Increase Jobsite Safety With Predictive Data

by TOPS Marketing | Jan 13, 2023 | Resources

Predictive data analysis helps companies use data and information to make good decisions, increase productivity and improve safety measures in the workplace. With predictable outcomes for your future projects, you can estimate how much you might need to spend on tasks or identify areas with a higher likelihood of causing injury.

Predictive data brings structure to structureless data. Data common to the construction industry may be hard to analyze or structure into understandable maps and tables. Predictive data analysis helps construction companies monitor important data to make their workplace safer and more efficient.

Benefits of Predictive Data

Using predictive data in the construction workplace has many benefits. Besides the typical benefits of risk reduction and increased safety measures, predictive data analytics reduce the chance of human error and lead to impressive results that will help a company thrive.

1. Risk Reduction

Predictive analytics gives you a lens to better understand data in real-world applications. You can get a good sense of your business structure and understand how to take steps toward a workplace free of incidents or injuries. If you can predict what specific tasks may cause injuries or increase risks based on previous data, you’ll be prepared to reduce risk in the workplace and work toward a successful and healthy team.

2. Less Human Error

The ability to learn from our mistakes is one of the most valuable life skills to have, and predictive analysis follows a similar mantra. With predictive analysis, construction workers can analyze previous data to help them reduce future errors.

Take this small-scale example: If a construction team notices they tend to experience more slip-ups onsite when it’s chilly outside, they can look at previous data to try and decipher the cause of the error. They may realize that the jackets they wear when it’s cold inhibit movement, increasing the likelihood of injury or mistakes.

Predictive analytics makes it easier to make the right decision that will most likely result in a positive outcome for your company.

If you need more computing power and want assistance with accurate decision-making, using predictive analytics can help you. Predictive analysis can reduce human error, which leads to the following benefits for your company:

• Ability to analyze large data sets: Predictive analysis uses a large set of data to inform results and records, making the decision process easier.
• Faster production: Predictive analysis can produce results quickly, helping your company keep up with decision-making on time.
• Improved precision: Predictive analysis data sets are precise and accurate. Accurate data allows your company to make informed and correct decisions about safety, products or materials.
• Improved safety: With a better, more precise and faster process, the overall safety of your company and employees can improve. You can make better product decisions and pinpoint areas where safety in the workplace could improve.

3. Impressive Results

Predictive analysis can also help your company and workplace thrive. For example, you can analyze workplace safety over a certain amount of time to see how many workplace injuries occur. Once you have that information, you can use predictive analysis to spot trends, see which activities most frequently lead to injury and make safety improvements to reduce the number of injuries.

You could also use predictive analytics for more than researching and analyzing data. Many companies have recently begun using predictive data and smart devices to increase safety and efficiency in the workplace. Smart devices can predict hazard areas or tell a worker if their actions may result in a possible injury.

For example, Caterpillar, a leading construction machinery and equipment company, began using Cat Smartbands. The device used a wristband with a mounted mobile device to detect fatigue levels in employees. It could also detect severe braking, swerving and inattentive driving when the wearer operated equipment. The Smartbands offered a great way to combine predictive analytics with modern technology to actively increase workplace safety for Caterpillar.

How Does Predictive Data Lead to a Safer Jobsite?

Knowledge of the benefits of predictive data can make construction sites safer. Completing integral jobs can be risky at any job site. While on the job, construction workers may get exposed to chemicals, experience burnout or anxiety or have to operate machinery that leads to injuries or damaged equipment.

The right software can help provide your company monitor valuable safety data. Safety managers can use data to improve workplace conditions through accurate datasets and predictions collected specifically for safety purposes. Remember that collecting unnecessary information about other kinds of predictive data may alter your safety analysis. If you intend to reduce safety concerns, keep your data analysis concise.

Some examples of data categories your company may want to explore include the following areas:

• Reported incidents: A description of the safety incidents reported and details about each type of injury or accident.
• Incident rates: The rate of recordable safety incidents in the workplace or warehouse.
• Injury costs: The cost of each reported injury, including medical bills, worker compensation and other money spent on repairing the damage.
• Training and certification: The kind of certifications or training each employee has received concerning the workplace and each reported incident.
• Safety incidents: Incidents related directly to safety violations when using heavy machinery and equipment or operating in the workplace.
• Fleet accidents: Accidents related to fleet operations and the details surrounding the accident and injuries.
• Tools: The tools used during the incident or any devices used during the day.
• Design elements: Specific design elements of equipment, machinery or tools that led to the injury.
• Compensation: Details on worker compensation related to injuries or incidents, including amounts and frequency.
• Severity: The severity of the injuries or incidents.
• Experience levels: The experience levels of employees in the workplace and those involved in the incident or injury.

