SATELLITE IMAGE INTERPRETATION

Course: Introduction to RS & DIP

Mirza Muhammad WaqarContact:

mirza.waqar@ist.edu.pk+92-21-34650765-79 EXT:2257

RG610

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Contents

Geographical Information System Remote Sensing & Satellite Image Processing Color Space Landsat 7 spectral bands Spectral Reflectance Curves Image Interpretation Spectral Ratioing Indices

Software

Geographical Information System (GIS)

Data

Site Suitability AnalysisSpatial Analysis3D AnalysisHydrological AnalysisFinding Shortest PathFinding Closest FacilityChange Detection

Methods

Remote Sensing & Satellite Image Processing

Spectral vs Spatial

Spectral pattern recognitionFamily of classification procedures that utilize pixel by pixel spectral information as the basis for automated land cover classification.

Spatial pattern recognitionCategorization of image pixels on the basis of their spatial relationship with pixels surrounding them.

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Landscape visualization

The ground view Field investigation and survey Great details, sample taken and field measurements High cost, time consuming, physically demanding

The bird-eye view Natural observation, perspective view Difficult for mapping and locationing

The orthographic view Professional aerial survey and space mapping High locational accuracy, fast coverage, economic Lack of 3-dimensional information, skill demanding

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The ground view

Ground view of Mt. Everest, the highest spot on earth.

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Visualization – Bird-Eye View

Bird-eye view of Mt. Everest. The photo was taken by astronauts on the International Space Station.

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Visualization – Orthographic View

Orthographic view of Mt. Everest. The photo was taken by

astronauts on the International Space Station in 1993.

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The concepts of image interpretation

Image interpretation: the process of identifying objects or conditions in images and determining their meaning or significance.

The interpreter’s task: use scientific tools and methodology to arrive at objective findings.

Geographical knowledge is needed to relate the visible characteristics on the image to the real-world geographical features, even though some of these features may not be physically visible.

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Spatial interpretation

Spatial interpretation means identifying geographical features using spatial characteristics of objects shown on images.

The most important tasks for spatial interpretation is to establish interpretation keys, i.e. identifying the typical spatial and spectral patterns of known geographical features.

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Multi-runway airfield used by carrier-based pilots for practicing short takeoffs and

landings (Broward County, Florida)

Low-altitude photograph of the Pentagon Building, headquarters of the US

Department of Defense

Obvious features

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Keys for image interpretation

Shape Size Pattern Shadow

Tone or colour Texture Association Site

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Shape

Some man-made features have unique shapes.

Alluvial fans along the east side of Death Valley, California. Alluvial fans can be easily recognised by their fan shape and adjacency to mountain fronts.

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Pyramids

Ground view of the Great Pyramids, Egypt.

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Shape

Centre-pivot irrigation system in Morrow County, Oregon. Most of the fields are planted with wheat.

Alluvial fans at the north of Turpan Depression, Xinjiang, China.

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A Centre-Pivot Irrigation System

A centre-pivot irrigation system in Ili, Xinjiang, China.

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An Alluvial fan

Ground view of alluvial fans at the north of Turpan Depression, Xinjiang, China.

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Size

Panchromatic photo of Bangkok, 1982. Note the size of buildings tends to indicate the nature and usage of them.

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The contrast between sand dunes (left) and loess (right) landscapes found near Yulin, Shannxi, northern China. The mobile sand dunes are well recognised by their repeated patterns, while the high density of gullies of the loess landscape suggests severe soil erosion and mass movement.

Pattern

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Natural Patterns

The patterns of forest and wetland show significant variation on remotely sensed images.

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Loess Landscape

The high density of gullies is the key for image interpretation of the loess landscape.

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Shadow

Shadow shown with low sun angle is the key to the interpretation of shape of Mt. Everest.

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Tone and colour are used to identify agricultural fields. The fields with crops or harvested are clearly separated by their tones and colours. Also note the tone difference shown on the bare fields indicating different soil moisture contents.

Tone or Color

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Texture

Textures associated with forest, pasture and cropland. The colour photograph shows the strong contrast in texture between forest (dark and coarse), pasture (light and smooth and farmland (light and smooth with regular road and drainage network).

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A chain of oasis is located along the toe of an alluvial fan in Turpan Depression, Xinjiang, China. There is a good supply of shallow groundwater to support irrigation system and human settlement in the extremely dry area.

Association

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Sea Port at Kowloon Peninsula of Hong Kong. The site is characterised by regular shore line and large concrete area of loading zones. The extensive transportation network also a good key to identify the port.

Site

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Spectral interpretation

The spatial interpretation keys are also employed to interpret multi-spectral images. Scale Spatial distortion

Multi-spectral images, however, add one more dimension (i.e. the spectral space) for image interpretation.

Understanding spectral signature is therefore mandatory for image interpretation.

Color Space

Red + Blue Magenta

Green + BlueCyan

Red + Green Yellow

Primary Colors

Magenta + Cyan Blue

Yellow + Cyan Green

Yellow + Magenta Red

Secondary Colors

Landsat 7

Enhanced Thematic Mapper Plus (ETM+)

Landsat 7Wavelength

(micrometers)Resolution (m)

Band 1 0.45 - 0.52 30

Band 2 0.52 - 0.60 30

Band 3 0.63 – 0.69 30

Band 4 0.77 – 0.90 30

Band 5 1.55 – 1.75 30

Band 6 10.40 – 12.50 60

Band 7 2.09 – 2.35 30

Band 8 0.52 – 0.90 15

Spectral Reflectance Curves of Different Land Covers

Source: Yasir YaqoobWateen Telecom

Reflection of Different Land Covers in Landsat Bands

* Vegetation Soil Snow Cloud Water

Band 1 10 % 20 % 97 % 70 % 5 %

Band 2 17 % 24 % 96 % 70 % 8 %

Band 3 10 % 28 % 94 % 70 % 2 %

Band 4 48 % 35 % 85 % 66 % 1 %

Band 5 38 % 50 % 10 % 52 % 1 %

Band 7 20 % 55 % 8 % 53 % 1 %

Islamabad Capital Territory – Raw Image

Vegetation: Green Dominating YellowSoil: ?Snow: ?Cloud: ?Water: ?

Band Combination RGB:542Vegetation:R=38% G=48% B=17%Grey Tone=17%-----------------------R=21% G=31% B=0%Yellow Tone= 21%-----------------------R=0% G=10% B=0%

Questions & Discussion