Alberta Wetland Mapping Standards and Guidelines: Mapping Wetlands at an Inventory Scale V1.0

ACKNOWLEDGEMENT

Prepared by Wetland Inventory Steering Comittee:

Alberta Environment and Parks - Nicole Skakun, Craig Mahoney, Danielle Cobbaert, Matthew Wilson, Dan Farr, Shane Patterson, Joshua Montogmery, Faye Wyatt (formerly with AEP).

Contirbutors and Stakeholder Workshop Participants, November 2019

Lyle Boychuk , Ducks Unlimited Canada Dennis Chao, Alberta Energy Regulator Laura Chasmer, University of Lethbridge Shari Clare, Fiera Biological Consulting Valery Companiystev, Alberta Environment and Parks Andy Dean, Hatfield Consultants Evan Delancy, Alberta Biodiversity Monitoring Institute Shantel Koenig, Fiera Biological Consulting Chris Mallon, Alberta Environment and Parks Micheal Merchant, Ducks Unlimited Canada Lisa Neame, Alberta Environment and Parks Alex Onojeghuo, Solstice Environmental Management Al Richard, Ducks Unlimited Canada David Speiss, Alberta Agriculture and Forestry Louise Versteeg, Solstice Environmental Management Jinkai Zhang, Alberta Agriculture and Forestry

This document may be cited as: Government of Alberta – Alberta Environment and Parks (GOA: AEP). 2020. Alberta Wetland Mapping Standards and Guidelines: Mapping Wetlands at an Inventory Scale v1.0. Edmonton, Alberta.

Title: Alberta Wetland Mapping Standards and Guidelines: Mapping Wetlands at an Inventory Scale v1.0 Program Name: Copyright 2020 Government of Alberta Number: ISBN 978-1-4601-4831-0 Effective Date: This document was July 15, 2020 updated on:

List of Updates

Update Version Section Description July 15, 2020 1.0 Version 1.0

HOW TO USE THIS DOCUMENT

This standard is intended to be used by those in Alberta that have a professional interest in/or are working on wetland conservation and management, including, wetland mapping and inventory development. These were developed based on minimum standards and guidelines to promote consistency and improve data quality in wetland mapping at a provincial scale within the Prairie/Parkland and Boreal/Foothills zones of Alberta.

3 TABLE OF CONTENTS

Acknowledgement...... 2 ...... 3 Table of Contents ...... 4 List of Figures ...... 6 List of Tables ...... 7 List of Acronyms ...... 8 Glossary ...... 9 References ...... 9 Terms ...... 9 1 INTRODUCTION ...... 10 1.1. Background ...... 10 1.2. Intent of Wetland Mapping Standards ...... 10 1.3. Key Needs ...... 12 1.4. Scope of Document ...... 13 1.5. Target Audience ...... 13 2 WETLAND CLASSIFICATION SYSTEM ...... 14 2.1 Wetland Definition ...... 14 2.2 Canadian Wetland Inventory ...... 14 2.3 Alberta Wetland Classification System ...... 14 2.3.1 Wetland Class ...... 15 2.3.2 Wetland Form ...... 16 3 WETLAND INVENTORY STANDARDS ...... 18 3.1 Prairie/Parkland Zone Wetland Mapping ...... 20 3.1.1 Classification ...... 20 3.1.2 Minimum Mapping Unit ...... 21 3.1.3 Classification Accuracy ...... 22 3.2 Boreal/Foothills Zone Wetland Mapping ...... 23 3.2.1 Classification ...... 23 3.2.2 Minimum Mapping Unit ...... 24 3.2.3 Classification Accuracy ...... 25 3.3 Boreal Transition Zone Wetland Mapping ...... 26 3.4 Methodological Guidelines for Wetland Inventory ...... 27 3.4.1 Wetland Classification...... 27 3.4.2 Accuracy Assessment...... 29 4 DATABASE STRUCTURE ...... 31 4.1 Overview ...... 31 4.2 Geodatabase ...... 31

4 4.2.1 Projection ...... 31 4.2.2 Feature Datasets ...... 31 4.2.3 Feature Classes ...... 31 4.3 Audit ...... 33 4.3.1 Topologic Validation...... 33 4.3.2 Attribution Validation ...... 34 5 METADATA ...... 34 5.1 Overview ...... 34 5.2 Dataset Metadata ...... 34 5.3 Resource ...... 34 6 REFERENCES ...... 36

5 LIST OF FIGURES

Figure 1: Geographic representation of the prairie/ parkland and boreal/ foothills zones within Alberta. Note, the boreal transition zone is spatially ambiguous and cannot be explicitly defined...... 19 Figure 2: Summary of wetland classification level and accuracy for the prairie/ parkland zone of Alberta...... 21 Figure 3: Summary of wetland classification level and accuracy for the boreal/ foothills zone of Alberta...... 24 Figure 4: Example of potential shortcomings of performing a wetland classification accuracy assessment using point locations (green triangles) only. a) illustrates the wetland as being misclassified using this method, whereas b) illustrates the wetland correctly classified as marsh...... 30

6 LIST OF TABLES

Table 1: Summarised subset of geospatial data available for appropriately mapping wetlands in the prairie/ parkland and boreal/ foothills zones of Alberta. Note additional appropriate data sources may exist for wetland applications. This table provides an example of a cross-section of appropriate data sources...... 26

7 LIST OF ACRONYMS

AMWI – Alberta Merged Wetland Inventory

AWP – Alberta Wetland Policy

AWCS – Alberta Wetland Classification System

BTZ – Boreal Transition Zone

CWI – Canadian Wetland Inventory

CWCS – Canadian Wetland Classification System

DEM – Digital Elevation Model

GOA – Government of Alberta

8 GLOSSARY

REFERENCES

In addition to the definitions below, this guide draws on others from the following documents:

