research notebook digital methods in...

Research NotebookDigital Methods in Archaeology

Crystal Lee

Winter Quarter 2015

Contents1 Introduction to Digital Methods 4

1.1 What are the digital humanities? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.2 Data storage types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3 Vector and bitmap images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.4 Lossless and lossy compression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 Scanners and Total Stations 52.1 Introduction of the Pumapunku . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 Why the Pumapunku? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.3 Early work on the Pumapunku . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.4 Main data sources for 3D printed blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.5 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.6 Advantages of 3D printing in archaeology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.7 Imaging and Digitization Exercise (second part of class) . . . . . . . . . . . . . . . . . . . . . 6

3 Panoramic Virtual Reality 73.1 Image stitching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.2 Image registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.3 Calibration/alignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.4 Blending . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.5 Projective layouts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.6 Limitations of image stitching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.7 Applications of image stitching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4 Three-Dimensional Printing 94.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.2 Printing materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.3 Printing machines available in Lathrop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.4 Printing guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.5 Creating models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104.6 Final precautions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

5 GIS and GPS 115.1 Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115.2 Projection distortions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

5.2.1 Tissot’s indicatrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115.3 Projected vs. geographic coordinate systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 135.4 Shape files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

5.4.1 Mandatory files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135.4.2 Optional files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

5.5 Reprojection, project-on-the-fly, and defined projections . . . . . . . . . . . . . . . . . . . . . 13

6 Raster GIS and Remote Sensing 146.1 Raster GIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146.2 Remote sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

6.2.1 Types of remote sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146.2.2 Collecting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166.2.3 Types of resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

6.3 Remote sensing applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

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7 Photogrammetry 177.1 Why 3D modeling? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177.3 Additional reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

8 Three-dimensional scanning 188.1 Basics of 3D modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188.2 Types of 3D scanners1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

8.2.1 Short range scanners (focal distance of <1 meter) . . . . . . . . . . . . . . . . . . . . 188.2.2 Mid to long range scanners (focal range of >2 meters) . . . . . . . . . . . . . . . . . . 19

8.3 Additional reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191Geomagic, “3D Scanners: A Guide to 3D Scanner Technology.” Retrieved 26 February 2015. http://www.rapidform.com/

3d-scanners/

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1 Introduction to Digital Methods

1.1 What are the digital humanities?• Use of computational and digital methods in order to conduct research in the humanities, usually in

the creation and processing of data

• Wide range from word processing to using geospatial data analysis, from digitized versions of researchmaterials to new ways of representing data

– Integrated/accessible collections of research materials (e.g. historical archives that are now freelyavailable on the Internet; OCR)

– Data aggregation, processing, and visualization (e.g. GIS, R)– Collaborative workspaces, academic community building (e.g. cloud storage services)– Dissemination and output (e.g. personal research blogs, informal articles, digitized journals)

1.2 Data storage typesBits A bit is the smallest unit of measurement for data, which must have a binary value.

Bytes A byte (equivalent to 8 bits) is used as the fundamental unit of measurement for data today,which can store 256 (28) different values.

1.3 Vector and bitmap imagesVectors Use mathematical formulas to draw lines and curves of an image, rather than assigning a color

to each pixel. As such, vector images tend to be smaller and more scalable than bitmap images.There are no backgrounds, and it is not good for rendering photo-realistic images.

• Common formats: EPS, PDF, PICT (Mac only)

• Pros: smaller file size, resolution independence = highly scalable.

• Cons: not well supported on the web so must be converted to a bitmap image before uploading, notgood at rendering photo-realistic images.

Bitmaps Also called raster images. Created with pixels in a grid, which makes it resolution dependent(resizing reduces quality). These types of images are easily converted, and restricted to rectangles.

• Common formats: BMP, GIF, JPEG, JPG, PNG, PCX, TIFF, PSD (Adobe Photoshop)

• Pros: good for web development, photo-realistic, easily converted.

• Cons: not easily scalable, larger file size.

1.4 Lossless and lossy compressionIt is possible to compress data so that it reduces the size of storage needed (or bandwith to transmit it) withno loss of information from the original file. You can convert an image, for example, by telling the computerto resolve an area of the same color by specifying that it is “200 red dots” instead of “red dot, red dot, ...,red dot.”

Lossless Compression style that allows you to recreate the original file exactly by breaking a file into“smaller” forms of transmission or storage and then putting it back together in a useable way. Itis always possible to return to the original file using this type of compression.

Lossy Compression style where some loss of quality is acceptable. (For example, since the human earcannot hear all frequencies, then it is acceptable for a lossy compression software to throw awayall parts that people can’t hear in order to create a smaller file.) However, it’s not possible torevert back to the original file with this type of compression.

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2 Scanners and Total Stations3D Printing the Stone Blocks of the Pumapunku: Guest Lecture by Alexei Vranich (UCLA)

2.1 Introduction of the PumapunkuScholarship of the Pumapunku primarily colored by conspiracy theorists that like to discuss how these peopleused alien technology in order to set the stones in place.

• Often difficult to do archaeological work in this context because the site is often saturated with peopletrying to film conspiracy documentaries

• Further complicated by visas/rights to archaeological sites by host government (Peru)

• No one knows how these blocks fit together—long-lasting archaeological mystery with no end in sight

2.2 Why the Pumapunku?• Started project completely by accident—started out doing work for USAID in Peru, became looped

into the archaeological site after USAID operations stopped for lack of funding

• Worked on the site with principal investigator, hired as part of the team–later gave tour of the Puma-punku site to then-First Lady Hillary Clinton, whose presence helped legitimize Vranich’s extendedstay at the archaeological site

2.3 Early work on the Pumapunku• Edmund Kiss (1939) received funding from Himmler to reconstruct the site so that the Pumapunku

could be used as a model for Hitler’s headquarters in Berlin

– Later work was hampered by the limited resources that needed to be funneled for war– Lots of available sketches housed in Germany from these excavations

• J. P. Protzen and architectural sketches: Protzen measured the blocks down to the millimeter andtheorized about how the blocks could fit together

– Diagrams are printed on the page, but there is never an entire sketch for what the finished scenecould look like

Most of the work that Vranich does on the Pumapunku has been in large part indebted to Protzen’s sketches.Almost all of the 3D prints are based on dimensions given by Protzen’s notes (which Vranich retrieved fromProtzen himself, and from libraries in Germany).

2.4 Main data sources for 3D printed blocks(1) 130 years’ worth of sketches from Edmund Kiss and J. P. Protzen

• Intuitive, easy to understand because these are interpretations by humans, for humans

• Easy to acquire because of Protzen’s generosity (getting notes from another academic to use for yourown research is usually a near-impossible task)

• Incredibly detailed notes in wonderful condition – very meticulous measurements!

