Remote Sensing Information Extraction Training
Remote Sensing Information Extraction Training Course – Hands-on
This Remote Sensing Information Extraction Training short course will review remote sensing concepts and vocabulary including resolution, sensing platforms, electromagnetic spectrum and energy flow profile. The workshop will provide an overview of the current and near-term status of operational platforms and sensor systems. The focus will be on methods to extract information from these data sources. The spaceborne systems include the following; 1) high spatial resolution (< 5m) systems, 2) medium spatial resolution (5-100m) multispectral, 3) low spatial resolution (>100m) multispectral, 4) radar, and 5) hyperspectral. The two directional relationships between remote sensing and GIS will be examined. Procedures for geometric registration and issues of cartographic generalization for creating GIS layers from remote sensing information will also be discussed.
Remote Sensing Information Extraction Training Course – Customize it
- We can adapt this Remote Sensing Information Extraction Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this Remote Sensing Information Extraction course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the Remote Sensing Information Extraction course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the Remote Sensing Information Extraction Training course in manner understandable to lay audiences.
Remote Sensing Information Extraction Training Course – Audience/Target Group
The target audience for this Remote Sensing Information Extraction course:
Remote Sensing Information Extraction Training Course – Objectives:
Upon completing this Remote Sensing Information Extraction course, learners will be able to meet these objectives:
- Operational parameters of current sensors.
- Visual and digital information extraction procedures.
- Photogrammetric rectification procedures.
- Integration of GIS and remote sensing.
- Accuracy assessments.
- Availability and costs of remote sensing data.
Remote Sensing Information Extraction Training – Course Content
- Remote Sensing Introduction. Definitions, resolutions, active-passive.
- Platforms. Airborne, spaceborne, advantages and limitations.
- Energy Flow Profile. Energy sources, atmospheric interactions, reflectance curves, emittance.
- Aerial Photography. Photogrammetric fundamentals of photo acquisition.
- Film Types. Panchormatic, normal color, color infrared, panchromatic infrared.
- Scale Determination. Point versus average scale. Methods of determination of scale.
- Area and Height Measurements. Tools and procedures including relative accuracies.
- Feature Extraction. Tone, texture, shadow, size, shape, association.
- Land Use and Land Cover. Examples, classification systems definitions, minimum mapping units, cartographic generalization.
- Source materials. Image processing software, organizations, literature, reference materials.
- Spaceborne Remote Sensing. Basic terminology and orbit characteristics. Distinction between research/experimental, national technical assets, and operational systems.
- Multispectral Systems. Cameras, scanners linear arrays, spectral matching.
- Moderate Resolution MSS. Landsat, SPOT, IRS, JERS.
- Coarse Resolution MSS. Meteorological Systems, AVHRR, Vegetation Mapper.
- High Spatial Resolution. IKONOS, EarthView, Orbview.
- Radar. Basic concepts, RADARSAT, ALMAZ, SIR.
- Hyperspectral. AVIRIS, MODIS, Hyperion.
- GIS-Remote Sensing Integration. Two directional relationships between remote sensing and GIS. Data structures.
- Geometric Rectification. Procedures to rectify remote sensing imagery.
- Digital Image Processing. Preprocessing, image enhancements, automated digital classification.
- Accuracy Assessments. Contingency matrix, Kappa coefficient, sample size and selection.
- Multiscale techniques. Ratio estimators, double and nested sampling, area frame procedures.