An Engineering Trade Space Analysis for a Space-Based Hyperspectral Chromotomographic Scanner

Hyperspectroscopy for fast transient events such as battlefield explosions is an undeveloped area of spectral imaging. This thesis is a discussion of issues involved with taking a laboratory design for a rotating prism hyperspectral chromotomographic (CT) instrument and producing a first approximation satellite payload design, operating scheme and trade space analysis to support demonstration of this technology in low-earth orbit. This instrument promises the capability of adding a time dimension to the normal spatial and spectral data produced by most hyperspectral imagers. The ultimate goal is to conduct experiments demonstrating the ultimate viability of spectral definition of transient combustion events on the ground from space. The experiment will be designed to use the CT scanner to collect, store and transmit data from any suitable target on the earth surface in the orbit footprint

Analysis of Slewing and Attitude Determination Requirements for CTEx

This thesis examines the slewing and attitude determination requirements for the Chromotomographic Experiment (CTEX), a chromotomographic-based hyperspectral imager, to be mounted on-board the Japanese Experiment Module (JEM) External Facility (EF). The in-track slewing requirement is driven by the facts that CTEx has a very small field of view (FOV) and is required to collect 10 seconds of data for any given collection window. The need to slew in the cross-track direction is a product of the small FOV and target/calibration site access. CTEx incorporates a two-axis slow-steering dwell mirror with a range of ± 8 degrees and an accuracy of 10 arcseconds in each axis to slew the FOV. The inherent inaccuracy in the knowledge of the International Space Station\u27s (ISS) attitude (± 3 degrees) poses significant complications in accurately pointing CTEx even with more accurate (0.3 degrees) attitude information provided by the JEM. The desire is for CTEx to incorporate a star tracker with 1 arcsecond accuracy to determine attitude without reliance on outside sources

An Integrated physics-based approach to demonstrate the potential of the Landsat Data Continuity Mission (LDCM) for monitoring coastal/inland waters

Monitoring coastal or inland waters, recognized as case II waters, using the existing Landsat technology is somewhat restricted because of its low Signal-to-Noise ratio (SNR) as well as its relatively poor radiometric resolution. As a primary task, we introduce a novel technique, which integrates the Landsat-7 data as a surrogate for LDCM with a 3D hydrodynamic model to monitor the dynamics of coastal waters near river discharges as well as in a small lake environment. The proposed approach leverages both the thermal and the reflective Landsat-7 imagery to calibrate the model and to retrieve the concentrations of optically active components of the water. To do so, the model is first calibrated by optimizing its thermal outputs with the surface temperature maps derived from the Landsat-7 data. The constituent retrieval is conducted in the second phase where multiple simulated concentration maps are provided to an in-water radiative transfer code (Hydrolight) to generate modeled surface reflectance maps. Prior to any remote sensing task, one has to ensure that a dataset comes from a well-calibrated imaging system. Although the calibration status of Landsat-7 has been regularly monitored over multiple desert sites, it was desired to evaluate its performance over dark waters relative to a well-calibrated instrument designed specifically for water studies. In the light of this, several Landsat- 7 images were cross-calibrated against the Terra-MODIS data over deep, dark waters whose optical properties remain relatively stable. This study is intended to lay the groundwork and provide a reference point for similar studies planned for the new Landsat. In an independent case study, the potential of the new Landsat sensor was examined using an EO-1 dataset and applying a spectral optimization approach over case II waters. The water constituent maps generated from the EO-1 imagery were compared against those derived from Landsat-7 to fully analyze the improvement levels pertaining to the new Landsat\u27s enhanced features in a water constituent retrieval framework

Hyperspectral Imaging from Ground Based Mobile Platforms and Applications in Precision Agriculture