(2) Laser scanner that Vranich and team brought into Peru (stuck at customs office for months)

• Often unwieldy, took too much time/effort to use because it simply collected too much data that theteam wasn’t interested in (e.g. texture of the stone block)

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• In some ways, laser scanner wasn’t as specific as Protzen’s drawings, as it didn’t fit the way that ourmind worked

• High probability of data loss because team couldn’t efficiently transfer information from the machineto computers (whose hard drives often failed in site conditions)

2.5 MethodsUsed a combination of SketchUp, MeshLab, and AccuTrans (cyanoacrylate infiltration in order to strengthenthe blocks right after they were finished printing)

• For the most part, Vranich seemed entirely uninterested in the methodology simply because he wantedthe blocks to be finished – had very little concern for the process

• Focus of Vranich’s research seems to be how the blocks are put together, which he often does in themorning while he drinks coffee and pets his cat (easier to actually think about how they will fit togetherwhen one is not intentional)

2.6 Advantages of 3D printing in archaeology• Tactile feedback allows us to quickly make connections between which blocks fit—impossible to do

with a simulation on a computer

• More intuitive way to work with information that is spatial in nature

• Gives instantaneous rendering of new ways to model the Pumapunku blocks

• Doesn’t involve the high level of technical proficiency to create the student reconstruction video (createdin Maya)

2.7 Imaging and Digitization Exercise (second part of class)The exercise from this class showed us how we could digitize published maps and scales it so that we cancalculate areas of excavated areas.

• The class exercise uses ImageJ and Didger (the latter is not compatible with Mac, so I used QGIS, anopen source GIS system that does more or less the same thing).

• Summary of exercise: use the listed scale (0 – 40 m) in ImageJ to show how the pixels in the imagerelate to the meters on the ground represented by the image

• Then, use QGIS or Didger to calculate the area of the bulldozed excavation area. (Instructions listedin Coursework site)

Notes from the exercise:

• Calibrate the image using Cartesian Coordinates, since we’re not actually geo-referencing the im-age—we’re creating a local coordinate system for the map itself

• The actual area of the bulldozed areas will be calculated using the polygon that you trace over thebulldozed areas (it is far from 100% accurate—there are many layers of human interpretation here).

• Possible to complete the entire exercise using just ImageJ (eliminate Didger entirely)

Reading for this class: Rick, John W. “Realizing the Illustration Potential of Digital Models and Images:Beyond Visualization.”

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3 Panoramic Virtual Reality

3.1 Image stitchingVirtual reality photography (VR photography) is the interactive viewing of wide-angle, panoramic pho-tographs.

• These images capture and create a complete scene in a single image from one position. The imagesare created by stitching together a large quantity of photographs that are taken in rotation, where theproduct is either a completely or partially computer-generated effect.

• This type of image stitiching requires nearly exact overlaps between images and identical exposures inorder to create final products with as few seams as possible. Many digital cameras today are able tostitch images together on the cameras themselves.

• Image stitching process has three major parts: image registration, calibration/alignment, and blending.

Figure 1: Composite images of Rochester, NY in stitching process

3.2 Image registrationImage registration is a process by which an algorithm minimizes the sum of absolute differences betweenoverlapping pixels. Both calibration/alignment and blending are types of image registration, and thefinal product is a composite image based on these two different processes.

3.3 Calibration/alignment• Algorithms are required to create an appropriate model that relates pixels of one image to pixels to the

next image that will be stiched into the final product. In order to estimate the correct alignment thatrelates multiple images, algorithms need to combine these pixel-to-pixel comparisons with referencesto the gradient descent in order to estimate these parameters.

• In order to minimize differences between these images, these algorithms attempt to calibrate thesetypes of optical defects:

– Image distortion/parallax– Exposure differences– Vignetting– Camera response and chromatic aberrations

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• When there are recurring objects across multiple images (e.g. the same car from different views inthe desired panorama), these algorithms attempt to compute a globally consistent set of alignments inorder to show how these images actually overlap. This is called keypoint/feature detection.

• It is also possible to think of image calibration or alignment as geometrical registration.

3.4 Blending• Image blending takes the adjustments from the calibration stage and remaps the images to create an

output projection. In this process, a couple of optical adjustments take place:

– Color adjusted between images (mitigate exposure differences)– High dynamic range images merged (compensate for motion in images, used to de-ghost images)– Seam line adjustment in order to reduce the visibility of the image seams (minimize intensity

difference of overlapping pixels)

• It is also possible to think of blending as photometric registration.

3.5 Projective layoutsDespite the fact that all image segments in image stitching are taken from the same point in space, the finalcomposite product can be arranged in a variety of projective layouts. A few examples:

• Cylindrical projection: most commonly used for printed panoramas with large range of longitude

• Spherical projection: stitched image shows 360 degree horizontal by 180 vertical field of view–theimage is wrapped into a sphere and viewed from within.

• Stereographic projection: conformal form of fish-eye projection where the distance from the centeris not equivalent to the spatial angle. Much easier on the eye for printing and display purposes.

• Fish-eye projection: conformal form of projection where the distance from the center is equivalentto the spatial angle

3.6 Limitations of image stitching• A major problem for panoramic stitching (especially 360 degree views) is parallax, lens distortion,

scene motion, and exposure differences. Some of these details can be overcome with additionalimages that have a reasonable amount of overlap, which will give us more detectable features withinthe image.

• The ideal set of images will have consistent exposure between the frames so that the composite imageis as seamless as possible. Misalignment of these frames (along with motion in the scene) will create“ghosting,” where some parts of the image are not fully rendered.

3.7 Applications of image stitchingPanoramic image stitching is also widely used in all sorts of different applications. “Video stabilization”in cameras, for example, uses frame-rate image alignment in order to eliminate wobble in the video image.

• High resolution photo mosaics/panorama creation

• Object insertion (add another image into the final product)

• Object removal (estimate background behind object)

• Video summarization, compression, and matting

• HDR composite images

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4 Three-Dimensional Printing

4.1 Introduction3D printing covers a wide variety of technologies that allow us to rapidly create prototypes in a cheaper,more accessible way. All production is created layer by layer (compared to traditional methods of moldingand casting).

• Processes originally created to be a faster, more cost-effective method for creating prototypes forproduct development.

• Goods will be much more customized, and though per-unit production cost might be higher, it will beoffset by the elimination of shipping and buffer inventories.

4.2 Printing materials• ABS plastic (petroleum based): requires a lot of ventilation/fume hood, reactive to acetone (great for

final products, doesn’t require too much sanding because you can use acetone to make edges cleaner)

• PLA plastic (corn/soy based): biodegradable in about 150 years, pretty safe material with little off-gassing. No ventilation system necessary.