The information provided through these data points can help your safety workers, managers or inspectors create a better work environment. Predictive models help your company pinpoint the exact areas that need immediate improvement.

Find out what led to injuries and where they occurred. You can also discover what equipment and tools are most likely to cause potential injuries and work to reduce safety hazards. Knowing the possible cost of injuries can also encourage a decrease in workplace injuries.

Consider the legal aspect as well — predictive data analytics can help create an accurate timeline of claims and injury costs. Information on your claims may become part of the litigation process, and a detailed account of each incident can assist stakeholders, CEOs and workers in reducing injury-related losses.

Getting Started With Predictive Data Analytics

Now that you understand the benefits of predictive data analytics, it’s time to get started collecting data. Before diving in, you may want to become familiar with the different areas of predictive data so that you’re fully prepared for every step. Here are eight essential factors to consider.

1. Focus Areas

One of the best ways to get started with predictive data analytics is to identify focus areas to create an efficient process. Remember not to choose areas that are too broad to ensure you get accurate results. You want to use your time — and data — efficiently.

Choose one or two focused areas to create a predictable analysis of data. Your data can help you anticipate and mitigate safety hazards, improve quality and reduce safety issues. With more visibility into risky projects and equipment, your company can prepare for every safety hazard and reduce the number of injuries each year.

2. The Right Tools

You can also use past data to grasp how tools have contributed to injuries to choose the right tools for the job. Using the right tools in the workplace is an essential part of risk management. It can also help you reduce costs and increase safety. After analyzing the differences between tool types, you can evaluate each one’s performance and work to mitigate risks in the workplace.

Safety managers may especially benefit from predictive analytics relating to tools, as they can predict potential behavioral hazards related to tool usage and work to implement better safety practices. Taking proactive measures using accurate data can help top managers and executives in the company identify and reduce risks before they become an issue.

3. Standardize and Centralize

Predictive data analytics also offer a helpful way to centralize and standardize your company’s data. You can provide structure to your company through proper research and reporting. Employees and managers can better utilize the information for hazard mitigation when they know where to find it.

Many companies enjoy that standardized data allows them to explore future technology in the workplace, such as machine learning or AI. Analyzing such options can help increase areas like project delivery and create an efficient company in and out of the workplace.

4. Budget Management

Your company must pay attention to each project’s financial and budget management forecasts during construction projects. For example, you may be required to monitor budgets in real-time, identify cost overruns or anticipate cash flow problems. These tasks are made easy with predictive data analytics that can quickly research and run data about anticipated financial risks and issues before they occur.

Your company can also use predictive data for the following purposes:

• Finding equipment to purchase: Use predictive data to buy the right equipment or machinery in the future.
• Deciding whether to purchase or lease: Decide when it may be best to purchase equipment or lease machinery for a project.
• Predicting revenue and profits: Monitor and predict your overall profit and revenue for every project.
• Discovering staffing needs: Decide what staffing requirements may be necessary for each project.
• Choosing future projects: Predict what tasks you may complete or acquire.

5. Easy Access to Information

Predictive analytics may also help you make informed decisions and encourages companies to provide easy access to data and information across teams. Many companies remain dependent on paper information in the construction industry, but adopting paperless data helps keep necessary materials stored in the cloud rather than binders. From stakeholders to contractors or third-party employees, people will benefit from easily accessible information. It also increases team members’ communication and collaboration while improving employees’ planning and decision-making.

6. Efficient Reporting

Many companies in the construction industry have relied on paper-based reporting in the past, which may lead to problems in the future, as papers may go missing or essential reports get lost in messy offices. Even subcontractors could get behind on filing paperwork, making the construction process challenging and inefficient or leading to delays.

Paperwork can also make it difficult to visualize data accurately or compile large amounts of information. With digital predictive data analytics, you can easily access reports online. Digitization saves time and helps companies avoid accessibility problems or human error during data entry.

7. Increase Worker Safety and Productivity

Remember that one of the main benefits of predictive data analytics is improved safety and productivity in the workplace. Data can help you maximize your productivity by keeping workers engaged and saving time and money that you might otherwise lose. Overworked or burned-out employees may result in overtime costs and high employee turnover.

