Remote sensing for land use analysis

Preparation of cataloging and indexing reports of land use remote sensor data is described. Topics discussed include: land use mapping and scribing; collation of LANDSAT investigation reports; and reformating and collation of Skylab 4 tabular and plot data for data bank entry

The Penn State ORSER system for processing and analyzing ERTS and other MSS data

The author has identified the following significant results. The office for Remote Sensing of Earth Resources (ORSER) of the Space Science and Engineering Laboratory at the Pennsylvania State University has developed an extensive operational system for processing and analyzing ERTS-1 and similar multispectral data. The ORSER system was developed for use by a wide variety of researchers working in remote sensing. Both photointerpretive techniques and automatic computer processing methods have been developed and used, separately and in a combined approach. A remote Job Entry system permits use of an IBM 370/168 computer from any compatible remote terminal, including equipment tied in by long distance telephone connections. An elementary cost analysis has been prepared for the processing of ERTS data

Shuttle derived atmospheric density model. Part 1: Comparisons of the various ambient atmospheric source data with derived parameters from the first twelve STS entry flights, a data package for AOTV atmospheric development

The ambient atmospheric parameter comparisons versus derived values from the first twelve Space Shuttle Orbiter entry flights are presented. Available flights, flight data products, and data sources utilized are reviewed. Comparisons are presented based on remote meteorological measurements as well as two comprehensive models which incorporate latitudinal and seasonal effects. These are the Air Force 1978 Reference Atmosphere and the Marshall Space Flight Center Global Reference Model (GRAM). Atmospheric structure sensible in the Shuttle flight data is shown and discussed. A model for consideration in Aero-assisted Orbital Transfer Vehicle (AOTV) trajectory analysis, proposed to modify the GRAM data to emulate Shuttle experiments

The EnMAP user interface and user request scenarios

EnMAP (Environmental Mapping and Analysis Program) is a German hyperspectral satellite mission providing high quality hyperspectral image data on a timely and frequent basis. Main objective is to investigate a wide range of ecosystem parameters encompassing agriculture, forestry, soil and geological environments, coastal zones and inland waters. The EnMAP Ground Segment will be designed, implemented and operated by the German Aerospace Center (DLR). The Applied Remote Sensing Cluster (DFD) at DLR is responsible for the establishment of a user interface. This paper provides details on the concept, design and functionality of the EnMAP user interface and a first analysis about potential user scenarios. The user interface consists of two online portals. The EnMAP portal (www.enmap.org) provides general EnMAP mission information. It is the central entry point for all international users interested to learn about the EnMAP mission, its objectives, status, data products and processing chains. The EnMAP Data Access Portal (EDAP) is the entry point for any EnMAP data requests and comprises a set of service functions offered for every registered user. The scientific user is able to task the EnMAP HSI for Earth observations by providing tasking parameters, such as area, temporal aspects and allowed tilt angle. In the second part of that paper different user scenarios according to the previously explained tasking parameters are presented and discussed in terms of their feasibility for scientific projects. For that purpose, a prototype of the observation planning tool enabling visualization of different user request scenarios was developed. It can be shown, that the number of data takes in a certain period of time increases with the latitude of the observation area. Further, the observation area can differ with the tilt angle of the satellite. Such findings can be crucial for the planning of remote sensing based projects, especially for those investigating ecosystem gradients in the time domain

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should be aware of, if not at the leading edge of, of advancements like DL. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as it relates to (i) inadequate data sets, (ii) human-understandable solutions for modelling physical phenomena, (iii) Big Data, (iv) non-traditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.Comment: 64 pages, 411 references. To appear in Journal of Applied Remote Sensin

Summary of shuttle data processing and aerodynamic performance comparisons for the first 11 flights

