Remote Sensing Applications PDF

Remote Sensing Applications Module: AEGIS3A LEANING UNIT/OUTCOME : 3 www.vut.ac.za 1  www.vut.ac.za...

Remote Sensing Applications Module: AEGIS3A LEANING UNIT/OUTCOME : 3 www.vut.ac.za 1  www.vut.ac.za CONTENTS 1. Multispectral remote sensing 2. Sensor types 3. Across track (Whiskbroom) 4. Along track (push broom) 5. Whiskbroom vs. Pushbroom 6. Image classification 2 7. Image classification 8. Microwave remote sensing The contents of this presentation is confidential. ©VUT 9. The Importance of RS  Multispectral remote sensing Definition Multispectral remote sensing is the collection of reflected, emitted or backscattered energy from an object or area of interest in MULTIPLE bands of the electromagnetic spectrum MS RS enables you to visualise data from the EMS that is not visible to the human eye. 3  Multispectral remote sensing Resolution is key consideration Spatial B G R NIR Spectral Temporal Radiometric 4 Multispectral remote sensing 5 Multispectral remote sensing 6  Sensor types Film Scanning mirror and discrete detectors (e.g. Landsat) Along track (pushbroom) (e.g. SPOT) Across track (whiskbroom) (e.g. AVIRIS) Area arrays (your cell phone) 7  Across track (Whiskbroom) “Back and forth” motion of the fore optics Scans each ground resolution cell one-by- one Instantaneous Field of View (IFOV) of instrument determines pixel size Image is built up by movement of satellite along the orbital track and scanning across-track Capture greater detail (telephoto lens) 8  Along track (push broom) Linear array of detectors (aligned cross-track) Reflected radiance passes through a lens and onto a line of detectors Image is built up by movement of the satellite along its orbital track (no scanning mirror) Dispersion used to split light into narrow spectral bands and individual detectors Gather more light (wide angle lens) 9  Whiskbroom vs. Pushbroom Wide swath width Wide swath width Complex mechanical Complex mechanical system system Simple optical system Simple optical system Filters and sensors Filters and sensors Shorter dwell time Shorter dwell time Pixel distortion Pixel distortion 10  Image classification Objective is to automatically classify all pixels in an image into land cover classes or themes. Different features have unique combinations of DN’s from reflectance and emittance properties – spectral signatures. The spectral pattern within the data is used as a numerical basis for classification Spectral patterns Spatial patterns Temporal patterns 11  Image classification Supervised classification Two steps – identify followed by classification. The pixel categorisation is specified by the numerical descriptors of a known land cover (training area). Unsupervised classification Classify by cluster analysis followed by identification. Hybrid classification 12  Microwave remote sensing Uses radiation in the 1mm to 1m range of the electromagnetic spectrum. Capable of penetrating the atmosphere under most conditions (clouds, mist, haze, smoke and also works in darkness). Synthetic aperture radar (SAR) on space platforms since the 1980’s. 13  Microwave remote sensing RADAR Interferometry Images recorded by two antennas in different locations. The analysis of the differential phase (change in distance) leads to information on terrain elevation. (Toutin & Gray, 2000) 14  The Importance of RS Large amounts of data needed, and Remote Sensing can provide it Reduces manual field work dramatically Allows retrieval of data for regions difficult or impossible to reach: Open ocean Hazardous terrain (high mountains, extreme weather areas, etc.) Ocean depths Atmosphere 15  The Importance of RS Allows for the collection of much more data in a shorter amount of time Leads to increased land coverage AND Increase ground resolution of a GIS Digital Imagery greatly enhances a GIS DIRECTLY: Imagery can serve as a visual aid INDIRECTLY: Can serves as a source to derive information such as… Land use/land cover Atmospheric emissions Vegetation Water bodies Cloud cover 16 Change detection (including sea ice, coastlines, sea levels, etc.)  Applications of Remote Sensing Images serve as base maps Observe or measure properties or conditions of the land, oceans, and atmosphere Map spatial distribution of “features” Record spatial changes 17  Applications of Remote Sensing Images serve as base maps Observe or measure properties or conditions of the land, oceans, and atmosphere Map spatial distribution of “features” Record spatial changes 18  Applications of Remote Sensing Change Detection - Flooding 19  Applications of Remote Sensing Monitoring Weather 20 Thank you !! www.vut.ac.za 21