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Mappt & QGIS Workflow: Using Drones to Enrich Field Assessments

DEM Dubai Airport Satellite Imagery Digital Surface Map orthomosaic sentinel 2 multispectral bands satellite imaging corporation

When it comes to fieldwork, the best outcome (aside from zero injuries) is to return having collected as much high-quality data as possible. We all want to ensure our project goals are reached successfully, so using a wide variety of relevant data to address the project criteria is a good strategy. An example of this is producing high resolution Digital Surface Maps (DSMs) using drones to complement field surveys conducted on-foot. These DSMs can provide additional information such as elevation, NDVI indices and more to complement the field survey data. 

DEM Dubai Airport Satellite Imagery Digital Surface Map orthomosaic sentinel 2 multispectral bands satellite imaging corporation

Digital Surface Map of Dubai International Airport by Sat Imaging Corp.

The workflow below describes the process for creating a DSM with QGIS to produce a data-rich field map, which complements field survey operations conducted using Mappt.

The Mappt team conducted a field survey at Kensington Bushland, in which we collected a range of points to characterise the local vegetation using Mappt.

Kensington Bushland, City of Victoria Park, walk leisure recreation natural park for

Kensington Bushland, City of Victoria Park

Each survey point contained a range of attributes for the field worker to fill out on location, including plant species, condition, time, % coverage etc. We created the attribute form using Mappt’s handy drop-down feature to collect all the field data. This was of course put together and pre-loaded prior to heading out into the field, like the intelligent and efficient field workers we are 🙂

(Click HERE for a free copy of our Ultimate Field Checklist)

Of most interest for this assessment was the species and condition of vegetation at the field site. The project goal was to explore trends that may explain any gradients in the species structure, coverage and/or condition. We collected additional drone imagery over the survey area, which was used to provide valuable complementary information on the vegetation community.

 

Now that we’ve returned from the field in good spirits and relatively unscathed, it’s time to begin our workflow process for the field survey!

Loading Mappt data into QGIS

First, we want to export the survey data collected using Mappt and bring it into QGIS. To do this, we want to navigate to the saved project file within Mappt and then click the export icon. We then want to select all layers, choose the GeoJSON format for QGIS, then choose to export to external apps, lastly selecting Google Drive as the export location. (See below)

Mappt user interface field mapping collecting georeferenced images for vegetation assessment screenshot_20190605-110141

That’s it, put down the tablets people! You’ve successfully collected and exported your field data from Mappt. Pretty easy right?

Now we want to move over to our desktop computer and load the Mappt data in for further processing in QGIS. Open up a new project in QGIS and check that the CRS projection is set to WGS 84 (under Project > Properties).

Next, add Google Satellite as a base layer for your project (click on the Web > QuickMapServices > Search QMS, then click on Google Satellite in the window that opens in the bottom-right).

 data-source-manager-icon

Click this icon to Import the Mappt data from Google Drive into QGIS through the Data Source Manager.

 

 

Now double-click on the Vector file in the Layer Window to make any style changes desired. For my data, I have characterised survey points into species type and given them different colours. I also filled in the polygon for the reserve area, and indicated my survey entry and exit points with coloured lines.

mapptdata

Now you’ve got your Mappt survey data looking schmick in QGIS, it’s time to bring in the drone images to create a DSM overlay! First, we will need to combine all the photos from your drone together into the one orthomosaic (to rule them all).

Creating a Digital Surface Map using Drone Deploy

Go to http://dronedeploy.com and create an account if this is your first time using it. Then simply upload all your images into the window and drone deploy will create an orthomosaic for you! You can change the processing time by toggling the speed vs quality bar under the ‘Advanced’ tab. Click ‘Upload Images’ to begin the process.

It might be time for a tea break now, as this does take a while.

drone deploy mapping software online orthomosaic creator drone imagery

Once the map has finished processing, you have the option to export the orthomosaic as a natural colour GeoTIFF, as well as NDVI index and Elevation map. Export any that you want and ensure they are GeoTIFFs.

Now, we want to bring QGIS back up and load in the files, once again using the Data Source Manager.

raster-icon Click this icon within Data Source Manager to load the GeoTIFFs as raster files.