Predictive data can help you pinpoint areas of improvement and trends in injuries and accidents during the day. With the right data, you can fix the problem and find areas where you could continue improving your workers’ conditions. You’ll see that efficiency and workflow increase significantly once employees work in a safe and healthy environment.

8. Dispute Resolution

Resolving disputes is a common problem in the construction industry and can result in costly resolutions. Predictive data can help your company find areas where conflicts may occur, such as progress or project status, time spent on projects and cost related to projects. Material usage or quality of material may also be a common reason for disputes. Understanding these key areas can help you create and analyze data sources to find the truth for both parties during a dispute. Using predictive data, you can reduce the chances of needing dispute resolution altogether.

Predictive Analytics: A Summary

With all this information in mind, you can leverage predictive analytics by using historical data to predict safety hazards or future events. Creating a safer workplace starts with informed decision-making, which is only made easier with predictive data. You can prevent problems before they exist with accurate data, reducing injury costs and safety hazards. With informed data in mind, your company can identify opportunities to improve workplace processes, operations and safety procedures.

Use Predictive Analytics at TOPs

At Take-off Professionals (TOPS), we offer 3D data for machine control and layout. From grading surfaces to layouts and utility trenches, our products assist rovers, machines, pavers and more. With predictive data analytics, your company can use our quality takeoffs to estimate the cost of a project, including the attributes and quantities of materials you’ll need to complete it.

From schools and commercial sites to streets, highways and home lots, our predictive data allows your company to use the right tools, materials and quantities at all times. Your company can become the most efficient and safe it has ever been. Contact us today to speak to a representative, or call us at 623-323-8441.

How to Determine Volume From Contour Lines

by TOPS Marketing | Dec 29, 2021 | Resources

Finding volume with contour lines is essential to your business operations. Increase precision by calculating volume from topographical 3D models.

What Are Contour Lines?

You can find contour lines on topographical maps. These lines define the elevation levels of a particular terrain. Contour lines with a wider distance between them indicate a more gradual slope. If they’re close together, that means that the elevation is steeper.

Contour lines represent an area where all locations on that line are at the same height. We use these lines to determine the elevation and topography of a landscape. In the case of construction work, surveying the land can help you decide where to locate new structures and where you may need leveling work.

What Are the Formulas?

You can determine volume using contour lines in two ways:

• Prismodial method: This method offers a precise way to get an estimate of the volume. The formula is generally known as Volume = L(A + the square root of (A*B) + B) divided by 3.
• Trapezoidal method: This method is also used in calculating volume with contour lines. The formula is Volume = L x 1/2 (A1 + A2) cubic meter.

Why Is Volume Calculation Important for Earthwork?

Measuring the volume of the land at your next project is vital for several reasons. First, if you want to create an accurate bid for the work, you need to know what type of landscape you’re working with. Using contour lines and topographical maps to determine volume will give you an idea of the work you’ll need to do. Then you can more accurately account for labor and material costs.

On that same note, calculating volume also allows you to use your materials effectively. When you know the volume of the area, you can take the guesswork out of how much material you need for a particular project.

Contact Take-off Professionals for More Information Today

At Take-off Professionals, we use your data to create 3D topographical models. We optimize what you gather from a quantity survey to make models with contour lines to determine volume. Ensure material and budget use and accuracy with our help.

Our team is composed of full-time professionals who work on these projects as their specialty. We focus on creating dependable 3D models to use for determining the volume of the terrain for your earthwork.

You can access our online platform to view your data and models. You can even add other files or notes to keep all related materials in one place. Take-off Professionals has over 20 years of experience and works on around 1000 3D models yearly.

We offer detailed quotes that describe the exact services you’ll be getting. Our turnaround times are quick too, ensuring that you can get your work done on time. We have trained professionals on a national scale, meaning that we can help you no matter where you live. For more information about our 3D modeling services, please get in touch with us online or call 623-323-8441.

Depth Map Sequences vs. Point Clouds

by TOPS Marketing | Jan 21, 2021 | Resources

A 3D model lets a civil contractor or construction professional perform machine control and layout planning before and during construction. Depth map sequencing and point cloud modeling are two examples of 3D modeling often used in construction. Although the two methods have some things in common, they ultimately have different goals and purposes. A point cloud is usually a collection of data points that form a shape, while a depth map conveys information about the distance between two objects in space.

