Lecture Outline. Lecture 4 Aerial Photography and Image Analysis. What Controls EMR Interactions within Water?

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1 Lecture 4 Aerial Photography and Image Analysis Dr Karen Joyce School of Environmental and Life Sciences Lecture Outline Revision Aerial photography history Camera types Image acquisition and distortion Annotation elements Photography basics focus, exposure, aperture Making measurements scale, distance, area, relief displacement Interpretation cues and keys Applications Field trip Bldg Purple What Controls EMR Interactions within Vegetation? Within leaf Photosynthetic processes, Photosynthetic + nonphotosynthetic pigments, Water content, Self-defense/regulatory mechanisms, Leaf internal and external structures Leaf Internal (structure, chemistry, processes) Form/morphology Orientation Coating Canopy Density and arrangement of leaves Crown form and layering Stand Structural properties Topography/microclimate Biomass Community What Controls EMR Interactions within Water? Water-interactions: Air-Water interface + atmosphere Water column Substrate features (sediment, benthic flora and fauna) Water-column: Absorption and Scattering Suspended and Dissolved matter Key controls: Surface roughness Organic matter Inorganic Matter Depth Substrate type 3 4 What Controls EMR Interactions within Minerals and Soils? Imaging Sensor Dimensions Minerals Similar controls on interactions as atmospheric gases Atomic level interactions of light with different minerals is unique due to their structure Results in distinctive mineral absorption spectra Source of minerals data: What controls the type of information you can extract from an image or a photograph taken from an aircraft or satellite? Image Information Size of objects and features Controlling Dimension Spatial Soils Main controls: - Mineral content (e.g. iron oxide) - Organic content (e.g. leaf litter) - Roughness / texture (sand, silt, clay) - Moisture content Colour of objects and features Contrast between objects and features Time of day, year, tidal cycle, growth cycle Spectral Radiometric Temporal 5 6 1

2 Resources Aerial Photographs Thomas M. Lillesand, Ralph W. Kiefer, Jonathan W. Chipman (2008) Remote Sensing and Image Interpretation, 6th Edition. John Wiley & Sons, Hoboken, NJ. ISBN Chapters 2,3,4 Northern Territory Library Aerial Photo collection NASA Remote Sensing Tutorial - Aerial Photography Section Australian Spatial Data Directory Australia's largest aerial survey company - Fugro Spatial Solutions Pty Ltd. RSCAL module 3 Aerial Photo Interpretation Original remote sensing data source Historic development of remote sensing Current status of this technology Future of aerial photography Digital camera systems matching spatial resolution multi-spectral digital, georeferenced data temporally stable automatic terrain correction generation of elevation surfaces and orthophotos Source: ISPRS Highlights Film vs. Digital Workflows DMC Panchromatic Image Analogue workflow Film Film processing in darkroom B&W Color Stereo plotter DTM Orthophotos B&W Color FCIR Films used alternatively FCIR Photoscan Mapping Revision Digital workflow Archive system Visualization GIS Data storage Post Processing Software Digital workstation Image analysis Classification RGB & NIR Sem Lecture 4 GEOM2000/7000 Remote Sensing Printer of Environment B&W Color MS 9 Source: G.Kelly Source: G.Kelly 10 DMC True Colour Image DMC Colour Infrared Image Source: G.Kelly 11 Source: G.Kelly 12 2

3 Current Airborne Systems LINE-ARRAYS Size Bands Leica ADS-40 12,000 wide 4 pan, 8 MS DLR HRSC 12,000 wide 5 pan, 4 MS Jenna Optronik 12,000 wide 5 pan, 4 MS FRAME ARRAYS Integraph DMC 13,824 x 7,680 4 pan, 4 MS Camera Types Vertical frame (metric or mapping) Large format camera Strip camera Multi-spectral or multi-band camera Panoramic camera Oblique cameras (high and low) MS Vexcel Ultracam DiMac 14,430 x 9,420 9 pan, 4 MS 10,500 x pan Vertical Aerial Photos Vertical Aerial Photos Vertical Aerial Photos Geometric Distortions Geometric distortions due to aircraft motion Roll Pitch Yaw 17 Source: Biology-resources.com / NASA 18 3

