Sensors and Data Interpretation II. Michael Horswell

Transcription

1 Sensors and Data Interpretation II Michael Horswell

2 Defining remote sensing 1. When was the last time you did any remote sensing? acquiring information about something without direct contact 2. What are the requirements for remote sensing to possible? - ability to detect something that defines the characteristics of what is being observed, - electromagnetic radiation (EMR) that objects either emit or reflect

3 The problematic view from space Unlimited perspectives on ourselves, the world and the cosmos around us Benefits cannot be over estimated Deployed against the environmental threat, to prevent new ecological and economic falling dominoes and enhance global security Rather than being embedded participants in the reality depicted, earth system scientists become disengaged observers of that reality When quantifiability monopolizes the mantle of legitimacy, qualitative values are given short shrift Decontextualization

4

5 A refined (formal) definition Remote sensing is the practice of deriving information about the Earth s land and water surfaces using images acquired from an overhead perspective, by employing electromagnetic radiation in one or more regions of the electromagnetic spectrum, reflected or emitted from the Earth s surface (Campbell 2006 p. 6)

6 History of remote sensing

7 1825: Photography 1956: Infra-red & plant health 1972: Landsat : From balloons : WWII: Non-visible radiation 1980s: Hyperspectral RS 1873: Electromagnetism The Great Depression 1990s: Hi-Res spaceborne images 1909: Airplanes 1914: WWI reconnaissance Present: Global RS systems & LiDAR

8

9 Interpreting images

10 Why interpret images? Classification: assigning discernible areas or features to classes Enumeration: counting or listing discrete items visible on an image Measurement: photogrammetry applying knowledge of image geometry to the derivation of accurate measurement Delineation: defining observable regions

11 Methods of interpretation Field observations If knowledge of interpreter is inadequate, a field visit may be required Field visits are routine as a method of checking accuracy Direct recognition Qualitative, subjective interpretation based on experience, skill and judgement Interpretation by inference Using an observable characteristics to infer the presence on a non-observable characteristic e.g. using landform and vegetation to infer soil characteristics

12 Methods of interpretation Probabilistic interpretation Integrating other information into the interpretation process, e.g. knowledge of crop rotation and crop calendar can help to identify the crop growing in a region if winter wheat is harvested in June, the crop on your August image is unlikely to be wheat A decision rule is created which expresses the knowledge as a probability, e.g. there is only a 2% probability that the crop is wheat

13 Methods of interpretation Deterministic interpretation Based on quantitative relationships inherent in the imagery itself, e.g. using stereo imagery pairs to develop elevation data Image interpretation will more than likely involve a mixture of interpretative strategies

14 Elements of interpretation Tone: refers to shades of grey (B&W) or colours in the image. Tone of the same feature type may vary seasonally. Texture: the result of changes in tone, or the arrangement of tone on a landscape (described as e.g. fine, medium, or coarse) Shadow: gives clues to the profile, and shape of landscape features but can obscure detail in other features, as well as alter the spectral signature of other features Pattern: the arrangement of objects into recurrent forms can facilitate their recognition Shape: is an important clue to identifying an object and helps, in particular, to distinguish between constructed and natural features Size: relative size - the size of an unknown object in relation to the size of a known object; absolute size - the actual size of a landscape features Association: some types of features can be identified despite no compliance with any other interpretative element, but through relationships with identifiable features

15 Convergence of evidence Image interpretation is a deductive process Features that can be detected and identified lead the interpreter to the location and identification of other features Deductive interpretation requires either the conscious or unconscious consideration of all of the elements of image interpretation The completeness and accuracy of an interpretation is related to the interpreter s understanding of the "how and the why" of the elements, and the techniques and methods of interpretation This is convergence of evidence combination of knowledge, expertise, image elements, interpretative strategies to come up with a defensible interpretation

16 People vs. computers Jelly bean that made the news People are extremely good at image interpretation pattern seeking and recognition Believed to have significant evolutionary value at little cost Computers are more sceptical

