Research Design (aaag-research-design)
The Annals spans four areas and accepts many methodologies, but is demanding about each. The design
must credibly connect the geographic argument (aaag-theory-building) to the evidence, and must take
space and scale seriously — spatial dependence, the MAUP, projection, and sampling are design
issues, not afterthoughts. This skill is mode-aware: pick the section that matches your work.
When to trigger
- Specifying identification, sampling, case selection, or measurement
- A reviewer questioned spatial autocorrelation, scale/MAUP, edge effects, validation, or a confound
- Justifying why the design adjudicates the rival account from
aaag-literature-positioning
Spatial / quantitative analysis & GIScience
- Take space seriously. Test and model spatial dependence (Moran's I, spatial lag/error,
GWR/MGWR where heterogeneity is the point); state how the MAUP / scale could change conclusions.
- Geography of the data. Document projection/CRS, areal units, edge effects, and the support of
measurements; spatial sampling and its biases.
- Inference. Cluster or use spatial SEs at the right level; for spatial autocorrelation, report
diagnostics; for prediction, use spatially-aware cross-validation (blocked/spatial CV), not random folds.
Remote sensing / physical-environmental
- Measurement validity. Sensor/resolution choices, atmospheric/geometric correction, and ground
truth; quantify accuracy (confusion matrix, kappa/F1, RMSE) with an independent validation sample.
- Process linkage. Tie observed pattern to an earth-surface process and its scale; state the
uncertainty budget end to end.
Qualitative / human-geography
- Case selection by design logic (typical, extreme, paired, regional contrast) — say what the case
is a case of. Convenience is not a rationale.
- Positionality, reflexivity, and rigor appropriate to the method (ethnography, interviews,
archives, discourse/textual analysis); state how interpretations were checked.
- Source/field transparency: plan how fieldnotes, interviews, and archives are documented and cited
(see
aaag-transparency-and-data), including consent and geoprivacy.
Nature-society / mixed methods
- Integrate, don't staple. Specify how the biophysical and social strands inform one another
(e.g., land-change observation + livelihood interviews), and how convergence/divergence is handled.
The adjudication test (Annals-specific)
For the single strongest rival explanation, write: "If the rival held rather than my argument, the
[spatial pattern / measurements / accounts] would look like ___; instead they look like ___." If the
design cannot distinguish them — including ruling out a scale or spatial-autocorrelation artifact —
it does not yet identify the contribution.
Referee pushback → Annals-specific fix
| Likely objection |
Area |
The fix |
| "Your OLS ignores spatial autocorrelation." |
Methods/Human |
Test residual Moran's I; move to a spatial model and report diagnostics. |
| "This is a unit-of-analysis artifact (MAUP)." |
Methods/Nature-Society |
Re-run across areal units/bandwidths; show stability or scope the claim by scale. |
| "Random CV overstates accuracy on spatial data." |
Methods/RS |
Use blocked/spatial CV; report the spatial structure of error. |
| "No independent validation of the classification." |
RS/Physical |
Add a held-out reference sample + area-adjusted accuracy. |
| "Convenience case; what is it a case of?" |
Human/Nature-Society |
State the case-selection logic and the population it represents. |
| "Whose voice / positionality?" |
Human |
Make reflexivity and interpretation-checking explicit. |
Calibration anchors
- Space is a design issue, not a covariate. Dependence, scale, projection, and sampling are decided
in the design, not patched in robustness.
- Each tradition on its own terms. A qualitative design is not weaker for lacking an estimand; it
needs case logic, reflexivity, and disconfirmation criteria instead.
- Mixed means integrated. Two parallel analyses are not mixed methods; specify the linkage.