4 Radiometric Distortions Radiometric distortions due to viewing angle differences in overlap areas Photographic Elements Annotation Date Level Run number Frame ID / Photo number North point Exposure Flight heading Flying height (AGL = above ground level or terrain (H ), ASL = above datum or sea level (H)) Focal length Copyright Fiducial marks (corners, sides) Use to locate photo centre Principal point Exact centre of photographic frame + Basis for measurements Conjugate principal point Principal points in overlapping photos NADIR point Ground point directly below camera optical axis Photographic Annotation Elements Geometry Heights H = height above datum (from altimeter) H = height above terrain h = terrain elevation above datum H = H h 1:25000 Colour aerial photograph, Amity Point, North Stradbroke Is. Copyright: Queensland Dept. of Natural Resources A ratio of distance (d) on an aerial photograph to the same distance on the ground (D). S = aerial photo distance/ground distance = d/d Scale calculation over flat terrain: S = d/d or S = f/h = f / (H-h), where f = focal length and H = height above terrain For variable terrain H will change over the photographed area, use an average H Express scale in specific units as: Representative fraction 1 / 25,000 Ratio 1 : 25,000 Verbal 1cm on the photo = 250m on the ground Scale 23 S = d/d Where, d = distance on photo D = distance on ground Scale Calculation Eg. Distance on photo (d) measure with a ruler = 2cm Distance on ground = 500m Ensure units are the same 2cm =.02m S = 0.02 / 500 Divide top and bottom by the numerator If you get an answer like , this is incorrect S = 1 / Or, 1cm on the photo = 250m on the ground 24 4

5 Scale Calculation S = f/h = f / (H-h) Where, f = focal length H = ht above terrain Large Scale or Small Scale? Scale is a fraction eg 1 / 25,000 Therefore large or small refers to the size of the fraction A low detail, large area map may be 1 / 250,000 Small! A high detail, small area map may be 1 / 5,000 Large! Eg. focal length (f) = 152mm Flying height (H)= 5,000m ASL Average terrain (h)= 100m Height above terrain (H ) = 5, = 4,900m Ensure units are the same 152mm = 0.152m S = f/h S = 0.152/4,900 Divide top and bottom by the numerator S = 1 / Or, 1cm on the photo = 322m on the ground Distance and Area Relief Displacement Distance calculation over flat terrain Calculate scale of photograph Measure distance on photograph Convert distance to scale units Multiply scale denominator by distance The radial distance between an object s image and its true plan position which is caused by changes in terrain elevation or object height. Top of the feature lies further from the photo center than the base Vertical feature appear to lean away from photo center Relief Displacement Relief Displacement d = rh/h d = relief displacement r = radial distance on the photo from the principal point to the top of the displaced feature h = Height above ground of the feature H = Flying height above the ground d will increase if r and/or h increase d will decrease if H increases

6 Relief Displacement What is the height of the tower? d = rh/h d = 2.01mm r = 56.43mm Flying height above ground H = 1220m Rearrange equation: h = dh/r h = 2.01 x 1220 / h = 43.4m PP Image Interpretation Systematic approach from general to specific interpretation Interpretation involves both: Detection of a feature Identification of a feature Automated photo and image interpretation now uses this technique Aerial Photography Analysis Success Perceptual ability Training Experience Discipline knowledge (forestry, geology, soils etc) Equipment (stereoscope, magnifying scale etc) Ancillary data (maps, fieldwork, reports etc) Interpretation Cues Cue Terminology Example Tone / Colour Dark, light, bright, dull Dark Blue (water) Texture Smooth, rough Rough (urban area); Smooth (grass) function of scale Shape Size Pattern Shadow Site / Association Rectangular, eliptical, regular, irregular Relative or absolute Regular, random, gridlike Presence, absence Description of spatial relationships Rectangular (crops) Small / large or 200x100m Repeating linear rows (vineyard) Long shadows observed to the SW of the feature (can indicate height of object, time of day, southern hemisphere). Influences tone and texture Large carpark beside large building (may indicate shopping centre rather than factory) Dichotomous Keys Minimum Mapping Units Smallest size entity to be mapped as a discrete feature Small MMU = high detail Large MMU = low detail Small MMU can be a step in the hierarchy of a large MMU e.g. river, lake, stream, creek, can be grouped together to the larger MMU of water body

