Using Collector for ArcGIS and Python to Improve Results for the Ports for National Defense Program

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Esri®’s Collector for ArcGIS was implemented for the Ports for National Defense (PND) program in September 2017, increasing accuracy with geographic information system (GIS) data collection. For 17 years, GeoDecisions has supported the PND program and GIS services for the United States Transportation Command (TRANSCOM) and Military Surface Deployment and Distribution Command Transportation Engineering Agency (SDDCTEA). Annually our team visits commercial and military seaports throughout the U.S. to update PND data used for military planning in the event of a large-scale military deployment. Each visit required up to 5 maps per port and multiple staff, to accurately capture the needed GIS data. In 17 years, more than 4,000 maps were used for this project! Using paper maps required additional resources and time – comparing and understanding handwritten marks and duplicating efforts to capture features on-site and again on the computer. By utilizing Collector to verify and analyze the data, information can be collected on-site and in real-time, making printed maps a thing of the past and meeting our commitment to conserving natural resources.

Collector for ArcGIS

A new way of collecting the required GIS data was needed. After researching options and security concerns in 2015, our team chose Esri’s Collector. Collector advantages included the ability to pan in and zoom out on the maps, add and update data in real time, attach site visit photos to features, and negate the need for printed maps. Because of the sensitivity of the data, Esri’s security settings had to go through rigorous testing before we could implement the technology. In September 2017, we began to use Collector.

Implementation

Collector is used on-site by the team members to capture specific infrastructure notes, photographs, and geospatial data such as longitude and latitude points in real time. The application allows us to reconcile any inconsistencies while still at the seaport.

There is more to this implementation than simply using Collector. Once the data is uploaded to the geodatabase, we use a tool we created with ArcPy, a Python site package that provides a better way to use Python coding language to perform geographic data analysis, data conversion, data management, and map automation. This tool checks attribute names across the different features, verifying that the infrastructure items entered on site using Collector were spelled correctly, in the right locations, and formatted correctly to match the client’s geodatabase features. Another tool, found in ArcMap 10.6.1, was used on the geodatabase to make sure the client’s topography rules were followed. Specific berth dimensions and boundaries are examples of topography rules. This tool would also identify where there were problems.

One more improvement included the creation of custom imagery. We purchase satellite imagery from DigitalGlobe™, allowing us to have timely, date-stamped images for several of our projects. After pre-processing these satellite images, they are uploaded to ArcGIS Online in order to work with Collector. This gives us the most accurate satellite images to work from, which is essential to this project.

Using Esri’s Collector for ArcGIS, custom satellite images, and verifying data with Python-based tools have improved time, efficiency, and accuracy for the PND program.  

We have a limited amount of time during each of our seaport visits for our contractor to obtain all of the GIS information that we need and collect it accurately. By using Collector, we can be assured that those data needs are captured correctly but also efficiently, which ultimately improves the quality of our written reports and at the same time being environmentally friendly.
— Matt Mulchek, Operations Research Analyst SDDCTEA, USTRANSCOM JDPAC