Traditional large Earth observation satellites (EOSs) are designed with simple imaging strategies. However, small satellites can satisfy immediate user needs through agile imaging modes. In this article, we model several agile imaging mode concepts and test them experimentally on the push-broom hyperspectral imaging cubesat HYPerspectral Smallsat for Ocean observation satellite 1 (HYPSO-1). Six imaging modes are tested: slewing, multitarget, dual-angle, wide swath, on-board processing, and dynamic pointing. The results show that the slewing and multiangle mode increased estimated signal-to-noise ratio (SNR) by$1.4\times $to$1.7\times $, the on-board processing mode decreased data latency, and the multitarget, wide swath, and dynamic pointing modes enhanced spatial coverage.

This paper presents a low-cost lightweight UAV payload for remote sensing purposes using a small imaging spectrometer made from COTS components. The novel design with an additional upward-facing spectrometer allows for reflectance computation by correcting the push-broom imaging spectrometer data of the ocean surface for different lighting- and atmospheric conditions.

The along track spatial resolution in push broom imaging systems depends on platform parameters and imaging settings. This paper present a method for achieving a consistent spatial resolution for varying exposure times. We consider the geometry of a simplified push broom imaging system to derive relationships between spatial resolution, platform parameters (altitude, speed, focal length, slit width) and recording settings (exposure time, frame rate). The method is tested and verified using data from the HYPerspectral Smallsat for Ocean observation-1 (HYPSO-1). The spatial resolution is consistent over the exposure time range of 4.41ms to 49.3ms for low off-nadir angles when choosing frame rates according to the method.

In this paper we present coregistration of hyperspectral imagery with photogrammetry for shallow-water mapping from an Unmanned Aerial Vehicle (UAV). The coregistration is based on a methodology for georeferencing that utilizes outputs from the photogrammetry pipeline through three steps. First, we perform the photogrammetry pipeline. This gives camera poses from Structure-from-Motion (SfM) and a dense point cloud from Multi-View Stereo (MVS). Performing a refraction correction of the dense point cloud yields high-resolution bathymetry. Second, poses from SfM are fused with UAV navigation sensors in a Kalman smoother. Third, the geometric model of the hyperspectral imager is calibrated to align hyperspectral images with photogrammetry. Then, ray tracing is performed to georeference spectral measurements onto the bathymetry from MVS. Using the georeferenced hyperspectral imagery, we present spectral bathymetry estimation. The methods were demonstrated for a coastal site (depth < 6 m) in Norway, using a UAV with a camera and a hyperspectral imager. The georeferencing yielded a horizontal Mean Absolute Error (MAE) of 22 cm between hyperspectral and photogrammetry, equivalent to one hyperspectral pixel. The MVS bathymetry gave a MAE of 14 cm with respect to ground truth acoustic. The spectral bathymetry estimator was calibrated on ground truth acoustics with a MAE of 10 cm. Comparing the bathymetry from MVS with the spectral bathymetry yielded a MAE of 11 cm. The results suggest that coregistration with photogrammetry yields accurate georeferencing of hyperspectral imagery. The results also show that we can map bathymetry accurately using MVS with refraction correction or the spectral estimator.

HYPSO-1 is a Small Satellite with a hyperspectral camera payload inside a six unit cubesat platform, launched january 2022. This paper describes how the operation of the same hyperspectral camera is validated by deployment on an experimental airplane, and how field trials are performed together with other remote sensing and in-situ agents. The payload is presented, in addition to how the operation was planned. The raw and radiance data are presented, and various practical aspects regarding implementation are discussed. Notwith-standing some minor issues, the procedures described were successfully used to gather valid data that can be used to infer properties of the imaged regions.