Learn more about the differences and similarities between point cloud modeling and depth map sequencing below.

What Is Point Cloud Modeling?

Point cloud modeling produces a set of small data points, which exist in three dimensions and on X, Y and Z coordinates. The data points represent a part of a surface in a defined area, such as the area of a construction site. When arranged together, the points produce a clearly identifiable structure.

The more data points in the point cloud, the more detailed the structure and image will be. You can compare the data points that make a point cloud to the pixels that make up a digital image. The more pixels there are in an image, the clearer the picture is.

Point Cloud Modeling Methods

Two methods can produce point cloud models — photogrammetry and Light Detection and Ranging (LiDAR), also known as remote sensing.

Photogrammetry is a relatively old process of collecting information about objects and surfaces. When photogrammetry is part of point cloud modeling, a drone takes multiple images of a work or construction site at various angles. After the drone takes the photos, the images are collected together and processed. Processing the images stitches them together, creating an overlapping picture and allowing you to build a 3D model from them.

While photogrammetry uses images to help you produce a 3D model, LiDAR uses laser beams. Typically, a device that transmits a laser is attached to an aerial vehicle. The vehicle goes up into the air, directing laser beams back to the Earth. The laser beams bounce off the Earth’s surface, returning to the vehicle.

LiDAR measures how long it takes for the laser beams to travel from the surface back to the aerial vehicle. In some ways, it is similar to echolocation, except instead of using sound waves to measure distances, LiDAR uses light beams. The information collected by LiDAR can then be transformed into a 3D model. Once the images or information is collected, the process of transforming them into a 3D model is similar for both photogrammetry and LiDAR.

Often, LiDAR collects more useful information than photogrammetry, particularly if there is dense tree cover over the area being measured and modeled. A photo can’t push through branches and leaves to give an accurate measurement to the ground below. A light beam can travel through the spaces or openings in the tree cover, allowing you to see how far below the ground is.

One drawback of LiDAR is that it can be more sensitive to weather conditions than photogrammetry. It can also have difficulty collecting accurate information when the surface is reflective.

The two methods also vary drastically regarding price. If you are on a budget, one method of capturing information for point cloud modeling might be more appropriate for you than the other.

What Is Point Cloud Modeling Used For?

Point cloud modeling has several uses in construction and engineering projects. You might need to create a point cloud for the following:

• Surveying: Point cloud modeling can quickly and cost-effectively produce representations of roads, bridges and other complex structures.
• Earthworks projects: Earthworks projects, such as excavating to produce a new road or lay pipe, can also benefit from the use of drones or aerial vehicles and point cloud modeling. Point cloud modeling allows your company to keep tabs on a project without visiting the site in person. It can also help improve worker safety on-site.
• 3D models: Point cloud modeling also allows for the construction of more accurate 3D models for a project. The data captured during point cloud modeling allows you to accurately identify and distinguish objects in the area so you can create a precise representation.

Benefits of Point Clouds

If you need to create a 3D model for an engineering or construction project, using point cloud modeling offers multiple benefits:

• Accuracy: A point cloud model is an accurate representation of an object or area. Both photogrammetry and LiDAR allow you to capture enough information to produce a detailed, correct model of a particular area.
• Ease of budgeting: Since the process of capturing information for point cloud modeling is so accurate, you can develop a budget for your project without too much concern about going over or spending more than you can afford. Point cloud modeling also minimizes the risk of mistakes, meaning you will spend less time and money on correcting errors. You will also save time on your project, which translates to cost savings.
• Efficiency: Point cloud modeling is a much more efficient process of building a 3D model, especially when compared to the time and effort it would take to create 3D models by hand. Increased efficiency means your project gets off the ground and can be completed sooner rather than later.

What Are Depth Map Sequences?

A point cloud lets you see every data point used to create an image. A depth map gives you a view of the data points from a particular angle. Another way to look at a depth map is as a 2D image that has been manipulated to look like a 3D image. A depth map has information on the distance between objects in a picture. It’s often shown in grayscale.

After the creation of a depth map sequence, the grayscale image is usually merged with the initial photo. Combining the two creates a third picture that looks 3D.

How to Create a Depth Map Sequence

To create a depth map, you start with a 2D image. Since the goal is to turn a 2D image into a 3D one, the source image must have several layers. Ideally, the starting photo will have a background, middle ground and foreground. To produce the depth map, you’ll need a photo and an image-editing program, such as Photoshop.

