Introduction

Wetlands are dynamic ecosystems with complex interrelationships of hydrology, soils and vegetation. Many wetlands dry up during the year, and in times of drought can remain dry for several years. Although the wetland plants wither and die during dry times, their seeds lie dormant in the soil, waiting to germinate when the moisture returns. Wetlands do not have to be wet all year to be functional wetlands. Both seasonal and permanent wetlands are important for wildlife habitat, recreation, and as possible sources of carbon sequestration. This section very briefly describes the role remote sensing has played and can play in assessing and monitoring wetlands. It is by no means conclusive and will, we hope, stimulate further discussion.

The Role of Remote Sensing

Remote sensing has become an important tool in wetland management. A wide variety of remote-sensing sensors are available, from airborne devices to earth-observation satellites. Remote sensing can be used in a number of ways by providing input on identification, classification and inventory, ecological studies, hydrologic studies, and monitoring change. The hydrologic parameters of wetlands change regularly. Therefore, the timely, repetitive coverage made possible with earth-observation satellites are an attractive source of monitoring information.

The disadvantage of satellite data and spectral analysis is related to the natural heterogeneity of wetland communities and resulting vegetation gradients. There are many spectral classes in uplands that can duplicate those in wetlands. A variety of remote-sensing techniques can be used to identify, inventory and monitor wetlands once a decision has been made on the requirements of the classification. Considerations for classification include the purpose of the classification; how often it is updated; the spatial accuracy requirements; the minimum mapping unit; the significance of the wetland and upland interface boundary; whether vegetation composition is a requirement; whether seasonal wetlands are important for optimum data collection; whether the surficial connections between wetlands are important; and what the implications are of surrounding land use and land cover for recharge. The answers to these questions are necessary to determine which remote-sensing technique will be most useful.

Issues Affecting the use of Remote Sensing to Monitor Change

The development of research and operational applications has demonstrated the ability to extract useful information about vegetation composition, hydrology, and associated soils of wetlands from remote-sensing data. At present there are two remotely sensed data sets generated from LANDSAT Thematic Mapper (TM) satellite imagery of the prairie and parkland regions. In 1995, a land use and land cover classification was generated from 1994 LANDSAT-TM for the Western Grain Transportation Payout Program (WGTPP) administered by the federal Prairie Farm Rehabilitation Administration (PFRA). A wetland class was incorporated into this classification. The minimum mapping unit was one hectare.

Ducks Unlimited has also generated a wetland habitat inventory using LANDSAT-TM imagery. The minimum mapping unit was 0.09 hectares (1 pixel). A report prepared by Pole Star Geomatics, Ottawa, for Environment Canada, indicates that Ducks Unlimited's Habitat Inventory data provides the best broad-coverage wetlands information for the Canadian prairies. Although no accuracy assessment has ever been applied to the data, Ducks Unlimited field staff are continually reviewing the data and a high level of confidence exists in the wetland inventory.

Ducks Unlimited has indicated that 80 per cent of the wetlands on the prairie and aspen parkland region are less than one hectare. Many are seasonally or temporarily inundated with water. In question, however, is whether the present methods for classifying wetlands at a regional level can be used for monitoring change. Since many of the wetlands are less than one hectare, the spatial resolution of LANDSAT is likely insufficient.

Sources of high-resolution satellite imagery exist that could be used for monitoring change. Using a synergistic approach of combining imagery data sets — such as SPOT or IRS and RADARSAT fine beam mode data — would capture the seasonal and spatial information necessary for monitoring. A stratified sampling approach could then be applied to the present Ducks Unlimited baseline data, first to assess the accuracy of the stratified sample and then to refine the sample.