Creating Orthomosaic in ArcPro

Introduction

The creation of orthomosaic is one of the most common ways to process UAS imagery data. In this lab, we used close to 200 images to create an orthomosaic. But generally speaking, what is an orthomosaic? This will be addressed. Also, professor Hupy showed us how tiepoints work, and how some of them were rejected for accuracy issues.


What is photogrammetry?
Photogrammetry is the subject, the science and an indirect measurement tool for photographs and digital imagery. The end product is typically 3D-models of objects and orthoimage mosaics (ortho maps). The production of orthoimage mosaics and digital elevation data is created through the concept of photogrammetry.


What types of distortion does remotely sensed imagery have in its raw form?
What is orthorectification? What does it accomplish?
Ortho mapping tends to focus on aerial photogrammetry, which covers areas from a distance and is typically nadir viewing (straight down viewing). To illustrate this, these two figures will display Professor Hupy's house from different angles.

Figure 1: Nadir viewing.

Figure 2: View from 60 degrees angle. 

In our case, we used a series of nearly 200 images that have collected as the sensor (UAV) has flown along a flight path. Typically, most images wear a distortion and therefore needs to go through a process of geometrically correct every single one of the orthoimages. The resulting images have the geometric integrity of a map. So, orthorectification is a method for geometrically correct distortions and produce accurate orthoimages. There is another concept as well. The product of stitching a number of orthoimages together into one layer is called orthomosaic. For every image, the sensor's position (derived from GPS, namely X₀, Y₀, Z₀) and orientation (the angles of w, j, k) is key. This displays where the UAV was at the very specific time of the image were taken. Other important features in this process are the tie points between the images and a Digital Elevation Model, preferably a high-resolution one.

If not the known ground positions (GCPs, x, and y) are delivered to the end-user, along with the images, the images need to be adjusted. This adjustment georeferencing process is done accordingly with the information one finds in the metadata.

Figure 3: Before the Block Adjustment

Also, taking elevation data into account generates a more accurate output but is more time-consuming. If the elevation data is unknown, it can be derived through stereo imagery from the overlapping images. When the Block adjustment is calculated the area and overlapping images were looking like Figure 4 below is illustrating. It looks distorted but is actually more accurate than Figure 3.

Figure 4: After Block Adjustment

Normally speaking about distortions, one refers to geometric and radiometric distortions. These two is removed during the orthorectification process. But there can also be lens distortion parameters on needs to take care of. So when creating an orthoimage from raw imagery one needs to pay attention to sensor distortions (so-called interior orientation).

With LiDAR images it is easier to find the ground since with laser one can return a number of echoes. Basically one can create both a Digital Terrain Model (DTM) a Digital Surface Model (DSM) directly with LiDAR technique. Since the level of accuracy increases the need for adjustment is reduced.

What is Bundle Block Adjustment (BBA)?
Bundle block adjustment is a computational process for fitting images together while statistically minimizing errors with the ground control. In order to compute the exterior orientation for each image, the process is using both GCPs and tie point information. The orientation for a whole bunch (called a block) of images is then adjusted to fit the ground.


What is the advantage of using this method? Is it perfect?

The obvious advantage with BBA is that the quality fitting images together increases when adjusting the residual errors. One of the disadvantages is that bloopers often occur in the BBA process. When trying to fit blocks of images to the ground together, there is a high likelihood the fitting is not performed perfectly. The anomaly points with high residual errors are often deleted and thereafter the adjustments can be recomputed until acceptable errors for each point is reached.

What is the Ortho Mapping Suite in ArcPro? How does it relate to UAS imagery?
The ortho mapping focuses primarily on aerial photogrammetry products and feature extraction software. Esri's tools are in the realm of UAS used primarily to produce different orthorectified products.

Methods/Lab Assignment

In order to create an orthomosaic, one has to go to the Ortho Mapping tab and under the Product group of features and click Orthomosaic. From there one follows the wizard, decisions about overlap (should be no less than 60%), balance method (preferable dodging), target raster (the reference base map data), and as the last step one can choose format. The Cloud raster format is a faster choice than TIFF selection, but latter is a lossless one and preserves all the graphical features of the image. After that, it is possible to start the process of orthorectification. The image below displays the processing time, 7 minutes and 52 seconds. 