Again, we can change the opacity and style of each layer to get the desired style. For my orthomosaic, I chose to reduce the opacity of the natural colour layer so that the elevation can be seen.

orthomosaic-data

There are some interesting features of the elevation that seem to overlap with some patterns in the vegetation structure! We should create a map to show the boss.

Creating a map in QGIS including Mappt survey data and DSM data

print-layout-icon To do this, we want to click on the Print Layout icon in QGIS.

This opens a blank page from which we can begin to draw our map.

addmap-iconIn the Composition Window that’s just opened, click the ‘Add Map’ icon.

Then click and drag an area over the canvas in the window to produce a map. The map produced is based on the view in your main QGIS window, so you may need to do some final style tweaks to finalise the image.

map-icons You can then add a Title, Legend and Scale bar to your map using their respective icons.

You can customise all of these to your liking by clicking on the feature then using the ‘Item Properties’ window on the right to adjust the information displayed.

imageicon Next, add a North Arrow by first clicking on the ‘Add Image’ icon.

Then, navigate over to the ‘Item Properties’ window and click on the ‘Search Directories’ drop down. Here you will find a number of images that are suitable as a North Arrow.

Lastly, click on the map itself and navigate through the item properties until you find the ‘Grids’ drop down (See below). Click on the green plus icon to add a grid, then click Modify Grid to set the scale. Once your grid is displayed nicely, lastly change the frame style to ‘Zebra’ and then close out.

grid

Voila! Your map is now complete for reporting. For my data I’ve found a pattern between increasing elevation on my DSM, and abundance of Banksia menziesii. Neat!

QGIS map of kensington bushland created using mappt and drones to produce digital surface map and vegetation survey data

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Quick Field Inspection Reports From Mappt

Mappt continues to prove itself as a versatile tool with new and innovative uses occurring regularly.  This post focuses on implementing field inspections and in-field reporting using Mappt. 

Using Mappt to perform on-site roadworks inspections

Using Mappt to perform on-site roadworks inspections

A recent client inquired about Mappt’s ability to generate in-field inspection reports suitable as a client deliverable.  As an agnostic data collector (i.e. unhindered by proprietary data formats) Mappt renders data in various formats – both GIS-specific (e.g. shapefiles) and generic (e.g. .csv files).  As an efficient data capture tool, Mappt gives users the flexibility to create field forms following a natural data collection hierarchy and progression.

Completed roadworks inspection report from Mappt

Completed roadworks inspection report from Mappt

In this instance, we were provided with the client’s standard field inspection report and tasked with developing a workflow within Mappt for capturing all data to be included within the report and to provide functionality to generate reports in-field as a client deliverable.

The client’s standard six page inspection report was inclusive of seven unique data types covering the following categories;

  • General Parameters: date, time, inspector, weather
  • Site Photos: works in progress & comments
  • Roadworks by Location:  specific road locations & activities
  • Manpower Classification: job classifications and aggregate hours
  • Equipment Type and Number:  equipment in operation on site
  • Quality Assessments: assessments of roadworks to design
  • Safety Compliance: titles and names of responsible parties, proper signage, etc.
Segregating inspection data types into Layers improves data management

Segregating inspection data types into layers improves data management

Breaking each category into separate layers was deemed most effective as some categories were not required to be populated during each inspection/site visit.  For example, inspections might occur when the contractor was offsite and therefore recording the “equipment in operation on site” was unnecessary.  In addition, a single category might include upwards of forty-five attributes.  Including the possibly hundreds of features in a single field form is less ergonomic, requires the user to look at their screen for an extended period, and possibly unsafe as the user could become unaware of equipment operating nearby.Creating a comprehensive layer inclusive of 45 attributesCreating a comprehensive layer inclusive of 45 attributes

A unique but useful utility in Mappt is the ability to call up Google Street views directly from Mappt.  It is useful for orienting site visitors who may be unfamiliar to the project or for inclusion into a client deliverable such as these field reports.

