Fresh water is arguably the most vital resource for many aspects of a healthy and stable environment. Monitoring the extent of surface water enables resource managers to detect perturbations and long term trends in water availability, and set consumption guidelines accordingly. Potential end-users of water-related observations are numerous and reflect society as a whole. They encompass scientists and managers at all levels of government, aboriginal groups, water/power utility managers, farmers, planners, engineers, hydrologists, medical researchers, climate scientists, recreation enthusiasts, public school to postgraduate students, many special interest groups and the general public. Water data and analyses generate information products that benefit water resources planning and management, engineering design, plant operations, navigation activities, health research, water quality assessments and ecosystem management. As well, they serve as inputs for flood and drought warnings and weather and climate prediction models. Radar data in general, and RADARSAT in particular, are very good for detecting open surface water and have been used operationally for flood monitoring in many countries. Significant radar data archives now exist to analyse seasonal, annual and decadal trends, in order to attain a better understanding of the freshwater cycle. Radar data are also useful for wetland classification and soil moisture estimation. With the increasing pressure on water resources, both from a quality as well as a quantity perspective, the need will continue to increase for reliable information.RADARSAT-2 has several innovations that will enhance the ability to provide useful information about water resources. This paper provides an overview of the use of radar in general, and RADARSAT-2 in particular, for the generation of information products useful to water resource managers.

This paper describes initial steps toward building an integrated earth sensing capability that encompasses both remote and in-situ sensing. Initial work has focused on the demonstration of in-situ sensorweb prototypes in autonomous remote operation in the context of monitoring applications in Earth and environmental science. The paper discusses integrated Earth sensing and sensorwebs, and reports on an in-situ sensorweb prototype demonstration in support of flood hazard monitoring in Manitoba, as well as on development plans for a more advanced, heterogeneous sensorweb in support of drought severity and rangeland/crop vigour monitoring in Alberta.

Environmental vector-borne diseases are plaguing much of the world and are a serious concern on a global scale. Many of these diseases are clearly associated with specific environmental conditions and landscape variables. The science and technology associated with remote sensing and geographic information systems (GIS) are suitable for identifying these environmental targets. Since vector-borne diseases are most often found in tropical environments and during rainy seasons with persistent cloud cover conditions, radar is an important sensor for monitoring and mapping the environmental indicators of disease. Preliminary investigations using RADARSAT-1 C-band horizontal transmit, horizontal receive (C-HH) imagery have proven especially useful for identifying wetland habitats and flooded areas. It is anticipated that the advancements associated with upcoming RADARSAT-2 sensors will improve the science of mapping vector-borne disease risk in tropical areas, particularly with access to increased spatial and temporal resolution and fully polarimetric data. This paper discusses the concept of using radar remote sensing for epidemiology applications, results using RADARSAT-1 for malaria risk mapping in coastal Kenya, and expected results with the advanced capabilities of RADARSAT-2.

Mapping and monitoring water quantity and quality is an important activity for resource management. Many applications such as agriculture, flood forecasting, urban development, and wetland conservation require routine monitoring of hydrological parameters. As hydrological resources are dynamic, timely information is essential for the accuracy required in these applications. The increased repeat time and larger spatial coverage of remote sensing tools give water resource managers up-to-date information over their areas of interest. Synthetic aperture radar (SAR) has been successfully utilized to monitor hydrological parameters because of its sensitivity to moisture. Polarimetric SAR systems provide many dimensions of information as polarization images can be synthesized from the phase information. The Canada Centre for Remote Sensing has been involved with numerous research projects aimed at developing SAR techniques for monitoring hydrological resources. Four main hydrological features are discussed: soil moisture, snow, wetlands, and flooding.

Estimating the amount of water stored in a soil profile is essential in most water management projects and for assessing the hydrologic state of a basin. It determines infiltration during a rainfall event and controls evapotranspiration between storms. Rarely, however, are soil moisture data available for model input. In many cases, particularly watershed scale monitoring or modelling, soil moisture is inferred from more easily obtainable hydrologic variables such as rainfall, runoff and temperature. As such, there is a strong need for procedures to estimate soil moisture in a watershed independently from the models. These procedures must provide not only basin average estimates but also the spatial distribution within a basin in order to meet the requirements of emerging distributed models. Active and passive microwave imagery are both candidate sources for these data. Active SAR imagery, with its high resolution, is particularly attractive for use in areas of mixed land cover. This paper addresses the potential of Radarsat and Envisat ASAR Synthetic Aperture Radar (SAR) data to extract information on soil moisture at the watershed scale. Multiple Radarsat and Envisat data acquisitions collected over the Roseau River watershed, located in Manitoba, for the period of September 2002 through June 2003 were analyzed in relation to ground observations and meteorological conditions. A method was then developed to produce soil moisture maps for input to a hydrological model for flood forecasting