Figure 5: Time elapsed for the orthorectification process.

What key characteristics should go into folder and file naming conventions?
File names should convey the most important information and what data the files contain.
Examples would be dates, names of locations, what kind of om digital model is used and file extension is key for naming files. Also, keep the filename without spaces. For instance: "20170613_wolfpaving_dsm.tif"

Why is file management so key in working with UAS data?
Working with UAS data means a lot of file types and extensions used. Good file organization is heavily aligned with the effectiveness of the user and it also helps other individuals to know what they are looking for.

What key forms of metadata should be associated with every UAS mission?
Examples of UAS metadata that could be included in every mission; the date of data collection, pilot name, weather conditions, UAS platform, sensor type, altitude, Ground Control coordinates, and UAS coordinates.

The key metadata we are working with, presented in the table in Figure 6.

Figure 6: Table with metadata for this UAS mission.

Results

My maps show Professor Hupy's home and wherein the state of Indiana the area of studies was performed.

Figure 7: The Bundle block adjusted UAS imagery and its location

Figure 8: After the block adjustment, this is the final compilation of stitching orthoimages together.

The quality in the center of the map, right below where the UAS data is retrieved, is superior. This is pretty comprehensible since there are more tiepoints that overlap each other there.

Figure 9: Many tiepoints and a big amount over overlap generate great quality of the map.

Figure 10 displays the outer layers of the image projection (the footprints), where the quality is poor and one can even see some clear break between the adjustments and orthorectification has failed.

Figure 10: Areas on the map where the data quality is poor

But still much better than the image from the reference data, the World Imagery.

Figure 11: Dr. Hupy's house displayed as World Imagery.

The imagery results can be seen in Figure 12 and the calculated statistics in Figure 13.

Figure 12: A transparent view of the elevation model. Layer included to the left.

Figure 13: Generated Statistics for the DSM

The creation of a Digital Elevation Model took about 45 minutes in total, seen in Figure 14.

Figure 14: In ArcGIS Pro, Digital Elevation Model also took some time.

Conclusions

To summarize the Orthomosaic Tool, one has to start with generating an ortho mapping workspace. Then a Bundle Block Adjustment (BBA) have to be performed before the establishment of ortho mapping products.

Creating the orthomosaic was not hard at all and took about 8 minutes. What was time intensive was the step before when we made the Bundle Block Adjustment, which took more than 30 minutes. We processed this through an online server. However, it would have been a lot faster if we would have done the process directly from c:\ instead. Another drawback, for some reason it was not possible to work with the GCPs at this stage. The quality of the process gets neater the more tiepoints and the higher degree of overlaps the images have.

 Using BBA is fine when accuracy is not a concern. For instance, using BBA when processing images taken from low altitude, generates sensible accuracy and a fast result. This wouldn't be recommended if the demand for accuracy (like in mining) was high nor when working in areas with erratic terrain, mountains, and valleys. The data created with UAS is more accurate than using images from satellites. But LiDAR is even more accurate than UAS imagery, goes down to center- or even millimeter.

Building a Map with UAS Data

Introduction

Why are proper cartographic skills essential in working with UAS data?
In order to create a functional map, one needs cartographic skills. To create maps by using UAS data, images, these skills would be applied to ordinary images of a particular area. For the user to interpret the map properly, cartographic skills are key.

What are the fundamentals of turning either a drawing or an aerial image into a map?
Every map should have a North arrow, a scale bar and a mini locator map of where the area is situated. Also, a watermark of the map's creator and relevant metadata like what sensor took the images would be appropriate information.

What can spatial patterns of data tell the reader about UAS data? Provide several examples.
Information about elevation is perhaps the most obvious spatial characteristics the user could retrieve from UAS data. One can find ridges and variances of height by managing UAS data properly. Also, distances are to be considered as a spatial attribute, that is objects location in relation to each other. Using hyperspectral sensors that give information about spectral classes to objects is another example.

What are the objectives of the lab?
The main objectives of the lab were to get a basic understanding of map creation with UAS data. We used ArcMap to create maps but was also introduced to ArcScene, which is a software tool for creating a scene over an area of interest. We tried to fly over it from a birds perspective.

