Remote Sensing (RS) ENY-C2005 Geoinformation in Environmental Modelling Miina Rautiainen

Transcription

1 Remote Sensing (RS) ENY-C2005 Geoinformation in Environmental Modelling : Wildfires in central Chile Miina Rautiainen Digital globe "Remote Sensing means the sensing of the Earth's surface from space by making use of the properties of electromagnetic waves emitted, reflected or diffracted by the sensed objects, for the purpose of improving natural resources management, land use and the protection of the environment." (United Nations) Often called Earth Observation (EO) Boko Haram s raids in NE Nigeria ( Euronews)

2 EO = Earth observation (remote sensing) EO data & experts are everywhere WHEN YOU GRADUATE! NOW Slide from: B. Hoersch, Sentinel-2 Mission Manager (ESA)

3 Today What can we do with remote sensing? What are the different types of remote sensing data? Where can we get remote sensing data? What s hot in remote sensing in 2017?

4 Endless possibilities to apply RS data Land-use monitoring: Growth of cities / irrigated areas / forests / Security alert and prediction systems: Wild fires, algae blooms in oceans, volcano eruptions Air quality & meteorological forecasts Harvest predictions, vegetation health and functions Flood monitoring Malaria risk areas Mapping natural resources: Geological prospecting, forest biomass mapping, water and ice,. And many more, still undiscovered! Physical principles of RS the same for all targets. Best result: RS data combined with ancillary GIS data Growth of irrigated areas in Kansas Fraction of sun light absorbedby vegetation Dust storms in Namibia and SA Africa Espionage in N Korea Rock minerals in California Algae bloom in Baltic sea Images NASA

5 Satellite images in the headlines: natural catastrophes Earthquake relief efforts / Nepal, April 2015 Tomnod crowd sourcing platform, ~ participants Worldview and Quickbird images before and after the earthquake Worldview and Quickbird images before and after the earthquake

6 Satellite images in the headlines: political terror Did Boko Haram attack leave 150 dead or 2,000? Satellite imagery sheds new light. (The Washington Post, ) GeoEye-1 Before raids WorldView-2 After raids

7 Satellite images in the headlines: destruction of ancient sites Ancient Temple of Bel, in Palmyra, Syria destroyed by ISIS August 2015 Images: Unitar/AFP/Getty Images

8 Satellite images in the headlines: growth of cities Jakarta, Indonesia Dubai, UAE million million million Images and captions courtesy of NASA and the USGS

9 Amplified Greenhouse Effect Shifts North's Growing Seasons Xu et al Nature Climate Change. The Northern hemisphere (> 45 N) is greening. Decreasing seasonality in the Eurasian boreal zone Based on a time series of AVHRR and MODIS satellite data, Watch videos!

10 Catching tax evaders Finding Swimming Pools with Google Earth: Greek Government Hauls in Billions in Back Taxes (SPIEGEL) the suburbs didn't have 324 swimming pools, as was reported, but rather 16,974. Greece is looking at increasing their tax revenues using remote sensing applications Google Earth / SPIEGEL

11 Fighting crop insurance frauds USA: Landsat images used to look for evidence of whether or not a farmer actually planted or harvested 50% of Landsat image analyses support a farmer s insurance claim and 50% indicate fraud. Read more:

12 Monitoring global green biomass Valerio Avitabile Decision support information: Crop biomass and food security? Droughts is major agricultural areas effects on annual crop prices? Which forests to preserve, which to log?

13 Monitoring start of spring -- and climate change Spectral vegetation indices to detect automatically onset and offset of growing season. Coarse spatial resolution satellite data (MODIS), emphasis on red and NIR spectral bands (e.g. time series of NDVI). Images Lars Eklundh

14 Detecting oil spills for marine life preservation Maps of oil spills: To delineate the extent and the thickest parts of the oil slicks. Use of optical satellite data: oil changes how the water surface reflects light, either by making the sun s reflection brighter or by dampening the scattering of sunlight (oily area darker) NASA

15 Mapping urban heat islands True color Landsat Thermal band Landsat Cleantechnica An urban heat island (UHI) is a city or metropolitan area that is significantly warmer than its surrounding rural areas due to human activities. NASA

