GIS overlay analysis vs. satellite-based parcel screening

A land acquisition manager scoping a new region usually starts the same way: pull parcel boundaries from the county GIS portal, lay a slope raster over them, add the NLCD land-cover layer, drop in the FEMA flood layer, and start eliminating parcels one by one. That's GIS overlay analysis. It's the standard method, and it works. It's also the part of the job that eats a week before anyone's even scheduled a site visit.

Satellite-based parcel screening does the same elimination, but it skips the manual stacking. Instead of an analyst opening ArcGIS or QGIS and building the overlay by hand, high-res multispectral imagery gets run against the same physical criteria, slope, aspect, size, shape, land cover, water and flood exclusion, and the output is a parcel table marked pass or fail. The difference isn't the criteria. It's who (or what) does the stacking, and how long it takes to get from "here's a county" to "here's a shortlist."

What the manual overlay actually involves

If you've done this yourself, you know the steps don't just take time, they take judgment calls that are easy to get wrong when you're moving fast across a few hundred parcels.

First there's data sourcing. Slope comes from a DEM, usually USGS 3DEP at 10m or better if you're lucky enough to have LiDAR coverage. Land cover comes from NLCD or a state-level dataset, and resolution varies enough between sources that two analysts working the same county can flag different parcels as forested versus cleared. Flood exposure means pulling FEMA FIRM panels, and if the county hasn't had a map update in a decade, you're cross-referencing against newer aerial imagery just to sanity-check the boundary.

Then comes the actual overlay. Clip each layer to the parcel boundary, calculate average and max slope, check contiguous buildable area against the project's acreage threshold, note anything that touches a wetland buffer or a 100-year floodplain. Multiply that by every parcel in a county, and a single analyst is realistically clearing twenty to thirty parcels a day if the data behaves. It usually doesn't. Gaps in county GIS layers, projection mismatches between datasets, parcels that straddle two counties with different flood maps, all of it slows the queue down.

None of this is a criticism of the method. It's the only option when the alternative is driving out to look at raw land with no idea which parcels are worth the gas money. But it's a desktop regional screen built by hand, and hand-built doesn't scale when a developer needs to clear five counties before a transmission queue window closes.

Where satellite-based screening changes the math

The physical tests stay the same. Slope still has to clear a threshold, land cover still has to be developable, flood zones still knock parcels out. What changes is that the overlay runs against current satellite imagery instead of a patchwork of county-sourced rasters and shapefiles, and the output arrives as a parcel pass/fail table rather than a set of layers an analyst has to interpret.

That matters most at the regional stage, before any single parcel has earned a site visit. A pass/fail table across a whole county does the triage work that used to take a GIS analyst a week of layer-stacking, and it does it from imagery that's current rather than whatever vintage the county's flood map happens to be. The analyst's time shifts from building the overlay to reviewing the shortlist and deciding where the landman goes next.

It's not a replacement for site-level due diligence. Geotech, title, interconnection studies, all of that still happens on the parcels that pass. The point of screening is narrowing the field before any of that spend gets committed, and a tool built specifically for that first pass is a different thing than a GIS analyst manually cross-referencing layers parcel by parcel, even though the underlying criteria overlap almost entirely.

Which one fits your workflow

If you're clearing a handful of parcels you already have under LOI, manual overlay in QGIS is fine, maybe even faster given the setup time of anything else. If you're staring down a whole county or a multi-county region and need a ranked list before you commit field time, the satellite-based pass/fail approach gets you there without the week of layer-stacking.

Solar Site Screening runs that regional pass against slope, aspect, size, shape, land cover, and flood exclusion, and hands back the parcel table.