An automated method for the detection of emperor penguin colonies from landsat 8 imagery
Detailed information on the emperor penguin colonies is crucial for estimating total populations and analysing population migration. This study presents a new method for detecting colonies of emperor penguins by identifying areas covered with their faeces using Landsat 8 data. Top of Atmosphere (TOA) reflectance and Brightness Temperature (BT) of Landsat images are used as inputs. This method first uses normalized spectral indexes (normalized difference water index (NDWI), normalized difference faeces index (NDFI), normalized difference snow index (NDSI)), band ratios and an individual band reflectance to produce probability masks for areas covered by faeces differentiating from other land cover types. Then, after eliminating those pixels that have abnormal elevations and performing a median filter, the probability masks for those areas covered by faeces are used to derive the corresponding polygons. Subsequently, the geometric centre of the polygons of those areas covered by faeces is used as the location for a corresponding colony. For a widely distributed set of data around the Ross and Somov Seas, the overall classification accuracy is as high as 91% with a small standard deviation of 0.12.
Geography, Geology, and Planning
Antarcticaa, Colony, Detection, Emperor penguins, Landsat 8, Normalized difference faeces index
Shen, Xiao-Yi, Chang-Qing Ke, Xin Miao, Xi Zhang, and Jie Zhang. "An automated method for the detection of emperor penguin colonies from Landsat 8 imagery." Remote Sensing Letters 8, no. 6 (2017): 596-605.
Remote Sensing Letters