16 History of remote sensing: from pictures to pixels Image: Wikipedia Image: Google Earth 1858: first aerial photo taken from a balloon 1868: electromagnetic theory published : aerial photos from airplanes 1930s: radar developed 1957: Sputnik launched 1960s: satellite images of daily cloud cover (Tiros-1) 1966: first geostationary weather satellite (ATS) 1972: first satellite sensor for monitoring natural resources (Landsat) 1970s: digital image processing develops 1980s: processing of satellite images done on desktop computers 1999: first satellite sensor (Ikonos) with high spatial resolution (in civil use) 2000: first hyperspectral satellite sensor (Hyperion) 2000s: global monitoring becomes operational, lidar techniques develop 2005: Google Earth brings satellite images to everybody 2008: All NASA remote sensing data sets become free and available to everybody

17 What is remote sensing (RS)? The radiation reflected from Earth is a combination of the physical and chemical status of the Earth s surface and atmosphere. RS data sets = Numerical matrices which contain a series of radiation measurements in different wavelengths connected to geographical coordinates.

18 Based on electromagnetic radiation Human eye (about nm) 18

19 Earth observation (EO) vs. remote sensing (RS)? Data across all borders Vast geographical areas Global assessments (e.g. climate change) Independent of national statistics / political situations Low cost (after launch), most data free. Potential for near real-time monitoring. Scientific research: development of algorithms to interpret satellite data. vs. layman s interest in satellite photos

20 Distances to Earth 11 km passanger s jet planes km Geostationary satellites 215 km Sputnik km International Space Station 595 km Hubble Space Telescope km Sun-synchronous satellites LEO MEO HEO km km km km GPS satellites image: BlueMarble

21 An Earth observation (EO) system 1. Platform 2. Instrument(s) Near-ground Airplane v Satellite + Passive, Active Analog, Digital Imaging, Non-imaging Panchromatic, Multispectral, Hyperspectral Spatial resolution Temporal resolution Viewing geometry Swath width Spectral resolution Radiometric resolution Image acquisition technique Specim ESA Microsoft

22 Instrument vs. Platform (= sensor vs. satellite) Instrument (Moderate Resolution Imaging Spectrometer) Platform (Terra) NASA Satellite (platform) A body in orbit around another body Can carry several instruments Approx functioning satellites in orbit < 10 % of satellites have sensors for mapping of natural resources Instrument (sensor) Measures EM radiation in a give direction and transforms it to a digital signal Described with spectral, radiometric and spatial resolution

23 Active and passive RS instruments Passive techniques: Energy source: solar radiation Aerial photos, optical satellite images The classic RS approach Active techniques: Energy source: own source for producing energy = the sensor emits radiation which is directed towards the target RADAR (RAdio Detection And Ranging) LIDAR (LIght Detection And Ranging)

24 Principles of optical satellite RS A Energy source B Radiative transfer in atmosphere C Interaction with target on ground (e.g. forest) D Reception of reflected signal E Electronic transfer of signal F Data interpretation G Mapping applications 1) Each target has its own way of absorbing and reflecting EM radiation. 2) RS instruments measure radiation reflected from the atmosphere, water bodies and terrestrial surfaces in different wavelengths and angles. 3) The reflected radiation is used to determine properties of the target (e.g. 3D structure, chemical properties). INVERSE PROBLEM 4) The interpretation of RS data is mathematical and statistical modeling. Data characterized by: spatial, spectral, radiometric and temporal resolutions

25 Some key concepts Exact definitions important! More detail in advanced courses. Spectral: refers to a radiometric quantity in a given wavelength (l) Radiance: the physical quantity linearly related to digital number (DN) radiant flux density emitted from a unit surface area into a unit solid angle [Wm -2 sr -1 ] sensor calibration: the procedure to determine the conversion coefficients of DN to radiance Lambertian surface: an ideal diffusely reflecting surface Same radiance when viewed from any angle Reflectance factor: the reflected radiance by a surface relative to that of an ideal Lambertian surface (0-1) Reflectance factor depends on viewing and illumination angles

26 Spectra? Optical remote sensing based on spectra of targets Reflectance of a target depends on: target s 3D structure target s chemical composition Illumination and measurement angles (state of atmosphere)

27 Atmospheric windows Interaction with the atmosphere = transmission NOT even across the spectrum Most RS sensors designed for mapping natural resources operate in these windows Some sensors (on meteorological satellites) directly measure absorption phenomena Visible + NIR part of the spectrum Windows roughly at: , , , and nm

28 The Multi-angle Imaging SpectroRadiometer (MISR) Zambia & Botswana Nadir Red, green, blue Nadir Green, red, NIR -70.5, nadir, Only red

29 Characterization of EO data Resolutions: spatial, spectral, temporal, radiometric Spatial resolution: The smallest angular or linear separation between two objects that can be resolved by the sensor. GSD ground sampling distance FOV field of view swath width IFOV instantaneous FOV GIFOV ground projected IFOV Note! GSD ( pixel size ) GIFOV Radiometric resolution: The sensitivity of the sensor to incoming radiance: How much change in radiance is needed before a change in recorded brightness value occurs?