– Pros: Cheaper and more flexible than ABS, great for prototyping, color with acrylic paint– Cons: Not reactive to acetone, must use file

4.3 Printing machines available in Lathrop• MakerBot Replicator 2 and MakerBot Replicator (new version): library will move away from MakerBot

in next couple of years in favor of better/more stable printers at the same price point

– Not inexpensive piece of equipment ($3000 per machine)– Plate removable for cleaning, use painter’s tape as a smooth surface for printing– Glass build plate is good for conducting heat, but not good for adhering on plastic (hence the

painter’s tape)– Available for check out: build plate and spatula to remove printed items

• Printing head/extruder of 3D printer: aluminum block that heats up to 200 C: everything in theMakerBot itself and the software is listed using the metric system

– Increments in the program always ask for millimeters, not centimeters.

• Heat sync and fan: if the extruder gets stuck, then we need to take it apart, but putting it backtogether is a very difficult experience. Don’t be afraid to ask for help!

• Printer head moves laterally for x, y, z axis system. Not a lot to control manually.

• Can only print two colors, and only by stopping the printing process and changing the filament. Mustbabysit the printer – there is no automation option!

4.4 Printing guidelines• First come, first serve resource: week 9 and 10 have a long printing queue. Get this done early!

• Assistive manual calibration: tighten screw (push the build plate up), loosen screw (bring the buildplate down).

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• Do not preheat the extruder until you have calibrated the build plate! Otherwise, it is possible thatyou will melt the plate or set the tape on fire. If you get burned or flames start, go to the tech desk(they have first aid kit and panic button).

• Exposed edges with corners exposed will cool at a faster rate and cause some distoration. To fix this,you can (1) slow down the speed of the printer, or (2) increase/decrease the temperature of the printing.

• Print a raft in order to make the object as accurate as possible: pause the pritner after the raft (canalso pause the printer and put painter’s tape on it). Know that it is often difficult to remove the raftif you don’t do it soon after the printing is done!

• With delicate parts, make sure to program the printer to go in a single spiral rather than in clockwise-counterclockwise motions.

Make sure you always have the scaling box checked so that the dimensions are standard(otherwise, it can change the fidelity of the object).

4.5 Creating models• Create models using MakerBot software, SketchUp, etc. Make sure to export to either OBJ or STL

software (or MakerBot’s proprietary file format, .thing)

• Scaling items: if you scale down the thickness of the walls and boundaries, infill matters.

– Size up or down the honeycomb structures according to your product’s needs.– Layer height can range from 0.10 mm to 0.40 mm (default is 0.20 mm).– Thicker layers are faster to print.

• Anything within 45 degrees from the vertical axis does not need support. However, a statue with armsoutstretched (for example) would require support: split things apart and then glue them together afterthe fact.

– You also have the option to have rafts and supports for the models (raft = flat surface, support= columns).

– Raft is always automatically checked.

• Try to make as many touch points on the platform as possible in order to minimize breakage.

• Advanced options: infill (10% solidity = 90% hollow). Things that are subjected to high tension requirehigher infill, which increases weight and material.

– This will adjust the printing speed!

4.6 Final precautions• PLA is not food safe! Lathrop library is not a food safe environment! Use models as a demonstration

only.

– Detritus is lying around. There is also a danger in the bits and crevices of the product itself – itis an ideal breeding ground for bacteria and fungus.

– Do not use for food-related items!

• If you need help, look for tutorials on lynda.com (there is a Stanford site license).

• Available create:space office hours for 3D printing-related help:

– Tuesdays 4:45 pm - 6:00 pm– Fridays 2:00 pm - 5:00 pm

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5 GIS and GPS

5.1 ProjectionsIs the world round? For the purposes of mapping, it’s difficult to turn a sphere (3 dimensions) into a plane(2 dimensions), which means that we will have to rely on projections–formulas to transform the 3D earthmodel into 2D–in order to conduct our analysis.

Datum System that allows us to determine any location on the globe in reference to it. It is a mathemat-ical reference network for geodetic coordinates defined by the latitude/longitude of an initiualpoint, the direction of a line from this point, and the parameters of the ellipsoid upon which theinitial point is located.

• Commonly used datums: North American Datum of 1927 (NAD27), NAD83, and World GeodeticSystem of 194 (WGS84).

• Modern definitions of sea levels are actually defined precisely by WGS84 and onward; datums are usedin navigation and surveying in order to translate positions indicated on maps (paper/digital) to theirreal positions on Earth.

• Difference in datums is referred to as datum shift.

5.2 Projection distortionsEach map projection has its own strengths and weaknesses, and recognizing the limitations of each projectionis key to choosing the appropriate projection for each project. While there are four spatial properties thatcan distort a projection (listed below), the only place on a map where there will be no distortion will be theline that marks the intersection of our paper with the surface of the earth. Any place that does not lie onthis line (i.e. most of the map) will suffer some distortion, but depending on the type of projection used, wecan preserve at least one of these four characteristics.

1. Shape: If a map preserves its shape, it is said to be conformal.

2. Area: If a map preserves its area, then it is said to be equal-area.

3. Distance: If a map preserves true scale for all straight lines passing through a single specified point,then it is said to be equidistant.

4. Direction: If a map preserves direction for all straight lines passing through a single specified point,then it is said to be azimuthal.

5.2.1 Tissot’s indicatrix

Tissot’s indicatrix illustrates where local distortions occur due to different map projections. The indicatrix isthe figure that results when a circle on the earth’s surface is plotted to the corresponding point on the map,where the shape, size, and orientation of an indicatrix at any given point depends on the map projectionused. In all conformal projections, the indicatrix is a circle and visually conveys a general impression ofdistortion. Mathematically, however, these indicatrices quantify the scale and angle of the distortion.

Figure 2: Space view of Tissot’s indicatrix

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Figure 3: Tissot’s indicatrix on the Mercator projection

Figure 4: Tissot’s indicatrix on the Robinson projection

Figure 5: Tissot’s indicatrix on the Winkel tripel projection

Figure 6: Tissot’s indicatrix on the equirectangular projection

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5.3 Projected vs. geographic coordinate systemsAll spatial files has to have its projection (coordinate reference system, or CRS) defined somewhere.

• A geographic coordinate system (GCS) uses a three dimensional spherical surface in 2D to definelocations on earth. In this system, a point is referenced in degrees by its longitude and latitude valuesthat are angles measured from the earth’s center to a point on the earth’s surface (e.g. WGS84,NAD83).

• A projected coordinate system is defined on a flat, two-dimensional surface, and the locations areidentified by x/y coordinates (e.g. UTM, State Plane, US National Atlas Equal Area, Mercator).

5.4 Shape filesA shapefile are (practically speaking) multiple files with different extensions, and they all must have thesame filename.

