Spatial Data Frameworks

After reading this Circular, compilers will be able to establish the spatial data foundations required for ocean accounting. The guidance covers five interconnected framework dimensions: (1) selecting and documenting coordinate reference systems and map projections, (2) defining ocean boundaries for the ecosystem accounting area, (3) setting minimum mapping units appropriate to ecosystem type and data source, and the Basic Spatial Unit resolution that follows from them, (4) ensuring temporal consistency across spatial data vintages, and (5) quantifying and reporting spatial uncertainty according to recognised metadata standards.

Section 3.3 is normative for the publication on spatial resolution. It sets minimum mapping units by ecosystem type and data source, relates them to BSU side length, and gives indicative BSU resolutions by marine context. Circulars that use spatially explicit accounts refer to it rather than specifying their own resolution, and the question a planning, assessment or management process asks is whether the resolution of the available accounts is adequate to the decision at hand.

The Circular does not address ecological modelling methods used to estimate ecosystem services — those are addressed in the relevant thematic circulars. It also does not duplicate the remote sensing data acquisition guidance in TG-4.1 Remote Sensing and Geospatial Data. Instead, it addresses the spatial framework that governs how remotely sensed and other geospatial data are organised, projected, and documented before they enter the accounting system.

• TG-0.1 General Introduction to Ocean Accounts — foundational framework, including the concept of ecosystem accounting areas and the scope of ocean accounts
• TG-0.2 Overview of Relevant Statistical Standards — classification and measurement standards referenced throughout this Circular, including SEEA EA spatial unit definitions
• TG-0.7 Quality Assurance Principles — QA requirements for spatial datasets, including documentation, reproducibility, and fitness-for-purpose assessment
• TG-4.1 Remote Sensing and Geospatial Data — primary spatial data source for ocean ecosystem extent mapping, and this Circular governs how those data are projected, bounded, and documented

Helpful background:

A coordinate reference system (CRS) is the mathematical framework that relates spatial measurements — positions, areas, distances — to locations on the Earth’s surface. For ocean accounting, CRS selection affects two distinct operations: data storage and exchange (which requires geographic consistency across data sources from different agencies and countries) and area-based accounting calculations (which require area-preserving properties that geographic CRS do not provide).

SEEA EA para. 3.89 notes that a Basic Spatial Unit (BSU)-based structure enables integration of spatial data “on different characteristics and hence account for varying spatial coverage, scales and projections.”, The BSU structure therefore requires compilers to select a single, documented CRS within which all BSU-level data are harmonised before they are assigned to ecosystem assets and accumulated into accounts.

Ocean accounts face CRS challenges that are less common in terrestrial accounting. EEZs may span the International Date Line, as in the case of many Pacific SIDS, and the projection chosen must avoid the resulting data discontinuities. Maritime zones are legally defined in geodetic terms, as nautical miles from baselines, not in projected coordinates. Global and regional data products used as inputs may also arrive in different CRS that must be transformed before integration.

3.1.2 Decision rule for CRS selection

To address both requirements simultaneously, this Circular recommends a two-tier CRS approach: one tier for data storage and exchange (prioritising interoperability), and one tier for area-based calculations (prioritising geometric accuracy). Figure 2.12.1 illustrates this two-tier workflow: data stored and exchanged under WGS84 are reprojected to an equal-area projection only when extent, area, or condition calculations are performed. An ISO 19115 metadata record documents the CRS and travels with the data into the account row.

Tier 1 — Storage and exchange CRS: Use the World Geodetic System 1984 (WGS84, EPSG:4326) as the reference datum for all spatial data storage and inter-agency data exchange. WGS84 is the global standard for geospatial data interoperability and is used by GPS, most satellite remote sensing products, and the maritime boundary datasets operated by the Flanders Marine Institute (VLIZ) Maritime Boundaries Geodatabase. Data received from agencies in other CRS must be transformed to WGS84 before ingestion into the accounting data system.

