{"uid":"cap_HQF7GFpNekLKETqxx-ipJ","slug":"tree-canopy-record-quality-audit-and-two-measure-correlation-0a516ed9","name":"Tree Canopy Record Quality Audit and Two-Measure Correlation","description":"Tree canopy observations — Record quality audit + Two-measure correlation: Record quality audit + 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-17-015?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}}},"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_x60JxOTVITOFdYHMsCfU9","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":"Audits quality of tree canopy observation records and computes correlation between canopy_m2 and plot_m2 measurements for up to 200 rows.","exampleAgentPrompt":"Can you audit the quality of these tree canopy observation records and also check how correlated canopy_m2 is with plot_m2? I have 4 rows: row-1 on 2026-10-01 with canopy_m2=10 and plot_m2=1 from group-a, row-2 on 2026-10-02 with canopy_m2=20 and plot_m2=2 from group-b, row-3 on 2026-10-03 with canopy_m2=15 and plot_m2=3 from group-a, and row-4 on 2026-10-04 with canopy_m2=30 and plot_m2=4 from group-b.","exampleUseCases":[{"title":"Pre-analysis data quality check","prompt":"Before I run any models, can you do a quality audit on my tree canopy dataset and tell me if any of the canopy_m2 or plot_m2 values look suspicious? I have 50 rows from station groups north-1 and north-2 collected in October 2026."},{"title":"Correlation check for field survey","prompt":"I collected canopy area and plot area measurements across 120 field sites — can you compute the correlation between canopy_m2 and plot_m2 and also flag any records that have data quality issues? The rows span station groups A through D and dates from 2026-09-01 to 2026-09-30."},{"title":"Vegetation monitoring data validation","prompt":"We just finished a vegetation monitoring survey and I want to run a record quality audit plus a canopy-to-plot correlation report on all 200 observation rows before handing the dataset off to the research team."}],"resultDescription":"Returns two analytical reports: (1) a record quality audit identifying missing values, outliers, or format issues across the supplied canopy observation rows, and (2) a statistical correlation analysis between the canopy_m2 and plot_m2 fields. No external data is fetched; all analysis is performed locally on the supplied rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, canopy_m2, plot_m2) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Null values in both canopy_m2 and plot_m2 across all rows may prevent correlation computation","Payment of 0.01 USDC not provided or rejected via x402 protocol"],"whenToPreferThis":"Choose this endpoint when you have tree canopy observation records with canopy_m2 and plot_m2 columns and need both a data quality audit and a two-measure correlation in a single low-cost call. It is best suited for offline, batch-style analytical checks on up to 200 rows of supplied data where no live data lookup, prediction, or external enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:27.282Z","isFirstParty":false,"canonicalSlug":"tree-canopy-record-quality-audit-and-two-measure-correlation-0a516ed9"}