Location Analysis Services

     This service identifies desirable commercial land by analyzing all parcels within a target area, filtering based on site conditions and regulatory compliance to reduce upfront time and costs, with detailed financial modeling performed later by analysts or automated valuation tools.

     Results are delivered and visualized through streamlined, mobile-friendly web maps designed for lead generation and mass LOI campaigns. For promising locations where landowners may be open to selling, we provide deeper analysis to assit with target demographics, demand potential, and development constraints.

     Our location analysis services service employs a hybrid approach, combining geospatial expertise with advanced GeoAI modeling. Human-driven decisions guide the front end, to interpret land use and territory specifics tailored to the preferences of individual land investors; these insights form the training data for the GeoAI model on the back end.

     This collaborative workflow reliably addresses fragmented regulatory data across thousands of U.S. jurisdictions and ensures validation of findings at every stage, with AI serving as an integrated, powerful analytic tool rather than a standalone solution.

     By integrating AI-assisted screening, the service streamlines the search toward practical opportunities worth pursuing, allows continuous adaptation to implement additional variables as needed, and maintains a feedback loop to reevaluate and refine the training data.

Multifamily Land Search
with GeoAI Integration

Multifamily Land Search Demo

Intended Land Use:
• Apartments, Townhouses, and Single-Family Residences (SFR)

Territory:
• All of Palm Beach County, FL (40 jurisdictions)

Preliminary Site Criteria:
• Median Household Income > $60,000
• Building Value < $2 million
• Parcel Size > 1 acre

     In August 2025, this multifamily (MF) land search demo was enhanced with two new map layers: Training Data Selected (red) and GeoAI Passed (teal), generated from a GeoAI model using the random forest approach. The model was trained on results from the original workflow and incorporates engineered features like zoning permissions, walkability to amenities, and parcel shape compactness to improve site screening accuracy.


Random Forest GeoAI Results:


Explanation:
     This analysis examines nearly 65,000 parcels larger than one acre, selected from an initial pool of almost 700,000 countywide. Of these, 42 parcels were originally identified as potentially suitable (SELECTED = 1) through initial review. The GeoAI model subsequently identified 2 additional parcels (PASSED = 1) with a probability above the 35% threshold. However, both new sites were excluded following front-end review: one was a GC-zoned property owned by the State FDOT, and the other was an RH-zoned retention pond serving an existing development.

     These particular exclusions, such as public ownership and retention ponds, could have been added to the GeoAI screening criteria. Certain real-world variables and filters, including potential multifamily sites within Planned Development designations, were intentionally excluded to keep the analysis practical and focused on clear, illustrative demonstration purposes.

     Additionally, the model’s enhanced criteria prompted manual re-evaluation of sites it did not pass, within the original set of 42 training sites. Each prediction in this model's current build is based on 355 input factors, including zoning, demographics, physical characteristics, and proximity to amenities, allowing for efficient analysis of complex land suitability criteria.

     Data sources: Palm Beach County property appraiser and P&Z data as of August 2024, and the 2020 U.S. Census.

Analysis of Development Characteristics:

Partial Site Analysis Demo

Location:
• Parcel 0263900060 St. Johns County, FL

     For this demonstration, the scope includes the subject parcel, assemblage parcels under common ownership, QL1 Lidar, wetlands, soils, DRI boundaries, AADT, and 2020 Census demographic data (block group and 3-mile median income). Parcel details are simplified for easier review, with acreage calculations for wetlands and soils included.

     This site was selected for partial analysis after standing out in the Northeast Region heat map below. It features an estimated median household income of ~$110K and is surrounded by Residential, Commercial, Retail, and Mixed-Use DRIs, along with developer-held lands. Its visible development constraints make it a useful example to demonstrate custom layers.

     A 3D site view is available via a Google Earth link in the parcel table; mobile users will need the Google Earth app. Tap the blue “Explore Earth” button once the link opens.

     Data sources: St. John's County property appraiser and P&Z data as of 5 2025, the 2020 U.S. Census, Q2 2021 DRI data from the University of Florida's GeoPlan Center, Wetland data from the U.S. Fish and Wildlife Service as of 10 2023, soils data from Natural Resource Conservation Service as of 2 2025, and FDOT traffic counts as of 1 2025.

FL Regions Heat Maps:

     A Florida regions median household income heat map series.

     An interactive heat map series that contains AADT and DRI data to serve as engaging content.

Southeast Region
Southwest Region
Central East Region
Central Region
Central West Region
Northeast Region

Next:

North Central Region
Northwest Region
Keys Region

Layers:
• Median household income > $70k
(as a heatmap @ 3 mile scale)
(note: the maps open @ 3 mile scale)
• 2 layers of DRIs by type:
1) Res, Comm, Retail, & Multi-Use
2) Ind & Power
• 2 layers of FDOT AADT trip counts:
1) 40k-60k
2) 60k+
• City/Municipal jurisdictions

     Data sources: 2020 U.S. Census, Jan 2025 FDOT traffic counts, and Q2 2021 DRI data from the University of Florida's GeoPlan Center.

Privacy:

     Spotter CRE LLC provides private, early-stage site selection and analysis results through standalone, interactive web maps. None of the work is outsourced, and users never need to log into an enterprise platform or run their own queries.

Contact:

     If you're a land investor looking for direct site selection assistance please send a message via LinkedIn to Reid Miller, using the link below.

LinkedIn

     The web maps linked on this page were created using open-source software to visualize data mining results extracted and tailored for promoting Spotter CRE LLC’s site selection services. Each map includes essential trackable identifiers.

Spotter CRE LLC does not sell software or data; this service bills only for time spent delivering customized results and passes through any necessary data costs. The primary data used is subject to the disclaimers of its original sources, which include, but are not limited to: the data should not be relied upon for property ownership or market value determinations, and no warranties are provided regarding accuracy, use, or interpretation.

© 2025 Spotter CRE LLC