EarthView 6.1.0 + Patch
Janet Denzel
The EarthView Dataset is a comprehensive collection of multispectral earth imagery. The dataset is divided into four distinct subsets sourced from Satellogic, Sentinel-1, Sentinel-2 (coming soon), and NEON imagers, each providing unique data.
Each subset (AKA configuration) in the EarthView dataset includes samples representing specific patches of the Earth. Each source (satellite type) has different characteristics, so the details for the samples in each of the subsets are subtly different. We provide a very simple library to access the images in the subsets.
Each subset has some peculiarities and a specific data format in the dataset. Each item (sample) in the dataset is a dictionary with a metadata field and one or more entries for the different image products available, such as rgb, chm, 1m, 10m (see below). All of the image fields are 4D arrays where dimensions are REVISITS, BANDS, HEIGHT, WIDTH.
We encourage you to use the supplied earthview library to simplify accessing the dataset, metadata and images. (For now, download the single python file and place in the same directory as your scripts, or in Python's path)
Satellogic images are captured with Satellogic's MarkIV satellite fleet. The payload produces RGB and NIR images at 1m native resolution (no PAN sharpening). Each sample in the dataset has 1 or 2 re-visits per location.
Sentinel-1 carries a Synthetic Aperture Radar (SAR) payload. The data (imagery) produced has two channels, for vertical and horizontal polarization. The data in the dataset contains just the two channels, the images returned by item_to_images() implements a standard mapping to return RGB images. (see the example below). Samples in the dataset contain varied numbers of re-visits per location.
The NEON subset is composed of very high resolution RGB images at 0.1m, 1m hyperspectral data (369 bands), and 1m Canopy Height Model out of a LIDAR sensor. Every sample in the dataset contains 3 re-visits.
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