SymGEO is proud to announce a new project with the Virginia Department of Transportation (VDOT), designed to explore the use of remote sensing techniques in the identification of wetlands. Traditional wetland delineation requires expert field work, which includes many hours of travel, sampling, and precise survey measurement to delineate what can actually be quite a variable environmental boundary. The best indicators of wetlands tend to be the vegetative species, ground elevation, and hydrology connectivity. Soil sampling and other methods are used to further validate findings, but in today’s data-rich environment, a pretty good indication of wetlands can be gathered through remote sensing.
For this project, LiDAR elevation information was combined with multi-spectral imagery to produce a 6-band composite image using ArcGIS Pro. This composite image was then used in conjunction with National Wetland Inventory (NWI) data to establish training sites for a supervised classification algorithm.
Once a suitable number of training sites were established, the supervised classification algorithm was run on the pilot study area. The results were compared with the National Wetland Inventory data, and a substantial improvement in boundary alignment was noted. This is critical in the accurate measurement of potential impacts to wetlands during road construction or property development, so that an equivalent, mitigating wetland area can be created elsewhere.
It was noted that upland forested areas were sometimes identified as wetland forested areas, indicating that elevation relative to nearest water needs to be included in the classification algorithm. The classification results are currently used as a guide for semi-automated wetland area delineation, but we believe the model could mature to include all required factors and accurately, automatically delineate the wetlands.
If you have supporting data and a need for efficient wetland delineation, SymGEO would love to talk!
I admit, I resisted for years. Workflow automation seemed like too much work to set up, and I always argued that my spatial data challenges were mostly one-off unique situations that weren’t conducive to setting up a workflow. Until one recent day I saw the light… and I blame California.
Perhaps you remember our work to incorporate near real-time remote sensing into crop drought monitoring? Well, it turns out that to keep an application like that up to date, the same process is needed time and again, and so the need for data automation was born into the world of SymGEO. Through automation, data layers and attribute fields are always named the same, and features can be over-written without fear of “something breaking” deep within a configurable application. There is also the added benefit of incorporating the usual workarounds that go into regular behind-the-scenes geospatial work such as calculating areas as acreage, or converting grid values into meaningful text. This saves countless hours of frustration and memory searching down the road when trying to repeat a process.
Needless to say, this does cause a model to expand once all the pieces are bolted on, but Esri’s ModelBuilder allows the easy configuration (and re-configuration) of the model until all works as designed.
This model has been run many times to make sure all products worked as expected, especially during initial configuration. However, the time savings was considerable with workflow automation given the number of steps involved and the dependency on intermediate layers. In hindsight, it seems to be the finding and configuring of the tools that takes time, not the actual running of the tool.
These work products were used to produce and optimize the Crop Drought Status dashboard, which is now ultra-responsive and designed for use at the county-level.
If you’d like a second pair of eyes on your data workflow, let us know, as SymGEO is ready to automate with ModelBuilder!
Do you have a mobile workforce in charge of inspecting, maintaining or interacting with assets? Watering trees, inspecting signs, putting up flyers, or targeted fundraising activities? If so, there is a new technology from Esri called Workforce that has your name all over it.
Beginning with asset data hosted in ArcGIS Online, a series of filters and queries can be used to determine which assets need to be assigned to your workforce. These might be assets over a certain age due for inspection, or locations where an issue has been reported. Assignments are made to named individuals in your ArcGIS organization, and contain information including location, priority level and due dates.
The assignments are then pushed to the mobile devices of your workforce, where they accept, navigate to, and complete the assignments. This may entail entering in notes, or taking pictures, and updating the assignment status. This information is sent back to the centralized cloud-based ArcGIS Online database in near real-time in a connected environment, or upon data synchronization if out of cell / wi-fi range.
Back in the office, the workforce administrator can use the information to check worker progress, see current worker status and location, and re-allocate resources if needed. The information is easily aggregated and displayed using a dashboard or configurable web application.
If you’d like a hand getting set up, let us know, and SymGEO will put Workforce to work for you!
SymGEO is pleased to share a glimpse into what’s possible using near-real time satellite sensor data and the power of GIS to produce a Crop Drought Status dashboard. In this example, we have used vegetation drought status and intersected it with crop data for a county in California to determine which crop types and how many acres are at risk. The vegetation drought data is available on a weekly basis nation-wide at relatively fine granularity with approximately a one week production lag-time, so it provides a very current glimpse into the on-the-ground situation.
This information could be used by farmers or irrigation districts for the planned allocation and distribution of water resources, leading to better decision for our agricultural industry. It could also provide insight into crop prices or forecast yields based on existing or modeled conditions.
The data was processed in ArcGIS Pro to convert the satellite data into usable classifications and then intersect the drought conditions with the crop type data. Be sure to learn more about how the processing was automated using Model Builder! Once processed and symbolized, the data was then published and hosted in ArcGIS online, from which the dashboard was constructed. Charts and numerical summaries update interactively based on the map window extents, and the two map views are synchronized to allow side-by-side comparison.
Check out the Crop Drought Status dashboard today and let us know what you think!
Ever wonder where the earners live? Looking for that link between education and income? Want to see how your community stacks up against the neighbors? Use SymGEO’s US Income Explorer to visualize and explore American Community Survey data from the US Census Bureau combined with income and benefit data published by the Internal Revenue Service, all delightfully symbolized using a novel “firefly” cartographic style recently published by Esri.
As explained very eloquently by Lisa Berry, a Cartographic Product Engineer at Esri, the symbology for the ACS data tells a very visual story by showing the predominant category for each data point, proportionally sized to the number of reporting households, and then given the brightness according to how dominant that category is compared to the other categories.
There’s a lot of data being calculated interactively to summarize only what’s shown in the visible extent. This allows a comparison between different areas within a state or around the country to be achieved relatively easily. Clicking on the map points or county areas shows a pop-up with detailed data, allowing a deep dive into the characteristics of select areas. A number of different ACS data layers can be turned on or off using the “layer” stack icon in the map viewing window.
The sharp geographic divides in neighborhood area characteristics can be quite shocking, and hopefully the presentation of this aggregated data by SymGEO will lead to productive discussions on how communities can work together to lessen those differences.
SymGEO is pleased to share a free and interactive Global Water Risk Dashboard to help inform policy decisions on water risk and spark international discussion around the world. Powered by Esri technology, this configurable application is based on population data provided by CIESIN, overall water risk data from Water Resources Institute, and country boundary data from GADM.
From WRI: “Overall water risk identifies areas with higher exposure to water-related risks and is an aggregated measure of all selected indicators from the Physical Quantity, Quality and Regulatory & Reputational Risk categories. Physical risks related to quantity identify areas of concern regarding water quantity (e.g. droughts or floods) that may impact short or long term water availability. Physical risks related to quality identify areas of concern regarding water quality that may impact short or long term water availability. Regulatory and reputational risks identify areas of concern regarding uncertainty in regulatory change, as well as conflicts with the public regarding water issues.”
These data sets can be explored in detail in the WRI’s Aqueduct application.
The data was processed in ArcGIS Pro to aggregate the number of people in each country by overall risk category using zonal statistics. Once processed and symbolized, the data was then published and hosted in ArcGIS online, from which the Operation Dashboard was constructed. Charts and numerical summaries update interactively based on the map window extents, and clicking on a country of interest reveals detailed overall water risk data for that country.
Check out the Global Water Risk Dashboard today and let us know what you think!