Continuing high spatial resolution data from the Landsat and SPOT satellites, passive microwave data from the special sensor/microwave imager (SSM/I) and continuing meteorological satellite coverage from the NOAA, GOES, GMS, and Meteosat series all mean that the remotely sensed techniques can continue to be employed and expanded upon. New sensors, particularly in the microwave region, promise great potential for hydrologie applications. There are several satellites, such as ERS-1/2 launched by the European Space Agency, the J-ERS-1 launched by the Japanese, and RADARSAT launched by the Canadians that will provide useful data for hydrologists. All carry single-polarization, single-frequency SARs. An additional satellite being planned that will have considerable hydrologie interest is the Tropical Rainfall Measurement Mission (TRMM) (Simpson et al., 1988).
The EOS (Earth Observational System) (Butler, 1988), and its counterpart European and Japanese platforms, will lead to considerable advances in the understanding of all the earth sciences, including hydrology. The EOS instruments of most interest to hydrologists would include the MODIS and AMSR; the latter is a microwave instrument with a C-band radiometer that should provide interesting data of the land surface moisture conditions. EOS also includes the organization of the data and of other earth science in an information system where time series of all the data will be readily available is also important. This data system will allow many types of data to be used simultaneously to calibrate or be assimilated into numerical models.
Future progress in the hydrological sciences will depend a great deal upon the availability of adequate data for model development and validation. Remote sensing can and should play a pivotal role in this progress. Without it, it is very possible that future progress in the hydrological sciences will be severely retarded if not completely stopped. With it, hydrological sciences should be able to advance rapidly and to successfully address some of the previously intractable problems. An issue that must be addressed is the modification or development of new models to specifically use remote-sensing data. For the most part, existing models have not been developed to effectively use remote-sensing data. A second point is that ground-based data are frequently available at shorter time intervals than remote-sensing data. This becomes important when simulating processes that are driven by the diurnal cycle.
Another very important issue that needs to be addressed by the hydrologic and remote-sensing communities is validation. We should not automatically assume that ground-based measurements provide the "truth." Ground-based data have an inherent weakness in that they are point measurements being applied to large, inhomo-geneous areas. There is a need to develop innovative approaches to validate not only the remote-sensing-derived products but also the application of water and energy balance models to large regions.
While remote-sensing systems generate large volumes of valuable spatial data, GIS offer an appropriate technology not only for efficient storage and retrieval of spatially referenced data but also for data manipulation and spatial analysis required in distributed hydrologic modeling. With the advent of an EOS suite of platforms and sensors, it is expected that the volume of data being received will require the use of fully integrated spatial information systems supported by knowledge-based techniques in all facets of data handling.
Future development of GIS application is controlled by the state of technology, and therefore assessing the probable developments is a difficult task. At the present time, the current level of integrated applications utilizes an environment largely free of the logistical considerations of data transfer between remote sensing and GIS. Over the next few years, more efforts need to be focused on the fundamental aspects of integration such as data generalization and accuracy specification. Several problems of a true integration of remote sensing and GIS could probably be solved by recognition that GIS and remote-sensing systems process and manage spatial information at different levels of representation. Ultimately, GIS and remote sensing should be viewed as one entity that will be concerned with handling and analyzing spatial hydrologic data. The unification of these technologies will lead to a synergistic integration of spatial data handling, and the final system would have more application capabilities than just the sum of the two.
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