Methods/Lab Assignment

What key characteristics should go into folder and file naming conventions?
Dates, names of locations, what kind of om digital model is used and file extension is key for naming files. Also, keep the filename without spaces. For instance: "20170613_wolfpaving_dsm.tif"

Why is file management so key in working with UAS data?
Working with UAS data means a lot of files. Good file organization is heavily aligned with the effectiveness of the user.

What key forms of metadata should be associated with every UAS mission?
Examples of UAS metadata could be; flown date, pilots name, UAS platform, sensor type, altitude, Ground Control coordinates, and UAS coordinates.

Create a table that provides the key metadata for the data you are working with.

Figure 1: Metadata

What base map did you use? Why?
I choose to open a Topographic map cause my goal was to choose an easy-navigated map. I thought that maybe choosing a map, which displays streets in an easy manner could be good.

Build Pyramids and Calculate Statistics for each data set. What is the difference between a DSM and DEM? Digital Elevation Model (DEM) often used as a generic term for Digital Surface Model (DSM) and Digital Terrain Models (DTM). Elevation refers to height above a given level, particularly the sea level. A DTM is an object scraped digital model, where the surface refers to the earth, that is ground without buildings, trees, and other vegetation.

DTMs are LiDAR-derived and with LiDAR (3D laser scanning) it is also possible to create another type of DEM by filtering out objects on the surface. This is how the so-called Normalized Digital Surface Model (nDSM) is created. To put it in other words, DSM - DTM = nDSM, or the height of objects standing on the surface of the earth.

Figure 2: Differences between various DEMs and the creation of an nDSM. Courtesy to Tiramisu.

ArcMap

Figure 3: Statistics of the Wolfpaving mosaic. These values represent pixel values, which goes from 0 til 255. It has four bands but since the fourth is transparent, only three will be relevant.

Figure 4: DSM of Wolvpaving. This represents height values.

I generated a hillshade for the DSM layer, the difference is displayed below. One can see there is a decent shade effect from a distance, but when zooming in it is not that great shading quality.

Figure 5: DSM without hillshade effect

Figure 6: DSM with hillshade added

In order to have better hillshade effect, using a so-called hillshade tool is common to use in conjunction with a DSM model.

Figure 7: This is rich and robust data set where it is much easier to see details.

Figure 8: Same data set, zoomed in.

Figure 9: Swipe tool applied to the DSM and orthomosaic data sets. to display differences.

Setting the transparency for the orthomosaic data set (in my content pane, the layer above) to 45%, we get the best from both worlds.

Figure 10: A nice hillshade effect integrated with the elevation features.

ArcScene

In order to remember some of the functions we learned in class, I will put some hints and traces below.

Figure 11: From properties and the Base height tab we access "Floating on a custom surface"-feature. It's where all the raster values from the DSM-model are assigned to their elevation values.

Figure 12: The rendering is giving shading to where the topography top a lot more.

Figure 13: A 3D rendition of the data set we created in ArcMap.

Figure 14: From the data frame properties, it is possible to extract the elevation values.

Figure 15: The result of the exaggeration, I just made. Settings at about 2.4.

What is the purpose of vertical exaggeration? What settings do you have for your data?
The reason one use exaggeration is basically to demonstrate elevations differences. After some playing with the values, I decided to go for exaggeration value as 1.

What color ramp did you use? Why?
I was elaborating a lot here but finally, came to the conclusion to use the Red-to green diverging color ramp. This was cause I like red to display the tops and green to represent the lowest areas. That said, if there would have been water in our data set I may have chosen the Spectrum-Full bright color ramp in order to have blue to display the bottom part of the scale.

What are the advantages of using ArcScene to view UAS DSM data vs. the overhead shaded relief in ArcMap. What are the disadvantages?
ArcScene is a great platform for visualizing 3D data and elevations are much easier grasp. Another advantage over ArcMap is that ArcScene is better for exporting 3D-models. One disadvantage by using ArcScene is that is is mainly for small study areas, wheras ArcMap is better of handling bigger geographical areas.

Find a zoom setting and angle you like in ArcScene and export the image as a jpeg or file of your choice. Is this export a map? Why or why not?