The Google Street View Icon lets can help orient users to new locations

The Google Street View Icon (red circle) launches Google Street View on your tablet

Google Street View captured in Mappt helps users find new locations

Google Street View captured in Mappt helps users find new locations

After data collection for the inspection report has been completed the data are exported as comma separated values files.  Using a previously formatted spreadsheet workbook, the data is imported to a data input worksheet and a second formatted worksheet makes reference calls to the first to generate a print-ready field inspection report.  Users can than render the report in a printer friendly format (e.g. .pdf) and email it to the client.  Spreadsheet software for Android tablets includes MS Excel, Google Sheets, and Polaris Office.

Formatted field inspection report with reference calls to input sheet

Formatted field inspection report with reference calls to input sheet

Visualising Roadworks Inspection Information on Your Desktop

To visualise the roadworks inspection information on your desktop, first share the layers from Mappt as either GeoJSON or Shape Files and them import them to your desktop GIS system.  We mentioned that each feature contains numerous attributes and it may be necessary to call this information up ‘on-the-fly’ to recap previous inspections or track progress onsite.  Tool tips in QGIS are an effective means to call up attribute information, especially text information like this.  By calling up the display properties for your layer, it’s possible to call up any attribute information possible using HTML syntax.  Referencing an attribute is as follows; [% “AttributeName” %].  Using <br> ensures that a carriage return is used and any text typed in will also appear in the tool tip.  You’ll need to enable map tips from the View tab in QGIS to switch on map tips.  When map tips are enabled, hovering your mouse over a feature in the active/selected layer will cause the tool tip to appear.

Syntax used for displaying multiple attribute information in QGIS

Syntax used for displaying multiple attribute information in QGIS

 

Displaying information for features with multiple text attributes in QGIS

Displaying information for features with multiple text attributes in QGIS.  

This exercise highlights how Mappt can simplify field inspection report generation and improve data integrity.


Harmeet Kuar developed the workflow for: Quick Field Inspection Reports with Mappt

Harmeet Kuar developed the workflow for: Quick Field Inspection Reports with Mappt

By Harmeet Kaur

Harmeet Kaur is a recent Geographic Information Systems graduate from the University of Western Australia and has recently completed an internship with Takor. While at Takor, Harmeet focused on developing workflows to improve Mappt’s in-field usability and has contributed to many of the blog posts you see here.


If you would like to know more about using Mappt as an efficient and robust field inspection utility, please contact us at: support@mappt.com.au

Try Mappt today by downloading it from the Google Play Store or Apple App Store

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1m Positional Accuracy in Mappt using Bad Elf GNSS Surveyor

Bad Elf GNSS Surveyor & Mappt Mobile GIS

Measuring 60x100mm the Bad Elf GNSS Surveyor can provide 1m accuracy

Measuring 60x100mm the Bad Elf GNSS Surveyor can provide 1m accuracy

Thanks to the helpful folks at Bad Elf, we recently got our hands on the Bad Elf Surveyor Bluetooth GNSS* for testing with Mappt. Combining Mappt with an external source of positional information delivers higher  accuracy than using the on-board GNSS for mobile phones and tablets. It also reduces battery consumption and CPU load on your mobile device.

Vendors like Bad Elf also provide applications offering enhanced functionality for data logging, device configuration, and data QC. Using external GNSS sources makes determining your position less “black box” and more hands-on when it comes to resolving your location and understanding the level of accuracy provided.
Compact and Compatible
Paring the Bad Elf GNSS with Mappt follows the same procedure we’ve detailed in a previous blog. The compact design (100x 60x20mm) and long lasting battery make the Bad Elf a handy field companion for mobile mapping and data collection. With a small LCD screen yielding important GNSS information, the Bad Elf keeps you well aware of the positional information available to you.

GNSS information available from the Bad Elf's compact 35x25mm LCD screen

GNSS information available from the Bad Elf’s compact 35x25mm LCD screen

Increased Accuracy
When either mapping or collecting data in the field, increased positional accuracy is always a plus. Often it’s necessary to revisit the field to account for seasonal changes (in the case of environmental sciences) or for relocating benchmarks or critical infrastructure such as utilities. The Bad Elf Surveyor offers up to 1m accuracy, an improvement over the 3-5m accuracy achievable with tablets and mobile phones.