NASA Space Shuttle aerodynamic and aerothermodynamic research is but one part of the most comprehensive end-to-end flight test program ever undertaken considering: the extensive pre-flight experimental data base development; the multitude of spacecraft and remote measurements taken during entry flight; the complexity of the Orbiter aerodynamic configuration; the variety of flight conditions available across the entire speed regime; and the efforts devoted to flight data reduction throughout the aerospace community. Shuttle entry flights provide a wealth of research quality data, in essence a veritable flying wind tunnel, for use by researchers to verify and improve the operational capability of the Orbiter and provide data for evaluations of experimental facilities as well as computational methods. This final report merely summarizes the major activities conducted by the AMA, Inc. under NASA Contract NAS1-16087 as part of that interesting research. Investigators desiring more detailed information can refer to the glossary of AMA publications attached herein as Appendix A. Section I provides background discussion of software and methodology development to enable Best Estimate Trajectory (BET) generation. Actual products generated are summarized in Section II as tables which completely describe the post-flight products available from the first three-year Shuttle flight history. Summary results are presented in Section III, with longitudinal performance comparisons included as Appendices for each of the flights

Technical Considerations in Remote LIMS Access via the World Wide Web

The increased dependency on the World Wide Web by both laboratories and their customers has led LIMS developers to take advantage of thin-client web applications that provide both remote data entry and manipulation, along with remote reporting functionality. Use of an LIMS through a web browser allows a person to interact with a distant application, providing both remote administration and real-time analytical result delivery from virtually anywhere in the world. While there are many benefits of web-based LIMS applications, some concern must be given to these new methods of system architecture before justifying them as a suitable replacement for their traditional client-server systems. Developers and consumers alike must consider the security aspects of introducing a wide area network capable system into a production environment, as well as the concerns of data integrity and usability

ExoMars 2016 Schiaparelli Module Trajectory and Atmospheric Profiles Reconstruction: Analysis of the On-board Inertial and Radar Measurements

On 19th October 2016 Schiaparelli module of the ExoMars 2016 mission flew through the Mars atmosphere. After successful entry and descent under parachute, the module failed the last part of the descent and crashed on the Mars surface. Nevertheless the data transmitted in real time by Schiaparelli during the entry and descent, together with the entry state vector as initial condition, have been used to reconstruct both the trajectory and the profiles of atmospheric density, pressure and temperature along the traversed path. The available data-set is only a small sub-set of the whole data acquired by Schiaparelli, with a limited data rate (8 kbps) and a large gap during the entry because of the plasma blackout on the communications. This paper presents the work done by the AMELIA (Atmospheric Mars Entry and Landing Investigations and Analysis) team in the exploitation of the available inertial and radar data. First a reference trajectory is derived by direct integration of the inertial measurements and a strategy to overcome the entry data gap is proposed. First-order covariance analysis is used to estimate the uncertainties on all the derived parameters. Then a refined trajectory is computed incorporating the measurements provided by the on-board radar altimeter. The derived trajectory is consistent with the events reported in the telemetry and also with the impact point identified on the high-resolution images of the landing site. Finally, atmospheric profiles are computed tacking into account the aerodynamic properties of the module. Derived profiles result in good agreement with both atmospheric models and available remote sensing observations

Trends in Planetary Data Analysis. Executive summary of the Planetary Data Workshop

Planetary data include non-imaging remote sensing data, which includes spectrometric, radiometric, and polarimetric remote sensing observations. Also included are in-situ, radio/radar data, and Earth based observation. Also discussed is development of a planetary data system. A catalog to identify observations will be the initial entry point for all levels of users into the data system. There are seven distinct data support services: encyclopedia, data index, data inventory, browse, search, sample, and acquire. Data systems for planetary science users must provide access to data, process, store, and display data. Two standards will be incorporated into the planetary data system: Standard communications protocol and Standard format data unit. The data system configuration must combine a distributed system with those of a centralized system. Fiscal constraints have made prioritization important. Activities include saving previous mission data, planning/cost analysis, and publishing of proceedings