Remote sensing and GIS for wetland inventory, mapping and change analysis

A multiple purpose wetland inventory is being developed and promoted through partnerships and specific analyses at different scales in response to past uncertainties and gaps in inventory coverage. A partnership approach is being promoted through the Ramsar Convention on Wetlands to enable a global inventory database to be compiled from individual projects and analyses using remote sensing and GIS. Individual projects that are currently part of this global effort are described. They include an analysis of the Ramsar sites' database to map the distribution of Ramsar sites across global ecoregions and to identify regions and wetland types that are under-represented in the database. Given the extent of wetland degradation globally, largely due to agricultural activities, specific attention is directed towards the usefulness of Earth Observation in providing information that can be used to more effectively manage wetlands. As an example, a further project using satellite data and GIS to quantify the condition of wetlands along the western coastline of Sri Lanka is described and trends in land use due to changes in agriculture, sedimentation and settlement patterns are outlined. At a regional scale, a project to map and assess, using remote sensing, individual wetlands used for agriculture in eight countries in southern Africa is also described. Land cover and the extent of inundation at each site is being determined from a multi-temporal data set of images as a base for further assessment of land use change. Integrated fully within these analyses is the development of local capacity to plan and undertake such analyses and in particular to relate the outcomes to wetland management and to compile data on the distribution, extent and condition of wetlands globally.     

Monitoring wetland changes with remote sensing: An East African example

Environmental managers need current, accurate information upon which to base decisions. Viable information, especially in developing countries, is often unavailable. Satellite remote sensing is an appropriate and effective data source for mapping the surface of the earth, including a variety of environmental features. Remote-sensing-derived information is enhanced by being one component within a geographic information system (GIS). These techniques were employed to study an expanding delta in East Africa.The Omo River flows from the Ethiopian Highlands into the northern end of Lake Turkana, creating a large delta extending between Ethiopia and Kenya. This isolated and unique wetland feature has expanded by over 500 sq km in the last 15 years as measured by space-borne remote sensing techniques and corroborated by low-altitude aircraft reconnaissance flights.The growth of the delta appears to be a function of both increased sedimentation and decreased lake levels and river flows. Within the delta there has been a selective decline in wildlife and an increase in human activity, both pastoral and agricultural. The uniqueness of this isolated delta suggests that consideration be given to its possible protection and management.On leave from Department of Geography, George Mason University, Fairfax, Virginia 22030, USA     

Using remote sensing technique to study soil sedimentation flow

Soils will behave differently when used for agriculture, forestry, and other purposes and must be managed differently. The difference is most evident in the Inverbrackie Creek catchment area in South Australia where the study reported in this article was conducted and where the soils are used extensively for grazing and dairy farming. This catchment covers an area of 8.38 km², comprising an undulating upland plain with irregularly high hills and broad interfluves. Previous information-gathering methods used to model the catchment's hydrologic activity have been derived from the downstream pluviographic point-source technique. The model input samples obtained by this technique are not truly representative of the catchment. The potential for using remote sensing color infrared imagery to delineate the areas contributing to soil sediment flow is demonstrated as a better alternative to obtaining representative samples to model this activity. This article reports on part of the work supported by the University Research Grant, University of Adelaide.     

The role of remote sensing in hydrological modelling of the Okavango Delta, Botswana

A coupled surface water-groundwater model of the Okavango Delta has been built based on the United States Geological Survey software MODFLOW 2000 including the SFR2 package for stream-flow routing. It will provide a new tool for evaluating water management and climate change scenarios. The delta's size and limited accessibility make direct, on the ground data acquisition difficult. Remote sensing methods are the most promising source of acquiring spatially distributed data for both model input parameters and calibration. Topography, aquifer thickness, channel positions, evapotranspiration and precipitation data are all based on remote sensing. Simulated flooding patterns are compared to patterns derived from visible to thermal NOAA-AVHRR data and microwave radar ENVISAT-ASAR data.     

Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data

The Mekong River Basin is considered to be the second most species rich river basin in the world. The 795,000 km(2) catchment encompasses several ecoregions, incorporating biodiverse and productive wetland systems. Eighty percent of the rapidly expanding population of the Lower Mekong Basin (LMB), made up in part by Lao PDR, Thailand, Cambodia and Viet Nam, live in rural areas and are heavily reliant on wetland resources. As the populations of Cambodia and Lao PDR will double in the next 20 years, pressure on natural resources and particularly wetlands can only increase. For development planning, resource and conservation management to incorporate wetland issues, information on the distribution and character of Mekong wetlands is essential. The existing but outdated wetland maps were compiled from secondary landuse-landcover data, have limited coverage, poor thematic accuracy and no meta-data. Therefore the Mekong River Commission (MRC) undertook to produce new wetland coverage for the LMB. As resources, funding and regional capacity are limited, it was determined that the method applied should use existing facilities, be easily adaptable, and replicable locally. For the product to be useful it must be accepted by local governments and decision makers. The results must be of acceptable accuracy (>75%) and the methodology should be relatively understandable to non-experts. In the first stage of this exercise, field survey was conducted at five pilot sites covering a range of typical wetland habitats (MRC wetland classification) to supply data for a supervised classification of Landsat ETM images from the existing MRC archive. Images were analysed using ERDAS IMAGINE and applying Maximum Likelihood Classification. Field data were reserved to apply formal accuracy assessment to the final wetland habitat maps, with resulting accuracy ranging from 77 to 94%. The maps produced are now in use at a Provincial and National level in three countries for resource and conservation planning and management applications, including designation of a Ramsar wetland site of international importance.     

Remote sensing water observation for supporting Lake Victoria weed management

This paper aims to assess the suitability of remote sensing for enhancing the management of water body resources and for providing an inexpensive way to gather, on a wide area, weed infestation extent and optical parameter linked to the water body status. Remotely sensed satellite images and ancillary ground true data were used to produce land cover maps, trough classification techniques, and water compounds maps, applying radiative transfer models. The study proposed within the framework of the cooperation between Italian Foreign Affair Ministry (through the University of Rome) and Kenyan Authorities has been carried out on the Kenyan part of the Lake Victoria. This lake is one of the largest freshwater bodies of the world where, over the last few years environmental challenges and human impact have perturbed the ecological balance affecting the biodiversity. The objective of this research study is to define the thematic products, retrievable from satellite images, like weed abundance maps and water compound concentrations. These products, if provided with an appropriate time frequency, are useful to identify the preconditions for the occurrence of hazard events like abnormal macrophyte proliferation and to develop an up-to-date decision support system devoted to an apprised territory, environment and resource management.     

An inventory of wetland impoundments in the coastal zone of Louisiana,USA: Historical trends

We inventoried wetland impoundments in the Louisiana, USA, coastal zone from the late 1900s to 1985. Historically, impoundment of wetlands for reclamation resulted in direct wetland loss after levees (dikes) failed and the impounded area was permanently flooded, reverting not to wetland, but to open-water habitat. A current management approach is to surround wetlands by levees and water control structures, a practice termed semi-impoundment marsh management. The purpose of this semi-impoundment is to retard saltwater intrusion and reduce water level fluctuations in an attempt to reduce wetland loss, which is a serious problem in coastal Louisiana. In order to quantify the total impounded area, we used historic data and high-altitude infrared photography to map coastal impoundments. Our goal was to produce a documented inventory of wetlands intentionally impounded by levees in the coastal zone of Louisiana in order to provide a benchmark for further research. We inventoried 370,658 ha within the coastal zone that had been intentionally impounded before 1985. This area is equal to about 30% of the total wetland area in the coastal zone. Of that total area, approximately 12% (43,000 ha) is no longer impounded (i.e., failed impoundments; levees no longer exist or only remnants remain). Of the 328,000 ha still impounded, about 65% (214,000 ha) is developed (agriculture, aquaculture, urban and industrial development, and contained spoil). The remaining 35% (114,000 ha) of impoundments are in an undeveloped state (wetland or openwater habitat). In December 1985, approximately 50% (78,000 ha) of the undeveloped and failed impoundments were open-water habitat. This inventory will allow researchers to monitor future change in land-water ratios that occur within impounded wetlands and thus to assess the utility of coastal wetland management using impoundments.     

Soil and water characteristics of a young surface mine wetland

Coal companies are reluctant to include wetland development in reclamation plans partly due to a lack of information on the resulting characteristics of such sites. It is easier for coal companies to recreate terrestrial habitats than to attempt experimental methods and possibly face significant regulatory disapproval. Therefore, we studied a young (10 years) wetland on a reclaimed surface coal mine in southern Illinois so as to ascertain soil and water characteristics such that the site might serve as a model for wetland development on surface mines. Water pH was not measured because of equipment problems, but evidence (plant life, fish, herpetofauna) suggests suitable pH levels. Other water parameters (conductivity, salinity, alkalinity, chloride, copper, total hardness, iron, manganese, nitrate, nitrite, phosphate, and sulfate) were measured, and only copper was seen in potentially high concentrations (but with no obvious toxic effects). Soil variables measured included pH, nitrate, nitrite, ammonia, potassium, calcium, magnesium, manganese, aluminum, iron, sulfate, chloride, and percent organic matter. Soils were slightly alkaline and most parameters fell within levels reported for other studies on both natural and manmade wetlands. Aluminum was high, but this might be indicative more of large amounts complexed with soils and therefore unavailable, than amounts actually accessible to plants. Organic matter was moderate, somewhat surprising given the age of the system.     