• Alberta Wetland Classification System • Alberta Wetland Policy

TERMS

Ericaceous – slightly acidic, nutrient poor

Graminoid – grass-like vegetation

Minimum Mapping Unit – the size of the smallest feature to be delineated

Mineral wetland – a wetland characterized by mineral soils and/or organic soils that have either no accumulation of peat or a peat layer of less than 40 cm deep

Peatland – a wetland with more than 40 cm of accumulated peat; includes bogs and fens and some swamps (i.e conifer – black spruce)

Shrubby – multi-stemmed vegetation of any height and/or single stemmed trees up to 3 metres tall

Wooded – a wetland form that contains more than 25% tree cover

9 1 INTRODUCTION

1.1. Background Alberta is one of the few provinces in Canada to provide a publicly available, comprehensive wetland inventory dataset. The current Alberta Merged Wetland Inventory (AMWI) was achieved by assembling and harmonizing the best available spatial wetland inventory data to provide unified provincial coverage. The AMWI is an assemblage of various wetland inventory data developed with different intents. Constituent inventories were derived from various remote sensing image sources, from multiple dates using various classification hierarchies and analytical methodologies. As a result, the spatial representation of wetlands and the quality of the AMWI is variable across the province.

The Government of Alberta (GOA) intends to update and improve the quality and consistency of the provincial wetland inventory to meet policy needs, and the needs of various partners and end users where feasible. A critical first step is the development of a provincial standard that outlines the minimum standards for classification of wetland types, minimum mapping unit, and classification accuracy, to build the framework for an updated wetland inventory for current and future monitoring, policy support and other multiple uses. An improved provincial wetland inventory will in turn improve wetland management strategies to meet Alberta Wetland Policy (AWP) goals.

The Alberta wetland inventory standards adheres to the Alberta Wetland Classification System (AWCS; ESRD, 2015) while also aligning with the national standards of the Canadian Wetland Inventory (CWI) (Canadian Wetland Inventory Data Model V 7.0; DUC, 2016) at the five major class level (Bog, Fen, Swamp, Marsh, Open Water).

1.2. Intent of Wetland Mapping Standards The intent of this document is to establish the following standards for wetland inventory mapping in Alberta:

• Classification - classification requirements for wetlands based on the Alberta Wetland Classification System for the Prairie and Parkland zones (hereafter Prairie/ Parkland) and Boreal and Foothills zones (hereafter Boreal/ Foothills).

• Minimum Map Unit – sets the minimum size of wetlands mapped in an inventory. The minimum map unit is set based on consideration of the spatial resolution of remotely sensed imagery that is available and practical to meet the majority of wetland inventory uses, and the size of important wetland features on the landscape.

10 • Classification accuracy - minimum classification accuracies are highest at the wetland class level (e.g. bog, fen, swamp, marsh, open water) and decrease with increasing classification levels (e.g. wetland form, and type). Determine accuracy thresholds and methodological guidelines for validation data and reporting accuracy and validation data.

The wetland mapping standards are based on remote sensing and/or air photo interpretation methodologies and consider what is achievable in terms of the classification level, minimum map unit and classification accuracy. The standards consider the challenges of consistency and repeatability of wetland mapping at a regional scale between the prairie/parkland and boreal/foothills zones. The standards also provide discussion on guidelines, or acceptable methods for image classifications and accuracy assessment techniques.

A key challenge for developing wetland inventory standards for Alberta is the diversity of wetland types and sizes and the surrounding landscape, which presents different challenges in accurately delineating and classifying wetlands. Different wetland inventory standards are appropriate to map wetlands in the prairie/ parkland and boreal/ foothills zones. The prairie/parkland zone is comprised of the grassland and parkland natural regions in southern Alberta and the boreal foothills of the boreal/foothills regions (Natural Regions Committee 2006). Wetlands in the prairie/parkland are primarily small, typically disconnected prairie-pothole marshes and shallow open water wetland classes with a surrounding landscape dominated by grasslands or parkland forests and agriculture and urban areas. Accurately mapping these small, isolated wetlands is a priority for wetland management in the Prairie/ Parkland zone, which requires high spatial resolution imagery (e.g. imagery within the range of 50-cm to 5-m). In contrast, wetlands of the boreal/foothills are often vast interconnected wetland complexes dominated by peatlands (bogs and fens) and a high prevalence of forested swamps with marshes and open water also present. These wetlands classes are comparatively difficult to differentiate from each other and the surrounding forested landscape. Mapping these wetlands requires interpretation from high spectral resolution (e.g. sensors with visible, near-infrared and shortwave infrared bands) or potentially fusion approaches using multiple types of remote sensing imagery and Digital Elevation Model (DEM). The Boreal Transition Zone (BTZ) exists between the prairie/parkland and boreal/foothills zones however lacks a spatially explicit boundary. The BTZ may include a mix of small marshes and open water wetlands as well as larger swamp and peatland complexes. As a result, additional work is needed to address and test wetland inventory standards for the Boreal Transition Zone.

The Alberta Wetland Inventory standards follows the hierarchy of the AWCS for classification and also maintaining a framework for additional classification attributes. The wetland mapping standards provide a framework for testing new approaches and methods for completing a wetland inventory using various remote sensing datasets (e.g. airborne and satellite optical imagery,

11 airborne lidar, spaceborne radar, and terrain data). New remote sensing methodologies involving data fusion and machine learning may offer innovative and cost-effective solutions.

1.3. Key Needs Land use decisions throughout the GOA and for stakeholders rely on foundational geospatial data that is current, complete and accurate. An updated provincial wetland inventory will improve wetland management and conservation strategies in Alberta. An updated provincial wetland inventory that is consistent, and accurate will provide high quality baseline information for the Government of Alberta to support wetland policy, monitoring, and planning needs.