Start by selecting areas of the foreground, using the magic wand or another selection tool to trace them. After tracing each section, create a layer. Once you’ve selected and created the layers for the foreground, select the part of the image that makes up the middle ground. After that, select the section of the photo that will be the background.

After selecting and creating the layers for your 3D image, grayscale each layer. The layers in the background should be a darker gray than the foreground layers, which should be the lightest gray. You might find it easier to work if you grayscale the image before you begin cutting out the layers.

Once you’ve produced the grayscale image, you’ll merge it with the original picture in the photo editing tool. The overlap of the two images produces a photo that looks 3D.

What Are Depth Maps Used For?

One use of a depth map sequence is to create 3D advertising images. Another use is for producing 3D models for engineering and construction projects. Compared to a flat image, a depth map lets you see what is around or behind objects in a picture, providing you with a more accurate presentation of the area.

Point Cloud Modeling vs. Depth Map Sequences: Similarities and Differences

The primary feature that point cloud modeling and depth map sequences share is both use images to transform data into 3D models. The two methods give you a way to view information.

One of the differences between depth maps and point cloud modeling is the image’s viewpoint. A point cloud lets you see every point. A depth map only gives you a view of the points visible from a particular angle.

Another way to look at the differences between a depth map and a point cloud is to consider the image’s dimensions. Cartesian coordinates include an X-axis and Y-axis, which intersect each other perpendicularly. X and Y axes are all that is needed for 2D images.

When an image is 3D, there’s also a Z-axis, which intersects the X and Y axes and runs vertically. X and Y are horizontal. With a point cloud, you can see the image from all three axes. In contrast, a depth map only gives you the information found on the Z-axis.

Work With a Data Modeling Expert

Your project’s success depends on what you do with your data. The team of experienced engineers at Take-off Professionals (TOPS) can transform your data into a working 3D model. All you need to do is send us your plans and the CAD files and we’ll take care of the rest. To learn more about our services and the benefits of working with data modeling experts, get in touch with us today.

Contact Us Today

Handling ALL That Data

by Marco Cecala | Dec 14, 2020 | Resources

UPDATE: Chasing Perfection on Civil Sites

by Marco Cecala | May 13, 2020 | Resources

Future of Surveying Technology

by TOPS Marketing | Dec 23, 2019 | Resources

From the ancient wonders of the world to the modern buildings we inhabit today, surveying technology has been helping us measure for thousands of years. We’ve come a long way from the rope stretchers of ancient Egypt, but land surveying technology is still evolving. Like every industry, the future of land surveying is set to change in the coming years. Between an increase in drone usage, improvements in mobile 3D mapping and changes in data management, surveying has many developments ahead of it. The trends have implications for the industry that can improve data collection, change data storage approaches and offer more accessible and flexible information gathering.

Today we’ll be going over what the future of land surveying technology looks like and what some of the top land surveying trends are shaping up to be.

The Use of UAVs

Unmanned aerial vehicles (UAVs) have become more and more accessible and affordable, making them great additions to a surveyor’s arsenal. Before their widespread availability, they were often thought to be cost-prohibitive for many applications and were reserved for military use. Now, they offer several advantages over both terrestrial surveying teams and manned aircraft. Drones can:

• Cover large surface areas in a short amount of time
• Cross difficult terrain
• Take detailed images of hard-to-reach landscapes
• Accomplish land surveys, photogrammetry, 3D mapping, topographic surveying and more

Traditional methods often couldn’t complete these tasks, whether due to complex terrain or the sheer amount of time it would take with land-based approaches. Surveyors can now get their aerial data quickly and accurately with modern drones. UAVs also make the job safer, so human operators don’t need to fly over or enter hazardous environments to take measurements. Drones are becoming standard, less of a “bonus” and more of a necessary component of landscape businesses. Using them may soon become an industry standard.

Drones are also often used for cadastre, opening up a significant area of use. In addition, they can provide data that integrates with computer-aided design (CAD) software to build models for land development and management. Another benefit of drone usage is that it can provide a variety of photos for recording land data and structures.