• For national-scale accounts: the national equal-area projection adopted by the country’s national mapping agency (if available and documented)
• For regional and comparative accounts: the Lambert Azimuthal Equal Area (LAEA) projection centred on the study area (EPSG codes vary by centre point)
• For Pacific SIDS and other dateline-crossing EEZs: the Equal Earth projection (EPSG:8857) or a custom Mollweide projection centred to avoid the antimeridian discontinuity

Before adopting EPSG:8857, compilers should confirm that it is available in their GIS software. Older ESRI ArcGIS releases (pre-10.7) and QGIS versions prior to 3.16 do not include EPSG:8857 in their bundled CRS catalogues and require manual WKT entry. If EPSG:8857 is unavailable, a custom Mollweide projection centred on the study area (example PROJ string: +proj=moll +lon_0=160 +x_0=0 +y_0=0 +datum=WGS84 +units=m for Pacific-centred accounts) provides an equivalent equal-area property. The WKT definition used must be recorded in spatial metadata.

All area statistics reported in ocean accounts must be calculated in the Tier 2 CRS. Results should be reported in square kilometres rounded to appropriate precision for the ecosystem type and scale of the account.

The CRS used for storage, transformation, and area calculation must be documented in the spatial metadata for each dataset (see Section 3.5). The metadata record must include: (a) the EPSG code or Well-Known Text (WKT) definition of the CRS, (b) the datum transformation rule applied where data were converted between CRS, and (c) any epoch qualification if GPS-era coordinates are used. Consistent CRS documentation is essential for reproducibility and for future compilation cycles.

The transformation method and the estimated residual positional error after transformation must be documented in the spatial metadata. Where datum transformation uncertainty exceeds the minimum mapping unit — meaning the spatial offset could systematically misplace feature boundaries by more than one mapping unit — the affected datasets should be flagged in the metadata and in the account quality disclosure as requiring geodetic verification before final publication.

3.1.4 Scope note on vertical and 3D frameworks

3.2 Ocean Boundary Definitions

3.2.1 Defining the ecosystem accounting area for ocean accounts

The ecosystem accounting area (EAA) is “the geographical territory for which an ecosystem account is compiled” (SEEA EA para. 3.22). For ocean accounts, the outer boundary of the EAA is normally the outer limit of the exclusive economic zone (EEZ), which extends up to 200 nautical miles from baselines under the United Nations Convention on the Law of the Sea (UNCLOS) Parts V and VI. SEEA EA para. 3.27 confirms: “the scope of national jurisdictions for ecosystem accounting should include all ecosystems across the terrestrial, freshwater and marine realms to the boundary of the exclusive economic zone.”

The EAA must be unambiguous, documented, and consistent across compilation cycles. Any change in the EAA boundary between vintages — for example, if a country ratifies a maritime boundary agreement — constitutes a change in accounting scope and must be disclosed in the compilation notes.

3.2.2 Maritime zone definitions

The following maritime zone definitions, drawn from UNCLOS, govern the outer limits of the ocean accounts EAA and its sub-zones:

Where maritime boundaries are subject to overlapping claims or bilateral disputes, compilers should document the boundary assumptions applied and flag the relevant zones in the compilation notes. Where feasible, any disputed area should be separately tabulated to maintain transparency. The VLIZ Maritime Boundaries Geodatabase provides unilateral and bilateral boundary layers (specifically the “EEZ Boundaries” and “Maritime Boundaries” layer products available at marineregions.org). Compilers should document which VLIZ boundary layer was selected as the operational source and note any divergence between the VLIZ boundary and the national claim in the compilation notes.

For SIDS and other countries with large EEZs relative to land area, the EEZ may include deep-water ecosystems for which data are limited. In these cases, compilers may initially scope accounts to cover ecosystems within the territorial sea or to the edge of the continental shelf, with a clear statement of scope limitation and a plan to extend coverage as data improve.