Alberta Wetland Policy

The Alberta Wetland Policy provides the strategic direction and tools to make informed management decisions in the long-term interest of Albertans, and is the main driver for continual improvement of wetland inventory (Government of Alberta, 2013). The goal of the Alberta Wetland Policy is to conserve, protect, and manage Alberta’s wetlands to sustain the benefits they provide to the environment, society, and economy (Government of Alberta, 2013). To achieve this goal, the policy focuses on the following outcomes:

1. Wetlands of the highest value are protected for the long-term benefit of all Albertans.

2. Wetlands and their benefits are conserved and restored in areas where losses have been high.

3. Wetlands are managed by avoiding and minimizing negative impacts, and where necessary, replacing lost wetland value.

The standards support advancement in knowledge and information needs for wetland policy as part of the wetland management framework. The standards promote currency and consistency of foundational wetland inventory data for making sound wetland management decisions, including enhanced tools that enable policy implementation such as Alberta Wetland Rapid Evaluation Tool ABWRET. An updated inventory will also support the Alberta Wetland Policy by providing up-to date and more accurate information on the current location and wetland classes that will be used in the for broad-scale land use planning and site-specific land management decisions including wetland avoidance. An updated wetland inventory will not replace the need for a detailed on-site wetland assessment for any proposed wetland losses and impacts as outlined by regulatory directives under the Alberta Wetland Policy.

12 Wetland Monitoring

An updated wetland inventory will be used to monitor and evaluate broad-scale landscape changes in wetland abundance, extent and condition over time. This include the ability to 1) detect changes in wetland area over time, and 2) evaluate the drivers of change so that the underlying cause of wetland loss and degradation can be identified and addressed. Consideration from a monitoring perspective include frequency of update (data currency, resolution, remote sensing platforms, classification accuracy and validation.

Land Use Planning

An updated wetland inventory will help to inform land use planning at a regional or sub-regional level (e.g. regional planning, environmental management frameworks, sub-regional plans and municipal planning). An updated wetland inventory will provide more accurate, up-to-date and consistent information on wetland extent and class that will be used to provide recommendations on wetland conservation areas, wetland management priorities, and regional planning scenarios.

1.4. Scope of Document The document defines the standards for classification, minimum mapping unit, and classification accuracy. The standards consider wetland types and spatial resolution for mapping wetlands in the prairie/parkland and boreal/foothills zones of Alberta. Additional work is needed to address and test wetland inventory standards in the Boreal Transition zone (BTZ) as the wetlands in the BTZ may include a mix of small marshes and open water wetlands better suited to higher spatial resolution mapping, and larger swamp and peatlands complexes better suited to imagery with high spectral resolution. The goal of this document is to provide a framework for wetland inventories in Alberta to enable consistency and repeatability for inventory developers and users of the data.

1.5. Target Audience This document is prepared with the intent of improving future wetland mapping in Alberta. The target audience are those with a professional interest in and/or responsibility for mapping wetlands in Alberta and contribute to and/or work with wetland inventory at multiple levels. The standards are based on a combined interest in conserving and managing wetlands by using a consistent wetland mapping standard. The document provides a technical framework for developing inventory while establishing consistency in expectations to end users of wetland inventories

13 2 WETLAND CLASSIFICATION SYSTEM

2.1 Wetland Definition Wetlands are land saturated with water long enough to promote the formation of water altered soils, growth of water tolerant (hydrophytic) vegetation, and various kinds of biological activity adapted to wet environments (Government of Alberta, 2013). Wetlands are highly diverse, productive ecosystems that provide a host of ecological services and form an integral component of Alberta’s diverse landscapes.

2.2 Canadian Wetland Inventory The CWI (Canadian Wetland Inventory Technical Committee, 2016) establishes a consistent framework and interpretation for mapping wetlands at a local, regional and national scale through a common data structure and classification system. Based on the nationally recognised Canadian Wetland Classification System (CWCS) (National Wetlands Working Group 1997), the CWI data model divides wetlands into five major wetland classes: bog, fen, swamp, marsh, and shallow open water and provides a framework for additional attribution for more detailed wetland information.

2.3 Alberta Wetland Classification System The AWCS is Alberta’s wetland classification system: it characterizes wetlands based on criteria that includes Alberta’s provincial flora and ranges of environmental, geological and climatic characteristics (ESRD 2015). Developed for use in Alberta, the AWCS provides a holistic classification system for the province that remains compatible with the nationally recognised CWCS (National Wetlands Working Group 1997) at the five major class level. For a comparison between the AWCS and the CWCS, refer to the Alberta Wetland Classification System documentation (ESRD 2015). The intent of the AWCS is to achieve a provincially consistent and standardized wetland classification system for Alberta.

The AWCS provides a framework for classifying wetlands in to the five major wetland classes defined by the CWCS. These five major classes can be subdivided in to wetland form based on dominant vegetation structure. Wetland form is further subdivided in to wetland type based on biological, hydrological, and chemical attributes. Current wetland inventory standards do not apply to wetland type. For more information on wetland type, vegetation species, soils, and moisture characteristics refer to the Alberta Wetland Classification System documentation (ESRD 2015).

14 Within the context of the AWCS, the Alberta Wetland Inventory Standards provides prescriptive information on the level of wetland classification detail reported for wetland inventories. The classification detail differs as a function of the zone in which wetland inventories are produced – prairie/parkland or boreal/foothills (Figure 1). Within the prairie/parkland zone, the reporting of wetland class is required, whereas wetland class and form are required in the boreal/ foothills zone. These classification requirements were defined with the intention to mitigate cost prohibitive analyses, often associated with form and type, where possible. As wetland type is optional in Alberta wetland standards, descriptive information has been deliberately omitted from this document. For wetland type information see ESRD (2015).

2.3.1 Wetland Class Wetland class information, as defined by the AWCS (ESRD 2015), is outlined below. These descriptions provide information for classifying wetlands remotely (by the use of geospatial data), and are not intended for use as field guides.

Bog Bogs are peatlands with a ground surface featuring a deep (> 40 cm) deposit of poorly decomposed organic material (referred to as peat). Bogs are hydrologically isolated from ground water and surface run-off inflows, receiving water from precipitation, only (defined as ombrotrophic). Hydrologic isolation means bogs are stagnant, non-flowing systems with low nutrient availability and support low biological diversity. Bogs typically have a low water table, appearing dry at the surface.

