Remote Sensing of Biophysical Parameters

Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf angle distribution) and biochemical parameters (leaf pigmentation and water content) have been employed to assess vegetation status and its dynamics at scales ranging from kilometric to decametric spatial resolutions thanks to methods based on remote sensing (RS) data.Optical RS retrieval methods are based on the radiative transfer processes of sunlight in vegetation, determining the amount of radiation that is measured by passive sensors in the visible and infrared channels. The increased availability of active RS (radar and LiDAR) data has fostered their use in many applications for the analysis of land surface properties and processes, thanks to their insensitivity to weather conditions and the ability to exploit rich structural and texture information. Optical and radar data fusion and multi-sensor integration approaches are pressing topics, which could fully exploit the information conveyed by both the optical and microwave parts of the electromagnetic spectrum.This Special Issue reprint reviews the state of the art in biophysical parameters retrieval and its usage in a wide variety of applications (e.g., ecology, carbon cycle, agriculture, forestry and food security)

Quarterly literature review of the remote sensing of natural resources

The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports

The data concept behind the data: From metadata models and labelling schemes towards a generic spectral library

Spectral libraries play a major role in imaging spectroscopy. They are commonly used to store end-member and spectrally pure material spectra, which are primarily used for mapping or unmixing purposes. However, the development of spectral libraries is time consuming and usually sensor and site dependent. Spectral libraries are therefore often developed, used and tailored only for a specific case study and only for one sensor. Multi-sensor and multi-site use of spectral libraries is difficult and requires technical effort for adaptation, transformation, and data harmonization steps. Especially the huge amount of urban material specifications and its spectral variations hamper the setup of a complete spectral library consisting of all available urban material spectra. By a combined use of different urban spectral libraries, besides the improvement of spectral inter- and intra-class variability, missing material spectra could be considered with respect to a multi-sensor/ -site use. Publicly available spectral libraries mostly lack the metadata information that is essential for describing spectra acquisition and sampling background, and can serve to some extent as a measure of quality and reliability of the spectra and the entire library itself. In the GenLib project, a concept for a generic, multi-site and multi-sensor usable spectral library for image spectra on the urban focus was developed. This presentation will introduce a 1) unified, easy-to-understand hierarchical labeling scheme combined with 2) a comprehensive metadata concept that is 3) implemented in the SPECCHIO spectral information system to promote the setup and usability of a generic urban spectral library (GUSL). The labelling scheme was developed to ensure the translation of individual spectral libraries with their own labelling schemes and their usually varying level of details into the GUSL framework. It is based on a modified version of the EAGLE classification concept by combining land use, land cover, land characteristics and spectral characteristics. The metadata concept consists of 59 mandatory and optional attributes that are intended to specify the spatial context, spectral library information, references, accessibility, calibration, preprocessing steps, and spectra specific information describing library spectra implemented in the GUSL. It was developed on the basis of existing metadata concepts and was subject of an expert survey. The metadata concept and the labelling scheme are implemented in the spectral information system SPECCHIO, which is used for sharing and holding GUSL spectra. It allows easy implementation of spectra as well as their specification with the proposed metadata information to extend the GUSL. Therefore, the proposed data model represents a first fundamental step towards a generic usable and continuously expandable spectral library for urban areas. The metadata concept and the labelling scheme also build the basis for the necessary adaptation and transformation steps of the GUSL in order to use it entirely or in excerpts for further multi-site and multi-sensor applications