5.4.1 Mandatory files

• .shp – shape format, the feature geometry itself

• .shx – shape index format (the positional index of the feature geometry that allows the user to seekforwards/backwards quickly)

• .dbf – attribute format, columnar attributes for each shape

5.4.2 Optional files

• .prj – projection format (coordinate system and projection information)

• .sbn / .sbx – spatial index of the features

• .fbn / .fbx – spatial index of the features for shapefiles that are read-only

• .ain / .aih – attribute index of active fields in a table

• .ixs – geocoding inde for read-write shapefiles

• .mxs – geocoding index for read-write shapefiles

• .atx – attribute index for the .dbf file

• .shp.xml – geospatial metadata in XML format

• .cpg – used to specify the code page (only for .dbf) for identifying the character encoding

5.5 Reprojection, project-on-the-fly, and defined projections• Reprojection: A permanent transformation of the map into new geographic coordinates. In this

instance, GIS creates a completely new file, where all the coordinates are transformed into a differentreference system. (Note: only files with projection information can be reprojected!)

• Project-on-the-fly: Layers of different projection are matched up geographically automatically. GIStakes the projection defined as default for the project (taken from the first layer that was loadedinto GIS) and transforms the layer that’s loaded next into the same projection. These layers visuallyoverlap.

• Defined projection: GIS creates projection information without touching the original map. Caution:this may overwrite the existing .prj file!

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6 Raster GIS and Remote Sensing

6.1 Raster GISRaster GIS makes use of grid structures for representing the properties of locations.

Raster An arrangement of regularly shaped, contiguous cells that fit together edge-to-edge to form a con-tinuous layer. These cells are the fundamental element of information in raster GIS (representinglocation), are typically square, and have their location recorded as x and y coordinates.

• Cells have their condition recorded as numeric value for each cell, and have the same values constitutinga single “zone.”

• They can be arranged in layers (rasters/grids), and a data set can be composed of many layers coveringthe same geographical areas.

• They can be formatted as ESRI grids and TIFF (GeoTIFF).

• Each raster data set has the following properties:

– Data source: name of data set, type, location– Number of columns/rows of pixels, number of bands, cell size, uncompressed size, format– Source type, pixel type (unsigned/signed, integer/floating point), pixel depth/bit depth– Colormap (present/absent), pyramids (present/absent), compression type– Extent, spatial reference, and summary statistics

Pyramids Downsampled version of the original raster dataset used to improve performance. These pyra-mids are created as a result of raster map algebra, which is a set-based algebra for manipulatinggeographic data that allows for two or more raster layers of similar dimensions to produce a newraster layer using algebraic operations such as addition and subtraction.

• There are four classes of GIS transformations that depend on the spatial neighborhood of the map.

– Local operations: algebraic transformation of individual raster cells (pixels)– Focal operations: algebraic transformation of individual cells and their neighbors– Global operations: algebraic transformation of entire raster layer– Zonal operations: algebraic transformation of cells that share the same value

6.2 Remote sensingRemote sensing, at its most basic sense, is the collection of data about an object from a distance. Thesesensors are often mounted a great distance away from the target object (e.g. by using a helicopter orsatellite), and they record information by measuring electromagnetic energy from reflecting and radiatingsurfaces.

6.2.1 Types of remote sensing

There are two main categories of remote sensing:

• Active sensors provide their own energy source for illumination (e.g. raditation towards the targetarea). The radiation that is reflected from the target is then detected and measured by the sensor.

– Advantages: creates ability to obtain measurements anytime (weather/sunlight independent),and allows for sensors to be used to examine wavelengths that are not provided by the sun (e.g.microwaves).

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Figure 7: Conceptual understandings of raster/map algebra

– Disadvantages: requires heavy energy generation to adequately illuminate targets, complicatedanalysis/cost-intensive.

– Examples: laser fluorosensor and synthetic aperture radar (SAR)

• Passive sensors rely on reflecting energy that already exists (e.g. sunlight or thermal radiation). Thepower measured by passive sensors is a function of surface composition, physical temperature, surfaceroughness, and other physical characteristics.

There are six main types of sensors:

• Digital frame camera area array

– Pros: well-defined geometry with long integration time– Cons: many detectors required

• Linear array (pushbroom): similar to whiskbroom sensors, but pushbrooms may have thousands ofdetectors per spectral band. Has one row of detectors with one array per band, which moves forwardwith the plane/satellite.

– Pros: uniform detector response in along-track direction with no mechanical scanner, somewhatlong integration time

– Cons: many detectors required per line, complex optics

• Whiskbroom (scanning mirror and single discrete detector with filters): rotating mirrorchanges the angle of the incident light (which determines which part of the ground is being detected),and there is 1 detector per spectral band.

– Pixel width is function of mirror rotation rate and IFOV. Pixel length if function of IFOV, sensorspeed, and sampling rate.

– Pros: uniformity of detector response over the scene with simple optics– Cons: short dwell time per pixel, high bandwidth and time response for the detector

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• Whiskbroom (scanning mirror and discrete detectors with dispersing element): uses lineararray of detectors for each spectral band, and the mirror angles the light across multiple detectorsinstead of just one.

– Pros: uniform detector response over the scene, simple optics, with more/narrower bands possible– Cons: many detectors per line required, complex optics, high response time for the detector itself

• Hyperspectral area array: combines pushbroom linear array with a dispersing element.

– Pros: uniform detector response in along-track direction, no mechnical scanner, somewhat longintegration time, more/narrower bands possible

– Cons: many detectors per line required, complex optics

6.2.2 Collecting data

Data can be collected from ground-based, airplane-based, and satellite-based sensors.

• Sun-synchronous polar orbits: most earth-imaging satellites are polar-orbiting, and are restrictedto imaging a particular place on the ground at certain times. They circle in a north-south ellipse whilethe earth revolves beneath them. While there is global coverage, these satellites have fixed crossingsand can be used for repeat sampling.

– Typical altitude: 500 - 1500 km. Examples: Terra/Aqua, LandSat

• Non sun-synchronous orbits: similar to previous satellite, but focuses primarily on tropics, mid-latitudes, and high-latitude coverage with varying sampling.

– Typical altitude: 200 - 2000 km. Examples: TRMM, ICESat

• Geostationary orbits: mostly regional coverage with continuous sampling over low-to-middle lati-tudes.

– Typical altitude: 35000 km. Example: GOES

6.2.3 Types of resolution

• Spatial resolution: primarily concerns pixel size in the instantaneous field-of-view (IFOV)

• Spectral resolution: describes the ability of a sensor to define fine wavelength intervals (the betterthe resolution, the narrower the wavelength range for a particular channel)

• Temporal resolution: describes the length of time for a satellite to complete an orbit cycle (e.g.LandSat = 16 days, MODIS = 1 day, NEXRAD = 6 minutes).