3.2.3 The coastal zone landward boundary

The ocean accounts EAA also requires a landward boundary where marine ecosystems transition to terrestrial ecosystems. The coastal zone is the transitional area between marine and terrestrial ecosystems, bounded seaward by the outer limit of the EEZ and landward by a compiler-specified boundary — typically mean high water datum, a fixed elevation contour, or an administrative boundary — that must be documented and applied consistently across compilation cycles. This landward boundary is not defined by UNCLOS and must be specified by the compiler based on the ecosystem types to be included. Table 3.2.3 below summarises common landward boundary definitions.

Table 3.2.3: Common landward boundary definitions for the coastal zone

For consistency with terrestrial national accounts and land-cover data, the landward boundary should align with the boundary used by the national mapping agency for coastal zone delineation. Where no national standard exists, the compiler should adopt the MHW datum, document the choice, and apply it consistently across compilation cycles. The operational boundary layer should be derived from the VLIZ Maritime Boundaries Geodatabase (https://www.marineregions.org/) for the EEZ outer limit and from national hydrographic or mapping agency data for the baseline and coastal zone boundary.

Intertidal ecosystem assets that straddle the MHW datum — including mangroves, salt marshes, intertidal seagrass beds, and rocky intertidal habitats — should be assigned in full to the ocean EAA (i.e., the marine side of the boundary), consistent with SEEA EA ecosystem asset definitions that treat the seaward-extending ecosystem unit as the defining asset. Where national accounts or prior assessments have applied a different intertidal assignment convention (for example, assigning mangroves to the terrestrial EAA for consistency with national land-cover datasets), the convention applied and any departure from the default must be documented in the compilation notes and disclosed in the account metadata so that users can assess cross-country comparability.

3.3 Minimum Mapping Units

3.3.1 Definition and importance

The minimum mapping unit (MMU) is the smallest area of an ecosystem type that is separately identified and mapped in the account. The MMU is determined by the spatial resolution of the primary data source and by analytical requirements: a smaller MMU increases the representational accuracy of accounts but requires higher-resolution data and greater processing capacity. A single MMU must be selected, documented, and applied consistently across the ecosystem accounting area and across compilation vintages (SEEA EA para. 3.44). Features smaller than the MMU are either subsumed into the surrounding ecosystem type or excluded from the account.

3.3.2 MMU by data source and ecosystem type

The appropriate MMU depends on the primary data source for each ecosystem type. Table 1 provides recommended MMU ranges for the principal marine and coastal ecosystem types encountered in ocean accounts.

Table 1: Recommended minimum mapping units by ecosystem type and primary data source

These recommendations are indicative. Compilers should document the MMU applied, the primary data source and its nominal resolution, and any post-processing steps (e.g., minimum contiguous patch filtering) that affect the effective MMU.

3.3.3 Minimum mapping unit and Basic Spatial Unit resolution

The minimum mapping unit and the Basic Spatial Unit are related but distinct. The MMU is the smallest area of an ecosystem type separately identified in the account; the BSU is the tessellation cell to which all data — ecosystem type, condition, economic activity, governance designation — are referenced. A BSU cannot usefully resolve features smaller than the MMU of the data compiled into it, so the BSU side length should be set such that the cell area is no smaller than the coarsest MMU applied within the accounting area.

For a square BSU grid, cell area is the square of the side length: a 250 m cell is 6.25 ha, a 1 km cell 100 ha, a 5 km cell 2,500 ha. Reading against the MMU ranges in Table 1, this gives the following indicative correspondence for marine applications. These are starting points rather than prescriptions; the operative constraint in any national context is the spatial precision of the primary data sources.

Table 3.3.3: Indicative BSU resolution by marine context

Setting the cell size does not by itself determine the account. A cell on the edge of an ecosystem asset is only part-covered, and the rule for assigning it a single type moves the recorded extent independently of the data. Two rules are in use. Under dominance, the type covering the largest share of the cell takes it. Under hierarchy, the cell goes to the highest-priority type present, however small its share, following a priority order the compiler documents in advance. Figure 2.12.2 applies both to the same four cells.