The presence of snow cover affects the regional energy and water balance, thus having a significant impact on the global climate system. Temporal knowledge of the onset of snow melt and snow water equivalent (SWE) values are important variables in the prediction of flooding, as well as water resource applications such as reservoir management and agricultural activities. Microwave remote sensing techniques have been effective for monitoring snow pack parameters (snow extent, depth, water equivalent, wet/dry state). Coincident ground data, airborne polarimetric C-band (5.3 GHz) Synthetic Aperture Radar (SAR) and passive microwave radiometer data (19, 37 and 85 GHz) were collected on four dates (1 December 1997, 6 March 1998, 12 March 1998 and 9 March 1999) over two flight lines in Eastern Ontario, Canada. The multitemporal, multi-sensor data were analysed for changes in SAR polarimetric signatures and microwave brightness temperatures as a function of changing snow pack parameters. Results indicate that certain parameters such as linear polarizations and pedestal height are sensitive to changes in snow pack parameters, and respond differently to various snow conditions. SWE values derived from the passive microwave brightness temperatures compare well with ground measurements, with the exception of low snow volume and in the presence of significant ice layers.

Malaria remains one of the greatest killers of human beings, particularly in the developing world. The World Health Organization has estimated that over one million cases of Malaria are reported each year, with more than 80% of these found in Sub-Saharan Africa. The anopheline mosquito transmits malaria, and breeds in areas of shallow surface water that are suitable to the mosquito and parasite development. These environmental factors can be detected with satellite imagery, which provide high spatial and temporal coverage of most of the earth's surface. The combined use of remote sensing and GIS provides a strong tool for monitoring environmental conditions that are conducive to malaria, and mapping the disease risk to human populations. Since many vector-borne diseases such as malaria are prevalent in tropical areas, persistent cloud cover often presents a challenge to remote sensing operations. Radar remote sensing has the capability of penetrating clouds, providing a solution to the cloud-cover problem often experienced with optical satellite remote sensing. This research investigates the use of RADARSAT-1 data for monitoring and mapping malaria risk in coastal Kenya. An object-oriented approach to image classification is taken in order to circumvent some of the limitations of traditional pixel-based classification of radar imagery. GIS routines are used to assess how classified land cover variables relate to the presence and abundance of malaria-carrying mosquitoes and their proximity to populated areas, in order to generate a malaria risk map. I. STUDY AREA The study site is located along the eastern coastal plain for Kenya, near the town of Mombasa, where malaria is a severe health concern. The environment consists of a mix of indigenous forest, grassland savanna, mangrove swamps, and wetland vegetation. Agriculture plantations (mainly coconut, sisal and cashews) are also found along the coast. The ground elevation ranges from sea level to approximately 400 metres above sea-level (ASL) and there are several small rivers that flow from the highlands to the Indian Ocean. Mosquito larval habitats in this area are diverse and change with the season. During the dry season, some rivers and streams become completely dry, while others have reduced flow and numerous isolated, residual pools of water in the main riverbed. Portions of mangrove swamps stay permanently flooded throughout the whole year. Seasonal swamps are also present and some are used for rice cultivation during the rainy season. These land cover types are particularly conducive to mosquito breeding.

The potential of high and low resolution polar and geostationary orbital Earth Resource Satellites have been shown to be an excellent tool for providing hydrological information. Operational geostationary meteorological satellites have the capability to provide precipitation estimates and soil wetness indices at the global scale, while polar orbital satellites can provide the quantification of catchment physical characteristics, such as topography and land use, and catchment variables such as soil moisture and snow cover. There have been many demonstrations of the operational use of these satellites for detailed monitoring and mapping of floods and post-flood damage assessment. This paper addresses the use of Earth Observation satellites for flood managers, flash flood analysis and prediction, and the user community. A remote sensing management cycle is presented that involves: (1) prevention where history, corporate memory, and climatology are important; (2) mitigation that insulates people or infrastructure from hazards; (3) pre-flood which is the preparation and forecast stage where remote sensing is essential; (4) response (during the flood) where "actions to be taken is of key importance and weather NOWCASTS (0-3 hour prediction of precipitation) using remote sensing is extremely useful; and (5) recovery (post flood) which is the post-mortem stage where damage assessment, procedures, and numerical weather prediction and hydrological models are validated. Gaps in our remote sensing capabilities, future improvements and requirements, and the requirement for demonstration projects to illustrate and educate the end-user community on the capabilities of satellite remotely sensed data to provide information during all of the phases of the disaster cycle are discussed.