• Radiometric resolution: describes the sensor’s senstitivity to the magnitude of electromagneticenergy (reflected or emitted). The finer the sensor, the more sensitive it is to detecting small differencesin energy.

6.3 Remote sensing applications• Mapping land use and cover for agriculture, soils mapping, forestry, city planning, archaeological

investigations, and military observation.

– Normalized Difference Vegetative Index (NDVI) measures the value of photosynthetically activeradiation from a pixel compared to the value of near-infrared radiation from a pixel. This formulausually yields a value that ranges from -1 (water or snow) to +1 (strong vegetative growth).

• Specialized photography has often been used in remote sensing to detect disease and insect damage inforest trees. The simplest forms of remote sensing have used photographic cameras in order to takeoblique aerial photographs of landscapes.

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7 Photogrammetry

7.1 Why 3D modeling?Three-dimensional models are interesting tools for documentation and interactive visualization purposes, asthey can also create virtual reality environments in order to re-explore an excavation site. In the case of thePumapunku, 3D models can be used in order to recreate destroyed objects (which can also be true of manyarchaeological artifacts today). Some interesting test cases:

• 3D models can be used to fill a virtual environment with real objects in order to approximate the “real”environment (e.g. interior of a historical building)

• Old images can be stitched together for a physical reconstruction of a deconstructed statue

7.2 MethodsUnlike other types of 3D modeling that relies on taking a point cloud in order to render a final image,photogrammetry obtains reliable measurements to create the 3D model through a series of photographs.The close-range photogrammetric pipeline involves the following steps:

1. Image retrieval/registration: the more photos you take at different angles with overlap, the better!

2. Camera calibration and orientation: consistent exposure and minimal movement

3. Image point measurements

4. Three-dimensional point cloud generation

5. Surface generation (mesh): relies on dense point cloud generated from original photos

6. Texturing

While this method requires approximating the unknown parameters in the corresponding points betweenimages, automated photogrammetric matching algorithms can produce very dense point clouds. In thissense, there are a few benefits to photogrammetry (compared to 3D scanning):

• Provides for accurate sensor calibration and object modeling using both analog and digital imagery.

• Very portable and affordable since it mostly uses existing equipment (e.g. digital cameras); multiplecommercial softwares available for image processing and 3D modeling.

• Good for close-range modeling that may be useful without the use of traditional topographic surveyor scanning instruments.

7.3 Additional reading• Remondino, Fabio, Alberto Guarnieri, and Antonio Vettore. “3D Modeling of Close-Range Objects:

Photogrammetry or Laser Scanning?” Institute of Geodesy and Photogrammetry, ETH (Zurich,Switzerland), and the University of Padua (Italy). https://www.academia.edu/6513242/3D_Modeling_of_close-range_objects_photogrammetry_or_laser_scanning

• Spielman, Jesse. “Open Source Photogrammetry: Ditching 123D Catch.” July 2013. http://wedidstuff.heavyimage.com/index.php/2013/07/12/open-source-photogrammetry-workflow/

• Davidhazy, Andrew. “Basic Photogrammetry Techniques.” Imaging and Photographic Technology,School of Photographic Arts and Scientists, Rochester Institute of Technology. https://people.rit.edu/andpph/text-basic-photogrammetry-methods.htm

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8 Three-dimensional scanning

8.1 Basics of 3D modelingPhotogrammetry and 3D scanning are two different things: 3D scanners only produce a point cloud fromthe object scanned.

• The color of the points in the dense point cloud from photogrammetry are automatically assigned! Youcan usually create a solid service from the dense point cloud and mesh, which is usually followed bytexture.

• A colored dense point cloud is intrinsically different from a textured mesh. There are very sophisti-cated measures that are interpolating the different colors within the textured mesh–this computationalcomplexity is what makes the point cloud different from the mesh.

• Dimensionality and detail: the point cloud is not a bitmap, it is composed of points in space (not agrid). The ways that scanners manage to produce fairly good looking models are based on the resolutionand the diameter of the points themselves in order to make the model look as solid as possible.

– However, if you were to try and print this 3D model, it actually isn’t solid–you have to processthe object so that it actually is solid–you have to manually fill in the blanks!

• How much is really gained from using $100K laser scanner vs. photogrammetry with a digital cameraand free processing software? How does the accuracy and batch processing methods differ betweenphotogrammetry and 3D scanning?

• Main purpose of a 3D scanner: create point cloud based on geometric samples on the surface of anobject, which will be used to extrapolate the object’s shape. The point cloud usually includes colorsof the object, but a single scan will rarely produce a complete model.

• Multiple scans are usually required to create a complete model, and these scans are processed through acommon reference system (e.g. alignment)–this is very similar to the image stitching process describedabove.

8.2 Types of 3D scanners2

8.2.1 Short range scanners (focal distance of <1 meter)

Laser triangulation scanners use a laser line or a single laser point to scan an object. A sensor thenmeasures the reflected light. Using trigonometric triangulation, the system then calculates the distance andangle between the object and the scanner.

• Pros: scanners are usually available in multiple forms (portable/enterprise), is less sensitive to ambientlight, and requires less preparation/set-up.

• Cons: generally less accurate and has lower resolution; often noisy.

Structured light scanners also use trigonometric triangulation, but instead of a single line or point, thesescanners use a series of linear patterns on the object. The sensor then examines the edges of each line onthe object’s surface.

• Pros: more accurate, higher resolution, low noise level.

• Cons: area scanners only, not as portable, more sensitive to surface (requires high level of preparationand specific lighting).

2Geomagic, “3D Scanners: A Guide to 3D Scanner Technology.” Retrieved 26 February 2015. http://www.rapidform.com/3d-scanners/

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8.2.2 Mid to long range scanners (focal range of >2 meters)

Laser pulse based scanners measures how long a beam of light takes to reach an object. Since the scannercan rotate both the laser and the sensor with a mirror, the scanner can scan up to a full 360 degrees arounditself (unlike the laser triangulation and structured light scanners). These systems usually send out millionsof pulses of light to return to the sensors and calculates the distance because the speed of light is a knownquantity.

• Pros: can often scan at focal distances from 2 m to 1000 m, allows for full rotation.

• Cons: slow data acquisition, often less accurate, and are often noisy.

Laser phase shift scanners are conceptually very similar to laser pulse based scanners, and compare thephase of the laser being sent out with its reflection.

• Pros: faster and more accurate data acquisition, often less noisy.

• Cons: can only scan at mid-range.

