GIS and spatial analysis | Knowledge Hub

Before you begin

The question

Which spatial layers are necessary for the decision—and at what scale?

Learning objectives

01Distinguish raster, vector and network representations.
02Choose spatial resolution without creating false precision.
03Connect spatial evidence to siting and logistics decisions.

Core explanation

Bioeconomy systems are spatial: feedstocks are dispersed, transport networks are uneven, land and water constraints vary, and facilities serve territories rather than abstract averages.

Raster layers suit continuous surfaces; vector features suit parcels, boundaries and facilities; network models capture travel along roads or waterways. The representation must fit the process.

Aggregation changes results. County averages can hide local scarcity, while very fine grids can imply accuracy absent from source data. Report source resolution and test sensitivity to zoning.

CONCEPTS

Key concepts

Raster

A grid of cells storing spatial values.

Vector

Points, lines and polygons representing discrete features.

Network distance

Travel through a transport network rather than straight-line distance.

Modifiable areal unit problem

Results change when spatial units or boundaries change.

MODEL

Visual explanation

How much nominal resource is reachable after distance and exclusion layers are applied? — **Supply, exclusions, infrastructure and demand become decision layers rather than one resource heat map.**Conceptual teaching visual — use it to orient the interaction below, not as measured evidence.

Explore · layer composer

Compose a GIS analysis while checking scale, provenance and spatial mismatch.

Turn layers on in decision order; the composer flags incompatible resolution or timing.

Authoritative source

layer composer4 layers active

EXAMPLE

Worked example

Illustrative worked case

From residue map to collection zones

A coarse supply layer is combined with roads, protected areas and facility candidates.

01
Exclude unavailable land and apply sustainable recovery fractions.
02
Route eligible supply through the transport network.
03
Aggregate by candidate catchment and retain resolution metadata.

Key takeaway

The map supports screening; field validation and temporal data still determine feasibility.

CASE FILE

Case file

Classic case1996

GIS-based biomass resource assessment with BRAVO

Why it is here: BRAVO is a clear historical case of GIS-mediated resource decision support.
What to inspect: Inspect data layers, aggregation and decision outputs.
Limitation: Its historic data and methods should be learned from, not copied uncritically.

DOI: 10.1016/0961-9534(95)00065-8 ↗

TOOLS

Tool in context

Core · QGIS / OSGeo

QGIS

Use it for this task: Compose, inspect and document spatial layers and transformations.
Limitation: Spatial precision does not guarantee data accuracy, causality or social acceptance.

Inputs, outputs & scope

What it is: An open-source geographic information system for viewing, managing and analysing spatial data.
Problem it addresses: Where are resources, constraints, infrastructure and people located?
Inputs: Vector and raster layers, coordinate systems, attributes and analysis rules.
Outputs: Maps, spatial metrics, buffers, overlays and exportable datasets.
Typical applications: Resource mapping, logistics, site screening, exposure and territorial analysis.

Explore the official tool ↗

Optional · LBNL / JBEI

BioSiting

Use it for this task: Inspect a purpose-built national biomass siting workflow.
Limitation: A screening map is not a permit, supply contract or deployability decision.

Inputs, outputs & scope

What it is: A geospatial platform for exploring U.S. bioeconomy resources, infrastructure and candidate sites.
Problem it addresses: What resources and infrastructure surround a candidate facility location?
Inputs: Location, buffer radius, resource layers, infrastructure and pathway choices.
Outputs: Mapped inventories, buffer summaries and downloadable spatial data.
Typical applications: Facility screening, resource context and early TEA/LCA framing.

Explore the official tool ↗

EVIDENCE

Core references

Noon and Daly (1996). GIS-based biomass resource assessment with BRAVO.https://doi.org/10.1016/0961-9534(95)00065-8 ↗
U.S. Department of Energy (2024). 2023 Billion-Ton Report: An Assessment of U.S. Renewable Carbon Resources.https://doi.org/10.23720/BT2023/2316165 ↗

Knowledge check

0 / 3

01Which statement best captures the central idea?A single laboratory yield is sufficient for every system decision.Spatial analysis is about relationships and constraints, not simply making a map.The largest theoretical value should always be selected.

02Which statement is the misconception to avoid?A high-resolution map guarantees high-resolution knowledge.Spatial analysis is about relationships and constraints, not simply making a map.A single laboratory yield is sufficient for every system decision.

03What evidence should be checked before making a decision?Only the technology nameOnly the best-case headlineSource scale, coordinate system, exclusions, network data, temporal coverage, aggregation and ground truth.

→

Key takeaway

Spatial analysis is about relationships and constraints, not simply making a map.

Common misconception

A high-resolution map guarantees high-resolution knowledge.

Evidence check

Source scale, coordinate system, exclusions, network data, temporal coverage, aggregation and ground truth.

GLOSSARY

Vocabulary in this lesson

Geographic information system (GIS)Network distance Spatial resolution