Superconducting nanowires operating at temperatures of a few degrees Kelvin can be biased so that a single photon--even one in the infrared--will initiate a sudden transition into a resistive state that is easily sensed by conventional amplifiers. The resulting signal preserves photon-arrival timing at the few-picosecond level and adds virtually no readout noise. Imagers are now being developed in this technology for a range of future applications. In this talk, I will present the current state-of-the-art of this technology.

The P4001 standard defines characteristics for hyperspectral camera performance. The standard will also include guidelines for measurement of these characteristics. The ambition to give a complete set of performance characteristics tends to require an extensive set of tests. An important aspect of the work is therefore to devise test protocols that are time efficient and have moderate requirements on the test equipment. Work is underway to define tests for radiometric performance, co-registration, spatial and spectral resolution, as well as stray light. The complete set of tests can be carried out using four test setups. These test methods, according to the current draft, will be outlined.

The goal of the P4001 Terminology Subgroup was to collate and define physics-based terminology in order to establish methods for testing and calibration that accurately convey product specifications. Written definitions and well-defined equations (where possible) that objectively and unambiguously define these terms is critical for success. Initial work has focused on collating terms for review. In order to align with the efforts of the Characterization & Testing Subgroup, the terms are divided into four categories: Spectral Terminology Spatial Terminology Signal/Radiometric Terminology System and Operational Terminology.

Ground-based remote sensing is an important technology to gain situational awareness of the environment surrounding space assets. Ground-based optical telescopes cannot spatially resolve objects in space that are distant (orbits beyond 1,000 km altitude, e.g. GEO) or that are small (e.g. CubeSats). These objects are denoted as unresolved resident space objects (URSO). Hyperspectral remote sensing has been proposed as a technology to extract quantitative information about URSOs. The high spectral resolution of hyperspectral sensors contains information about URSO material composition. Even though the object cannot be spatially resolved, it may be spectrally resolved. Simulation models provide an alternative to the limited access to real data for algorithm testing and validation. They also provide a platform to perform “controlled” experiments to understand algorithm performance before processing real observations. Here we will present our work in combining tools such as MATLAB, STK and DIRSIG to develop simulation models of different levels of complexity to generate data sets to support remote sensing algorithm testing and validation.

Thermal satellite images are used to estimate Land Surface Temperature (LST), which aid in the monitoring of Urban Heat Islands (UHI). UHI studies are limited by the tradeoff in spatial and temporal resolution of satellite platforms. Epitomic representation have been proposed by Malkin et al. to create a high-resolution land label map by fusing a low-resolution land class map and high-resolution imagery. In this paper, we present an extension from classification to downscaling a continuous variable like LST. The approach is used to fuse 2km GOES-16’s LST with 30m NDVI and NDUSI from Landsat 8 to created 30m LST product.