17 When is enough proof enough? A definitive determination of landcover based on remotely sensed data is achieved when all relevant elements of interpretative process have been considered, and the assessment of no single element stands in strong contradiction to the overall assessment

18 More than meets the eye: Multispectral imagery

19 The electromagnetic spectrum Continuous range of electromagnetic radiation from radio waves (low frequency, long wavelengths) to gamma rays (high frequency, short wavelengths)

20 Reflection and absorption Objects reflect and absorb different parts of the EMS The combination of these generates a set of observable characteristics that allow us to identify the object

21 Beyond the visible Although we cannot see outside of the visible spectrum, we can detect these wavelengths using sensors Pictures depict flowers refection in the UV part of the spectrum bee s eye view

22 Spectral signatures The particular reflectance and absorption characteristics of EM radiation from the surface of an object is called its spectral signature All surfaces on earth have a specific spectral signature A surface type or material can be identified if the sensor has adequate spectral resolution do distinguish it from other materials The spectral signature of an object is a plot of the fraction of radiation reflected as a function of the incident wavelength

23 Multispectral imagery Measures of radiation in more than one part of the spectrum not only the visible part Each part in which measurement occurs is called a spectral band - a discrete part of the EMR spectrum Spectral bands of satellite-based remote sensors have been selected to enable the discrimination of major surface materials The specific parts of the EMR spectrum that a sensor can detect is called its spectral resolution

24 Landsat spectral bands Landsat 8: OLI & TIRS Band Wavelength EMS Area / Target Coastal aerosol Blue Green Red Near infrared (NIR) Short-wave infrared (SWIR) Short-wave infrared (SWIR) Panchromatic Cirrus TIRS TIRS 2 Landsat 4,5: TM & Landat 7: ETM+ Band Wavelength EMS Area / Target Blue Green Red Near infrared (NIR) Short-wave infrared (SWIR) Short-wave infrared (SWIR) Panchromatic Thermal Infrared

25 Spectral response curves Represent the reflectance of target objects across the EMS Define the objects due to the characteristic reflectance of objects Equivalent to tone in traditional image interpretation

26 Vegetation reflectance Chlorophyll absorbs red and blue parts of the visible spectrum Palisade mesophyll grouped as it is, means green light is reflected Chlorophyll transmits NIR, but the arrangement of cells in the spongy mesophyll layer causes high reflection in NIR

27 Characteristic reflectance Feature Water Bodies Soil Vegetation Man-Made Materials Snow and Ice Reflectance Response Generally reflect high in the visible spectrum, however, clearer water has less reflectance than turbid water. In the Near IR and Mid-IR regions water increasingly absorbs the light making it darker. This is dependent upon water depth and wavelength. Increasing amounts of dissolved inorganic materials in water bodies tend to shift the peak of visible reflectance toward the red region from the green region (clearer water) of the spectrum. Northern latitudes have black soils and tropical regions have red soils. Soil reflectance decreases as organic matter increases. As soil moisture increases, reflectance of soil decreases at all wavelengths. Texture of soil will cause increased reflectance with decreased particle size, i.e., the bigger particles (rocks, sand, and soils) basically cast a larger shadow. The spectral reflectance is based on the chlorophyll and water absorption in the leaf. Needles have a darker response than leaves. There will be various shades of vegetation based on type, leaf structure, moisture content and health of the plant. Healthy vegetation has high IR reflectance decreases with plant stress. Concrete and asphalt both display spectral curves that generally increase from the visible through the Near IR and Mid-IR regions. However, as concrete ages, it becomes darker and as asphalt ages it becomes lighter. Old snow may develop a compacted crust and the moisture content increases which make it less reflective in the Near IR and Mid-IR region. It is possible to compare old and new snow by its Mid-IR reflectance. GIS & Remote Sensing Applications 27