7 Classification Guidelines (from USGS LU/LC mapping) Interpretation and Class Aggregation Overall accuracy <= 85% Individual category accuracy should be about equal Repeatable results between interpreter and over time Applicable over extensive areas Suitable for use with data obtained at different times of the year Categories should be divisible into more detailed sub categories Aggregation of categories must be possible Comparison with future date should be possible Multiple uses of a category should be recognised where possible Image Interpretation Classification Example What features can you see in this image and what interpretation cues would you use to create a key for different features? Worldview 2 Image Dark or bright? Non Water Btn land and water Inter-tidal Land Green Not green Circular, Irregular rough, shape, shadows smooth Trees Grasses Artificial Surfaces Water Small, urban pattern Assoc. trees, grass Large, Assoc. main roads Surrounded by Long, thin water 39 Inter-tidal Trees Grasses Housing Commercial / Industrial Roads Jetty Water 40 Aerial Photography and Geology Infrastructure Mapping 41 Source: AAM 42 7

8 High Resolution 3D Mapping / Modelling Source: AAM Mine Site Monitoring 43 Landcover / Landuse Geothermal Assessments Source: Fugrospatial 45 Low Cost Aerial Photography Source: Fugrospatial 44 S.Bayley, Horizons Regional Council Low Cost Aerial Survey 48 S.Bayley, Horizons Regional Council 8

9 NASA Ikhana Unmanned Airborne System To Support Airborne Wildfire Monitoring Capabilities, a Number of Key Variables Were Identified: Ability for long endurance / long legs. Linger ability Medium to High Altitude Autonomous Payload Capability Data Collection and Distribution Primary products: GEOTIFF and Shapefiles Data usually available within 3-5 minutes Google Earth and WMS provide first look at data Message notifies when data are available Google Earth Payload GCS GEOTIFF Shapefile Data Processing KML conversion WMS CAP notification Publish Internet WMS web server FTP Server Operate in Hazardous Conditions (if necessary) IC Ikhana capable of ~24-hour mission endurance; ~4000 miles; >40K feet altitude; Payload to 1500 lbs FTP mirror site Ikhana is Native American-Choctaw word meaning: intelligent, aware V.Ambrosia et al., NASA 49 UAV Imagery in Google Earth UAV Process 51 The UAV in Perspective Grass Valley & Slide Fire October Global Hawk 53 V.Ambrosia et al., NASA 50 V.Ambrosia et al., NASA 54 9

10 Field Trip This Thursday 28 th March Bus departs 8.15am outside CDU bus stop Noonamah pick up 9am, Bachelor at 9.40am for those students who have already requested it Make sure you wear: Comfortable, CLOSED shoes (not thongs or sandals) Appropriate clothing, including long pants Field Trip Make sure you bring: Clip-board with paper or exercise book Pens/pencils Ruler Scientific calculator Food and drinks for the day (NB: there will not be any opportunity to purchase food or drink during the day) Sunscreen Aerogard or similar Hat Togs / towel if you plan to swim at lunch Change of clothes / shoes if the weather is wet Coming Up 1 st Practical assessment due Image Characteristics and Dimensions Easter Break next week (no lecture or prac) Next lecture Digital Image Processing - 1 Next prac Digital Image Processing part