Transcript Slide 1
Environmental Remote Sensing GEOG 2021 Lecture 8 Observing platforms & systems and revision Sensors, systems and applications • • • • Polar orbiting v. geostationary High v. low spatial resolution High v. low temporal resolution Choice of spectral region – Optical (SW, NIR), passive microwave (TIR), active microwave (RADAR) Remember trade-offs in space, time, wavelength etc. • Global coverage means broad swaths, moderate-to-low resolution – Accept relatively low spatial detail for global coverage & rapid revisit times – Land cover change, vegetation dynamics, surface reflectance, ocean and atmospheric circulation, global carbon & hydrological cycle – E.g. MODIS (Terra, Aqua) (near-polar orbit) • 250m to 1km, 7 bands across visible + NIR and some thermal • Swath width ~2400 km • So, revisit time of hours – 1 or 2 days, depends on location– coverage much denser at high latitudes than equator Remember trade-offs in space, time, wavelength etc. • Global coverage means broad swaths, moderate-to-low resolution – AVHRR (near-polar orbit) • 1.1 to 5km, only 2 bands across visible + NIR, very broad bands (0.58-0.68m, 0.725-1m) • Swath width ~2900km • Revisit time 2 daily • Widely used in weather forecasting Remember trade-offs in space, time, wavelength etc. • Sea-WIFS – Designed for ocean colour studies – 1km resolution, 2800km swath, 16 day repeat (note difference) Remember trade-offs in space, time, wavelength etc. • Can look away from optical in passive microwave (thermal) or active microwave (RADAR) – Passive e.g. ATSR 1 & 2 on ENVISAT • Sea surface temperature – RADAR has benefit of all-weather, day or night • E.g. SAR on ERS-2, 30m spatial, 100km swath, C-band, various polarisations • ASAR on ENVISAT, 30m to 1km res., various swaths, C-band, 5 polarisations http://earth.esa.int/ers/ Change in Greenland ice sheet thickness over 11 years Remember trade-offs in space, time, wavelength etc. • Global coverage means broad swaths, moderateto-low resolution – E.g. MERIS (near-polar orbit) • ~300m, 15 bands across visible + NIR • Swath width ~1100 km • So, revisit time of hours – 2 days, depending on where on globe you are – coverage much denser at high latitudes than equator – METEOSAT 2nd Gen (MSG) (geostationary orbit) • 1km (equator) to 3km (worse with latitude) • Views of whole Earth disk every 15 mins • 30+ years METEOSAT data Remember trade-offs in space, time, wavelength etc. MERIS image of Californian fires October 2007 Remember trade-offs in space, time, wavelength etc. MSG-2 image of Northern Europe “Mostly cloud free” Remember trade-offs in space, time, wavelength etc. • Local to regional – Requires much higher spatial resolution (< 100m) – So typically, narrower swaths (10s to 100s km) and longer repeat times (weeks to months) – E.g. Landsat (polar orbit) • 28m spatial, 7 bands, swath ~185km, repeat time nominally 16 days BUT optical, so clouds can be big problem Remember trade-offs in space, time, wavelength etc. • SPOT 1-4 – Relatively high resolution instrument, like Landsat – 20m spatial, 60km swath, 26 day repeat • IKONOS, QuickBird – Very high resolution (<1m), narrow swath (10-15km) – Limited bands, on-demand acquisition A changing world: Earth Palm Jumeirah, UAE Images courtesy GeoEYE/SIME Summary • Instrument characteristics determined by application – How often do we need data, at what spatial and spectral resolution? – Can we combine observations?? – E.g. optical AND microwave? LIDAR? Polar and geostationary orbits? Constellations? Revision • L1: definitions of remote sensing, various platforms and introduction to EM spectrum, atmospheric windows, image formation for optical and RADAR • L2: image display and enhancement, histogram manipulation, colour composites (FCC, pseudoclour), image arithmetic (e.g. band ratios, NDVI, differences etc.) Revision • L3: spectral information - optical, vegetation examples, RADAR image characteristics, spectral curves, scatter plots (1 band against another), vegetation indices (perpendicular, parallel) • L4: classification - producing thematic information from raster data, supervised (min. distance, max likelihood etc.) & unsupervised (ISODATA), confusion matrix. Revision • L5: spatial operators - convolution filtering, smoothing (low pass), edge detection (high pass, gradient filters). • L6: Modelling 1 - types of model, physical v. empirical, deterministic & stochastic, empirical models relating biomass to backscatter, or NDVI • L7: Modelling 2 - more types of model, population, regression, hydrological, calibration and validation, forward & inverse References • Global land cover & land cover change • • • • http://glcf.umiacs.umd.edu/services/landcoverchange/ B. L. Turner, II*, , Eric F. Lambin , and Anette Reenberg The emergence of land change science for global environmental change and sustainability, PNAS 2007, http://www.pnas.org/cgi/content/full/104/52/20666 http://lcluc.umd.edu/ http://visibleearth.nasa.gov/view_rec.php?id=3446 • Deforestation • http://visibleearth.nasa.gov/view_set.php?categoryID=582