@article {Seto:2004:0143-1161:4309,
title = "Linking spatial patterns of bird and butterfly species richness with Landsat TM derived NDVI",
journal = "International Journal of Remote Sensing",
parent_itemid = "infobike://tandf/tres",
publishercode ="tandf",
year = "2004",
volume = "25",
number = "20",
publication date ="2004-10-01T00:00:00",
pages = "4309-4324",
itemtype = "ARTICLE",
issn = "0143-1161",
eissn = "1366-5901",
url = "https://www.ingentaconnect.com/content/tandf/tres/2004/00000025/00000020/art00015",
doi = "doi:10.1080/0143116042000192358",
author = "Seto, K. C. and Fleishman, E. and Fay, J. P. and Betrus, C. J.",
abstract = "The ability to predict spatial patterns of species richness using a few easily measured environmental variables would facilitate timely evaluation of potential impacts of anthropogenic and natural disturbances on biodiversity and ecosystem functions. Two common hypotheses maintain that faunal species richness can be explained in part by either local vegetation heterogeneity or primary productivity. Although remote sensing has long been identified as a potentially powerful source of information on the latter, its principal application to biodiversity studies has been to develop classified vegetation maps at relatively coarse resolution, which then have been used to estimate animal diversity. Although classification schemes can be delineated on the basis of species composition of plants, these schemes generally do not provide information on primary productivity. Furthermore, the classification procedure is a time- and labour-intensive process, yielding results with limited accuracy. To meet decision-making needs and to develop land management strategies, more efficient methods of generating information on the spatial distribution of faunal diversity are needed. This article reports on the potential of predicting species richness using single-date Normalized Difference Vegetation Index (NDVI) derived from Landsat Thematic Mapper (TM). We use NDVI as an indicator of vegetation productivity, and examine the relationship of three measures of NDVI--mean, maximum, and standard deviation--with patterns of bird and butterfly species richness at various spatial scales. Results indicate a positive correlation, but with no definitive functional form, between species richness and productivity. The strongest relationships between species richness of birds and NDVI were observed at larger sampling grains and extent, where each of the three NDVI measures explained more than 50% of the variation in species richness. The relationship between species richness of butterflies and NDVI was strongest over smaller grains. Results suggest that measures of NDVI are an alternative approach for explaining the spatial variability of species richness of birds and butterflies.",
}