Advanced light management concepts for perovskite photovoltaics

Um die rasante Zunahme der Treibhausgasemission zu bremsen und damit die globale Erderwärmung, ist ein schneller Umstieg von fossilen Brennstoffen auf erneuerbare Energien unabdingbar. In dieser Hinsicht spielt die Photovoltaik (PV) eine entscheidende Rolle, um eine effiziente Dekarbonisierung der globalen Stromerzeugung voranzutreiben. Dafür wird gegenwärtig sowohl an bestehender Silizium-PV, als auch an neuen PV-Technologien geforscht. Der prominenteste Kandidat unter den neuen Technologien sind die Perowskit-Solarzellen. Diese haben in den letzten 10 Jahren eine beispiellose Effizienzsteigerung durchlaufen und erzielen heute Rekordwirkungsgrade über 25%. Die rasche Entwicklung der Perowskit-basierten PV ist vor allem durch das Versprechen einer kostengünstigen, effizienten und skalierbaren Technologie motiviert. Sie gilt zum einen als Konkurrenz zur bestehenden Silizium-PV und zum anderen als Partner für die Anwendung in Perowskit/Silizium Tandem-PV. In dieser Hinsicht bietet die Perowskit-basierte Tandem-PV die Aussicht, den derzeitigen Rekordwirkungsgrad von Silizium (c-Si) Solarzellen (≈27%) und sogar die Shockley-Queisser-Grenze für Einfachsolarzellen (≈34%) zu übertreffen. Eine verbleibende Herausforderung, sowie ein aktuell stark untersuchtes Forschungsthema von Perowskit/c-Si-Tandemsolarzellen, ist ihre geringere Lichtausbeute im Vergleich zu konventionellen c-Si Solarzellen. Dies ist insbesondere auf zusätzlich erforderliche Funktionsschichten, wie die transparenten Elektroden, Ladungstransportschichten und Passivierungsschichten zurückzuführen, die gemeinsam zu Reflexionsverlusten und Verlusten durch parasitäre Absorption beitragen. Dies reduziert sowohl den Wirkungsgrad (PCE) als auch den Energieertrag (EY) der Tandem-Solarzelle. Um Reflexions- und Absorptionsverluste zu minimieren, ist ein fortschrittliches Lichtmanagement unerlässlich. Da sich die realistischen Einstrahlungsbedingungen stark von typischen Standardtestbedingungen unterscheiden (z.B. spektrale Variation und variabler Einfallswinkel des Sonnenlichts), ist es zwingend notwendig, PV-Module nicht nur für den PCE, sondern auch für den EY zu optimieren. Daher ist ein ausgeklügeltes Lichtmanagement nicht nur auf Tandem-Solarmodule beschränkt, sondern für jede Art von Solarmodul wichtig. In dieser Arbeit werden verschiedene Lichtmanagementkonzepte für die Perowskit-basierte-PV diskutiert und in Bezug auf den PCE und den jährlichen EY bewertet. In diesem Zusammenhang werden Mikrotexturen für eine verbesserte Lichteinkopplung an der Luft/Glas-Grenzfläche untersucht, was für alle PV-Technologien relevant ist. Die Mikrotexturen an der Vorderseite des Solarmoduls bieten die Möglichkeit, die Luft/Glas-Reflexion fast vollständig zu eliminieren und bei schrägen Einfallswinkeln (z.B. 80°) um ca. 80%rel zu reduzieren. Die experimentelle Realisierung zeigt die Erhöhung des PCE um 12%rel bzw. 5%rel für planare und texturierte Siliziumsolarzellen. Darüber hinaus werden Mikrotexturen auf Perowskit/c-Si-Tandem-Minimodulen realisiert, die den PCE um 10%rel verbessern. Aufgrund der ausgezeichneten Winkelstabilität der Mikrotexturen spiegelt sich die Verbesserung des PCE auch im EY wider, was durch Simulationen gezeigt wird, bei denen die Verbesserungen im EY die des PCE um 2%rel übertreffen. Zusätzlich zur ersten Grenzfläche jedes Solarmoduls werden die Reflexionsverluste an den vorderen halbtransparenten Indiumzinnoxid (ITO) Elektroden der Perowskit-Solarzellen untersucht. Mit Hilfe von nanotexturierten Glas/ITO-Grenzflächen können diese Verluste minimiert werden, was zu einem verbesserten Strom in der oberen Perowskit- und unteren c-Si-Solarzelle führt. Dies verbessert den Tandem-PCE um 2%rel. Darüber hinaus sind die nanotexturierten Elektroden winkelstabil und versprechen in den Simulationen eine Erhöhung des EY um 10%rel, was höher ist als die simulierte Verbesserung des PCE um 9%rel. Weitere nanophotonische Modifikationen der Absorberschicht der Perowskit-Solarzelle führen zu einer verbesserten Absorption in der Nähe der Bandlücke, indem das einfallende Licht in quasi-geführte Moden eingekoppelt wird. Simulationen zeigen, dass dies die Stromerzeugung in den Perowskit-Solarzellen um bis zu 6%rel verbessert. Erste experimentelle Ergebnisse demonstrieren eine Verbesserung um 2%rel. Darüber hinaus bieten die nanophotonischen Perowskit-Solarzellen eine einfache Möglichkeit, den um-weltschädlichen Bleigehalt in den Perowskit-Solarzellen bei gleichbleibendem Wirkungsgrad, um 30%rel zu verringern. Darüber hinaus verändert die nanophotonische Modifikation des Absorbers die Winkelabhängigkeit der Perowskit-Solarzellen nicht und führt zu den äquivalenten Verbesserungen des EY. Schließlich wird ein neuartiges Herstellungsverfahren für Perowskit-Solarzellen vorgestellt, dass eine einfache Laminierung der Perowskit-Solarzellen ermöglicht. Damit umgeht die Laminierung Inkompatibilitäten bei konventionellen Schichtabscheidungs-techniken und bietet somit mehr Flexibilität und Freiheit bei der Wahl der Ladungstransportmaterialien für die Perowskit-Solarzellenherstellung. Erste Prototypen zeigen eine ausgezeichnete Langzeit- und Temperaturstabilität der laminierten Perowskit-Solarzellen mit einem PCE über 14%. Das vorgestellte Laminierungskonzept bahnt damit den Weg für eine direkte Laminierung von Perowskit-Solarzellen auf die bestehende Siliziumtechnologie und hat so ein großes Potential für die aktuelle Perowskit-basierte Tandemforschung