28 Visualizing non-visible wavelengths Band 2 Band 3 Band4 Band5 Band6 Band7

29 Band combination: 432 The "natural colour" band combination Because the visible bands are used in this combination, ground features appear in colours similar to their appearance to the human visual system, healthy vegetation is green, recently cleared fields are very light, unhealthy vegetation is brown and yellow, roads are grey, and shorelines are white This band combination provides the most water penetration and superior sediment and bathymetric information, it is also used for urban studies Cleared and sparsely vegetated areas are not as easily detected here as in the 562 or 543 combination Clouds and snow appear white and are difficult to distinguish Vegetation types are not as easily distinguished as the 562 combination The 432 combination does not distinguish shallow water from soil as well as the 764 combination does

30 Band combination: 432

31 Band Combination: 543 The standard "false colour" composite Vegetation appears in shades of red, urban areas are cyan blue, and soils vary from dark to light browns Coniferous trees will appear darker red than hardwoods Deep red hues indicate broad leaf and/or healthier vegetation while lighter reds signify grasslands or sparsely vegetated areas Ice, snow and clouds are white or light cyan Urban areas are shown in light blue This band combination gives results similar to traditional colour infrared aerial photography This band combination is useful for vegetation studies, monitoring drainage and soil patterns and various stages of crop growth.

32 Band Combination: 543

33 Band Combination: 562 Healthy vegetation appears in shades of reds, browns, oranges and yellows Soils may be in greens and browns, urban features are white, cyan and grey, bright blue areas represent recently clear-cut areas and reddish areas show new vegetation growth, probably sparse grasslands Clear, deep water will be very dark in this combination, if the water is shallow or contains sediments it would appear as shades of lighter blue The addition of the Mid-IR band increases sensitivity of detecting various stages of plant growth or stress; however care must be taken in interpretation if acquisition closely follows precipitation Use of OLI5 and OLI6 shows high reflectance in healthy vegetated areas Compare flooded areas and red vegetated areas with the corresponding colours in the 432 combination to assure correct interpretation

34 Band Combination: 562

35 Band Combinations: 564 This combination offers added definition of land-water boundaries and highlights subtle details not readily apparent in the visible bands alone Inland lakes and streams can be located with greater precision when more infrared bands are used Vegetation type and condition show as variations of hues (browns, greens and oranges), as well as in tone Demonstrates moisture differences and is useful for analysis of soil and vegetation conditions. Generally, the wetter the soil, the darker it appears, because of the infrared absorption capabilities of water.

36 Band Combination: 564

37 Band Combination: 753 Penetrates atmospheric particles and smoke. Healthy vegetation will be a bright green and can saturate in seasons of heavy growth, grasslands will appear green, pink areas represent barren soil Dry vegetation will be orange and water will be blue Sands, soils and minerals are highlighted in a multitude of colours It is useful for geological, agricultural and wetland studies Fires would appear red. This combination is used in the fire management applications for post-fire analysis. Urban areas appear in varying shades of magenta Grasslands appear as light green. The light-green spots inside cities indicate grassy land cover - parks, cemeteries, golf courses Olive-green to bright-green hues normally indicate forested areas with coniferous forest being darker green than deciduous.

38 Band Combination: 753

39 Band Combination: 764 Penetrates atmospheric particles, smoke and haze Vegetation appears in shades of dark and light green during the growing season, urban features are white, grey, cyan or purple; sands, soils and minerals appear in a variety of colours Provides well defined coast lines and highlighted sources of water within the image. Snow and ice appear as dark blue Hot surfaces such as forest fires and volcano calderas saturate the Mid-IR bands and appear in shades of red or yellow Flooded areas should look very dark blue or black, compared with the 432 combination in which shallow flooded regions are difficult to distinguish.

40 Band Combination: 764

41 Band Combination: 765 This combination involves no visible bands It provides the best atmospheric penetration Coast lines and shores are well defined It may be used to find textural and moisture characteristics of soils Vegetation appears blue This band combination can be useful for geological studies

42 Band Combination: 765

43 Band Combination: 654 This combination provides the user with a great amount of information and colour contrast Healthy vegetation is bright green and soils are mauve Use of Band 6 ensure maximal agricultural information This combination is useful for vegetation studies, and is widely used in the areas of timber management and pest infestation

44 Band Combination: 654

45 Remember CONVERGENCE OF EVIDENCE Spectral response alone may not be enough to determine the characteristics of an observed object