Results from an investigation on the evaluation of RADARSAT (C‐HH) imagery for monitoring ice growth and decay, and related processes of shallow sub‐Arctic (tundra and forest) lakes in northern Manitoba, Canada, are presented. Field observations on the structural and stratigraphic characteristics of snow and ice from four lake sites are used in support of the interpretation of changes in synthetic aperture radar backscatter intensity as a function of time and incidence angle (20–49°). Results show that bubble inclusions, most of which are tubular and oriented in the direction of growth, strongly influence backscatter intensity from floating ice in RADARSAT Standard beam mode imagery. It is shown that radar return can vary considerably as a function of incidence angle. Differences of as much as 6·5 dB were observed for the same ice cover when observed at steeper (20–35°) compared with shallower (35–49°) incidence angles. During the early stages of ice growth and/or when the ice volume contains a small amount of tubular bubbles, backscatter intensity from the floating ice measured at shallower incidence angles (35–49°) is similar to that observed from the grounded ice at any incidence angle (−17 to −11 dB). A strong decrease in backscatter was observed at all sites during spring thaw and was explained by the microwave signal being absorbed by the wet snow cover and by specular reflection from the standing water (ponds) on the lake ice surface. With its multiple beam mode configurations, RADARSAT offers an improved temporal coverage over ERS‐1/2, thus making it possible to determine more precisely freeze‐up and break‐up dates, and timing of bottom freezing from shallow Arctic and sub‐Arctic lakes. Copyright © 2002 John Wiley & Sons, Ltd.

Although the interaction between linear polarized microwaves and agricultural targets has been studied extensively, far less is understood about the added information provided from polarimetric Synthetic Aperture Radars (SARs). Using 1994 Spaceborne Imaging Radar-C (SIR-C) data, this study examines the sensitivity of linear polarizations and polarimetric parameters to conditions present on agricultural fields during the period of preplanting and postharvest. The polarimetric parameters investigated include circular polarized backscatter, pedestal height, and co-polarized phase differences (PPD). The co-polarizations signature plots are also discussed. Results indicate that the dominant scattering mechanism from these fields varies depending on the type and amount of residue cover, and whether the crop had been harvested. Radar parameters most sensitive to volume and multiple scattering perform best at characterizing these surface conditions. These parameters are the pedestal height, as well as the linear cross-polarization (HV) and the circular co-polarizations (RR). The co-polarizations signature plots and the standard deviation associated with the PPD are also useful in categorizing these cover types. However, the field average PPD provides little information on residue and soil characteristics.

Following the 1997 flood, the Red River Basin Task Force recommended the development of an international geospatial database. This database will consist of remotely sensed and GIS data that will eventually be implemented in the decision support system, to improve forecasting and modelling of the Red River basin. This project demonstrates the cross border issues and challenges encountered in the process of merging roads and hydrography vectors from Canadian and US federal governments. The major differences in the datasets between countries are: classification systems, details of attributes, validation dates, and mapping scales. Discrepancies include: horizontal offsets, feature density variations, feature discontinuities, and attribute discontinuities at the border. Flood extent vectors were extracted from RADARSAT images to provide an overview of flood extent at specific time within the Red River basin.

The incidence and spread of vector-borne infectious diseases are increasing concerns in many parts of the world. Earth observation techniques provide a recognised means for monitoring and mapping disease risk as well as correlating environmental indicators with various disease vectors. Because the areas most impacted by vector-borne disease are remote and not easily monitored using traditional, labour intensive survey techniques, high spatial and temporal coverage provided by spaceborne sensors allows for the investigation of large areas in a timely manner. However, since the majority of infectious diseases occur in tropical areas, one of the main barriers to earth observation techniques is persistent cloud-cover.Synthetic Aperture Radar (SAR) technology offers a solution to this problem by providing all-weather, day and night imaging capability. Based on SAR's sensitivity to target moisture conditions, sensors such as RADARSAT-1 can be readily used to map wetland and swampy areas that are conducive to functioning as aquatic larval habitats. Irrigation patterns, deforestation practises and the effects of local flooding can be monitored using SAR imagery, and related to potential disease vector abundance and proximity to populated areas.This paper discusses the contribution of C-band radar remote sensing technology to monitoring and mapping malaria. Preliminary results using RADARSAT-1 for identifying areas of high mosquito (Anopheles gambiae s.l.) abundance along the Kenya coast will be discussed. The authors consider the potential of RADARSAT-1 data based on SAR sensor characteristics and the preliminary results obtained. Further potential of spaceborne SAR data for monitoring vector-borne disease is discussed with respect to future advanced SAR sensors such as RADARSAT-2.