Where data resolution improves — through new high-resolution imagery or expanded bathymetric survey — the grid may be refined. Any change in spatial resolution must be recorded as a methodological revision in the extent account for the relevant period, so that genuine ecosystem change is distinguished from reclassification arising from improved measurement (see TG-3.1 Asset Accounts Section 3.5.1). Countries beginning marine ecosystem accounting should start at the best available resolution and refine as data infrastructure improves.

Sensor and product resolution thresholds that constrain the achievable minimum are set out in TG-4.1 Remote Sensing and Geospatial Data. Sub-national accounting areas apply the same guidance through TG-3.11 Sub-National Ocean Accounts Section 3.1.

Once an MMU is adopted, it must be applied consistently across the dimensions summarised in Table 3.3.4 below.

Table 3.3.4: MMU consistency requirements

3.3.5 Remote and deep ocean data gaps

For ecosystems within the EAA that cannot be mapped due to data inaccessibility — particularly in remote offshore areas, deep-sea zones, and submarine terrain lacking bathymetric survey coverage — compilers must adopt an explicit gap treatment rather than recording a zero extent, which would falsely imply absence. The following rules apply:

3.4 Temporal Consistency of Spatial Layers

3.4.1 The temporal consistency challenge

Spatial data for ocean accounts are derived from multiple sources — satellite imagery, airborne surveys, in-situ monitoring, and administrative records — each with different acquisition dates, revisit frequencies, and temporal aggregation conventions. The goal of temporal consistency is to ensure that spatial data representing different aspects of the ecosystem all refer to the same reference period, so that the account reflects a coherent snapshot of the ecosystem at a single point in time.

Opening and closing stocks. Ecosystem extent is measured as of the first and last day of the accounting period (1 January and 31 December). In practice, imagery is rarely available on exactly these dates. The compiler should select the imagery acquired closest to the target date, within a temporal window of ±90 days for ecosystems with low seasonal variability, and ±45 days for ecosystems with high seasonal variability (e.g., seagrass, which exhibits summer dieback at high latitudes). The acquisition date and cloud cover of selected imagery must be documented in spatial metadata.

Seasonally variable ecosystems. Some marine ecosystems exhibit strong seasonal extent variation (intertidal seagrass beds, algal mats). Where seasonal variation is material to policy questions (e.g., monitoring seagrass recovery under marine protected area management), compilers should consider compiling both a peak-season and an end-of-season extent to bracket the annual range, and report both in the account notes.

3.4.3 Change detection and baseline years

For change detection to be meaningful, the imagery and classification methods used for consecutive vintages must be consistent: changes in sensor, classification algorithm, or MMU between vintages will produce spurious conversions that do not reflect real ecosystem change.

Table 3.4.3 below summarises requirements that compilers should follow for change detection and baseline years.

Table 3.4.3: Change detection and baseline year requirements

3.4.4 Inter-layer temporal consistency

When multiple spatial layers from different data sources are combined into a single accounting extent mosaic — for example, a mangrove layer from January, a coral reef layer from March, and a seagrass layer from October of the same reference year — the temporal spread across layers introduces a consistency risk. Apparent ecosystem conversions detected at boundaries between layers may reflect genuine land cover change or may be artefacts of the different acquisition dates, particularly for ecosystems with seasonal dynamics.

3.5 Spatial Uncertainty and Metadata Standards

3.5.1 Sources of spatial uncertainty in ocean accounts

Spatial data products used in ocean accounts carry uncertainty from multiple sources. SEEA EA paras. 2.90—2.95 identify four categories of uncertainty in ecosystem accounting: (1) uncertainty in physical measurement, (2) uncertainty in valuation, (3) uncertainty related to ecosystem dynamics, and (4) uncertainty regarding future values. For spatial data specifically, the most material sources are:

Spatial datasets used in ocean accounts must be documented using ISO 19115 as the minimum metadata standard. Implementing agencies should adopt an ISO 19115-compliant metadata catalogue — such as GeoNetwork or ESRI Geoportal — to store and serve spatial metadata alongside account outputs.

At minimum, each spatial dataset used in an ocean account must have a metadata record that includes the elements summarised in Table 3.5.2 below.