Figure 8: How do these scanners work? (Ibid)

(a) Laser triangulation scanners (b) Structured light scanners

(c) Laser pulse based scanners (d) Laser phase shift scanners

8.3 Additional reading1. Marc Levoy, Kari Pulli, Brian Curless, Szymon Rusinkiewicz, David Koller, Lucas Pereira, Matt Ginz-

ton, Sean Anderson, James Davis, Jeremy Ginsberg, Jonathan Shade, and Duane Fulk. 2000. “Thedigital Michelangelo project: 3D scanning of large statues.” SIGGRAPH 2000. ACM Press/Addison-Wesley Publishing Co., New York, NY, USA, 131-144. http://dx.doi.org/10.1145/344779.344849

2. Yastikli, Naci. “Documentation of Cultural Heritage Using Digital Photogrammetry and Laser Scan-ning.” Journal of Cultural Heritage 8.4 (September-December 2007): pp. 423-427.

3. Boehler, Wolfgang, and Andreas Marbs. “3D Scanning Instruments.” Institute for Spatial Informationand Surveying Technology, University of Applied Sciences. Mainz, Germany. http://i3mainz.de/sites/default/files/public/data/p05_Boehler.pdf

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Research Notebook for Digital Methods in ArchaeologyPart II – Workflows and Tutorials

Crystal Lee

Winter Quarter 2015

This workbook is intended to create an introductory FOSS (free and open source software)workflow for researchers working on projects that require 3D modeling and geospatial analysis.All exercises are written with users of almost any mainstream operating system in mind withthe hopes that these methods can be used with the highest amount of analytical return with thelowest up-front cost possible.

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Contents1 Image Processing 3

1.1 Scaling images with ImageJ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.1.1 Exercise: Setting image scale and measuring surface area with ImageJ . . . . . . . . . 3

1.2 Add-on for ImageJ: Fiji (Fiji Is Just ImageJ) . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3 Online tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.4 Recommended reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 Image Digitization 52.1 Online tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 Recommended reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3 Photogrammetry 73.1 Online tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.1.1 Python Photogrammetry Toolbox (PPT) . . . . . . . . . . . . . . . . . . . . . . . . . 73.1.2 VisualSFM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.1.3 Clustering Views for Multi-view Stereo (CMVS) . . . . . . . . . . . . . . . . . . . . . 7

3.2 Recommended reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

4 Introductory GIS and Mapping 84.1 Online tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4.1.1 ArcGIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.1.2 QGIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.1.3 D3.js . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4.2 Recommended reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

5 Geographic Data and 3D Printing 95.1 Online tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

5.1.1 3DEM, AccuTrans, and Blender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.2 Recommended reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

6 Software Packages 10

List of Figures1 Scaled object using Ancondieta data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Image digitization workflow for medieval maps (Lilley, Mapping Medieval Chester) . . . . . . 6

List of Tables1 Software Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

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1 Image Processing

1.1 Scaling images with ImageJ

ImageJ is a public domain Java image-processing program that can display, edit, analyze, process, save,and print bitmap images. Originally developed at the National Institute for Health, the program has beenprimarily used as a laboratory tool to perform medical imaging and microscopy analysis, but it has foundapplications in a number of fields, like the material sciences and archaeology. For archaeological and historicalscholarship, ImageJ can be used in order to measure the surface area of artifacts, count the number of cellson a given item, and recalibrate images. The analytical power of this program is almost limitless: it cancreate density histograms and line profile plots, and it can perform standard image processing functions suchas geometric transformations (scaling, rotations, flips), contrast manipulation, Fourier analysis, smoothing,sharpening, median filtering, and edge detection. The program is limited only by your computer’s availablememory, as it can support batch processing of any number of images at the same time.

1.1.1 Exercise: Setting image scale and measuring surface area with ImageJ

1. Start ImageJ and import the image you would like to analyze.

2. In order to let the software figure out the appropriate scale between image pixels and meters, zoom inuntil the scale bar begins to pixelate.

3. Choose the Line tool and draw a line overlapping the scale bar as precisely as you can.

4. Choose Analyze, and select Set Scale. The length in pixels of the line we’ve just drawn on the imagewill now appear, and set the Known Distance to 40 meters. Note: if you check the box for “Global,”it applies the scale to all images open in ImageJ (you can batch process images in the utility).

5. Use either the Polygon or Freehand tool to outline the bulldozed areas. Note: Since the bulldozedarea is delineated with a dotted line, it’s impossible for us to use the Wand to automatically outlinethe area of interest. (But you should definitely feel free to use the Wand tool in other examples tospeed up the process!)

6. Choose Analyze, and select Measure. A dialog box will appear showing the area of the (freehand)polygon you have just drawn. Continue until you have also drawn the polygon for the second bulldozedarea (additional calculations will fill the Results box until you manually clear them).

Figure 1: Scaled object using Ancondieta data

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1.2 Add-on for ImageJ: Fiji (Fiji Is Just ImageJ)

While ImageJ itself is a wonderful image processing program, it can be supplemented by Fiji, a self-described“batteries-included distribution of ImageJ,” which bundles Java, Java3D, and plugins organized in a menustructure.1

Useful plug-ins for analysis:

• Background subtraction/masking

• Image blending, image stitching

• Lasso selection

• Statistical region merging

• Stochastic de-noise

1.3 Online tutorials

1. National Institute of Health. “Tutorials and Examples.” ImageJ Documentation. http://imagej.nih.gov/ij/docs/examples/

2. FIJI. “Tutorials and Examples.” FIJI Documentation. http://fiji.sc/Category:Tutorials

3. Cordona, Albert. “ImageJ Programming Tutorials.” April 12, 2008. http://albert.rierol.net/imagej_programming_tutorials.html

4. ImageJ Information and Documentation Portal. “ImageJ Beginner Tutorial.” http://imagejdocu.tudor.lu/doku.php?id=video:beginner_help:imagej_beginner_s_tutorial

5. Fiji Tutorial for Beginners. http://imagejdocu.tudor.lu/doku.php?id=video:beginner_help:imagej_beginner_s_tutorial

1.4 Recommended reading

1. Herbert, Alex. “ImageJ Batch Processing.” MRC Genome Damage and Stability Center, School of LifeSciences, University of Sussex. http://www.sussex.ac.uk/gdsc/intranet/pdfs/ImageJBatchProcessing.pdf

2. Reinking, Larry. “ImageJ Basics.” Department of Biology, Millersville University. Biology 211 Labo-ratory Manual (June 2007). http://rsb.info.nih.gov/ij/docs/pdfs/ImageJ.pdf

3. Montufo, Antonio M. “The Use of Satellite Imagery and Digital Image Processing in Landscape Ar-chaeology: A Case Study from the Island of Mallorca, Spain.” Geoarchaeology: An International Jour-nal 12.1 (1997): 71-85. http://ggnindia.dronacharya.info/ITDept/Downloads/QuestionBank%5COdd%5CV%20sem/Use_Satellite_Imagery_Digital_Image_Processing_landscape_Archaeology.pdf

4. Clogg, Phil, Margarita Diaz-Andreu, Brian Larkman. “Digital Image Processing and the Recordingof Rock Art.” Journal of Archaeological Science 27.9 (September 2000): pp. 837-843. http://www.sciencedirect.com/science/article/pii/S0305440399905228

5. Green, Jack, Emily Teeter, and John A. Larson. Picturing the Past: Imaging and Imagining theAncient Middle East. Chicago, IL: Oriental Institute Museum Publications 34. The Oriental Instituteof the University of Chicago. September 2012. https://www.academia.edu/1193100/Picturing_the_Past_Imaging_and_Imagining_the_Ancient_Middle_East

1LOCI and the Tomancak Laboratory, “Fiji is Just ImageJ.” http://fiji.sc/Fiji

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2 Image DigitizationGeneral image digitization workflow2:

If no digital image exists...