Fen Fens, like bogs, are peatlands with a deep (> 40 cm) peat ground surface, but are hydrologically connected, receiving water from a combination of ground water, surface run-off, and precipitation. Fens can be nutrient poor or rich, depending on nutrient input from inflowing ground and surface water sources. Nutrient poor fens closely resemble bogs, whereas nutrient rich fens support greater biological diversity. Fens are hydrologically complex with high water tables, capable of transporting water and nutrients across the landscape, often connecting wetland systems over great distances.

Swamp Swamps, for the purposes of this document, are considered mineral wetlands (≤40 cm peat depth), although they may also exist as peatlands (>40 cm peat depth) in some cases, with woody plant cover that comprises more than 25% of the total area (ESRD 2015). The ground surface is typically characterised by soils derived from minerals and/or rocks, containing little organic material, although sub-surface peat may exist in some settings. Swamps receive water from a combination of ground water, run-off, and precipitation. Water movement ranges from stagnant to dynamic,

15 where fluctuating water tables result in seasonal flooding. Swamps typically represent transition zones between other wetlands and non-wetland areas, known as uplands, and support high biological diversity.

Marsh Marshes are mineral wetlands that commonly represent the transition between Shallow Open Water and basin edge, but can exist in isolation. Marshes exhibit a variable water table, where water levels may occur near, at or above the ground surface at different periods throughout the season. Marshes receive water from a combination of ground water, run-off, precipitation, and through connecting streams. Marshes periodically dry, exposing the ground surface to oxygen allowing nutrient enrichment, promoting the growth of a diverse range of emergent, grass-like (graminoid) vegetation. Graminoid cover dominates through all wetland zones, where shrub cover is more interspersed in the drier, peripheral wetland zones.

Shallow Open Water Shallow open water are mineral wetlands with a water depth up to a maximum of 2 metres. Open water wetlands receive water through a combination of ground water, run-off, precipitation and stream inflow. The deepest, open water zone may support floating and/or submersed aquatic vegetation, contingent on nutrient availability. Open water wetlands are typically permanently flooded but water levels may fluctuate seasonally, exposing bare earth.

2.3.2 Wetland Form Multiple wetland classes share similar wetland forms, based on dominant vegetation characteristics. For example, periodically flooded wetland classes permit the presence of graminoid, shrubby, or wooded vegetation, where only wetlands that are typically permanently flooded allow the establishment of aquatic vegetation.

Bog Bogs take wooded (coniferous), shrubby and graminoid forms. Wooded coniferous bogs are dominated by sparse, stunted (< 10 m tall) black spruce (Picea mariana), with low-lying shrubs (< 1 m tall), and sphagnum moss. Ericaceous, low-lying shrubs and sphagnum moss dominate shrubby bogs. Shrubs areal cover exceeds 25 % of the wetland zone, whilst wooded vegetation cover is 25% or less. Graminoid bogs (also known as open bogs) are dominated by sphagnum moss, with few trees and shrubs (comprising less than 25 % coverage).

Fen Fens support wooded coniferous, shrubby, and graminoid forms. Wooded fens are dominated by black spruce and tamarack (Larix laricina) (≥ 25 % areal coverage, typically <10 m in height), where the former is more prevalent in nutrient poor fens, and the latter in nutrient rich fens. Shrub birches

16 (Betula spp.) and willows (Salix spp.) dominate the understory up to a height of 2 m, whilst brown and sphagnum mosses interspersed with graminoid and forb species form the ground layer. Shrubby fens may exhibit similar wooded, shrub, and ground layer species as wooded fens, but areal tree cover is limited to 25 %, whilst shrub cover exceeds 25 %. Graminoid fens are ground layer dominated, exhibiting a maximum of 25 % tree and shrub cover.

Swamp Swamp forms are wooded or shrubby based on the presence or absence of trees, where wooded forms are identified by a minimum of 25 % tree cover and typically ≥10 m in height, and dominant stand type (i.e. coniferous, mixedwood, or deciduous). Wooded coniferous swamps consist of at least 75 % conifer species cover, typically black spruce (Picea mariana), occasionally interspersed with white spruce (Picea glauca) and tamarack (Larix laricina). Wooded deciduous swamps are dominated (≥ 75 %) by deciduous species, where Alaska birch (Betula neoalaskana), balsam poplar (Populus balsamifera) and white birch (Betula papyrifera) are common. Coniferous species may exist, representing a small portion of areal coverage. Wooded mixedwood swamp share similarities with both wooded coniferous and deciduous swamps, but neither conifer nor deciduous species exist with ≥ 75 % abundance. All swamps exhibit a shrub dominated understory that may include willow (Salix spp.), alder (Alnus spp.), and red-oiser dogwood (Cornus sericea) usually greater than 2 m tall. Shrubby swamps are dominated by these species with a minimum of 25 % areal coverage, whilst wooded species do not exceed 25 % cover.

Marsh Marshes have only one form – graminoid. They are dominated by graminoid species (≥ 25 %) but may exhibit up to 25 % shrub cover predominantly comprised of willows (Salix spp.) with other shrub species interspersed in and around the wetland margin.

Shallow Open Water Shallow Open Water wetlands take either aquatic or bare forms, identified by vegetation presence or absence. Aquatic forms exist in the deepest wetland zone where floating and/or submersed aquatic vegetation covers a minimum of 25 % of the area in the majority of years. Bare Shallow Open Water systems exhibit sparse vegetation coverage, often as a result of high salinity.

17 3 WETLAND INVENTORY STANDARDS

In the context of wetlands, Alberta can be divided into two major zones – the prairie/ parkland and the boreal/ foothills zones (Figure 1), separated by the boreal transition zone. Wetland inventory standards defined in each zone are intended to meet Government of Alberta needs (Section 1) through remote classification methods using geospatial data.

