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Challenge

Build a STAC Agricultural Drought Vegetative Loss Assessor

Quantify vegetation stress over commercial crop fields using multi-temporal STAC Catalog items. Compute vegetation anomaly percentiles across the growing season to assist in agricultural claim evidence preparation.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Quantify vegetation stress over commercial crop fields using multi-temporal STAC Catalog items. Compute vegetation anomaly percentiles across the growing season to assist in agricultural claim evidence preparation.

Agricultural Claims Investigator

Ingest field parcel boundaries and historical normal NDVI reference curves.

Query STAC API for Sentinel-2 cloud-free Item collections over the target growing cycle.

Calculate parcel-level average NDVI and compute seasonal biomass deficit percentages.

Assemble an objective crop loss claim evidence report with direct STAC asset links.

Web interface displaying parcel NDVI time-series charts alongside thumbnails retrieved from STAC assets.

Access public STAC APIs for Sentinel-2 COGs (e.g., Earth Search) or load local mock STAC collection directories. Starter examples below are synthetic. They are not downloaded records.

STAC specification Interrogates STAC Item collections, bounding boxes, and asset links for multispectral bands as specified in STAC standard.

anthropic-claude, pystac-client, rasterio. Claude analyzes complex multi-temporal vegetation anomaly trends and synthesizes objective, structured claim evidence memos. Hosted Claude API for expert-level interpretation and structured summarization of seasonal crop vigor curves.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Queries STAC Items matching parcel geometry and seasonal date range.

Calculates mean NDVI deficit compared to baseline expected reference value.

Formats output containing all parent STAC Collection IDs and asset hrefs.

```json [ { "input": { "_record_type": "simplified synthetic app record", "parcel_id": "PARCEL-KS-771", "crop_type": "Winter Wheat", "baseline_ndvi": 0.72, "stac_observations": [ { "item_id": "S2A_20230501", "mean_ndvi": 0.45 }, { "item_id": "S2A_20230515", "mean_ndvi": 0.42 } ] }, "expected_output": { "parcel_id": "PARCEL-KS-771", "mean_observed_ndvi": 0.435, "deficit_percentage": 39.58, "loss_evidence_grade": "SUBSTANTIAL_ANOMALY" } }, { "input": { "_record_type": "simplified synthetic app record", "parcel_id": "PARCEL-KS-772", "crop_type": "Winter Wheat", "baseline_ndvi": 0.7, "stac_observations": [] }, "expected_output": { "parcel_id": "PARCEL-KS-772", "mean_observed_ndvi": null, "deficit_percentage": null, "loss_evidence_grade": "NO_OBSERVATIONS" } } ] ```

Vegetative deficit reports are evidence preparation materials and do not constitute formal adjuster appraisal or claim settlement. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Vegetative deficit reports are evidence preparation materials and do not constitute formal adjuster appraisal or claim settlement. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Queries STAC Items matching parcel geometry and seasonal date range. Calculates mean NDVI deficit compared to baseline expected reference value. Formats output containing all parent STAC Collection IDs and asset hrefs.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Ingest field parcel boundaries and historical normal NDVI reference curves. Query STAC API for Sentinel-2 cloud-free Item collections over the target growing cycle. Calculate parcel-level average NDVI and compute seasonal biomass deficit percentages. Assemble an objective crop loss claim evidence report with direct STAC asset links.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Queries STAC Items matching parcel geometry and seasonal date range. Calculates mean NDVI deficit compared to baseline expected reference value. Formats output containing all parent STAC Collection IDs and asset hrefs.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Web interface displaying parcel NDVI time-series charts alongside thumbnails retrieved from STAC assets.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Vegetative deficit reports are evidence preparation materials and do not constitute formal adjuster appraisal or claim settlement.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Ingest field parcel boundaries and historical normal NDVI reference curves.

  • Query STAC API for Sentinel-2 cloud-free Item collections over the target growing cycle.

  • Calculate parcel-level average NDVI and compute seasonal biomass deficit percentages.

  • Assemble an objective crop loss claim evidence report with direct STAC asset links.

Resources and assets

Reference links and supporting material

Dataset notes

Access public STAC APIs for Sentinel-2 COGs (e.g., Earth Search) or load local mock STAC collection directories. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Anthropic Claude

LLM for code generation & more

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest field parcel boundaries and historical normal NDVI reference curves. Query STAC API for Sentinel-2 c...
  • Queries STAC Items matching parcel geometry and seasonal date range. Calculates mean NDVI deficit compared...
  • Web interface displaying parcel NDVI time-series charts alongside thumbnails retrieved from STAC assets.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 1 configured tool

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Anthropic Claude · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a STAC Agricultural Drought Vegetative Loss Assessor