SATELLITE IMAGE INTERPRETATION Mirza Muhammad Waqar Contact mirza

SATELLITE IMAGE INTERPRETATION Mirza Muhammad Waqar Contact: mirza. waqar@ist. edu. pk +92 -21 -34650765 -79 EXT: 2257 RG 610 Course: Introduction to RS & DIP

Contents 2 Geographical Information System Remote Sensing & Satellite Image Processing Color Space Landsat 7 spectral bands Spectral Reflectance Curves Image Interpretation Spectral Ratioing Indices

Geographical Information System (GIS) Data Methods Software Site Suitability Analysis Spatial Analysis 3 D Analysis Hydrological Analysis Finding Shortest Path Finding Closest Facility Change Detection

Remote Sensing & Satellite Image Processing

Spectral vs Spatial Spectral pattern recognition Family of classification procedures that utilize pixel by pixel spectral information as the basis for automated land cover classification. Spatial pattern recognition Categorization of image pixels on the basis of their spatial relationship with pixels surrounding them.

Landscape visualization 6 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

The ground view 7 Ground view of Mt. Everest, the highest spot on earth.

Visualization – Bird-Eye View 8 Bird-eye view of Mt. Everest. The photo was taken by astronauts on the International Space Station.

Visualization – Orthographic View 9 Orthographic view of Mt. Everest. The photo was taken by astronauts on the International Space Station in 1993.

The concepts of image interpretation 10 Image interpretation: the process of identifying objects or conditions in images and determining their meaning or significance. The interpreter’s task: use scientific methodology to arrive at objective findings. tools and 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.

Spatial interpretation 11 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.

Obvious features 12 Low-altitude photograph of the Pentagon Building, headquarters of the US Department of Defense Multi-runway airfield used by carrierbased pilots for practicing short takeoffs and landings (Broward County, Florida)

Keys for image interpretation 13 q q Shape Size Pattern Shadow q q Tone or colour Texture Association Site

Shape 14 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.

Pyramids 15 Ground view of the Great Pyramids, Egypt.

Shape 16 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.

A Centre-Pivot Irrigation System 17 A centre-pivot irrigation system in Ili, Xinjiang, China.

An Alluvial fan 18 Ground view of alluvial fans at the north of Turpan Depression, Xinjiang, China.

Size 19 Panchromatic photo of Bangkok, 1982. Note the size of buildings tends to indicate the nature and usage of them.

Pattern 20 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.

Natural Patterns 21 The patterns of forest and wetland show significant variation on remotely sensed images.

Loess Landscape 22 The high density of gullies is the key for image interpretation of the loess landscape.

Shadow 23 Shadow shown with low sun angle is the key to the interpretation of shape of Mt. Everest.

Tone or Color 24 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.

Texture 25 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).

Association 26 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.

Site 27 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.

Spectral interpretation 28 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 Secondary Colors Primary Colors Red + Blue Magenta Green + Blue Cyan Magenta + Cyan Blue Yellow + Cyan Red + Green Yellow Green

Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Landsat 7 Wavelength (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 Yaqoob Wateen 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 Band Combination RGB: 542 Vegetation: R=38% G=48% B=17% Grey Tone=17% -----------R=21% G=31% B=0% Yellow Tone= 21% -----------R=0% G=10% B=0% Vegetation: Green Dominating Yellow Soil: ? Snow: ? Cloud: ? Water: ?

Questions & Discussion