The prairie/ parkland zone is defined based on a combination of the grassland and parkland natural regions of Alberta (Natural Regions Committee 2006) and spans southern Alberta. Mineral wetlands (marsh and shallow open water) dominate prairie wetland basins, with swamps increasingly more common in (treed) parklands, towards the northern extent of the zone; peatlands (bogs and fens) are very rare. The spatial extent of most prairie wetlands varies through the year, linked to seasonal snow melt and precipitation. This results in temporally and spatially dynamic wetlands which makes their classification challenging.

The boreal/ foothills zone is defined as the combined areal coverage of the boreal forest and foothills natural regions of Alberta (Natural Regions Committee 2006) and covers northern Alberta and the eastern foothills of the Rocky Mountains. Peatlands are most common in the zone, covering large areas, followed by swamps, where marsh and open water mineral wetlands are less common. Wetlands exist where the water table is near or at the ground surface, and therefore tend to occur within landscape depressions or on flat land that is poorly drained. Wetlands are less dynamic in comparison to the prairie/ parkland wetlands due to higher, more consistent water availability throughout the year.

The boreal transition zone exists between pure prairie/ parkland, and boreal/ foothills zones. The zone shares characteristics of both zones, therefore, a clear definition of this zone is not objectively feasible.

Figure 1: Geographic representation of the prairie/ parkland and boreal/ foothills zones within Alberta. Note, the boreal transition zone is spatially ambiguous and cannot be explicitly defined.

19 3.1 Prairie/Parkland Zone Wetland Mapping

3.1.1 Classification

The classification level for the Prairie/Parkland zone wetlands is Class

The prairie/parkland zone is dominated by marsh, shallow open-water and swamp wetlands. Wetland inventory standards require classification to the five major AWCS classes (Figure 2); mapping wetland form and type is optional. Necessary wetland biophysical and biochemical indicators needed for wetland form and type characterisation are difficult to obtain at appropriate spatial resolutions and are cost prohibitive from geospatial sources (Adam et al. 2010). Furthermore, the difficulty in attempting to distinguish wetland form and type is exacerbated by such geospatial data resolution limitations (Ozesmi et al. 2002) as resident wetlands in this zone are small in size (typically < 1 ha) presenting detectability challenges. For example, determining the presence of aquatic vegetation in open-water wetlands is challenging due to shared spectral characteristics between the vegetation and underlying water column (Silva et al. 2008); a similar challenge exists in determining swamp dominant vegetation cover due to spectral similarities between some vegetation types (Ozesmi et al. 2002). These challenges are potentially surmountable by using data from multiple sensors that provide both spectral and structural information (e.g. optical imagery and LiDAR), but are often cost prohibitive. The classification framework for the prairie/parkland zone under current wetland inventory standards is summarised in Figure 2.

Figure 2: Summary of wetland classification level and accuracy for the prairie/ parkland zone of Alberta.

3.1.2 Minimum Mapping Unit

A minimum mapping unit (MMU) of 0.04 hectares (ha) is defined for mapping prairie/ parkland wetlands.

A minimum mapping unit (MMU) of 0.04 hectares (ha) is defined for mapping prairie/ parkland wetlands, which considers the high occurrence of small wetlands on the landscape and their high loss rate (Serran and Creed 2016). Achieving this MMU in the prairie/ parkland region using open- source data (e.g. Sentinel-2) may be challenging, therefore inventory producers will likely need to use finer resolution data sources (Table 1) or various data fusion approaches to achieve this MMU. For example, wetland inventories with an MMU < 0.04 ha have been produced in the prairie/

parkland zone using high resolution data sources such as the fusion of aerial photographs and elevation data.

Regardless of imagery used, when using raster data sources, a minimum cluster of 4 pixels (as a square) is used to enhance confidence in spatial attribution by effectively reducing the variability in data (spectral reflectance, SAR backscatter, etc.) ranges (Chuvieco et al. 1988). This approach reduces the variability of data signatures from individual pixels within a cluster; the use of pixel clusters has demonstrated improvements to classification accuracies (Mui et al. 2015, Costa et al. 2017). The defined MMU (0.04 ha) accounts for pixel clusters, therefore individual image pixels may be no larger than a 10 m square. The defined MMU captures 70% of wetlands below 0.1 ha, which represents approximately 85% of all prairie/ parkland wetlands in Alberta (IWWR 2014, Government of Alberta 2018), while enabling the use of open-access and low-cost geospatial data sources for classification purposes. A subset of geospatial data sources capable of mapping wetlands at an MMU of 0.04 ha include, but are not limited to: Sentinel-2, Planetscope, Worlview, Rapideye, etc.

The defined MMU is a definition of the upper limit at which any wetland inventory can be produced while qualifying for inclusion into an updated provincial wetland inventory. The production of finer resolution wetland inventories is optional, while still subject to other sections of the wetland mapping standards.

3.1.3 Classification Accuracy

Minimum achievable wetland classification accuracies are required for separating wetlands from uplands at 90 %, and at 80 % for classifications of wetland class.

Classification accuracies in the prairie/ parkland zone decrease with increased wetland attribution detail i.e. distinguishing wetlands from upland should be reported with higher accuracy than wetland class. Minimum achievable wetland classification accuracies are required for separating wetlands from uplands at 90 %, and at 80 % for classifications of wetland class (i.e. bog, fen, marsh, swamp, and open-water).

The accuracy of wetland perimeters are not assessed in the current wetland inventory standards for the prairie/ parkland zone. This is primarily due to natural intra- and inter-annual fluctuations in surface water extent (Dronova 2015, Gallant 2015), but also because condition of the environment

22 reporting and/or inventory needs focus on the quantification of wetland area. High accuracy individual wetland perimeter assessment remains a requirement of wetland policy (typically only achievable with high-cost, high-resolution geospatial data or by field delineation).