30 Spectral resolution B4 B4 NEMO HCRF B B1 B2 B3 B Wavelength [nm] Hyperspectral - Dozens / hundreds of bands - high spectral resolution - Continuous cover Multispectral - Several bands - medium spectral resolution - Non-continuous cover of sampled interval Panchromatic - Single band - low spectral resolution - Non-continuous cover of sampled interval

31 What are these targets? Bidirectional reflectance factor Target A Target B Target C Target D Wavelength, nm Targets measured by a hyperspectral satellite sensor (EO-1 Hyperion) in central Finland in July 2010.

32 Temporal resolution How often the RS system records imagery of a particular area ( revisit time ). Latitude influences the revisit time. Pointability improved revisit time by altering satellite viewing geometry ( pointing on target ) High temporal resolution: < 24 hours 3 days Medium temporal resolution: 4 16 days Low temporal resolution: > 16 days Satellite imaging corporation

33 The trade-off between resolutions The higher the spatial resolution: The smaller the image area ( the lower the temporal resolution) The lower the spectral and radiometric resolutions The higher the spectral resolution The lower the spatial resolution The higher the radiometric resolution The lower the spectral and/or spatial resolution Solution? 1) To lay emphasis upon the most important resolution 2) To lay no emphasis on one specific resolution ( all medium resolutions)

34 1. Raw data (downloaded on computer) 3. Image enhancement = Making features of interest more visible / easier to interpret Visual Histogram normalization Color composites Filters / Texture Spatial filtering techniques Texture measures Information compression Many statistical methods (e.g. PCA) Vegetation indices (e.g. NDVI) 2. Preprocessing Radiometric Gives a scale to the pixel values i.e. DN to radiance Changes during the lifespan of a sensor Geometric Images into the correct projection, coordinate system and free of geometric distortions = Raw data transformed into a form that can be handled by the interpreter Atmospheric To remove the effect of atmosphere on the measured signal Not needed for all applications 4. Information extraction Image classification Unsupervised Supervised Final product retrieval Empirical regressions Physical models Operational products

35 Choosing the right RS data type 1) How large is the area? 2) How often? (Temporal resolution) 3) What are the physical and chemical properties of the target? (Spatial and spectral resolution) 4) Available funds / human resources / time?

36 Level 0 Product Typical processing levels of RS data Raw data Preprocessing A large number of methods Radiometric correction Level 1 Product At-sensor radiance data Choice depends on, e.g. accuracy requirements of end-user, available ground data and e.g., meteorological data Geometric and atmospheric correction Level 2a Product Level 2b Product Orthorectified data Atmospherically corrected data Statistical or physical models Validation Level 3 Product Thematic variables (mapped on uniform space-time grid scales)

37 Weaknesses of RS data Trade-off between resolutions (spectral, temporal, spatial, radiometric) For passive RS: cloudiness and darkness (Near-) polar regions in winter Boreal and tropical regions Continuity of satellite missions Sometimes: handling the large data volumes, underdeveloped and unautomated interpretation methods Often high initial costs

38 What s hot & future prospects Climate change monitoring Hyperspectral data Mapping natural resources and land use Public security systems and hazard monitoring Fusion of data from different sensor types Buzz words: gap filling, up- and down-scaling Time series analyses Hyperspectral missions Assimilation of optical and radar data Hazard monitoring DLR Sentinel missions NASA Sentinel 2A ESA

39 Internet resources RS data usually downloaded from web portals. New portals developed constantly. A wealth of RS data online! Most satellite data free. Most data available very soon after acquisition. NASA data free since 2008, portals user-friendly. Check:

40 Photosynthetic activity of vegetation in

41 After this lecture Learn about the Landsat missions, the most widely used RS data. Read Roy et al Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145: Open access article available at: