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    <identifier>10.57760/sciencedb.26017</identifier>
    <datestamp>2025-06-06T14:40:55Z</datestamp>
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  <dc:date>2025-06-06</dc:date>
  <dc:title>Ecological Health Index (EHI), Ecological Risk Index (ERI), Ecosystem Service Index (ESsI) (2000/2005/2010/2015/2020)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.26017</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset includes the Ecological Health Index (EHI), Ecological Risk Index (ERI), Ecosystem Service Index (ESsI), and Ecological Security Index (ESI) for the source regions of the Yangtze and Yellow Rivers from 2000 to 2020. All data are in raster format.Ecological Risk Index (ERI) is a composite indicator, comprising Drought Risk (SPEI + NDMI + SWI), Landscape Pattern Risk (Fragmentation Degree + Separation Degree + Fractal Dimension), and Human Activity Intensity (HAILS). ​The weights are determined using the entropy method, a standardized and robust approach.​​​Ecosystem Health Index (EHI)​​ employs the ​VOR Model, divided into Vigor (NDVI), Organization (a combination of landscape indices), and Resilience (InVEST Habitat Quality). Notably, the weighting within the Organization component is highly detailed (landscape heterogeneity 0.4 / landscape connectivity 0.4 / landscape shape 0.2).​Ecosystem Service Index (ESsI)​​ focuses on five key services: Windbreak and Sand Stabilization (RWEQ), Water Yield (InVEST), Carbon Storage (InVEST), Soil Conservation (a modified InVEST version), and Water Conservation Capability (calculated using Terrain Index and Saturated Hydraulic Conductivity). ​The weights are determined via a combined AHP + Entropy Method approach, effectively integrating objective data with expert knowledge.​​​Ecological Security Index (ESI) is a coupled outcome of the preceding three indices:​​&amp;nbsp;ESI = (EHI &amp;times; ESsI / ERI)1/2. ​This formula design is sophisticated, clearly embodying the logic that health and services provide positive contributions to security, while risk exerts a negative constraint.​​Particular attention is warranted for several key technical details:​Spatial Consistency:​​ All data was unified to a ​1km grid​ and the ​Albers projection​ to ensure precision in spatial analysis.​Landscape Risk Calculation:​​ Utilized ​Fragstats output at 5km grids.</dc:description>
  <dc:subject>Ecological Assessment; Ecological Analysis;  ecological environment</dc:subject>
  <dc:creator>Li Zhiyi</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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