Accuracy assessments need to be reported as a confusion matrix with associated user, producer, and overall accuracies, accompanied by Cohen’s kappa statistic (Cohen 1960, Congalton 1991) and a per-class F1 score (Pouliot et al. 2019). This allows users to identify the classification accuracy of each class, and provides an overall assessment based on the performance of each class.

3.2 Boreal/Foothills Zone Wetland Mapping

3.2.1 Classification

The classification level for the Boreal/Foothills wetlands is Class and Form

In the boreal/ foothills zone, reporting wetland class and form attribution levels are required, wetland type is not required. (Figure 3). Reporting wetland type is challenging because the necessary biochemical information needed for characterisation is often difficult to obtain, and cost prohibitive from geospatial sources (Adam et al. 2010). Increased changes in wetland dominant vegetation (wooded, shrub, or graminoid) dynamics, reported under wetland form, necessitate reporting wetland form. As an example, increases in nitrogen loading associated with oil sands development activities have induced wetland nitrification in bogs and poor fens, which has led to changes in wetland vegetation species composition (Wieder et al. 2019). A top down approach, similar to that employed for prairie/ parkland wetland mapping, is applicable in the boreal/ foothills zone. However, classifications have also been completed using a bottom up approach where wetlands are first identified based on the characterization of vegetation species and structure, which subsequently provides the basis for reporting the class level (Ducks Unlimited Canada, 2015). The classification levels for the boreal/ foothills zone under current wetland inventory standards are summarised in Figure 3.

Figure 3: Summary of wetland classification level and accuracy for the boreal/ foothills zone of Alberta.

3.2.2 Minimum Mapping Unit

The minimum mapping unit (MMU) for Boreal/Foothills wetlands is 0.9 ha.

The minimum mapping unit (MMU) for Boreal/Foothills wetlands is 0.9 ha. This accommodates the use of open source (e.g. Landsat, Sentinel-1/2), ‘water seeking’ data from optical imagery and/or Synthetic Aperture Radar (Brisco 2015, Montgomery et al. 2019) (Table 1). The ABMI photoplot data (Castilla et al. 2016) indicates that an MMU of 0.9 ha captures approximately 91 % of all wetlands >0.5 ha on the landscape, representing 99.6 % of wetland areas >0.5 ha. Vegetated wetlands should be captured using larger pixel groupings partly because of their heterogeneous vegetation composition and structure, but also because they often exist as constituents of a wetland complex that may transition from one class to another (Dronova 2015, Gallant 2015, Mahdavi et al. 2018). As an example, a single pixel may identify a marsh, but when the surrounding landscape is considered, fen may emerge as the dominant wetland class.

24 Similar to the MMU identified for the prairie/ parkland zone, the boreal/ foothills MMU is defined as an upper limit for wetland inventory production. The production of finer resolution inventories is optional, and would be valid for inclusion iinto an updated provincial wetland inventory, whilst still subject to other sections of the wetland inventory mapping standards.

3.2.3 Classification Accuracy

Wetlands are to be distinguished from uplands with 90 % accuracy. Wetland class and form are to be reported with 80 % and 70 % accuracies, respectively.

Classification accuracies in the boreal/foothills zone decrease with increased wetland attribution detail i.e. wetland class should be reported with higher accuracy than finer attribution levels (e.g. wetland form, and (optionally) type). Wetlands are required to be distinguished from uplands with 90 % accuracy. Wetland class and form are required to be reported with 80 % and 70 % accuracies, respectively. Additional information is needed to assess classification accuracy quantitatively at each attribution level.

The spatial assessment of wetland perimeters are not required in the current wetland inventory standards for the boreal/ foothills zone. This is because wetland complexes are interconnected with temporally transitioning wetland classes, sometimes making the identification of individual wetland classes challenging (Dronova 2015, Gallant 2015). Moreover, the accurate reporting of wetland perimeters by geospatial data at a provincial-scale is inefficient and cost prohibitive.

Methods for assessing the wetland inventory of the boreal zone follows similar procedures to the prairie/parkland wetland classification validation. Accuracy statistics are presented in a confusion matrix with associated user, producer, and overall accuracies, accompanied by Cohen’s kappa (Cohen 1960, Congalton 1991) and per-class F1-scores (Pouliot et al. 2019).

25 Table 1: Summarised subset of geospatial data available for appropriately mapping wetlands in the prairie/ parkland and boreal/ foothills zones of Alberta. Note additional appropriate data sources may exist for wetland applications. This table provides an example of a cross-section of appropriate data sources. Data type Source Available Cost Applicable zone resolution(s) (Prairie, Boreal, Both) Multi-spectral Landsat 15 – 30 m Free Boreal optical imagery Sentinel-2 10 – 60 m Free Both Rapideye 5 – 6.5 m Mid Both SPOT 1.5 – 20 m Mid Both Planetscope 3 m Mid Both Worldview 0.3 – 2.5 m High Both Aerial photographs < 0.3 – 10 m High Both Synthetic aperture Sentinel-1 3.5 – 40 m Free Both Radar Radarsat constellation mission 3 – 100 m Free Both ALOS PALSAR 10 – 100 m Mid Both Radarsat-2 3 – 100 m High Both Topographic Shuttle Radar Topology 30 – 90 m Free Boreal Mission Airborne Light Detection And < 1 – 15 m High Both Ranging (LiDAR)

3.3 Boreal Transition Zone Wetland Mapping Standards for mapping, classification and attribution of wetlands in the boreal transition zone are currently undetermined. The minimum standards defined for both the prairie/parkland and boreal/foothills may not be achievable in this zone. This is due to the combination of high wetland diversity and various land use practices that may affect wetland vegetation and hydrological processes, resulting in altered wetland conditions and/or extents. Given that mapping standards from both zones are challenging to apply in the boreal transition zone, a hybrid approach is suggested until appropriate mapping standards are defined through quantitative and/or qualitative data. Under the current prescribed hybrid approach any bogs, fens, and swamps should comply with boreal/ foothills standards, whereas marsh, and shallow open water classes should adhere to prairie/ parkland standards.

