Extension of ERIM multispectral data processing capabilities through improved data handling techniques

The improvement and extension of the capabilities of the Environmental Research Institute of Michigan processing facility in handling multispectral data are discussed. Improvements consisted of implementing hardware modifications which permitted more rapid access to the recorded data through improved numbering and indexing of such data. In addition, techniques are discussed for handling data from sources other than the ERIM M-5 and M-7 scanner systems

MIDAS prototype Multispectral Interactive Digital Analysis System for large area earth resources surveys. Volume 2: Charge coupled device investigation

MIDAS is a third-generation, fast, low cost, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensors. MIDAS, for example, can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The need for advanced onboard spacecraft processing of remotely sensed data is stated and approaches to this problem are described which are feasible through the use of charge coupled devices. Tentative mechanizations for the required processing operations are given in large block form. These initial designs can serve as a guide to circuit/system designers

Investigations in adaptive processing of multispectral data

Adaptive data processing procedures are applied to the problem of classifying objects in a scene scanned by multispectral sensor. These procedures show a performance improvement over standard nonadaptive techniques. Some sources of error in classification are identified and those correctable by adaptive processing are discussed. Experiments in adaptation of signature means by decision-directed methods are described. Some of these methods assume correlation between the trajectories of different signature means; for others this assumption is not made

Active and passive multispectral scanner for earth resources applications: An advanced applications flight experiment

The development of an experimental airborne multispectral scanner to provide both active (laser illuminated) and passive (solar illuminated) data from a commonly registered surface scene is discussed. The system was constructed according to specifications derived in an initial programs design study. The system was installed in an aircraft and test flown to produce illustrative active and passive multi-spectral imagery. However, data was not collected nor analyzed for any specific application

MIDAS, prototype Multivariate Interactive Digital Analysis System for large area earth resources surveys. Volume 1: System description

A third-generation, fast, low cost, multispectral recognition system (MIDAS) able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensots is described. The program can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principle objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in the overall program is described. The system contains a midi-computer to control the various high speed processing elements in the data path, a preprocessor to condition data, and a classifier which implements an all digital prototype multivariate Gaussian maximum likelihood or a Bayesian decision algorithm. Sufficient software was developed to perform signature extraction, control the preprocessor, compute classifier coefficients, control the classifier operation, operate the color display and printer, and diagnose operation

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented

Economic damages from on-going climate change imply deeper near-term emission cuts

Pathways toward limiting global warming to well below 2 ∘C, as used by the IPCC in the Fifth Assessment Report, do not consider the climate impacts already occurring below 2 ∘C. Here we show that accounting for such damages significantly increases the near-term ambition of transformation pathways. We use econometric estimates of climate damages on GDP growth and explicitly model the uncertainty in the persistence time of damages. The Integrated Assessment Model we use includes the climate system and mitigation technology detail required to derive near-term policies. We find an optimal carbon price of $115 per tonne of CO2 in 2030. The long-term persistence of damages, while highly uncertain, is a main driver of the near-term carbon price. Accounting for damages on economic growth increases the gap between the currently pledged nationally determined contributions and the welfare-optimal 2030 emissions by two thirds, compared to pathways considering the 2 ∘C limit only

Experimental determination of the complete spin structure for anti-proton + proton -> anti-\Lambda + \Lambda at anti-proton beam momentum of 1.637 GeV/c

The reaction anti-proton + proton -> anti-\Lambda + \Lambda -> anti-proton + \pi^+ + proton + \pi^- has been measured with high statistics at anti-proton beam momentum of 1.637 GeV/c. The use of a transversely-polarized frozen-spin target combined with the self-analyzing property of \Lambda/anti-\Lambda decay allows access to unprecedented information on the spin structure of the interaction. The most general spin-scattering matrix can be written in terms of eleven real parameters for each bin of scattering angle, each of these parameters is determined with reasonable precision. From these results all conceivable spin-correlations are determined with inherent self-consistency. Good agreement is found with the few previously existing measurements of spin observables in anti-proton + proton -> anti-\Lambda + \Lambda near this energy. Existing theoretical models do not give good predictions for those spin-observables that had not been previously measured.Comment: To be published in Phys. Rev. C. Tables of results (i.e. Ref. 24) are available at http://www-meg.phys.cmu.edu/~bquinn/ps185_pub/results.tab 24 pages, 16 figure

Demand-side approaches for limiting global warming to 1.5 °C

The Paris Climate Agreement defined an ambition of limiting global warming to 1.5 °C above preindustrial levels. This has triggered research on stringent emission reduction targets and corresponding mitigation pathways across energy economy and societal systems. Driven by methodological considerations, supply side and carbon dioxide removal options feature prominently in the emerging pathway literature, while much less attention has been given to the role of demand-side approaches. This special issue addresses this gap, and aims to broaden and strengthen the knowledge base in this key research and policy area. This editorial paper synthesizes the special issue’s contributions horizontally through three shared themes we identify: policy interventions, demand-side measures, and methodological approaches. The review of articles is supplemented by insights from other relevant literature. Overall, our paper underlines that stringent demand-side policy portfolios are required to drive the pace and direction of deep decarbonization pathways and keep the 1.5 °C target within reach. It confirms that insufficient attention has been paid to demand-side measures, which are found to be inextricably linked to supply-side decarbonization and able to complement supply-side measures. The paper also shows that there is an abundance of demand-side measures to limit warming to 1.5 °C, but it warns that not all of these options are “seen” or captured by current quantitative tools or progress indicators, and some remain insufficiently represented in the current policy discourse. Based on the set of papers presented in the special issue, we conclude that demand-side mitigation in line with the 1.5 °C goal is possible; however, it remains enormously challenging and dependent on both innovative technologies and policies, and behavioral change. Limiting warming to 1.5 °C requires, more than ever, a plurality of methods and integrated behavioral and technology approaches to better support policymaking and resulting policy interventions