Abstract
Information on habitat preferences is critical for the successful conservation of endangered species. For many species, especially those living in remote areas, we currently lack this information. Time and financial resources to analyze habitat use are limited. We aimed to develop a method to describe habitat preferences based on a combination of bird surveys with remotely sensed fine-scale land cover maps. We created a blended multiband remote sensing product from SPOT 6 and Landsat 8 data with a high spatial resolution. We surveyed populations of three bird species (Yellow-breasted Bunting Emberiza aureola, Ochre-rumped Bunting Emberiza yessoensis, and Black-faced Bunting Emberiza spodocephala) at a study site in the Russian Far East using hierarchical distance sampling, a survey method that allows to correct for varying detection probability. Combining the bird survey data and land cover variables from the remote sensing product allowed us to model population density as a function of environmental variables. We found that even small-scale land cover characteristics were predictable using remote sensing data with sufficient accuracy. The overall classification accuracy with pansharpened SPOT 6 data alone amounted to 71.3%. Higher accuracies were reached via the additional integration of SWIR bands (overall accuracy = 73.21%), especially for complex small-scale land cover types such as shrubby areas. This helped to reach a high accuracy in the habitat models. Abundances of the three studied bird species were closely linked to the proportion of wetland, willow shrubs, and habitat heterogeneity. Habitat requirements and population sizes of species of interest are valuable information for stakeholders and decision-makers to maximize the potential success of habitat management measures.
Highlights
Satellite remote sensing plays an increasingly important role in ecology, e.g., for estimating and monitoring biodiversity [1,2], the quantification of ecosystem services [3], and for evaluatingRemote Sens. 2020, 12, 38; doi:10.3390/rs12010038 www.mdpi.com/journal/remotesensingRemote Sens. 2020, 12, 38 the effectiveness of conservation interventions [1,3]
Best results were obtained with broad land cover categories combined with information about landscape features, both recorded in a high spatial resolution in field surveys
In this study we aimed at evaluating the ability of a high-resolution remote sensing product with a full range spectral band suite (VIS-NIR-shortwave infrared (SWIR), based on SPOT 6 and Landsat 8 data) to map fine scale habitat characteristics at a large spatial extent, in to the sole use of SPOTsensing
Summary
Satellite remote sensing plays an increasingly important role in ecology, e.g., for estimating and monitoring biodiversity [1,2], the quantification of ecosystem services [3], and for evaluatingRemote Sens. 2020, 12, 38; doi:10.3390/rs12010038 www.mdpi.com/journal/remotesensingRemote Sens. 2020, 12, 38 the effectiveness of conservation interventions [1,3]. The classical multispectral configuration of Landsat-4 to Landsat-8 provides a pixel size of 30 × 30 m and an image extent of 185 × 185 km This allows linking Landsat data to environmental data collected at a similar spatial extent and resolution. Rhodes et al [14] compared the value of field surveys and remote sensing for biodiversity assessment while using different datasets for the modelling of bird species abundances at the 1 km level. They found the resolution of the analyzed remote sensing data (>0.5 ha) to be a bottleneck for reliable models. Best results were obtained with broad land cover categories combined with information about landscape features (as hedges or single trees), both recorded in a high spatial resolution in field surveys
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