Anti-patterns
- Ignoring spatial autocorrelation, then reporting OLS SEs as if observations were independent
- No MAUP/scale sensitivity when the result could be a unit-of-analysis artifact
- Classification/prediction with no independent validation, or random CV on spatial data
- Convenience case selection dressed up as theory-driven; positionality omitted in interpretive work
- A nature-society design that never actually links the two strands
Output format
【Mode】spatial-quant / remote-sensing-physical / qualitative / mixed
【Estimand or claim】what is identified/shown
【Spatial integrity】dependence / MAUP-scale / projection / validation handled? [Y/N]
【Rival ruled out】the adjudication sentence (incl. scale/spatial-artifact)
【Robustness】planned checks
【Next】aaag-data-analysis
Supplementary resources
Source: brycewang-stanford/Awesome-Journal-Skills → Annals-of-the-American-Association-of-Geographers-Skills/skills/aaag-research-design/SKILL.md
1---2name: aaag-research-design3description: Use when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and physical-environmental methods, qualitative human-geography inference, or nature-society mixed methods. The Annals judges each tradition on its own terms. Strengthens the design; it does not write code.4---567# Research Design (aaag-research-design)89The Annals spans four areas and accepts many methodologies, but is demanding about each. The design10must credibly connect the geographic argument (`aaag-theory-building`) to the evidence, and must take11**space and scale seriously** — spatial dependence, the MAUP, projection, and sampling are design12issues, not afterthoughts. This skill is mode-aware: pick the section that matches your work.1314## When to trigger1516- Specifying identification, sampling, case selection, or measurement17- A reviewer questioned spatial autocorrelation, scale/MAUP, edge effects, validation, or a confound18- Justifying why the design adjudicates the rival account from `aaag-literature-positioning`1920## Spatial / quantitative analysis & GIScience21- **Take space seriously.** Test and model **spatial dependence** (Moran's I, spatial lag/error,22 GWR/MGWR where heterogeneity is the point); state how the **MAUP / scale** could change conclusions.23- **Geography of the data.** Document projection/CRS, areal units, edge effects, and the support of24 measurements; spatial sampling and its biases.25- **Inference.** Cluster or use spatial SEs at the right level; for spatial autocorrelation, report26 diagnostics; for prediction, use spatially-aware cross-validation (blocked/spatial CV), not random folds.2728## Remote sensing / physical-environmental29- **Measurement validity.** Sensor/resolution choices, atmospheric/geometric correction, and ground30 truth; quantify accuracy (confusion matrix, kappa/F1, RMSE) with an independent validation sample.31- **Process linkage.** Tie observed pattern to an earth-surface process and its scale; state the32 uncertainty budget end to end.3334## Qualitative / human-geography35- **Case selection** by design logic (typical, extreme, paired, regional contrast) — say what the case36 is a *case of*. Convenience is not a rationale.37- **Positionality, reflexivity, and rigor** appropriate to the method (ethnography, interviews,38 archives, discourse/textual analysis); state how interpretations were checked.39- **Source/field transparency**: plan how fieldnotes, interviews, and archives are documented and cited40 (see `aaag-transparency-and-data`), including consent and geoprivacy.4142## Nature-society / mixed methods43- **Integrate, don't staple.** Specify how the biophysical and social strands inform one another44 (e.g., land-change observation + livelihood interviews), and how convergence/divergence is handled.4546## The adjudication test (Annals-specific)4748For the **single strongest rival explanation**, write: *"If the rival held rather than my argument, the49[spatial pattern / measurements / accounts] would look like ___; instead they look like ___."* If the50design cannot distinguish them — including ruling out a **scale or spatial-autocorrelation artifact** —51it does not yet identify the contribution.5253## Referee pushback → Annals-specific fix5455| Likely objection | Area | The fix |56|------------------|------|---------|57| "Your OLS ignores spatial autocorrelation." | Methods/Human | Test residual Moran's I; move to a spatial model and report diagnostics. |58| "This is a unit-of-analysis artifact (MAUP)." | Methods/Nature-Society | Re-run across areal units/bandwidths; show stability or scope the claim by scale. |59| "Random CV overstates accuracy on spatial data." | Methods/RS | Use blocked/spatial CV; report the spatial structure of error. |60| "No independent validation of the classification." | RS/Physical | Add a held-out reference sample + area-adjusted accuracy. |61| "Convenience case; what is it a case *of*?" | Human/Nature-Society | State the case-selection logic and the population it represents. |62| "Whose voice / positionality?" | Human | Make reflexivity and interpretation-checking explicit. |6364## Calibration anchors6566- **Space is a design issue, not a covariate.** Dependence, scale, projection, and sampling are decided67 in the design, not patched in robustness.68- **Each tradition on its own terms.** A qualitative design is not weaker for lacking an estimand; it69 needs case logic, reflexivity, and disconfirmation criteria instead.70- **Mixed means integrated.** Two parallel analyses are not mixed methods; specify the linkage.7172## Anti-patterns7374- Ignoring spatial autocorrelation, then reporting OLS SEs as if observations were independent75- No MAUP/scale sensitivity when the result could be a unit-of-analysis artifact76- Classification/prediction with no independent validation, or random CV on spatial data77- Convenience case selection dressed up as theory-driven; positionality omitted in interpretive work78- A nature-society design that never actually links the two strands7980## Output format8182```83【Mode】spatial-quant / remote-sensing-physical / qualitative / mixed84【Estimand or claim】what is identified/shown85【Spatial integrity】dependence / MAUP-scale / projection / validation handled? [Y/N]86【Rival ruled out】the adjudication sentence (incl. scale/spatial-artifact)87【Robustness】planned checks88【Next】aaag-data-analysis89```9091## Supplementary resources9293- [`../../resources/external_tools.md`](../../resources/external_tools.md) — spatial-analysis, GIS, remote-sensing, and CAQDAS tooling by area94- [`../../resources/official-source-map.md`](../../resources/official-source-map.md) — areas, scope, and review model9596---9798**Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `Annals-of-the-American-Association-of-Geographers-Skills/skills/aaag-research-design/SKILL.md`
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