1. Scan image (digital scanner with manual feed)

2. Correct image and input metadata (Adobe Lightroom/Photoshop)

3. Save (export archival TIF and JPG derivative to internal server)

4. Update database (e.g. create Omeka record and upload JPG derivative file)

If an uncorrected digital image exists...

1. Correct image and input metadata (Adobe Lightroom/Photoshop)

2. Save (export archival TIF and JPG derivative to internal server)

3. Delete (remove unedited image off of hard drive)


1. Gandhi, Ujaval. “Digitizing Map Data.” QGIS Tutorials and Tips. http://www.qgistutorials.com/en/docs/digitizing_basics.html

This is by far the best online tutorial I’ve done that shows you how to easily digitize mapdata. Not only is it extremely comprehensive, but it beyond showing you how to do discretetasks, it really shows you some of the broader principles of map digitization within the QGISenvironment. This is a must for anyone that wants to learn how to digitize maps!

2. Brown University. “Georeferencing and Digitizing Images/Maps.” Spatial Structures in the Social Sci-ences. Image/Map Georeferencing and Digitizing. http://www.s4.brown.edu/S4/Training/Modul2/Georeferencing%20and%20Digitizing%20%20in%20ArcGIS.pdf

3. Old Maps Online. “Scanning and Digitization: Parameters and Formats.” 2009. http://help.oldmapsonline.org/scan

4. GRASS. “Digitizing Vector Maps.” GRASS Tutorials.


1. Rybakov, Anna. “Image Digitization: Workflow and Documentation.” American Museum of Natu-ral History, November 2013. http://images.library.amnh.org/san/amnhdigitizationprocedure.pdf

2. Clarke, Catherine. “Digital Mappings.” Mapping Medieval Chester. http://www.medievalchester.ac.uk/mappings/mapintro.html

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1. Rybakov, Anna. “Image Digitization: Workflow and Documentation.” American Museum of Natural History, November2013. http://images.library.amnh.org/san/amnhdigitizationprocedure.pdf

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Figure 2: Image digitization workflow for medieval maps (Lilley, Mapping Medieval Chester)

(a) Scanned map of Medieval Chester(British Library)

(b) Extract of Map from Chester (Chester Record Of-fice)

(c) Screenshot of Chester project in GIS with historic map layers (d) Screenshot of Chester project in GIS with digitized features

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3 PhotogrammetryThree-dimensional models are interesting tools for documentation and interactive visualization purposes, asthey can also create virtual reality environments in order to re-explore an excavation site. In the case ofthe Pumapunku, 3D models can be used in order to recreate destroyed objects (which can also be true ofmany archaeological artifacts today). Unlike other types of 3D modeling that relies on taking a point cloudin order to render a final image, photogrammetry obtains reliable measurements to create the 3D modelthrough a series of photographs.


3.1.1 Python Photogrammetry Toolbox (PPT)

1. Download instructions for Linux, Mac, and Windows. This includes the Python libraries andthe PPT GUI. http://184.106.205.13/arcteam/ppt.php

2. No author. “How to Make 3D Scans with Pictures and the PPT GUI.” ATOR (Arc-Team OpenResearch). 28 December 2012. Accessed 26 January 2015. http://arc-team-open-research.blogspot.com.br/2012/12/how-to-make-3d-scan-with-pictures-and.html

3. Moulon, Pierre, and Alessandro Bezzi. “Python Photogrammetry Toolbox: A Free Solution for Three-Dimensional Documentation.” IMAGINE. Ecole des Ponts Paris Tech and Centre Scientifique et Tech-nique du Batiment. No date. Accessed 26 January 2015. http://imagine.enpc.fr/publications/papers/ARCHEOFOSS.pdf

3.1.2 VisualSFM

1. Download instructions for Linux, Mac, and Windows. http://ccwu.me/vsfm/

2. Wu, Changchang. “VisualSFM: A Visual Structure from Motion System.” Documentation with detailson basic usage, advanced usage, GUI workflows, command line workflows within Visual SFM, andFAQ. http://ccwu.me/vsfm/doc.html

3. Duffy, Brenden. “Image Post Processing, Tutorial 1 with Visual SFM and CMVS.” http://flightriot.com/visualsfm-cmvs-post-processing-tutorial/

Note: This tutorial shows you how to ortho-rectify UAV aerial imagery to generate 3Dpoint clouds using software that is freely available for non-commercial use.

3.1.3 Clustering Views for Multi-view Stereo (CMVS)

1. Furukawa, Yasutaka. “CMVS Introduction.” http://www.di.ens.fr/cmvs/

Note: This software takes the output from structure-from-motion (SFM) software anddecomposes the images into a set of image clusters that are of a manageable size. Then,the MVS software processes each cluster independently and reconstructs it so that the wholeimage can be derived from its parts.

2. Seitz, Steven M., Brian Curless, James Diebel, Daniel Scharstein, and Richard Szeliski. “A Comparisonand Evaluation of Multi-View Stereo Reconstruction Algorithms.” http://vision.middlebury.edu/mview/seitz_mview_cvpr06.pdf


1. Mallison, Heinrich, and Oliver Wings. “Photogrammetry in Paleontology: A Practical Guide.” Journalof Paleontological Techniques 12 (July 2014).

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2. Spielman, Jesse. “Open Source Photogrammetry: Ditching 123D Catch.” We Did Stuff – PersonalBlog. 12 July 2013. Accessed 26 January 2015. http://wedidstuff.heavyimage.com/index.php/2013/07/12/open-source-photogrammetry-workflow/

3. Versperman, Brian. “123D Catch is Not Useless.” 3D Printing Camp. 7 July 2012. Accessed 26January 2015. http://www.3dprintingcampwi.com/2012/07/07/123d-catch-is-not-useless/

4. Hernandez, Carlos, George Vogiatzis, and Yasutaka Furukawa. “3D Shape Reconstruction from Pho-tographs: A Multi-View Stereo Approach.” http://carlos-hernandez.org/cvpr2010/

5. Fernandez, William. “Three Dimensional Modeling with Photogrammetric Information Point Clouds.”Department of Transportation Design Training Expo. http://www.dot.state.fl.us/officeofdesign/training/designexpo/2014/presentations/WilliamFernandez-3DSurfaceModeling.pdf

4 Introductory GIS and Mapping


4.1.1 ArcGIS

Harvard Map Collection. “GIS Tutorials and Exercises.” 1 June 2009. http://hcl.harvard.edu/libraries/maps/gis/tutorials.cfm

This is a collection of wonderful tutorials that uses ArcGIS with a package of exercises thatthe Harvard Map Collection has collected. It introduces the basic terminology in GIS, providesfamiliarity with the general operations and applications of GIS, and shows some examples of thetypes of analysis that can be performed.