This thesis focuses on the use of line scanning hyperspectral sensors on mobile ground based platforms and applying them to agricultural applications. First this work deals with the geometric and radiometric calibration and correction of acquired hyperspectral data. When operating at low altitudes, changing lighting conditions are common and inevitable, complicating the retrieval of a surface's reflectance, which is solely a function of its physical structure and chemical composition. Therefore, this thesis contributes the evaluation of an approach to compensate for changes in illumination and obtain reflectance that is less labour intensive than traditional empirical methods. Convenient field protocols are produced that only require a representative set of illumination and reflectance spectral samples. In addition, a method for determining a line scanning camera's rigid 6 degree of freedom (DOF) offset and uncertainty with respect to a navigation system is developed, enabling accurate georegistration and sensor fusion. The thesis then applies the data captured from the platform to two different agricultural applications. The first is a self-supervised weed detection framework that allows training of a per-pixel classifier using hyperspectral data without manual labelling. The experiments support the effectiveness of the framework, rivalling classifiers trained on hand labelled training data. Then the thesis demonstrates the mapping of mango maturity using hyperspectral data on an orchard wide scale using efficient image scanning techniques, which is a world first result. A novel classification, regression and mapping pipeline is proposed to generate per tree mango maturity averages. The results confirm that maturity prediction in mango orchards is possible in natural daylight using a hyperspectral camera, despite complex micro-illumination-climates under the canopy

The EnMAP imaging spectroscopy mission towards operations

EnMAP (Environmental Mapping and Analysis Program) is a high-resolution imaging spectroscopy remote sensing mission that was successfully launched on April 1st, 2022. Equipped with a prism-based dual-spectrometer, EnMAP performs observations in the spectral range between 418.2nm and 2445.5nm with 224 bands and a high radiometric and spectral accuracy and stability. EnMAP products, with a ground instantaneous field-of-view of 30m×30m at a swath width of 30km, allow for the qualitative and quantitative analysis of surface variables from frequently and consistently acquired observations on a global scale. This article presents the EnMAP mission and details the activities and results of the Launch and Early Orbit and Commissioning Phases until November 1st, 2022. The mission capabilities and expected performances for the operational Routine Phase are provided for existing and future EnMAP users

Design Analysis of a Sapce Based Chromotomographic Hyperspectral Imaging Experiment

This research develops the design of several components and/or systems for an experimental space-based chromotomographic hyperspectral imager that is being built by the Air Force Institute of Technology. The design work includes three separate topics. The first topic was the development of a structure utilizing finite element analysis and eigenanalysis for the ground-based version of the chromotomographic experiment (CTEx). The ground-based experiment was performed as a risk mitigation measure for the space-based experiment. The second topic includes a design review of a contractor\u27s proposed off-axis Mersenne telescope for the space-based chromotomographic hyperspectral imager. The work included the creation of preliminary verification requirements from the contract and sub- sequent analysis of the telescope design based on those requirements. The third topic addressed was a trade study of on-orbit focus, alignment, and calibration schemes for the space-based version of CTEx. The selected imaging focusing method entails imaging Earth-based sodium lights at night while stepping through several focus settings. The optimal focus setting shows the clearest sodium spectral features. The critical alignment concerns were identified as the alignment of the prism and of the collimated light onto the prism. The space-based CTEx utilizes three separate calibration methods involving vicarious Earth-based targets, and on-board laser diodes and spectral filters. The results of the research varied by topic. For the first topic, a structural assembly was successfully fabricated that allowed the goals of the ground-based CTEx to be met, validating the design approach. The design review for the second topic was successful with the contractor\u27s telescope design currently undergoing fabrication with delivery in May 2010. For the third topic, applicable methods and procedures were developed for the space-based CTEx

CEOS Land Surface Imaging Constellation Mid-Resolution Optical Guidelines

The LSI community of users is large and varied. To reach all these users as well as potential instrument contributors this document has been organized by measurement parameters of interest such as Leaf Area Index and Land Surface Temperature. These measurement parameters and the data presented in this document are drawn from multiple sources, listed at the end of the document, although the two primary ones are "The Space-Based Global Observing System in 2010 (GOS-2010)" that was compiled for the World Meteorological Organization (WMO) by Bizzarro Bizzarri, and the CEOS Missions, Instruments, and Measurements online database (CEOS MIM). For each measurement parameter the following topics will be discussed: (1) measurement description, (2) applications, (3) measurement spectral bands, and (4) example instruments and mission information. The description of each measurement parameter starts with a definition and includes a graphic displaying the relationships to four general land surface imaging user communities: vegetation, water, earth, and geo-hazards, since the LSI community of users is large and varied. The vegetation community uses LSI data to assess factors related to topics such as agriculture, forest management, crop type, chlorophyll, vegetation land cover, and leaf or canopy differences. The water community analyzes snow and lake cover, water properties such as clarity, and body of water delineation. The earth community focuses on minerals, soils, and sediments. The geo-hazards community is designed to address and aid in emergencies such as volcanic eruptions, forest fires, and large-scale damaging weather-related events