Table 3.5.2: Minimum metadata elements for spatial datasets in ocean accounts

• document the version used for each accounting vintage
• assess the spatial extent of any coverage or boundary change between versions
• disclose any resulting difference in account totals in the account compilation notes Where a national SDI or data catalogue assigns internal version codes to official spatial layers, those codes constitute sufficient version control provided they are uniquely resolvable and recorded in the data management plan.

3.5.3 Tiered accuracy reporting

In data-poor contexts, full confusion matrix reporting may not be feasible. A tiered accuracy reporting scheme, adapted from established remote sensing validation frameworks, allows compilers to document uncertainty at the level achievable given available resources:

The tier applied must be stated in the metadata record and in the account’s quality disclosure section. When accounts compiled at different accuracy tiers are aggregated (e.g., national totals from subnational accounts), the lowest tier applies to the aggregate.

A 10% underestimate in mangrove extent translates approximately to a 10% underestimate in mangrove carbon stock value (all else equal). Compilers should:

• Report a central estimate and, where feasible, a confidence interval (e.g., 90% confidence) for ecosystem extent by type.
• Document the propagation pathway in the account quality disclosure, noting which downstream accounts are affected.
• Flag monetary estimates derived from Tier 3 accuracy spatial data as provisional.

3.6 Worked Example: Spatial Framework for a Mangrove-Seagrass Complex

This worked example demonstrates how the five framework dimensions apply to a national-level ocean account for a hypothetical small island developing State (SIDS) with an EEZ of approximately 400,000 km², a territorial sea of 12 nm, and a coastline featuring mangrove estuaries, seagrass beds, and fringing coral reefs.

3.6.2 CRS selection (§3.1)

The SIDS national mapping agency uses WGS84 for all official geospatial data products. The NSO adopts:

• Storage/exchange CRS: WGS84 (EPSG:4326) — consistent with all incoming data from satellite operators and the national mapping agency
• Calculation CRS: Equal Earth (EPSG:8857) — selected because the SIDS EEZ crosses the International Date Line, and Equal Earth avoids the antimeridian discontinuity while preserving area relationships across tropical latitudes

All agency data delivered in UTM Zone 58S (EPSG:32758) are transformed to WGS84 on ingestion, with the datum transformation documented.

3.6.3 Boundary delineation (§3.2)

The EAA outer limit is the EEZ boundary derived from the VLIZ Maritime Boundaries Geodatabase. The landward boundary is defined by mean high water (MHW) derived from the national tidal model at 30-arcsecond resolution, aligned with the national mapping agency coastal zone product. Internal waters (within the archipelagic baseline) are included. Intertidal mangrove and seagrass assets that straddle the MHW datum are assigned in full to the ocean EAA, consistent with the default rule in §3.2.3. A note is added that the account does not cover high-seas complementary accounts at this stage. This omission is identified as a future development.

3.6.4 MMU selection (§3.3)

The three ecosystem layers (mangrove, seagrass, coral reef) are derived from different acquisition windows spanning January to October 2023 — a date range exceeding 6 months. The compiler assesses that ecosystem conversion detectable at inter-layer boundaries is unlikely to be an artefact of temporal lag given the stable dry-season conditions. This assessment is documented in the account quality notes.

3.6.6 Uncertainty and metadata (§3.5)

Table 3.6.6 below summarises the accuracy assessment for each ecosystem type.

Table 3.6.6: Accuracy assessment for the worked example

Aggregate account tier: Tier 2 (seagrass is the lowest-accuracy component). All metadata records stored in GeoNetwork instance hosted at the NSO. The account quality disclosure notes that seagrass extent should be treated as provisional and that a full Tier 1 assessment is planned for the 2025 vintage. The VLIZ Maritime Boundaries Geodatabase release version (2023 edition, [VLIZ 2023 release DOI — to be confirmed at publication; take from the marineregions.org citation page for the version used]) is recorded in the ISO 19115 lineage metadata for the EEZ boundary layer, illustrating the version control practice recommended in §3.5.2.