Some other forms of data that you can collect from drones include:

• 2D Orthomosaic maps: Stitch together photos from a drone to create a top-down aerial view.
• 3D Orthomosaic maps: Stitch together images to compile a 3D birds-eye view of a space.
• 3D models: Create detailed models from powerful mapping software.
• Thermal maps: Record and identify abnormal heat signatures in an area.
• LiDAR point clouds: We’ll talk more about LiDAR in the next section, but drones can help you create a high-density point cloud for use with this system.
• Multispectral maps: Data outside the visible light spectrum can offer a variety of uses, including missile detection and satellite imaging.
• Building information modeling (BIM): Combine high-resolution 3D programmatic or laser models with pre-made BIM objects. This information can help to identify variations and respond accordingly.

When it comes to achieving the greatest possible accuracy, drones can use additional tools, like real-time kinematics (RTK) and post-processing kinematic (PPK) positioning. Both are positioning techniques that can improve the precision of the data using information from satellite-based systems.

Mobile 3D Mapping

Mobile mapping systems can provide extremely detailed images in a short time. They are flexible and allow you to create 3D models from a wide variety of environments. Indoor, outdoor and underground areas can all be extensively detailed with mapping technology.

It is fairly straightforward to collect geospatial data and use software solutions for fast and simple mapping. Surveyors can create digital replicas without cumbersome equipment or the need to wait hours to see the results. Versatile equipment options, handheld devices and aerial recording make mobile 3D mapping a viable and effective approach for many land surveyors. Many of the sites a surveyor visits can be dangerous or difficult to access. While they could spend valuable time and money trying to get into the area on foot and use traditional terrestrial tools, a more efficient option would be to use a UAV. Plus, this method keeps them out of any treacherous terrain. Similarly, if a surveyor needs to make a model of an extensive area, they can attach their recording devices to a vehicle and move through the site this way, offering a less physically taxing job and a faster result. These methods require very little training and are easy for new users to operate.

Mobile 3D mapping is available without the use of GPS and in durable, splash-proof products, offering additional flexibility. This kind of product can help you map out hard-to-reach places, whether they are dark, dank or dangerous, through several different methods. Tools are often made to be light and portable for ease of use.

One of the most notable benefits of this kind of mapping includes real-time, instant results. You can transform your data into 3D visuals quickly, reducing the time it takes to see results. 3D-mapping software also tends to offer robust organizational features, such as bundling data into projects and managing single uploads automatically. This organization can extend to mobile devices, including apps and third-party plugins. Some even provide features such as automated measurements, asset inventory workflows, face blurring and more to offer more of an all-in-one approach.

Data Accessibility

Another growing piece of technology is LiDAR, a form of 3D laser scanning. LiDAR stands for Light Detection and Ranging and uses a pulsed laser in ultraviolet, visible or near-infrared light to measure variable distances to the ground or nearby objects. The machine is composed of a laser, a special GPS receiver and a scanner, and they usually utilize airplanes and helicopters to gather their data across large areas. This remote sensing method collects information from the light pulses and other data collected from the aerial system to create detailed 3D models or gather survey information about the physical characteristics of the Earth.

There are several different types of LiDAR, including:

• Terrestrial: This type of LiDAR maps the Earth’s surface through topographical measurements that are mounted on the ground. Surveyors can map 3D-point clouds from the scanner with digital images to quickly make realistic 3D models. It can bypass the cumbersome tasks of measuring each item, like power lines, bridges, trees and more that may be in an area.
• Bathymetric: Bathymetric LiDAR measures elevations of riverbeds and seafloors with the help of a green light that penetrates water and its reflection back to a sensor. The measurements are typically taken from the air.
• Airborne: A laser scanner can be attached to an aircraft and used to create a 3D-point cloud model of a landscape. It is detailed and accurate, helping to create digital elevation models (DEM) and digital surface models (DSM).

This system provides a new level of precision and flexibility to the measurement of both organic and manmade structures. It may also pave the way for the automation of vehicles and assisting in lunar-landing vehicles. LiDAR is growing in use in a wide range of applications:

• Agriculture: Topographical data from LiDAR can help identify patterns of sun exposure, insect behavior and features in the landscape to improve farming tactics.
• Archaeology: Archaeologists use LiDAR technology to help plan field campaigns, map features under tree cover and create DEMs of archaeological sites for more detailed images. For instance, in 2013, it was used to rediscover the city of Mahendraparvata in the Cambodian mountains.
• Atmosphere: LiDAR is used in meteorological applications to provide information on surface pressure, greenhouse gas emissions, fires and photosynthesis. It can measure backscatter from the atmosphere and reflections that scatter off a hard surface.
• Physics and astronomy: LiDAR can help measure distances and the position of the moon and create topographic information about other planets.
• Wind farms: LiDAR can measure wind speeds and turbulence to help optimize the performance of wind farms.