Figure 16: This image export from ArcScene is not a map. It does either contain the direction of North, a scale bar, a locator map, metadata nor does it contain a watermark.

Building Maps

This section demonstrates map creation done in both with an orthomosaic image and a Digital Surface Model image as a base. An orthomosaic image is an aerial photograph that is geometrically corrected so that the scale is uniform. An orthomosaic image can be used to measure true distances because it is an accurate representation of the earth’s surface.

Figure 17: Orthomosaic map over Wolfpaving.

Figure 18: DSM Map over Wolfpaving. This looks like a DTM but is actually a DSM, taking in Nadir viewing.

Conclusions
UAS Data gives the cartographer and GIS user a variety of useful options to shape his or her map for whatever intention. UAS can be used both professionally but can also for used under more private circumstances.

The data that comes from UAS is raster values which brings some limitations. Another huge disadvantage, especially when working in 16 bit ArcMap is the long processing time. Zooming in too close could cost the user a lot of time. I know.. Zooming with scroll button on the mouse is not the preferred way to go ahead, instead of using the zooming glass feature and try to be as specific as a possible help. Finally, other areas mapping and UAS data could be a useful tool is for security issues and searching operations, e.g. for missing people.

Working with and understanding Geospatial Data

Introduction

Briefly described, geospatial data is any data referring to a specific position on earth. For example, this could be a house, trees, mountains, and buildings. The spatial component for most geographic data is geographic coordinates, latitude, and longitude.

What differentiates an ordinary digital map from data in GIS is that GIS is more or less something that professor Joseph Hupy refers to as a "smart map". Integrated with the digital map, there is a database with attribute data. To see an example, click the hyperlink of hurricanes through time.

Having a notion of geospatial data is fundamental when working with UAS data for numerous reasons. UAS is deeply involved in keeping track of earthly positions. The geographical information one can extract from a single image is mindboggling. Today, most companies, maybe unknowingly, rely heavily on geospatial data in their everyday business activities. Customer address records, customer locations, and areas of interest linked to sales, are all considered geographic data.

There are two basic types or forms of geospatial data: vector and raster. The vector format uses points, polylines, and polygons to represent spatial features such as buildings and roads. The less complex raster format uses pixels to represent spatial features.

This lab will focus on how one can apply UAS data into ArcMap. Different features and a more hands-on approach to understanding the concepts of how coordinates work will be demonstrated.

Methods/Lab Assignment

Why is file management so key in working with UAS data?
In a GIS-file, there are multiple file types. The different file extensions for the Tornado-file is shown in Figure 1. When working with UAS-data one will gather a lot of information. In order to separate them, using file management is key.

Figure 1.

ArcCatalog

What is the purpose of establishing a folder connection?
What is the difference between viewing the files in Arc Catalog vs. Windows explorer?
Why is it so important, beyond maintaining proper file management/naming, to use Arc Catalog for managing your GIS data?

During the semester we will have space at the server in order to save and access a file that we are going to use. Having an own folder will facilitate to locate the data one is searching for. But the most important things, as one can see below in Figure 2, is that each shapefile includes a lot of information. The information from Figure 1 is all covered in a single shapefile, in this case, TORNADO_tracks.shp in Figure 2. Using the ArcCatalog will keep track of the important files, but without losing any data. The information one wants to work with is transparent and easily accessible when adding files into the ArcMap.

Figure 2

What do those icons mean?

These are all vector data. The icons to the left of the text displays if it is a single point, polylines or polygons in that direction:

What topic/term relates to this description tab?

This all relates to metadata.

Why is having this information so important in the UAS realm?

This information is crucial for geospatial technology to work. The planning phase and ultimately making decisions is based on metadata. Examples of UAS metadata could be; pilot, flying date, UAS platform, sensor type, altitude, Ground Control coordinates, and UAS coordinates.

What does it say?

The "20170613_wolfpaving_dsm.tif" in the Wolfpaving_X5 folder is stating that "Statistics have not been calculated".

What types of tasks rely on statistics?

Statistics is important when performing certain tasks on imagery. For instance, applying a contrast stretch or different types of classifications.

Min elevation of the DSM:    281.04708862305

Max elevation of the DSM:   323.08865356445

Mean elevation of the DSM: 296.9669108356

Why would this information be important for data processing, analysis, and communication with the client? 