In this paper, we preview and demonstrate how the technical improvements included in RADARSAT-2 will impact the system's potential utility for 32 applications in the fields of agriculture, cartography, disaster management, forestry, geology, hydrology, oceans, and sea and land ice.

The Flood Information Management System (FIMS) represents the confluence of several cutting edge technologies and methodologies. The FIMS website combines real-time in situ data, internationally recognized hydraulic and hydrologic models, multiresolution remotely sensed images and a customized Web interface all within one coherent and easily accessible Internet location. The FIMS prototype development focused on two river basins with active river monitoring programs, the Fraser River in British Columbia and the St. John River in New Brunswick. Near-real-time sensors in both these river basins provide FIMS with its water quantity baseline data. Web-based software engineering provides the bridge between hydraulic/hydrologic models and the graphical user interfaces used to display the near-real-time geospatial results on the Internet. Users are able to interactively visualise Ikonos, Radarsat, and Landsat image maps of their areas, visualize hydrometric station locations and actual flow data, then run models that show flood hazard, risk and extents based on current and predicted flows.

Estimating the amount of water stored in a soil profile is essential in most water management projects and for assessing the hydrologic state of a basin. It determines infiltration during a rainfall event and controls evapotranspiration between storms. Rarely, however, are soil moisture data available for model input. In many cases, particularly watershed scale monitoring or modelling, soil moisture is inferred from more easily obtainable hydrologic variables such as rainfall, runoff and temperature. As such, there is a strong need for procedures to estimate soil moisture in a watershed independently from the models. These procedures must provide not only basin average estimates but also the spatial distribution within a basin in order to meet the requirements of emerging distributed models. Active and passive microwave imagery are both candidate sources for these data. Active SAR imagery, with its high resolution, is particularly attractive for use in areas of mixed land cover. This paper addresses the potential of Radarsat to extract information on soil moisture in pastures in a mixed landcover watershed located in eastern Ontario, Canada. A series of 6 Radarsat Standard Beam Mode 1 images covering the watershed for the period of September 2000 through July 2001 were analyzed in relation to ground observations, weather radar and meteorological conditions. A method was then developed to produce soil moisture maps for input to a hydrological model.

Soil moisture information is an important parameter in hydrological modelling, although providing reliable data is difficult due to its spatial variability and dynamic nature. The ability to estimate soil moisture from synthetic aperture radar (SAR) has been the topic of numerous investigations. To date, most of these investigations have been limited to single or multiple linear polarized configurations. However, Radarsat-2 will be launched in 2004 and will have fully polarimetric C-Band SAR capability. In preparation for a new generation of spaceborne polarimetric SARs, Environment Canada's Convair 580 airborne polarimetric C-band SAR acquired data over an agricultural area west of Ottawa, Canada on September 22, 2000, April 26, 2001 and May 20, 2001. Coincident ground measurements (soil moisture, biomass, and surface roughness) were collected over pasture on all dates and bare fields in the spring of 2001. Analysis includes linear polarizations (/spl sigma//spl deg//sub HH/, /spl sigma//spl deg//sub VV/ /spl sigma//spl deg//sub HV/), circular polarizations (/spl sigma//spl deg//sub RR/, /spl sigma//spl deg//sub RL/, /spl sigma//spl deg//sub LL/), as well as fully polarimetric parameters such as pedestal height, total power, phase difference, and polarimetric signatures. This paper presents preliminary results of the September 22, 2002 data.

An In-Situ Sensor Measurement Assimilation Program is being established at the Canada Centre for Remote Sensing. This paper highlights the goals and general framework of this new, strategic initiative. The in-situ sensing framework is illustrated conceptually in the context of three remote sensing applications. The paper also looks ahead to the use of sensor webs and sensor pods, as technology moves towards the concept of a global virtual presence.