 

How does it do that?
The Bad Elf Surveyor uses information from three satellite constellations; GPS, GLONASS, and QZSS. Thus from wherever you are globally, there’s an increased probability that you will have the required four satellites to resolve your position. Many devices derive location from a single satellite constellation thus limiting the amount of satellites available to them. The Bad Elf Surveyor also implements SBAS, Satellite Based Augmentation System, to gain positions within 1m. Serving as an augmentation to Global Navigation Satellite Systems, it works by collecting raw positioning data from regional Continuously Operating Reference Stations (CORS), computing error corrections, and sharing these corrections to users via a geostationary communications satellite. While southern hemisphere regions don’t have their own SBAS, Australia is currently implementing its own SBAS test-bed to be operational by January 2019.
Alongside SBAS, the Bad Elf Surveyor also implements PPP, Precise Point Positioning, which removes GNSS system errors providing a high level of position accuracy from a single receiver. This solution depends on GNSS satellite clock and orbit corrections. These corrections are delivered to the receiver via satellite to provide positioning accurate to within several deicmetres.

 

Mobile Device GPS Behavior Versus Dedicated GPS Units
Mobile device GNSS chipsets have been designed to compliment an integrated system (your tablet/phone) delivering a wide variety of applications. Just count the number of apps you’ve downloaded from the app store. Can you imagine carrying a separate component for each of these?  These mobile applications are optimized to reduce load on the system by reducing battery consumption and processor load. The optimisation for mobile GPS chipsets puts limiting battery usage at the top of the list with time-to-fix location second and positional accuracy third. Dedicated GNSS devices like Bad Elf devices flip this priority on it’s head, placing positional accuracy first followed by time-to-fix and lastly the reduction of battery power. While it may seem like the Bad Elf would quickly run out of juice, it can continuously stream Bluetooth GNSS information for 24 hours. We have yet to see a tablet with that type of battery power!

We took the Bad Elf GNSS Surveyor to our favourite bushland, Signal Hill Park

We took the Bad Elf GNSS Surveyor to our favourite bushland, Signal Hill Park

Mapping Tips n Tricks Learned Using the Bad Elf Surveyor
Creating Polygons in Mappt –  Turn on the enter polygon tool and record each significant point of the polygon (corners and inflection points) as you walk out the perimiter. This ensures that corners/vertices are not shortcut and an accurate shape of the area is recorded.  It’s possible to create polygons in Mappt using the GPS Tracking tool, then walking out the perimeter of the polygon, and finishing off by converting the polyline to a polygon to enclose the area. This method helps when moving continuously (such as when in a vehicle) as you don’t need to stop and record points around the area. However the points associated with your polyline are created at the frequency of GPS updates from your device and you may end up not recording those key corner points!
GNSS Location – Place your external GNSS device in a way that provides a clear view of the sky. Some websites suggest affixing the GNSS face-up to the top of your hat! While you will have great reception, this limits the opportunity to check parameters on the LCD screen. Affixing the GNSS to a surveyors staff gives you both a walking stick and place to mount your tablet. This setup affords both good GNSS reception and makes data entry easier as the tablet is held steady by the staff.  Note:  The team at Bad Elf are currently developing hardware designed with rapid mobile mapping in mind.

The crew at Bad Elf are working on a clever monopole mount for the Bad Elf Surveyor

The crew at Bad Elf are working on a clever monopole mount for the Bad Elf Surveyor

Bad Elf has developed an integrated GPS and mobile device monopole for rapid mobile mapping

Bad Elf has developed an integrated GPS and mobile device monopole for rapid mobile mapping

Bad Elf GNSS Logging – The Bad Elf allows continuous logging of points. After a hard day in the field, it’s nice to know how much ground you covered. Logged information can be downloaded as GPX files and visualised in desktop GIS solutions such as QGIS.

Signal Hill Park Map from QGIS. Bad Elf track points (orange) displaying the total ground covered in this mapping exercise.

Signal Hill Park Map from QGIS. Bad Elf track points (orange) displaying the total ground covered in this mapping exercise.

*GNSS, Global Navigation Satellite System, is the collective term for all navigation satellites groups (constellations) including GPS.

