{"uid":"cap_j7Foxi5D9pWUHbfMd41Ye","slug":"tree-canopy-observations-iqr-outlier-flags-two-measure-correlation-864662aa","name":"Tree Canopy Observations — IQR Outlier Flags + Two-Measure Correlation","description":"Tree canopy observations — IQR outlier flags + Two-measure correlation: IQR outlier flags + Two-measure correlation for supplied tree canopy observations records (canopy_m2, plot_m2). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-17-176?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","canopy_m2","plot_m2"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"plot_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"canopy_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","plot_m2":1,"canopy_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","plot_m2":2,"canopy_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","plot_m2":3,"canopy_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","plot_m2":4,"canopy_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["canopy_m2","plot_m2"],"type":"string","default":"canopy_m2"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_GYm6LrZY-cEkh1qLuI6LY","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs IQR-based outlier detection and two-measure correlation analysis on supplied tree canopy observation records (canopy_m2 and plot_m2) for up to 200 rows.","exampleAgentPrompt":"I have 150 tree canopy observation records with canopy_m2 and plot_m2 measurements across several station groups — can you run IQR outlier detection on the canopy_m2 field and also compute the correlation between canopy_m2 and plot_m2 for me?","exampleUseCases":[{"title":"Urban tree survey quality control","prompt":"I've got 80 rows of urban tree survey data with canopy_m2 and plot_m2 columns from three station groups collected in October 2025 — can you flag any canopy_m2 outliers using IQR and show me how strongly canopy area correlates with plot area?"},{"title":"Forest monitoring data validation","prompt":"Before I submit my forest monitoring dataset to the review board, can you check these 120 canopy observation records for IQR outliers in the plot_m2 field and give me the two-measure correlation report between canopy_m2 and plot_m2?"},{"title":"Multi-station canopy anomaly detection","prompt":"I'm comparing tree canopy readings across four station groups and suspect a few bad measurements crept in — please run IQR outlier flagging on canopy_m2 and compute the canopy-to-plot correlation across these 60 observation rows."}],"resultDescription":"Returns two analytical reports for the supplied dataset: (1) an IQR outlier flags report identifying which rows have canopy_m2 or plot_m2 values outside the interquartile range, and (2) a two-measure correlation report quantifying the relationship between canopy_m2 and plot_m2 across all supplied rows. No external data is fetched; analysis is performed locally on the submitted records only.","failureModes":["Empty or missing rows array returns validation error","More than 200 rows submitted triggers a row-count limit error","Invalid date format (not YYYY-MM-DD) causes schema rejection","Null values in both canopy_m2 and plot_m2 across all rows may produce degenerate correlation output","Invalid field enum value returns a schema validation error","Fewer than 3 non-null rows may produce unreliable IQR or correlation statistics"],"whenToPreferThis":"Choose this endpoint when you have tree canopy observation data (canopy_m2, plot_m2) and need both IQR-based outlier detection and a cross-measure correlation analysis in a single paid call. It is purpose-built for environmental/forestry datasets up to 200 rows and delivers two bundled statistical reports for $0.01 USDC. Prefer this over general-purpose analytics APIs when your data specifically includes canopy and plot area measurements organized by station group and date.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T12:42:09.724Z","isFirstParty":false,"canonicalSlug":"tree-canopy-observations-iqr-outlier-flags-two-measure-correlation-864662aa"}