Monitoring A Large-Scale Construction Project Using Land Use Change and Object Detection Algorithms (Part I)

How geospatial analytics can help you see changes that were unseen in the past with Facility Intelligence

Introduction

Modern leaders face many challenges that confront businesses today. Whether it is changing consumer habits, emerging competitors, supply chain disruptions, global economic volatility, climate change, or military conflict, leaders are often blind to changes that could impact their operations. In a world where there is more data than ever before, it is critical to develop new methods and tools that can combat these forces, meet your organizational goals and ensure you are on a path to success.

Geospatial analytics can help businesses make smarter decisions. Leaders can answer business-critical questions because they can see everything in near real-time. Advanced analytical solutions such as Facility Intelligence enable you to monitor your strategic assets and customer or competitor’s infrastructure to know how changes will impact your business. This two-part blog series will demonstrate how geospatial analytics illuminates the supply chain to bring ground truth to changes you think might affect your business. 

The LNG Industry

The global consumption of natural gas has increased drastically over the past century. Gas to Liquid (GTL) technologies have made it possible to convert natural gas to a liquefied state, allowing for easier transport to global consumers. The supply of Liquid Natural Gas (LNG) is constantly in flux. Leading producers of LNG, such as the United States and Qatar, have altered their domestic production capacity to accommodate increased domestic and global demand. 

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Cheniere's article this past February (2022) detailed the completion of a 6th liquefaction train at Cheniere’s Sabine Pass, an LNG export terminal located on Louisiana’s Gulf Coast. A liquefaction train consists of industrial components that process, purify, and convert natural gas into a liquefied state (LNG). The train’s completion means the terminal can now produce up to 30 mtpa (million tonnes per annum) of LNG, making it the largest LNG terminal in the world. The train construction began in 2019, and completion of the terminal has been highly anticipated. 

Without tools to gain visibility outside of the news and other media, industry stakeholders were unable to track construction progress over time, and were left to guess at crucial questions: 

• When did construction begin, and when did it finish? 
• How does the increased capacity from Train 6 influence operations and production at the plant itself? 
• Can we detect a change in patterns at the plant when the train goes online? 

It is not always possible to answer these questions using just the news. And that’s where geospatial analytics comes in.

Geospatial Intelligence Process

Using the Orbital Insight geospatial intelligence platform, LNG consumers, stakeholders, and investors have the power to gain insights about Sabine Pass Train 6 on a granular level. It starts with the most simple questions - Where exactly is Sabine’s new liquefaction train, and what is the construction timeframe? Once the when and where of construction are determined, monitoring the areas of interest (AOIs) can begin. From a geographic perspective, an AOI is simply a boundary or polygon drawn by a user on the map. There is no limit to how large or small an AOI can be, as size mainly depends on how large or granular a user wishes their results to be. Running algorithms on Macro AOIs provide insights on a large scale.

An example would be drawing a polygon around the entire Sabine LNG Terminal. In contrast, running algorithms on micro AOIs will elicit results at a more refined level. Examples of micro AOIs might include employee parking lots or small buildings. The initial analysis results help develop a baseline operating picture at the plant—and the opportunity to ask more questions and developing an understanding of when and where leads to insight into the how and why. 

The first step is to determine the location of Sabine Train 6 and monitor physical construction and other related activities over time. A user can do all of the above by analyzing changes to satellite imagery, land use, and geolocation data sourced from connected vehicles. 

Running Algorithms 

Various news articles mention that construction on Train 6 began in June 2019 and got done in February 2022. This information indicates the relevant time range to analyze. The Land Use algorithm, which uses satellite images to detect critical changes to the earth during a specified period, can be run across the entire LNG Terminal during that time range. The results will show changes categorically and what images were used in the process. Figure 1 shows the results of the land use algorithm at the beginning of the project.

Figure 3: Time Slider Shows Creation in Progress | The visualization above shows a zoomed-in view of Sabine Train 6 and details changes to the land over the fixed interval. Notice the changes that occur to the buildings and roads throughout construction. Notice that the number of buildings is never fixed. When construction begins, the site is bare. As workers stage the site, roads are constructed, and temporary buildings are placed to accommodate the movement and planning. Some of these assets are removed closer to construction completion, as they are no longer needed.

Don't miss Part 2...

In the second part of this blog series, we will apply Orbital Insight’s object detection algorithms to analyze vehicle traffic and discuss the combined results. Read on to learn more.

More to explore...

• Facility Intelligence offers comprehensive visibility at any industrial facility to identify change, mitigate risk and gain operational insights
  
• Download the eBook, 7 Keys to Your Supply Chain Success, and see how customers like Unilever, Celanese, BP, and others, are using geospatial analytics to gain Supply Chain Intelligence