26 3.4 Methodological Guidelines for Wetland Inventory It is recognised that multiple methods exist to classify and assess the accuracy of wetland classifications. A primary rationale for wetland standards is the promotion of consistency in resulting classifications, and innovation in the development of classification techniques. As a result, these guidelines do not prescribe methodologies for classifying wetlands, but briefly summarise ‘best practises’ for wetland classification methods using remote sensing data. In addition, multiple methods exist to assess the accuracy of classifications. These guidelines provide best practises for applying accuracy assessment techniques.

3.4.1 Wetland Classification To date, supervised statistical machine learning classifiers have been the most successful means of classifying wetlands using remote sensing as ancillary data. Numerous classifiers have been investigated within the scientific community, concluding that the Random Forest algorithm (Breiman 2001) produces the most accurate classifications most frequently, resulting in its historic popularity and continued use (Felton et al. 2019, Slagter et al. 2020). Deep learning algorithms, a branch of machine learning, has recently emerged as a prominent tool for wetland classification. Deep learning has demonstrated superior classification results compared to traditional machine learning in some settings, however, results remain inconclusive regarding which method is most favourable for wetland classification (DeLancey et al. 2019). Deep learning exhibits potential to surpass traditional methods for wetland classification and is currently considered state-of-the-art.

Machine learning classifiers require sampled areas of known information (e.g. wetland class), defined as reference data, to drive and assess classification accuracies. Reference data should be determined from high-precision classifications assigned by a qualified observer in the field geolocated with high precision Global Navigation Satellite System (GNSS) information, and/or assigned by a qualified interpreter of appropriate imagery. For the latter, reference data should be interpreted from imagery of appropriate date (e.g. within a single year of ancillary data) and quality (e.g. geolocation accuracy), and should be of higher resolution than ancillary data. Where possible, reference data should exhibit a sample distribution similar to the population distribution in the study area for all wetland attribution levels (i.e. wetland class, form, and type as applicable), and all ancillary data characteristics.

Reference data may be interpreted in two forms: as polygons (objects) outlining the extent of wetlands, or as points located within wetlands. A minimum of two locations within a wetland require identification for point form reference data, where points should be distributed across the wetland, capturing the wetland centre and edge/transition zone. Polygon reference data are favoured to drive classifiers, where possible. However, their use should be avoided to drive pixel-based classifications because they represent information sourced over a spatial area that is greater than

27 a single pixel, which may lead to misclassification in outputs. As polygons can be more challenging to interpret, point form reference data can be utilised to drive object-based wetland classifications.

Reference data should be subset into training and assessment sets with respective proportions of 67 % and 33 % (unless independent assessment data are available), which represents common practice (Congalton 1991). If sample sizes proportional to the landscape population cannot be achieved, a minimum of 20 samples per wetland attribution level is favoured for model training, where multiple points or a single polygon per wetland constitutes a single sample. As an example, the development of a classification of AWCS classes needs ≥ 20 samples for bog, fen, swamp, marsh, and open water (constituting ≥ 100 samples in total); similarly ≥ 260 samples should be used to drive an AWCS classification of 13 wetland forms.

Object-Based Image analysis (OBIA) has been proven to be provide less fragmented and more accurate wetland classifications compared to pixel-based analyses (Dronova 2015) and is favoured for wetland classification. However, state-of-the-art image segmentation algorithms are currently only available through commercial software, which may be cost prohibative. Considering this, classifications created using pixel-based approaches should be spatially filtered to reduce fragmentation, and eliminate small features to effectively reduce noise that is common in pixel- based analyses (Amani et al. 2017).

The fusion of multiple streams of remote sensing data has been proven more effective for accurately mapping wetlands compared to any single data source analysed in isolation (Chasmer et al. In Review). Fusion wetland studies should utilise passive optical imagery as foundational and supplement with actively sensed data such as Lidar and/or SAR where possible. The inclusion of the latter data sources allows the identification of beneath canopy features such as three dimensional structure and areas of flooded vegetation (Chasmer et al. 2016, Montgomery et al. 2019).

Optional Classifications

The optional identification of marsh, open-water, and swamp type should be based on monitoring their spatial extents, which vary intra- and inter-annually (Stewart and Kantrud, 1971). The acquisition of multiple datasets necessary for suitable wetland extent monitoring can be cost prohibitive. The duration that the wetland is present on the landscape throughout the ice-off period of the year (i.e. permanence) should be classified as either in to either ‘seasonal’ or ‘semi- permanent’. For the purpose of these standards, seasonal wetlands conform to Stewart and Kantrud classes I, II, III, and tilled basins (in agricultural settings), and semi-permanent wetlands are Stewart and Kantrud classes IV, V, and VI. See Stewart and Kantrud (1971) for additional information on seasonal and semi-permanent class compositions. Assignment of these water

28 permanence groups is achievable using geospatial data through the application of a frequency analysis to water masks from multiple, temporally distinct datasets (Montgomery et al. 2018).

3.4.2 Accuracy Assessment A subset of the available reference data should be used to assess wetland classification accuracies. Field acquired high precision GNSS located reference data is favoured for the assessment of wetland classifications due their inherently high (often sub-metre) precision (Awange 2012). Reference data interpreted from high-resolution imagery provides a secondary assessment source. Both datasets represent a robust means to validate wetland products (Dronova, 2015). Assessment data should represent a minimum of 33 % of all reference data (training and assessment), unless independent data are available; regardless, a minimum of 10 samples per wetland attribution level is standard. As an example, a minimum of 50 samples are needed to adequately assess a 5 wetland class classification (10 per class); a minimum of 130 samples are needed to assess a 13 wetland form classification, where multiple points or a single polygon per wetland constitutes a single sample.