Going hyperspectral: the 'unseen' captured?

All objects, name them soil, water, trees, vegetation, structures, metals, paints or fabrics, create a unique spectral fingerprint. A sensor determines these fingerprints by measuring reflected light, most of which registers in wavelengths, or bands, invisible to humans. This is what the crime scene investigation (CSI) television programs have popularized how DNA or fingerprints can be used to solve crimes. Similarly, forest CSI of “seeing” the trees in the deep high mountain tropical forest is now a major focus in the air and spaceborne hyperspectral sensing technology and in other different applications such as agriculture, environment, geology, transportation, security, and several others. The availability of sub-meter resolution colour imagery from satellites coupled with internet based services like Google Earth and Microsoft Virtual Earth have resulted in an enormous interest in remote sensing among the general public. The ability to see one’s home or familiar landmarks in an image taken from hundreds of kilometers above the earth elicits wonder and awe. Deciding where, when, what and how to sense or measure the DNA of individual trees from the air or space is a crucial question in the sustainable development and management of our Malaysian tropical forest ecosystems. However, to monitor, quantify, map and understand the content and nature of our forest, one would ideally like to monitor it everywhere and all the time too. This is impossible, and consequently, forest engineers must select relatively very high to high near to real time resolution sensors with the ability to transcend boundaries, capabilities, features and interfacing realms for such measurement. The dynamic interplay of these elements is precisely coordinated by signaling networks that orchestrate their interactions. High-throughput experimental and analytical techniques now provide forest engineers with incredibly rich and potentially revealing datasets from both air and spaceborne hyperspectral sensors (also known as imaging spectrometers). However, it is impossible to exhaustively explore the full experimental and operational hyperspectral sensors available in the market out there and so forest engineers must judiciously choose which one is the best to perform and fulfill their project objectives and missions. The complexity and high-dimensionality of these systems makes it incredibly difficult for forest engineers and other users alone to manage and optimize sensing processes. In order to add or derive value from a hyperspectral remotely sensed image several factors such as resolution, swath, and signal to noise ratio, amongst others need to be considered. A grand challenge for the forest engineer’s scientific discovery in the 21st Century is therefore, to devise very high real-time ultra-spatial and spectral air and space borne sensors that automatically measure and adapt sensing operations in large-scale and economical systems with the unseen captured. This lecture therefore focuses on the emerging theory, origin of the hyperspectral sensors, research, practice, limitations and identifies future challenge and outlook of hyperspectral sensing systems in the quest towards a sustainable Malaysian forestry context and other different applications to capture the “unseen”. It is quite certain that advances in hyperspectral remote sensing and more sophisticated analytical methods will resolve any “unseen” issues in time with the best approach of transcending boundaries and interfacing remote sensing data with precise information from the field plots. Unfortunately, as a relatively new analytical technique, the full potential of air and spaceborne hyperspectral imaging has not yet been realized in Malaysi