A methodology to estimate the denitrifying capacity of a riparian wetland

Numerous studies have shown that riparian wetlands can play an important role in reducing nitrate concentrations before the ground water discharges into streams. Denitrification has been identified as an important process for this removal. Several approaches have been proposed to predict the denitrifying removal capacity of a riparian wetland, but no widely used tool exists to precisely quantify this capacity at the landscape scale. We propose such a methodology based on modeling the spatial variation of soil-water interactions in the entire riparian wetland. Mean values of denitrification enzyme activity (DEA) within three soil-denitrifying classes were 604, 212, and 24 ng N g(-1) h(-1) for Classes 3, 2, and 1, respectively. The study area, having a ground surface of about 15000 m2, was underlain by an aquifer with a calculated volume of 60000 m3, less than 10000 m3 of which corresponded to active denitrifying horizons (Classes 2 and 3). By volume, approximately 30% of Class 3 and 70% of Class 2 were interacting with ground water. The denitrifying removal capacity of our wetland was calculated to be about 1.8 kg N m(-2) yr(-1). The calculated denitrifying capacity of our site was less than expected. This is due to the fact that not all ground water interacts with the horizons having the highest denitrifying capacity. Thus, we show that whatever the system is, specific local pedological and hydrogeological conditions and their interactions are paramount in controlling the denitrification process.     

An introduction to digital methods in remote sensing of forested ecosystems: Focus on the Pacific Northwest,USA

Aerial photography has been routinely used for several decades by natural resource scientists and managers to map and monitor the condition of forested landscapes. Recently, along with the emergence of concepts in managing forests as ecosystems, has come a significant shift in emphasis from smaller to larger spatial scales and the widespread use of geographic information systems. These developments have precipitated an increasing need for vegetation information derived from other remote sensing imagery, especially digital data acquired from high-elevation aircraft and satellite platforms. This paper introduces fundamental concepts in digital remote sensing and describes numerous applications of the technology. The intent is to provide a balanced, nontechnical view, discussing the shortcomings, successes, and future potential for digital remote sensing of forested ecosystems.     

Quantitative assessment of tidal wetlands using remote sensing

Effective management of tidal wetlands requires periodic data on the boundaries, extent, and condition of the wetlands. In many states, wetlands are defined wholly, or in combination with other criteria, by the presence of particular emergent halophytic plants. Many important characteristics of the wetlands ecosystem are related directly to the production of emergent plant material or may be inferred from knowledge of the distribution of emergent plant species. Remote-sensing techniques have been applied to mapping of the distribution of wetland vegetation but not to quantitative evaluation of the condition of that vegetation.Recent research in the tidal wetlands of Delaware and elsewhere has shown that spectral canopy reflectance properties can be quantitatively related to the emergent green biomass ofSpartina alterniflora (salt marsh cord grass) throughout the peak growing season (April through September, in Delaware). Periodic measurements of this parameter could be applied to calculations of net aerial primary productivity for large areas ofS. alterniflora marsh in which conventional harvest techniques may be prohibitively time consuming. The method is species specific and, therefore, requires accurate discrimination ofS. alterniflora from other vegetation types. Observed seasonal changes in species spectral signatures are shown to have potential for improving multispectral categorization of tidal wetland vegetation types.     

Using Landsat data to estimate evapotranspiration of winter wheat

An evapotranspiration (ET) model that accurately estimates daily water use and soil moisture on a regional basis is required for many agricultural and hydrological studies. The model should use meterological data that are readily available and crop information that is responsive to the changing vigor of the plants.We evaluated an ET model with a weighing lysimeter and then applied it to winter wheatfields at four Kansas locations. Model inputs are solar radiation, temperature, precipitation, and leaf area index (LAI); included in the outputs are estimates of transpiration, evaporation, and soil moisture. An equation was developed to estimate LAI from Landsat data. Because LAI can be estimated from satellites, the ET model can potentially be used on a regional basis.     