One of the major benefits of LiDAR is that it offers real-time point clouds. Not all systems have this option, but many do. This feature can provide significant advances in the way of speed and accessibility, making projects more flexible and efficient.

As LiDAR systems become less expensive and more accessible, they are likely to be more common in survey projects.

Outside of LiDAR, general data accessibility is likely to improve, as more advanced tools become more affordable. Products that were previously reserved for only the most prestigious of tasks, like those in the military, will become more commonplace and may even become industry standards.

Cloud Storage of Data

As scanning technologies have become more complicated and advanced, they have started to create more data. All of that data takes up valuable space and can quickly become a burden on the IT capabilities of land surveying organizations. Many of them don’t have the storage infrastructure to support such a growing amount of information in a physical, on-site data center. To remedy this, many companies are turning to cloud storage, in which data is kept off-site, in a secure location and managed by a third-party company. Often, these companies offer high levels of security with dedicated experts working around the clock to protect their clients’ data. Most importantly, it takes the burden of finding space for the data away from the survey companies. They can spend less time worrying about the security of their information and more time working on projects or investing in better equipment.

These survey organizations have to store data for thousands of projects, and they can repeatedly outgrow their capacity as they accumulate more projects and business. Cloud storage is scalable and allows land survey companies to leave the issue of storage capacity to their servicer. Storage infrastructure can be costly and time-consuming, so many organizations are aiming to offset these problems and let someone else manage their information. Similarly, processing power can also be scalable. Some point-cloud software uses significant amounts of processing power from an off-site cloud center to deliver high-demand results to the user. The option to beef up power when needed is often appealing to surveying companies.

Another reason that many companies are moving to cloud-based storage is for the ability to share and access data more easily. Cloud storage eliminates the need to send files, which is essentially copying and redownloading them, often resulting in duplicates or creating unnecessary data. As well as taking up extra space, this can lead to misinformation or outdated files. With cloud storage, users can instead access the same data, and they can do so from a variety of devices wherever they have a connection. In-field access is an excellent tool for surveyors, offering them the ability to upload scans and view data as needed while on-site.

Here are a few more reasons companies are moving to the cloud:

• Manageable costs: Startup costs for extensive data storage can be high, but many cloud data servicers run off of subscription models. This approach can make the service more affordable and predictable for land surveying companies, but it would also be a monthly cost rather than a capital investment. Organizations will have to decide if that approach is right for them.
• Reduced maintenance: Surveying companies don’t have to worry about updating or installing local software and may save on IT costs and time. Plus, they receive the help of dedicated digital storage professionals to keep an eye on things.
• High power: Some organizations need to run robust programs to read and analyze their data, which may take ages on a local computer. Cloud-based software can offer higher-powered programs that may be able to get the job done quicker.
• Automated scans: Some programs can automatically start registering scans into a composite point cloud as they are uploaded. This approach can speed up the process and even help surveyors access completed point cloud data from the worksite.
• Collaboration: Many surveyors have to work with a variety of partners, including contractors, engineers and other stakeholders. Cloud services make sharing data with third parties much more straightforward than before. Surveyors, management, engineers, clients and more can share information quickly and with controlled permissions, improving collaboration between parties. Surveyors can ensure that only those who need access can view the data, as well.

Though cloud-based storage is a powerful tool, it can change the way organizations operate. For those using massive amounts of data, costs can add up. Surveying companies must crunch the numbers and analyze their unique needs to find out if cloud data is right for them.

Work With Data Modeling Experts

For your data modeling needs, Take-Off Professionals has been creating accurate 3D models for over 20 years. Whether you are a contractor or surveyor, we can provide fast and accurate quotes for 3D machine control models.

When you work with us, you work with industry experts. Our team of licensed engineers, surveyors and 3D technicians ensures that we stay up to date on the latest technology and industry trends in land surveying. Whether its the ease of use and versatility of UAVs, the flexibility of mobile mapping or the changes in data storage, you can be confident that our staff is up to date on these topics and whatever comes next for the future of land surveying and surveying technology.

Learn more about our data preparation, quantity takeoff, and GPS machine control modeling services!