Earth resources: A continuing bibliography with indexes (issue 59)

This bibliography lists 518 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors

Transforming scientific research and development in precision agriculture : the case of hyperspectral sensing and imaging : a thesis presented in partial fulfilment of the requirements for the degree of Doctor in Philosophy in Agriculture at Massey University, Manawatū, New Zealand. EMBARGOED until 30 September 2023.

Embargoed until 30 September 2023There has been increasing social and academic debate in recent times surrounding the arrival of agricultural big data. Capturing and responding to real world variability is a defining objective of the rapidly evolving field of precision agriculture (PA). While data have been central to knowledge-making in the field since its inception in the 1980s, research has largely operated in a data-scarce environment, constrained by time-consuming and expensive data collection methods. While there is a rich tradition of studying scientific practice within laboratories in other fields, PA researchers have rarely been the explicit focal point of detailed empirical studies, especially in the laboratory setting. The purpose of this thesis is to contribute to new knowledge of the influence of big data technologies through an ethnographic exploration of a working PA laboratory. The researcher spent over 30 months embedded as a participant observer of a small PA laboratory, where researchers work with nascent data rich remote sensing technologies. To address the research question: “How do the characteristics of technological assemblages affect PA research and development?” the ethnographic case study systematically identifies and responds to the challenges and opportunities faced by the science team as they adapt their scientific processes and resources to refine value from a new data ecosystem. The study describes the ontological characteristics of airborne hyperspectral sensing and imaging data employed by PA researchers. Observations of the researchers at work lead to a previously undescribed shift in the science process, where effort moves from the planning and performance of the data collection stage to the data processing and analysis stage. The thesis develops an argument that changing data characteristics are central to this shift in the scientific method researchers are employing to refine knowledge and value from research projects. Importantly, the study reveals that while researchers are working in a rapidly changing environment, there is little reflection on the implications of these changes on the practice of science-making. The study also identifies a disjunction to how science is done in the field, and what is reported. We discover that the practices that provide disciplinary ways of doing science are not established in this field and moments to learn are siloed because of commercial constraints the commercial structures imposed in this case study of contemporary PA research

Fire

Vegetation plays a crucial role in regulating environmental conditions, including weather and climate. The amount of water and carbon dioxide in the air and the albedo of our planet are all influenced by vegetation, which in turn influences all life on Earth. Soil properties are also strongly influenced by vegetation, through biogeochemical cycles and feedback loops (see Volume 1A—Section 4). Vegetated landscapes on Earth provide habitat and energy for a rich diversity of animal species, including humans. Vegetation is also a major component of the world economy, through the global production of food, fibre, fuel, medicine, and other plantbased resources for human consumptio