A spatial-statistical approach for modeling the effect of non-point source pollution on different water quality parameters in the Velhas river watershed--Brazil

In this article, a methodology for evaluating the effect of land use/land cover on the quality of nearby stream water in a semiarid environment is described and tested on a large watershed in Southeastern Brazil. The approach aims at identifying the width of the riparian area having the strongest effect on different water quality parameters. The land use/land cover data were generated from remotely sensed data while water quality point data were supplied by a government agency. Testing was conducted for both the rainy and dry seasons in an effort to understand the direct effect of surface runoff. The approach combines cartographic modelling using a geographical information system (GIS) and statistics to establish the strength of the relationship between water quality, land use and the distance from the stream. Results suggest a strong relationship between land use/land cover and turbidity, nitrogen and fecal coliforms. They also suggest that each of these parameters has a unique behavior when distance from the stream is considered. Finally, although it was expected that the models would apply better during the wet season, some parameters had the opposite behavior and displayed a better fit during the dry season.     

Soil erosion and non-point source pollution impacts assessment with the aid of multi-temporal remote sensing images

Soil erosion associated with non-point source pollution is viewed as a process of land degradation in many terrestrial environments. Careful monitoring and assessment of land use variations with different temporal and spatial scales would reveal a fluctuating interface, punctuated by changes in rainfall and runoff, movement of people, perturbation from environmental disasters, and shifts in agricultural activities and cropping patterns. The use of multi-temporal remote sensing images in support of environmental modeling analysis in a geographic information system (GIS) environment leading to identification of a variety of long-term interactions between land, resources, and the built environment has been a highly promising approach in recent years. This paper started with a series of supervised land use classifications, using SPOT satellite imagery as a means, in the Kao-Ping River Basin, South Taiwan. Then, it was designed to differentiate the variations of eight land use patterns in the past decade, including orchard, farmland, sugarcane field, forest, grassland, barren, community, and water body. Final accuracy was confirmed based on interpretation of available aerial photographs and global positioning system (GPS) measurements. Finally, a numerical simulation model (General Watershed Loading Function, GWLF) was used to relate soil erosion to non-point source pollution impacts in the coupled land and river water systems. Research findings indicate that while the decadal increase in orchards poses a significant threat to water quality, the continual decrease in forested land exhibits a potential impact on water quality management. Non-point source pollution, contributing to part of the downstream water quality deterioration of the Kao-Ping River system in the last decade, has resulted in an irreversible impact on land integrity from a long-term perspective.     

Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management

The Lower Rio Grande Valley (LRGV) of south Texas is an agriculturally rich area supporting intensive production of vegetables, fruits, grain sorghum, and cotton. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yields. Intensive agricultural activities in past decades might have caused potential contamination of soil, surface water, and groundwater due to leaching of pesticides in the vadose zone. In an effort to promote precision farming in citrus production, this paper aims at developing an airborne multispectral technique for identifying tree health problems in a citrus grove that can be combined with variable rate technology (VRT) for required pesticide application and environmental modeling for assessment of pollution prevention. An unsupervised linear unmixing method was applied to classify the image for the grove and quantify the symptom severity for appropriate infection control. The PRZM-3 model was used to estimate environmental impacts that contribute to nonpoint source pollution with and without the use of multispectral remote sensing and VRT. Research findings using site-specific environmental assessment clearly indicate that combination of remote sensing and VRT may result in benefit to the environment by reducing the nonpoint source pollution by 92.15%. Overall, this study demonstrates the potential of precision farming for citrus production in the nexus of industrial ecology and agricultural sustainability.     

An analysis of urban development and its environmental impact on the Tampa Bay watershed

Urbanization has transformed natural landscapes into anthropogenic impervious surfaces. Urban land use has become a major driving force for land cover and land use change in the Tampa Bay watershed of west-central Florida. This study investigates urban land use change and its impact on the watershed. The spatial and temporal changes, as well as the development density of urban land use are determined by analyzing the impervious surface distribution using Landsat satellite imagery. Population distribution and density are extracted from the 2000 census data. Non-point source pollution parameters used for measuring water quality are analyzed for the sub-drainage basins of Hillsborough County. The relationships between 2002 urban land use, population distribution and their environmental influences are explored using regression analysis against various non-point source pollutant loadings in these sub-drainage basins. The results suggest that strong associations existed between most pollutant loadings and the extent of impervious surface within each sub-drainage basin in 2002. Population density also exhibits apparent correlations with loading rates of several pollutants. Spatial variations of selected non-point source pollutant loadings are also assessed.     