Numerous methodologies exist to assess the accuracy of wetland classification products (Dronova 2015, Chasmer et al. 2016, Montgomery et al. 2019). As an example, a mapped wetland may be compared to a wetland classified in the field where the geographic centre of the wetland represents its position on the landscape (green triangle in Figure 4). This approach effectively performs an assessment on a per wetland basis and disregards any areas of the wetland that may be misclassified (if any). This is demonstrated at the wetland in Figure 4, which is misclassified as upland when the point location is used to assess classification accuracy. Point based approaches with location bias (i.e. points consistently at or near the wetland centre) may offer an artificially inflated accuracy assessment because a single point represents the entire variability with the wetland extent, thereby minimising potential noise. Moreover, a wetland’s centre is typically easiest to identify because it is furthest from edges and any transition zones that may confound definitive identification, and therefore typically constitutes the purest area of the wetland. Alternatively, classifications may be assessed against polygons representing the spatial extent of individual wetlands. Assessment using polygons is favoured because all pixels within the assessment polygon are considered, thus allowing the derivation of more robust assessment statistics. The primary method for classification assessment using polygons should consider all classified pixels within each assessment polygon to produce the necessary assessment statistics; similarly all points should be used to inform assessment statistics when assessment polygons are unavailable.

A standard method for classification assessment is not yet developed. In the meantime, the assessment guidelines provided here, should be followed where possible and provided as ancillary data. The use of alternate assessment methods may be acceptable but should have an

29 accompanying rationale and a detailed step-wise description of how classification results were obtained.

Figure 4: Example of potential shortcomings of performing a wetland classification accuracy assessment using point locations (green triangles) only. a) illustrates the wetland as being misclassified using this method, whereas b) illustrates the wetland correctly classified as marsh.

30 4 DATABASE STRUCTURE

4.1 Overview This section outlines the standard for geodatabase structure for wetland inventory data.

4.2 Geodatabase

4.2.1 Projection The projection is in Ten Degrees Transverse Mercator Projection with a 500,000 metre false easting (10TM AEP Forest) North American Datum 1983 (NAD 83).

4.2.2 Feature Datasets The Wetland Inventory Feature Dataset will contain the Wetland Inventory, Wetland Inventory Status and Provincial Wetland Inventory Index features classes.

4.2.3 Feature Classes Wetland Inventory Feature Class The attributes in the data model for the Wetland Inventory Feature Class will be structured the same as the Alberta Wetland Classification System. This will allow for necessary fields to be attributed while also allowing for the attribution of optional fields where this level of detail exists.

Class • Bog (B), • Fen [F], • Marsh [M], • Open Water [W], • Swamp [S]

Dominant Vegetation Form

Bog [B] • Wooded, coniferous [Wc], • Shrubby [S],

31 • Open with herbaceous or bryophyte ground cover [O]

Fen [F] • Wooded, coniferous [Wc], • Shrubby [S], • Graminoid [G]

Marsh [M] • Graminoid [G]

Shallow Open Water [W] • Submersed and/or floating aquatic vegetation [Aq] • Bare [B]

Swamp • Wooded, coniferous [Wc], • Wooded, mixedwood [Wm], • Wooded, deciduous [Wd], • Shrubby [S]

Type (Water Permanence) • Temporary [II], • Seasonal [III], • Semi-permanent [IV], • Permanent [V], • Intermittent [VI]

Extent • The extent of the project area, this can be linked to the extent field in the Alberta Merged Wetland Inventory Status Feature Class

Wetland Inventory Status Feature Class The Wetland Inventory Status feature class will capture the wetland data properties.

IMAGERY TYPE • The imagery sensor used for the wetland inventory (e.g. aerial photography, Landsat, Light Detection and Ranging (LiDAR), Sentinel, SPOT, RapidEye, Worldview, Synthetic Aperture Radar (SAR) etc.) IMAGERY DATE • The data or range of dates of the imagery used in the inventory, (specify universal time (UTC) date) IMAGE RESOLUTION • The nominal resolution (m) of a single pixel of imagery INVENTORY SYSTEM • The wetland inventory mapping program MINIMUM MAPPING UNIT • The minimum feature size or smallest area mapped (hectares) PROJECT AREA • The name of the project area for source data EXTENT • The abbreviated name of the project area, this can be linked to the extent field in the Wetland Inventory (polygons) SOURCE • Creator of inventory, citation of the source Wetland Inventory Index Feature Class • The Wetland Inventory Index feature class captures the extent of the data.

4.3 Audit

4.3.1 Topologic Validation The Wetland Inventory Topology contains two rules:

• POLYGON features are be larger than cluster tolerance • POLYGON features do not overlap This topology class is intended to identify overlapping polygons, particularly those along the edge of an area of new capture. The cluster tolerance is 0.001 metre and the coordinate resolution is 0.0001 metre, both the default values in ArcGIS.

33 4.3.2 Attribution Validation Validation to ensure all attributes are populated and consistent with the inventory framework. 5 METADATA

5.1 Overview Title

The Title will be the official name by which a resource is formally known. Meaningful titles support access, speed of identification, and control of content.

Purpose

This element answers the question “why has the data set been created?” This information should be as concise as possible.

Abstract

A brief narrative summary of the dataset. This element answers the question “what is the data set?” This information should be as concise as possible.

Resource Citation

Sufficient contact information to be provided so that data users can contact an individual with the data set accountability. The name of an organization or individual the developed the data.

5.2 Dataset Metadata Metadata Contact

Contact is the party responsible for the metadata, sufficient personal contact information needs to be provided so that data users can contact an individual with the data set accountability.

5.3 Resource Contstraints

The restrictions for access, use and distribution of the dataset. These include any constraints applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations on the dataset.

Quality

The positional and attribute accuracy and quality for the dataset. This can include details on the horizontal and positional accuracy and methods used to verify accuracy of both the spatial and attribute aspects of the dataset.

Lineage

Information about the events, parameters, and source data which constructed the data set, and information about the responsible parties.

35 6 REFERENCES

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