Blanding’s Turtle (Emydoidea blandingii) Potential Habitat Mapping Using Aerial Orthophotographic Imagery and Object Based Classification

Rebecca Barker,Douglas J. King

doi:10.3390/rs4010194

Abstract

Blanding’s turtle (Emydoidea blandingii) is a threatened species under Canada’s Species at Risk Act. In southern Québec, field based inventories are ongoing to determine its abundance and potential habitat. The goal of this research was to develop means for mapping of potential habitat based on primary habitat attributes that can be detected with high-resolution remotely sensed imagery. Using existing spring leaf-off 20 cm resolution aerial orthophotos of a portion of Gatineau Park where some Blanding’s turtle observations had been made, habitat attributes were mapped at two scales: (1) whole wetlands; (2) within wetland habitat features of open water, vegetation (used for camouflage and thermoregulation), and logs (used for spring sun-basking). The processing steps involved initial pixel-based classification to eliminate most areas of non-wetland, followed by object-based segmentations and classifications using a customized rule sequence to refine the wetland map and to map the within wetland habitat features. Variables used as inputs to the classifications were derived from the orthophotos and included image brightness, texture, and segmented object shape and area. Independent validation using field data and visual interpretation showed classification accuracy for all habitat attributes to be generally over 90% with a minimum of 81.5% for the producer’s accuracy of logs. The maps for each attribute were combined to produce a habitat suitability map for Blanding’s turtle. Of the 115 existing turtle observations, 92.3% were closest to a wetland of the two highest suitability classes. High-resolution imagery combined with object-based classification and habitat suitability mapping methods such as those presented provide a much more spatially explicit representation of detailed habitat attributes than can be obtained through field work alone. They can complement field efforts to document and track turtle activities and can contribute to species inventory planning, conservation, and management.

Highlights

Habitat loss and degradation are primary threats to amphibian and reptile populations [1]
The high-resolution orthophotos and the processing methods used in this research were able to identify wetlands/water bodies that were probably smaller than the minimum mapping unit or resolution of previous mapping efforts
Similar accuracies were achieved using maximum likelihood pixel-based classification (MLC) of Landsat ETM+ imagery to classify a pond and marsh wetland class [67], and using fusion of radar and Landsat ETM+ data [68] but for wetland sizes much larger than many of those classified in this study

Summary

Introduction

Habitat loss and degradation are primary threats to amphibian and reptile populations [1]. Remote sensing of habitat attributes often uses abiotic and biotic spatial variables such as topography and vegetation type to characterize and map suitable habitat for a given species [2]. Land cover, which is a common attribute derived from remotely sensed data, can be used to infer habitat through implied relationships or through the explicit integration of other spatially referenced information (e.g., data points representing species presence) or environmental factors [3]. Specific habitat attributes that directly or indirectly manifest in remotely sensed imagery can be extracted and combined in mapping of potential habitat. Canopy spatial heterogeneity, as measured in high-resolution satellite imagery, was shown to be a strong predictor of nest occurrence and potential habitat. This paper presents a study that took a similar species-centered approach for the threatened

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