4.1.2 QGIS

Sutton, T., O. Dassau, and M. Sutton. “A Gentle Introduction to GIS.” Department of Land Affairs, EasternCape, South Africa.

http://download.osgeo.org/qgis/doc/manual/qgis-1.0.0_a-gentle-gis-introduction_en.pdf

This is by far the most comprehensive and easy-to-use guide on QGIS I have found, andthe resource is absolutely invaluable in terms of understanding vector/raster data, data capture,topology, coordinate reference systems, and map production. Any GIS class that uses QGISshould be using this as a reference, as its explanations are easy to understand and supplementedwith many reference photos. I could not have done anything in QGIS without working throughthese pages!

4.1.3 D3.js

1. Gutierrez, Sebastian. “Dashing D3.JS.” https://www.dashingd3js.com/table-of-contents

2. D3.JS Documentation and Tutorials. 3 February 2015. https://github.com/mbostock/d3/wiki

D3.JS is a JavaScript library for manipulating data using HTML, SVG, and CSS, andits emphasis on web standards gives you full capabilities web browser capabilities that allowusers to create powerful visualizations without a proprietary framework.


1. Hogenboom, Karen. “An Introduction to GIS.” University Library, University of Illinois at Urbana-Champaign. http://www.library.illinois.edu/sc/datagis/introtogis2013fall.pdf

2. US Geographical Survey. “What is GIS?” 22 February 2007. http://egsc.usgs.gov/isb//pubs/gis_poster/

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5 Geographic Data and 3D Printing


5.1.1 3DEM, AccuTrans, and Blender

1. Shapespeare. “Making 3D Prints from LIDAR Data.” https://www.youtube.com/watch?v=t4-ICkvyJv0

This is the original tutorial that got me interested in making 3D prints from LIDAR datain the first place, and the amount of detail that goes into showing users how to manipulatethe LIDAR data in different environments so that it can become a watertight model isreally incredible. The user, “Shapespeare,” also has some incredible prints of National Parkgeography, which are all available on Thingiverse.

2. Blender (official). “Documentation and Tutorials.” http://www.blender.org/support/tutorials/

These tutorials show users how to navigate through Blender, create some basic objectswith materials and different light sources, and understand texturing, mesh topology, andcolor randomization. The tutorials later graduate towards incredibly complex topics, likemaking models of photo-realistic human heads, eyeballs, and scenes. These are absolutelyindispensable for anyone interested in using Blender for 3D printing.

3. Hirsig, Neal. “Blender 3D Design Course.” Tufts University, 2013. http://gryllus.net/Blender/3D.html

This course–taught at the Tufts Multimedia Program–includes video tutorials and step-by-step PDFs that teach users how to manipulate objects and understand lighting, animation,articles, constraints, textures, and sculpting in Blender. To do There are a series of fourprojects (each in 2 parts) that are spectacular for hands-on learning.


1. “Tantillus: The Portable Open Source 3D Printer.” 2012. http://www.tantillus.org/Home.html

While this is not necessarily a feasible option for most people (i.e. printing one’s own 3Dprinter), the amount of documentation that is available on how the 3D printer is constructedis absolutely incredible, and it really allows readers to understand how 3D printers work.This is indispensable reading for anyone interested in 3D printing from the ground up: whilethere are flaws in its design, the fact that this person was able to create his own 3D printer(which can then print another 3D printer) is nothing short of incredible.

2. Schmidt, Ryan. “3D Printing Workshop.” Toronto ACM SIGGRAPH. http://toronto.siggraph.org/wp-content/uploads/2014/03/Autodesk_3DPrintingTutorial_Meshmixer_Toronto_ACM_SIGGRAPH_Chapter.pdf

This is an excellent (albeit basic) resource for general 3D printing guidelines. It has agood overview of how 3D printing works in practice, with some interesting insights as to howit might be used in the future. The Metropolitan Museum of Art also has a quick guide that,while simplistic, has a more beautiful graphic rendering of how 3D modeling works. (SeePitukcharoen, Decho. “3D Printing Booklet for Beginners.” Spring 2014.)

3. Allard, T. T., M. L. Sitchon, R. Sawatzky, and R. D. Hoppa. “Use of Hand-held Laser Scanningand 3D Printing for Creation of a Museum Exhibit.” Sixth International Symposium on VirtualReality, Archaeology and Cultural Heritage 2005. M. Mudge, N. Ryan, and R. Scopigno (eds). http://public-repository.epoch-net.org/publications/VAST2005/shortpapers/short3006.pdf

4. Scopigno, Roberto, Marco Callieri, Paolo Cignoni, Massimiliano Corsini, Matteo Dellepiane, FedericoPonchio, and Guido Ranzuglia. “3D MOdels for Cultural Heritage: Beyond Plain Visualization.” IEEEComputer Society, 2011. http://v-must.net/sites/default/files/CNR-ISTI_IEEE.pdf

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6 Software Packages

Table 1: Software Compatibility

The listed softwares are only listed as “cross-platform” if they are compatible with Mac OSX, Windows, andLinux. When it is available, I have also listed availability on mobile platforms. If the software is listed asfree, it is not just a free trial–it will be demarcated as free for educational use with no limitations.

Image Processing

Name Platform-independent? Mobile Cost

ImageJ Yes No Free

Fiji Yes No Free

GIMP Yes No Free

3D Modeling Software


123D Catch Yes Android only Free

123D Sculpt+ N/A Android, Apple Free

123D Design Yes iPad only Free

123D Make Yes iPhone, iPad Free

TinkerCAD Yes, web-based No Free

K3D Yes No Free

Google SketchUp Yes No Free*

Meshmixer Yes No Free

Blender Yes No Free

* With student license.

Photogrammetry


Python Photogrammetry Toolbox Yes No Free

Visual SFM Yes No Free

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GIS and Mapping


QGIS Yes Android only Free

Open Layers 3 Yes; JavaScript library No Free

Open EV Yes No Free

uDig Yes No Free

GeoMOOSE Yes, web-based No Free

Marble KDE Yes Android only Free

D3.js Yes No Free

OpenGTS Yes No Free

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