviation_1km");
var uniformity = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/uniformity_1km");
var variance = ee.Image("projects/sat-io/open-datasets/global_habitat_heterogeneity/variance_1km");

Sample Script: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:earthenv-bd-ecosystems-clim-layers/GLOBAL-HABITAT-HETEROGENEITY

License

Global Habitat Heterogeneity Metrics Version 1 by Tuanmu & Jetz is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Permissions beyond the scope of this license may be available at Global 1-km Consensus Land Cover - EarthEnv.

Dataset Citation

Tuanmu, M.-N. and W. Jetz. (2015) A global, remote sensing-based characterization of terrestrial habitat heterogeneity
for biodiversity and ecosystem modeling. Global Ecology and Biogeography. DOI: 10.1111/geb.12365.

Project Website: Global 1-km Consensus Land Cover - EarthEnv

App Website: App link here

Curated by: Samapriya Roy

Keywords: Earthenv, habitat heterogeneity, shannon, simpson, pielou, dissimilarity, homogeneity, variance, contrast

Last updated: 2021-05-09

 

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