# Loamist Geospatial

> Compare land and logistics on one map. Multicriteria siting, from carbonizers to data centers.

Canonical: https://www.loamist.com/geospatial

A geospatial decision platform that combines multicriteria site analysis with cost modelling. Teams compare complex scenarios side by side, from carbonizer sites to data centers, with every assumption traceable to its source and access set by role.

- **PG&E, USFS**: Clients include
- **Multicriteria**: Site analysis
- **Traceable**: Every assumption
- **Role-based**: Access

## Fig. 01 · Siting a mobile carbonizer: Where to build, and whether it beats current practice.

A dot map of Northern California with seven candidate sites for a mobile carbonizer, the selected site, and the route to disposal. From the Loamist Geospatial tool.

| Transport footprint | Miles driven | Transport CO₂e |
|---|---|---|
| Carbonize @ site | 326.3 mi | 0.5 t |
| Haul to disposal | 1,384.9 mi | 2 t |

**+1,059 mi** and **+1.50 t CO₂e** saved by carbonizing at this site. Each figure traces to its source: route distances, vehicle factors, and the site inputs your team approved.

## Fig. 02 · Multicriteria analysis: Four criteria, one answer.

Four criterion maps merge into one combined suitability map. Each criterion has a weight from 0 to 10, and the map re-scores as the weights change. The top 5% of cells form the shortlist. Protected or too-steep ground is excluded. The inputs shown on the page are illustrative.

- **Slope under 15%** (default weight 5): gentler ground scores higher
- **Road access** (default weight 7): closer to a usable road
- **Fire-risk buffer** (default weight 6): further from high-risk areas
- **Feedstock within 5 mi** (default weight 8): more treatable material nearby

## Case study · PG&E · Mobile carbonizers: Preventing catastrophic wildfires.

Thinning removes the fuel that turns ground fire into crown fire. Treating that material where it lies is what makes thinning affordable at scale.

A data-driven animation shows the 2021 Antelope Fire reaching an untreated stand (dense, with low crowns) and a thinned and burned stand (treated 20 and 10 years earlier). The untreated crowns burn; the treated crowns survive.

- **60 pts**: lower probability of tree mortality in thinned and burned stands
- **86 pts**: less crown volume consumed by the fire
- **5 to 7×**: fewer trees per hectare after thinning
- **20 yrs**: thinning still limited crown fire two decades later

Source: Brodie, E. G., E. E. Knapp, W. R. Brooks, S. A. Drury, and M. W. Ritchie. 2024. Forest thinning and prescribed burning treatments reduce wildfire severity and buffer the impacts of severe fire weather. *Fire Ecology* 20: 17. [doi.org/10.1186/s42408-023-00241-z](https://doi.org/10.1186/s42408-023-00241-z)

A randomized, replicated 1,200 ha experiment on the Klamath National Forest, burned by the 2021 Antelope Fire. Figures compare thinned-and-burned stands with untreated controls. Stand drawing to scale: crown base 3 m on pole trees, 11 m on large trees.

- **The question**: PG&E clears hazardous vegetation to reduce the risk of catastrophic wildfire. Where should a mobile carbonizer go, and does treating that material on site beat hauling it to disposal?
- **What we modelled**: Candidate sites scored on slope, road access, fire-risk buffer, and nearby feedstock. Each site then carried its own transport and cost model against current practice.
- **What it showed**: At the selected site, carbonizing in place meant 326 miles of driving against 1,385 to haul the same material to disposal.

Saved at the selected site: **1,059 mi** fewer miles driven, **1.50 t** less transport CO₂e. From the Loamist Geospatial tool. Every figure traces to its route, vehicle factor, and site input.

### Same method, any siting question. Including data centers.

Multicriteria analysis + cost model.

1. **Data centers.** Grid capacity, water, fiber, land cost, permitting, and hazard exposure, weighed together.
2. **Mobile carbonizers.** Where to treat material, and whether it beats hauling to disposal.
3. **Energy and storage.** Interconnection, resource quality, land use, and environmental constraints.
4. **Logistics facilities.** Drive times, labor, road access, and lease cost against demand.

## § 01 · What it does: Every answer shows its work.

1. **Multicriteria site analysis.** Weigh terrain, access, risk, and feedstock together, then see how the ranking moves when priorities change.
2. **Cost modelling.** Each scenario carries its own cost model, compared directly against current practice.
3. **Traceable assumptions.** Every number links to the dataset, rate card, or study it came from.
4. **Role-based access.** Planners, analysts, reviewers, and sub-contractors each contribute data at their own permission level. Every tenant sees only what it is allowed to see, and nothing more is shared.

## Start

Bring a siting question. We will model it with you.

- [Book a scenario session](https://www.loamist.com/contact.html)
- [About Loamist](https://www.loamist.com/)

Loamist products: [Loamist Trade Finance](https://www.loamist.com/trade-finance) · [Loamist Geospatial](https://www.loamist.com/geospatial) · [Loamist Evals](https://www.loamist.com/evals) · [Loamist Services](https://www.loamist.com/services)