4.7 Article

Land surface phenology as an indicator of biodiversity patterns

Journal

ECOLOGICAL INDICATORS
Volume 64, Issue -, Pages 281-288

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2016.01.007

Keywords

Biodiversity; Floristic similarity; Image fusion; Landsat; MODIS; Phenologic similarity; Spectral vegetation indices; Visible atmospherically resistant index

Funding

  1. U.S. National Science Foundation (NSF) [Macrosystems Biology and Dynamics of Coupled Natural and Human Systems (CNH) programs, Office of International Science and Engineering]
  2. Michigan AgBioResearch

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With the rapid decline in biodiversity worldwide it is imperative to develop procedures for assessing changes in biodiversity across space. The synoptic view provided by imaging remote sensors constitutes a suitable approach for analyzing biodiversity from local to regional scales. A procedure based on the close relationship between floristic similarity and the similarity in land surface phenology was recently developed and successfully applied to assess diversity patterns using time series imagery acquired by the Moderate Resolution Imaging Spectro-radiometer (MODIS). However, as it depends on high temporal resolution remotely sensed data (e.g., MODIS), the procedure is constrained by the coarse spatial resolution characterizing these high temporal resolution data. Using an optimized technique for image fusion, we combined high temporal resolution data acquired by the MODIS sensor system with moderate spatial resolution data acquired by the Landsat TM/ETM+ sensor systems. Our results show that the MODIS/Landsat data fusion allows the characterization of land surface phenology at higher spatial resolutions, which better corresponded with information acquired within vegetation survey plots established in temperate montane forests located in Wolong Nature Reserve, Sichuan Province, China. As such, the procedure is useful for capturing changes in biodiversity induced by disturbances operating at large spatial scales and constitutes a suitable tool for monitoring and managing biodiversity. (C) 2016 Elsevier Ltd. All rights reserved.

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