Utility Analysis for Optimizing Compact Adaptive Spectral Imaging Systems for Subpixel Target Detection Applications

Since the development of spectral imaging systems where we transitioned from panchromatic, single band images to multiple bands, we have pursued a way to evaluate the quality of spectral images. As spectral imaging capabilities improved and the bands collected wavelengths outside of the visible spectrum they could be used to gain information about the earth such as material identification that would have been a challenge with panchromatic images. We now have imaging systems capable of collecting images with hundreds of contiguous bands across the reflective portion of the electromagnetic spectrum that allows us to extract information at subpixel levels. Prediction and assessment methods for panchromatic image quality, while well-established are continuing to be improved. For spectral images however, methods for analyzing quality and what this entails have yet to form a solid framework. In this research, we built on previous work to develop a process to optimize the design of spectral imaging systems. We used methods for predicting quality of spectral images and extended the existing framework for analyzing efficacy of miniature systems. We comprehensively analyzed utility of spectral images and efficacy of compact systems for a set of application scenarios designed to test the relationships of system parameters, figures of merit, and mission requirements in the trade space for spectral images collected by a compact imaging system from design to operation. We focused on subpixel target detection to analyze spectral image quality of compact spaceborne systems with adaptive band selection capabilities. In order to adequately account for the operational aspect of exploiting adaptive band collection capabilities, we developed a method for band selection. Dimension reduction is a step often employed in processing spectral images, not only to improve computation time but to avoid errors associated with high dimensionality. An adaptive system with a tunable filter can select which bands to collect for each target so the dimension reduction happens at the collection stage instead of the processing stage. We developed the band selection method to optimize detection probability using only the target reflectance signature. This method was conceived to be simple enough to be calculated by a small on-board CPU, to be able to drive collection decisions, and reduce data processing requirements. We predicted the utility of the selected bands using this method, then validated the results using real images, and cross-validated them using simulated image associated with perfect truth data. In this way, we simultaneously validated the band selection method we developed and the combined use of the simulation and prediction tools used as part of the analytic process to optimize system design. We selected a small set of mission scenarios and demonstrated the use of this process to provide example recommendations for efficacy and utility based on the mission. The key parameters we analyzed to drive the design recommendations were target abundance, noise, number of bands, and scene complexity. We found critical points in the system design trade space, and coupled with operational requirements, formed a set of mission feasibility and system design recommendations. The selected scenarios demonstrated the relationship between the imaging system design and operational requirements based on the mission. We found key points in the spectral imaging trade space that indicated relationships within the spectral image utility trade space that can be used to further solidify the frameworks for compact spectral imaging systems

Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences

The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences—geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future

Emerging approaches to measure photosynthesis from the leaf to the ecosystem

Measuring photosynthesis is critical for quantifying and modeling leaf to regional scale productivity of managed and natural ecosystems. This review explores existing and novel advances in photosynthesis measurements that are certain to provide innovative directions in plant science research. First, we address gas exchange approaches from leaf to ecosystem scales. Leaf level gas exchange is a mature method but recent improvements to the user interface and environmental controls of commercial systems have resulted in faster and higher quality data collection. Canopy chamber and micrometeorological methods have also become more standardized tools and have an advanced understanding of ecosystem functioning under a changing environment and through long time series data coupled with community data sharing. Second, we review proximal and remote sensing approaches to measure photosynthesis, including hyperspectral reflectance- A nd fluorescence-based techniques. These techniques have long been used with aircraft and orbiting satellites, but lower-cost sensors and improved statistical analyses are allowing these techniques to become applicable at smaller scales to quantify changes in the underlying biochemistry of photosynthesis. Within the past decade measurements of chlorophyll fluorescence from earth-orbiting satellites have measured Solar Induced Fluorescence (SIF) enabling estimates of global ecosystem productivity. Finally, we highlight that stronger interactions of scientists across disciplines will benefit our capacity to accurately estimate productivity at regional and global scales. Applying the multiple techniques outlined in this review at scales from the leaf to the globe are likely to advance understanding of plant functioning from the organelle to the ecosystem