The client could be a company and in order for them to make good decision making, they need statistics. UAS will provide companies with a bunch of statistics which they can use for various interests.

Cell Size (X,Y): 0.02077, 0.02077

Format: TIFF

XY Coordinate System: WGS_1984_UTM_Zone_16N

Linear Unit: Meter

Datum: D_WGS_1984

Pixel size in square cm: 2cm*2cm = 4cm^2

ArcMap

One way of adding data to ArcMap is by using the in-ArcMap ArcCatalog and dragging a shapefile to the screen and it will show up as a layer. Another way is to have ArcCatalog open in another window and drag it into ArcMap. Also, there is a third way to open the desired data, and that with a shortcut button with the name "Add data".

What basemap did you use? Why?
I choose to open a Street map cause my goal was to choose an easy-navigated map. I thought that maybe choosing a map, which displays streets in an easy manner could be good.

What type of GIS data is this? This is Polygon data. Each polygon in Figure 3 represents a specific state.

Figure 3: Polygons

What type of GIS data is this? The tornado data is represented through vector polylines as shown in Figure 4:

Figure 4: Polylines of tornadoes

Figure 5: Zoomed in polylines

What type of GIS data is this? Adding the "dams00x020.shp" new vector points appear representing dam locations. In Figure 6, one can clearly see that some points have been added to the base map:

Coordinate systems for the three layers:

Tornado_tracks: 

Projected Coordinate System (PCS): NAD_1983_UTM_Zone_16N

Geographic Coordinate System (GCS): GCS_North_American_1983

Dams: 

Geographic Coordinate System (GCS): GCS_North_American_1983

States:

Projected Coordinate System (PCS): USA_Contiguous_Equidistant_Conic

Geographic Coordinate System (GCS): GCS_North_American_1983

Are all of these coordinate systems the same? Why might that be an issue?

The tornado tracks and the states layers have different PCSs. Using two different coordinate systems can and will cause problems. Using different framework when determining real-world locations, will place global attributes on different spots and provide misleading information. A physical location on Earth has a different coordinate value in a different GCS. When these layers do not refer to the same coordinate system, a datum transformation needs to be executed.

How might the need for metadata relate to coordinate systems?

The metadata should illustrate what kind of coordinate system is used. It is of highest interest to know what coordinate system is used. a GCS uses a 3D spherical surface to define locations on Earth, while a PCS defines a flat 2D surface. Among other, what differs these two is that a PCS has constant lengths and angles across the map plane.

Think of some different types of attribute data that could be used in conjunction with UAS data and list it here with a useful example. UAS data that could be useful in a GIS-environment and added into the attributes table would, for instance, be flight height, the flying date, flight pilot, sensor type, what kind of coordinate system etc. This refers to the metadata.

What type of data is this? This is raster data with 4 different bands. Every pixel represents a single value (integer). 

What is the format? The orthomosaic file extension is TIFF, which is preferred format cause it keeps the information lossless.

What is the projection? The projection coordinate system here is UTM, which provides a mechanism to project maps onto a 2D Cartesian coordinate plane (XY).

Figure 7: illustrates the transparent mosaic layer of Wolfpaving

What is the projection? This is a UTM-projection from zone 16N.

Does this projection match the Ortho? The orthomosaic shapefile is also a UTM-projection,

Why is this so important? The reason why this is important has been stated above.

Do the points line up with the markers on the ground? As Figure 8 illustrates it seems like the ground control points are well placed to the markers but as one zooms in, one finds out that there is a deviation. As displayed in Figure 10, the accuracy was about 10 centimeters from where it was supposed to. This makes sense since we from the metadata found out that every pixel was 2 cm long and from the image, it looks like the deviation is 5 pixels. From the image, it looks like it is a bit steep, which could play in.

Figure 8

Figure 9

Figure 10

Measure tool: Measure several features on the map. How might this type of tool be useful in working with UAS data? This is a tool that one can use to find distances between objects, like above for example. In Figure 11 the one can also choose area if that is preferable. One can choose different units like meters and inches.

Figure 11

Identify tool: Use the identify tool on several of the GCP points. Also, turn on the DSM and identify pixels on that layer. How might this tool come in handy when working with UAS data? This tool will be very useful to find specific locations on the Earth. As Figure 12 shows, both East, North and the height is displayed.

