Uncovering Ecological Patterns with Convolutional Neural Networks

CNNs enable ecologists to identify biophysical components in high-resolution remotely sensed imagery by leveraging spatial context, and are particularly effective when ecological components have distinct shapes. CNNs can be used for both object detection, where key components are identified throughout an image, and semantic segmentation, where each pixel is classified individually. CNN accuracy is similar to human-level classification accuracy,...