 

If you would like to know more about configuring an external GNSS to work with Mappt, please contacts us at: support@mappt.com.au

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External GPS sources for Mappt Part 2: Mapping in the Field with RTK GNSS (survey-grade GPS)

In our last post we covered how to configure your tablet or phone to receive an external GPS signal via Bluetooth.  Here we share our experience of linking up Mappt with survey-grade RTK GNSS (Real Time Kinematic Global Navigation Satellite System) to achieve centimetre-level positional accuracy.

 

Utilising RTK GNSS and Mappt for centimetre-level positional accuracy

Utilising RTK GNSS and Mappt for centimetre-level positional accuracy

Achieving Survey-Grade Positional Accuracy with Mappt

Joe user asks, “Hey how can I achieve high positional accuracy with Mappt?

The short answer is, “Bluetooth to an RTK GNSS to achieve centimetre level accuracy“.

What’s GNSS?

GNSS, is the collective term for all satellite positioning systems which includes GPS (USA), BeiDou (China), GLONASS (Russia), Galileo (Europe), IRNSS (India), and QZSS (Japan).  Phones, tablets, and survey-grade systems use satellites from multiple positioning systems, thus we’re referring to these systems as GNSS (rather than GPS).

The Benefits of Using Mappt in conjunction with RTK GNSS

Mappt’s flexibility and onboard functionality helps users achieve the full benefits of high accuracy RTK GNSS while in the field.  For example when using Mappt in conjunction with RTK GNSS, users have in-field access to these mapping tools;

  • Locate and save point features with unlimited attributes
  • Thematic Mapping gives users the ability to colour code mapped information while in the field
  • Layering of data types to achieve hierarchal data structure and visualisation
  • Interactive functionality (exclusion & inclusion zone warnings) improving field safety
  • The ability to display web-based aerial/satellite imagery and other GIS information such as WMS, WMTS, & WFS
    • With a data connection, this data is continuously updated as you move to new areas
  • Offline display of high resolution aerial and satellite images (ECW, JP2)
  • Multi-user data capture & updates using MapptAir.

RTK GNSS Gear

In our previous post we detailed how to configure your mobile device to receive location information via Bluetooth.  Thanks to Mangoesmapping and Ascon Surveys both for their technical support and equipment (on loan) used to complete our trial.  We found the Emlid Reach RS RTK GNSS units (available from Mangoesmapping) suitable for this trial.

Our Field Experience

The following data was acquired in less than one hour (including setup and pack down of the RTK base unit and survey pole mounted rover unit).  Data collection in this small urban bushland was on-the-fly as point types were added as deemed necessary.  Points types collected included kerb locations, footpath limits and walking tracks.  Point types were added to our field form as necessary thus the list of point types was added to as new elements were observed.  *To save time, a dropdown list of point ID’s can be created prior to leaving for the site.  In the limited time spent onsite, three point IDs were all that was necessary.  We also utilised the geotracking utility to map in the trails crossing the site as well as to create a geofenced area at the park’s centre.  Lastly we tested Mappt’s geofence alerts feature by entering and exiting our geofenced area.  Have a look at this video showing how it works.

Mappt mobile GIS data gathering using RTK GNSS at Signal Hill, Belmont, WA

Mappt mobile GIS data gathering using RTK GNSS at Signal Hill, Belmont, WA

What we took away from the experience.

It was a simple step to download all data gathered to shape files and import them into QGIS.  We mapped in such features as the back of kerb, footpath limits, and bush tracks.  RTK GNSS units have the ability to validate/qualify positional information with an audible “Fixed” to indicate that positional information is within your specified accuracy.  Likewise when the positional information is below spec an audio warning “Float” will alert users that possibly more time at that location is needed to gain a fixed position or that trees or buildings are hampering satellite reception.  Our recommendation is to have this activated on your RTK GNSS receivers to eliminate collecting data of low positional uncertainty (occurs in areas of high tree cover and when adjacent to tall buildings) .

QGIS map showing GIS data gathered using RTK GNSS and Mappt

QGIS map showing GIS data gathered using RTK GNSS and Mappt