With the aim to provide a coherent, comparable and reusable global spectroscopy, we present best practice efforts allowing to compare and validate observed, modeled and in-situ measured spectroscopy data from disparate data sources. We will present key messages ranging from data acquisition to product dissemination and discuss challenges related to those data. In particular, we will focus on systematic definitions for radiance and reflectance data, systematic product generation and validation as well as presenting new approaches to allowing convergence in data, products and validation approaches. The talk envisages to spark an international discussion resulting in both, a position paper as well as best practice with the aim to providing global spectroscopy.

EnMAP (Environmental Mapping and Analysis Program) is a German Earth observation satellite mission which will use imaging spectroscopy to obtain a diagnostic characterization of the Earth‘s surface to study environmental changes and ecosystem responses to human activities in the fields of vegetation monitoring, soils, geology and resources, water quality as well as environmental pollution through hazardous matters, and urban areas.
In the last decade a mission exploitation program was established which supports the science community to explore new application potentials and develop algorithms and products in the different fields of applications. The implementation of specific algorithms and applications in the EnMAP Box 3.0 (open source QGIS-plug-in) enables an easy data processing of simulated EnMAP data and hyperspectral airborne data today and EnMAP data in the future.
Training of students and young scientist is funded and supported by EnMAP schools including training to use the EnMAP Box. The implementation of the online learning platform HYPERedu as part of the EnMAP education initiative will support hyperspectral remote sensing training at master level. Additional program goals of the mission exploitation program are the support of national and international cooperation and the exploration of synergies with other missions such as within the Copernicus program.

CSIRO utilizes Earth Observation (EO) data, from both science and operational missions, to develop innovative applications of national importance in support of more than 100 government programs (both state and federal). Significant opportunities exist for innovative applications to be developed through the smart integration of multiple EO data types (conventional and new) with in-situ ground data and/or simulation models. With the imminent launch of the next generation of science and demonstration hyperspectral sensors, there is an opportunity to develop new applications using data from a combination of these new and operational sensors such as Landsat OLI and Copernicus Sentinel-2 in a synergistic matter.
However, to enable these advances, solutions to the following challenges need to be addressed:
(1) automated data pipelines for key EO sensors from relevant space agencies and data providers;
(2) rapidly growing EO data volumes that necessitate enterprise-wide, high-performance EO data processing systems and tools, that can handle petabytes of EO data more efficiently; and
(3) data analytics including utilizing the latest Deep Learning algorithms.
CSIRO is working towards solving some of these challenges bringing together CSIRO’s past and current research, analysis tools and investments into “BigData” analytics platforms, processing capabilities, and expertise in hyperspectral and optical applications development. This presentation will outline the development work planned for the near future.

The National Academy’s 2017 Earth Science Decadal Survey (DS) called for five high value ‘Targeted Observables”, including Surface Biology and Geology (SBG), for which the objectives can be satisfied using hyperspectral VSWIR and multi-spectral Thermal IR observations. In response, candidate architecture studies have been initiated involving several NASA centers. The 2017 DS objectives can be binned into two groups functionally: the majority can be met using a systematic, “mow-the-lawn” concept of operations, with data acquisitions at regular intervals separated by up to 16 days; and another, smaller, set of objectives for which event-driven tasking would be appropriate, with off-pointing to achieve hourly to daily revisit times.

The SBG architecture study team — a cooperative effort, involving multiple NASA centers — is casting a wide net to identify physical architectures to satisfy these objectives. These range from a single large platform to multiple smaller platforms; from a NASA-only implementation to partnering with other space agencies, or working with commercial enterprise; from a system with no data latency requirement, to near real-time downlink of information. Multiple launch options are under consideration, and different downlink scenarios from orbit.

As part of the physical trade space, coordination of data acquisition plans across the many international platforms planned for the coming decade would be beneficial for both functional architectures, but especially for event-driven tasking. Synchronized observations of episodically occurring phenomena, for example snow accumulation, wildfires, volcanic activity, and other natural hazards, would be one way to push the revisit period toward the desired frequency.

The study of imaging spectrometers suitable for space missions began at the end of the 80s. In 2001 the first space mission NASA EO-1 HYPERION was launched and it has acquired thousands of images until the mission end in 2017. INGV has been involved in scientific and technical research on image spectrometers since 1990 and participated to a large number of airborne campaigns using airborne sensor at national and international level to define instrument characteristics and products for geological and geophysical applications. In the frame of ASI mission study PRISMA which has been launched in the spring of 2019, INGV coordinated a research project (ASI-AGI) to analyze PRISMA mission requirements and suitable procedures including common utilities as atmospheric correction, topographic corrections, data fusion and dedicated procedures for mineral analysis of exposed surfaces, forest fires, volcanic gas emission and active lava fields as well as construct specifics spectral libraries for volcanic areas. Actually INGV is involved the ESA project CHIME coordinated by ISPRA to better define the scientific requirements for next generation of hyperspectral missions and train new generation of researchers in the use of hyperspectral data.