TRADE: Trash Rapid Assessment Data Exchange (ArcGIS Hub)
Trash Rapid Assessment Data Exchange (TRADE) is a publicly funded, publicly available platform designed to help community-based (citizen science) trash monitoring programs produce data that can be used by municipalities (MS4 permittees) for stormwater monitoring and reporting, including support for municipal stormwater permit compliance.
What TRADE is for
TRADE is built around a practical need in stormwater programs: generating consistent, quality-assured rapid trash assessment data at scale—often to support Track 2 / full-capture-equivalency style compliance approaches that rely on ongoing field assessments.
It aims to:
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Provide a public data exchange where trained community participants can contribute trash assessment data in a standardized format
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Offer a dashboard-style interface to visualize and download data for permittee monitoring/programming/reporting
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Serve as a replicable model platform for other regulatory contexts and geographies
Who should use TRADE
TRADE is most relevant for:
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MS4 programs that need broader spatial/temporal coverage for on-land trash condition assessment and reporting
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Watershed groups, NGOs, and community science programs that want their field observations to be more interoperable and decision-relevant
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Researchers and practitioners working on trash monitoring program design, QA/QC, or data standardization
How TRADE works (high-level workflow)
TRADE (as described in the technical literature and project documentation) supports a two-part approach:
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Field data collection using a standardized schema (including site attributes, rapid/qualitative trash condition scoring, itemized counts, and photos).
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Quality control + analytics support, including approaches that can compare/validate qualitative “Litter Index” type scores against quantitative inputs (e.g., item counts), with machine learning described as one mechanism used in the TRADE context.
Data you can expect to find on TRADE
Typical inputs
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Site/assessment metadata (location, context descriptors)
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Rapid condition score (qualitative category-based “index” style scoring)
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Itemized trash counts by material/item groupings
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Photo documentation (where collected)
Typical outputs
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Downloadable datasets suitable for analysis, reporting, and mapping
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Visualizations/dashboards to explore trends across sites and time
TRADE QA/QC and standardization notes
A core design intent of TRADE is to support consistent, quality-assured data collection appropriate for municipal reporting contexts. The project documentation explicitly emphasizes consistent formatting and quality assurance as central goals.
Practical QA/QC concepts to look for when implementing TRADE-aligned workflows include:
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Volunteer/staff training to support repeatable rapid-condition scoring
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Internal checks comparing qualitative scoring vs. quantitative inputs (where implemented)
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Photo documentation to support review/verification (when collected)
TRADE Strengths
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Bridges community science and regulatory needs for trash/stormwater programs
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Emphasizes standardized schemas and quality-assured contributions
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Designed for visualization + download, making it easier to operationalize data
Limitations and considerations
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Rapid qualitative scoring can be training-sensitive; program success depends on training/re-training and calibration practices.
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Coverage, frequency, and representativeness depend on local program design and resourcing (as with most monitoring networks).
Use cases for Plastiverse readers
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Building or modernizing a trash monitoring program (especially where data needs to support MS4 reporting)
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Creating a standardized dataset for spatial targeting of mitigation (hotspots, corridors, priority land uses)
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Supporting broader plastic/trash monitoring strategies that integrate community-based datasets as a scalable layer
Keywords/tags: trash monitoring, litter assessment, MS4, stormwater, citizen science, ArcGIS Hub, data exchange, rapid assessment, California Trash Amendments, Track 2 compliance