Surveying earth resources by remote sensing from satellites

This paper reviews the techniques and recent results of orbital remote sensing, with emphasis on Landsat and Skylab imagery. Landsat (formerly ERTS) uses electronic sensors (scanners and television) for repetitive observations with moderate ground resolution. The Skylab flights used a wider range of electro-optical sensors and returned film cameras with moderate and high ground resolution. Data from these programs have been used successfully in many fields. For mineral resources, satellite observations have proven valuable in geologic mapping and in exploration for metal, oil, and gas deposits, generally as a guide for other (conventional) techniques. Water resource monitoring with satellite data has included hydrologic mapping, soil moisture studies, and snow surveys. Marine resources have been studied, with applications in the fishing industry and in ocean transportation. Agricultural applications, benefiting from the repetitive coverage possible with satellites, have been especially promising. Crop inventories are being conducted, as well as inventories of timber and rangeland. Overgrazing has been monitored in several areas. Finally, environmental quality has also proven susceptible to orbital remote sensing; several types of water pollution have been successfully monitored. The effects of mining and other activities on the land can also be studied. The future of orbital remote sensing in global monitoring of the Earth's resources seems assured. However, efforts to extend spectral range, increase resolution, and solve cloud-cover problems must be continued. Broad applications of computer analysis techniques are vital to handle the immense amount of information produced by satellite sensors.Abbreviations SSRERTS Symposium on Significant Results Obtained from the Earth Resources Technology Satellite - TERTSS Third Earth Resources Technology Satellite-1 Symposium National Academy of Sciences-National Research Council Research Associate at NASA Goddard Space Flight Center, 1974/75.Goddard Space Flight Center     

Remote sensing of the global distribution of total ozone and the inferred upper-tropospheric circulation from Nimbus IRIS experiments

The global distribution of total ozone is derived for the period April, May, June and July of 1969 from Nimbus-3 Infrared Interferometer Spectrometer (IRIS) experiment. Preliminary estimates of ozone amounts from Nimbus-4 IRIS for the same period of 1970 show similar results. The standard error of estimation of total ozone from both IRIS experiments is 6% with respect to Dobson Spectrophotometer measurements. A systematic variation in the ozone distribution from April to July in the tropical, middle and polar latitudes is observed indicating the changes in the lower stratospheric circulation.The total ozone measurements show a strong correlation with the upper tropospheric geopotential height in the extratropical latitudes. From this relationship total ozone is used as a quasi-stream function to deduce geostrophic winds at the 200 mb level over extratropical regions of the northern and southern hemispheres. These winds reveal the subtropical and polar jet streams over the globe.Allied research associates.     

An approach to using snow areal depletion curves inferred from MODIS and its application to land surface modelling in Alaska

Snowcover areal depletion curves inferred from the moderate resolution imaging spectroradiometer (MODIS) are validated and then applied in NASA's catchment‐based land surface model (CLSM) for numerical simulations of hydrometeorological processes in the Kuparuk River basin (KRB) of Alaska. The results demonstrate that the MODIS snowcover fraction f derived from a simple relationship in terms of the normalized difference snow index compares well with Landsat values over the range 20 ≤ f ≤ 100%. For f < 20%, however, MODIS 500 m subpixel data underestimate the amount of snow by up to 13% compared with Landsat at spatial resolutions of 30 m binned to equivalent 500 m pixels. After a bias correction, MODIS snow areal depletion curves during the spring transition period of 2002 for the KRB exhibit similar features to those derived from surface‐based observations. These results are applied in the CLSM subgrid‐scale snow parameterization that includes a deep and a shallow snowcover fraction. Simulations of the evolution of the snowpack and of freshwater discharge rates for the KRB over a period of 11 years are then analysed with the inclusion of this feature. It is shown that persistent snowdrifts on the arctic landscape, associated with a secondary plateau in the snow areal depletion curves, are hydrologically important. An automated method is developed to generate the shallow and deep snowcover fractions from MODIS snow areal depletion curves. This provides the means to apply the CLSM subgrid‐scale snow parameterization in all watersheds subject to seasonal snowcovers. Improved simulations and predictions of the global surface energy and water budgets are expected with the incorporation of the MODIS snow data into the CLSM. Copyright © 2005 John Wiley & Sons, Ltd.