Figure 12

Swipe tool: Use the swipe tool to move between the Orthomosaic and the DSM. How might this tool be useful when working with UAS data? Beneath in Figure 13, the swipe function is illustrated. This will come in handy to separate between Digital Surface Models and other kinds of Digital Elevations Models.

Figure 13

Conclusions

Like illustrated in this post it is obvious, using UAS data gives the GIS-user various opportunities to display maps and adopt geospatial technology into their own specific needs. However, concerns do exists. When pairing points from the UAS data to the ground, the accuracy and quality is not interesting if the coordinate system is totally off. Using UAS data in combination with Forestry brings a lot of interesting options.

Welcome to my UAS Online Portfolio!

On this blog, I will provide information about me, my past and assessments of we are doing in class. I will post weekly updates and post my exercises as reports.

UAS Background

My background may look slightly different from the other students. I was working in finance as a stockbroker for almost ten years before throwing in the towel and decide to invest long term through an engineering degree. I went into the field of geomatics, which amongst other subfields particularly focus on surveying but also photogrammetry. Still today, UAS is used commonly in surveying, but the industry is positive this will increase by staggering proportions coming years. This said it is strange that no UAS courses are provided at my home University. Thus, one of the reasons I decided to go on Exchange to Purdue University was actually that I wanted to learn about UAS and how it can be applied to the field of geomatics. Languages disabilities and the fact that I have no knowledge about UAS from before may imply that the course will be hard for me in the beginning. But I am eager to learn and find new ideas in how to adapt principles from AT 319 into my own field. Who knows, maybe I will have my own private UAS integrated surveying company in the future.

Previous Students E-Portfolio Critiques

Wil Blouin, GEOG 390, Spring 201

Wil had decided not to have his pages represented as horizontal tabs. Instead, he put them on the vertical, beneath the Blog Archive. To me, a blog seems better organized and is easier to navigate having the pages horizontally. The white background made the blog eye appealing and tons of interesting course images were found. However, I would have preferred if he also had a separate page which showed the figures and had a hyperlink to the actual post. In that way, it would be possible to locate the topic of the image that one finds interesting.

Todd Horn, AT 40900, Fall 2018

Todd had put up a decent amount of information. To my eyes, though, I would prefer a larger font size. Also, I would choose a background that not steals the attention from the content. On the good side on the Assessments page, he had put up criteria for the grading. After scrolling through some web pages, I found that some had chosen not to describe what the grading represented.

Dylan McQueen, AT 40900, Fall 2018

Not sure how much effort Dylan put into his blog, but it seems a bit incomplete. Only three pages exist and the good pictures one can find in some of the posts cannot be found under the Figure page. The posts are made in a transparent manner which in combination with the background makes it unnecessarily difficult to read.

Evan Hockridge, AT 40900, Fall 2018

Evan had made a very thorough effort to present his skills. Content included everything from well-explained posts, what the course was all about, to good color contrast. It had an abundant amount of information. Perhaps he could have worked a bit more on the Contact page and had some more delightful images. To summarize this fine work, it was easy-navigated, user-friendly and the blog wore a character of simplicity over itself.

Kyle Sheehan, AT 40900, Fall 2018

Kyle had also put in great effort in order to attract eyes to his blog. It really captured your attention. Particularly I liked the easy navigated way of sorting his posts. A short abstract with a heading and light-colored background appealed to me. Even though I would prefer a horizontal bar of the pages, the classic sidebar on the left worked here. The width of the posts was dimensioned perfectly, not too long, not too short.

Thoughts

After scrolling through most of the blogs for AT 40900 and GEOG 390 I intend to produce my blog in a simple easy-navigated way, not having it unnecessarily detailed. I will go for a horizontal bar and having brief abstracts to every post and a comfortable color scheme will be chosen. I will also add relevant images to my gallery. I guess more ideas will come through the semester and I make a reservation that I may adapt the appearance as time goes by.

The UAS curriculum looks very interesting, I am looking forward to learning and I am curious about how the labs are going to turn out. Especially, I have an interest in learning ArcPRO and ArcMAP and how one can implement UAS data into them.