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A new remote sensing index based on the pressure-state-response framework to assess regional ecological change

  • Xisheng Hu
  • Hanqiu Xu
Research Article
  • 33 Downloads

Abstract

Ecological indicators have widespread appeal to scientists, environmental managers, and the general public. Remote sensing is unique in its capability to record variety of spatio-temporal information on land surface with complete coverage, especially with regard to larger spatial scales, which has been proven to be an effective data source to create indicators to rapidly identify regional eco-environment. In this paper, a new index, remote sensing based ecological index (RSEI) based on the pressure-state-response (PSR) framework, was applied to assess regional ecological changes in Fuzhou City of Fujian Province, southeastern China, using Landsat ETM+/OLI/TIRS images. Taking the advantages of being totally free of artificial interference in the calculation using principal components analysis (PCA) to assign weights of each variable, the RSEI can assess the regional ecological status more objectively and easily. The effectivity of the new index was validated by four approaches, including point-based, classification-based, correlation-based, and urban-rural-gradient-based comparisons. The case study showed that Fuzhou has witnessed ecological improvement during the study period, with the value of RSEI increasing from 0.663 in 2000 to 0.675 in 2016. Spatial variation analysis showed that the poor level of RSEI distributed mostly in the central urban areas, and the ecological degradation was attributed to the fast expansion of the built-up area, characterized by increasing greatly in the value of the normalized differential built up and soil index (NDBSI) in such areas.

Keywords

Remote sensing Principal components analysis Pressure-state-response, Fuzhou City 

Notes

Funding information

This research was funded by the China Postdoctoral Science Foundation (No.2017M610390), the National Natural Science Foundation of China (No.41201100), and the Annual Project of Social Science Planning of Fujian Province (No. FJ2017B090).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Environment and ResourcesFuzhou UniversityFuzhouChina
  2. 2.College of Transportation and Civil EngineeringFujian Agriculture and Forestry UniversityFuzhouChina

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