Use of Radar Remote Sensing (RADARSAT) to Map Winter Wetland Habitat for Shorebirds in an Agricultural Landscape

Many of todays agricultural landscapes once held vast amounts of wetland habitat for waterbirds and other wildlife. Successful restoration of these landscapes relies on access to accurate maps of the wetlands that remain. We used C-band (5.6-cm-wavelength), HH-polarized radar remote sensing (RADARSAT) at a 38° incidence angle (8-m resolution) to map the distribution of winter shorebird (Charadriiformes) habitat on agricultural lands in the Willamette Valley of western Oregon. We acquired imagery on three dates (10 December 1999, 27 January 2000, and 15 March 2000) and simultaneously collected ground reference data to classify radar signatures and evaluate map accuracy of four habitat classes: (1) wet with 50% vegetation (considered optimal shorebird habitat), (2) wet with > 50% vegetation, (3) dry with 50% vegetation, and (4) dry with > 50% vegetation. Overall accuracy varied from 45 to 60% among the three images, but the accuracy of focal class 1 was greater, ranging from 72 to 80%. Class 4 coverage was stable and dominated maps (40% of mapped study area) for all three dates, while coverage of class 3 decreased slightly throughout the study period. Among wet classes, class 1 was most abundant (about 30% coverage) in December and January, decreasing in March to approximately 15%. Conversely, class 2 increased dramatically from January to March, likely due to transition from class 1 as vegetation grew. This approach was successful in detecting optimal habitat for shorebirds on agricultural lands. For modest classification schemes, radar remote sensing is a valuable option for wetland mapping in areas where cloud cover is persistent. Also, Department of Fisheries and Wildlife, Oregon State University, Corvallis, Oregon 97331, USA     

Use of Radar Remote Sensing (RADARSAT) to Map Winter Wetland Habitat for Shorebirds in an Agricultural Landscape

Many of todays agricultural landscapes once held vast amounts of wetland habitat for waterbirds and other wildlife. Successful restoration of these landscapes relies on access to accurate maps of the wetlands that remain. We used C-band (5.6-cm-wavelength), HH-polarized radar remote sensing (RADARSAT) at a 38° incidence angle (8-m resolution) to map the distribution of winter shorebird (Charadriiformes) habitat on agricultural lands in the Willamette Valley of western Oregon. We acquired imagery on three dates (10 December 1999, 27 January 2000, and 15 March 2000) and simultaneously collected ground reference data to classify radar signatures and evaluate map accuracy of four habitat classes: (1) wet with 50% vegetation (considered optimal shorebird habitat), (2) wet with > 50% vegetation, (3) dry with 50% vegetation, and (4) dry with > 50% vegetation. Overall accuracy varied from 45 to 60% among the three images, but the accuracy of focal class 1 was greater, ranging from 72 to 80%. Class 4 coverage was stable and dominated maps (40% of mapped study area) for all three dates, while class 3 coverage decreased slightly throughout the study period. Among wet classes, class 1 was most abundant (30% coverage) in December and January, decreasing in March by 15%. Conversely, class 2 increased dramatically from January to March, likely due to transition from class 1 as vegetation grew. This approach was successful in detecting optimal habitat for shorebirds on agricultural lands. For modest classification schemes, radar remote sensing is a valuable option for wetland mapping in areas where cloud cover is persistent. Also, Department of Fisheries and Wildlife, Oregon State University, Corvallis, Oregon 97331, USA     

Temporal changes in wetland landscapes of a section of the St. Lawrence River,Canada

Historical aerial photographs (from 1946 through 1983) were used to study and describe the nature and extent of changes in wetland vegetation of a section of the St. Lawrence River and to evaluate the relative importance of water level, fire, and vegetational development as causal factors of these historical changes. Data were encoded and analyzed using a geographical information system, autocorrelation, and Mantel tests. Results show three temporal patterns in wetland dynamics. First, some wetland zones have been reduced by human activities (urbanization, landfilling, canal dredging). The second group consists of wetland areas that remain stable and do not change over time. They are generally protected sites artificially maintained by water-level control. A third situation has occurred in the Lake Saint-François National Wildlife Area, where no significant wetland losses were detected, but where landscape structure has changed greatly. Modeling with Mantel tests suggests that, in the latter case, these changes in wetland landscape are related to the suppression of burning (fires set deliberately by Indians) since the purchase of the territory by the Canadian federal government. This situation has caused rapid replacement of wet meadows byAlnus rugosa scrub and a possible decline in habitat diversity.     

Aerospace wetland monitoring by hyperspectral imaging sensors: a case study in the coastal zone of San Rossore Natural Park

The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces.