Application of satellite imagery to hydrologic modeling snowmelt runoff in the southern Sierra Nevada
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Hannaford, J. F.↗
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Identifying and locating land irrigated by center-pivot irrigation systems using satellite imagery
A methodology for using Landsat imagery for the identification and location of land irrigated by center-pivot irrigation systems is presented. The procedure involves the use of sets of Landsat band 5 imagery taken separated in time by about three weeks during the irrigation season, a zoom transfer scope and mylar base maps to record the locations of center pivots. Further computer processing of the data has been used to obtain plots of center-pivot irrigation systems and tables indicating the distribution and growth of systems by county for the state of Nebraska, and has been found to be in 95% agreement with current high-altitude IR photography. The information obtainable can be used for models of ground-water aquifers or resource planning.
Hoffman, R. O.↗
Surveying the area of deforestation of the Amazon by LANDSAT satellite imagery
LANDSAT imagery was used to determine the amount of deforestation in a study area comprising 55 million hectares of the Amazon region. Results show that more than 4 million hectares were deforested. Maps and pictures of the deforested area in relation to the total area of the Amazon are included.
Dejesusparada, N.↗
A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect
A climatological model/variable termed the sponge (a measure of moisture availability based on daily temperature maxima and minima, and precipitation) was tested for potential biogeograhic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic form, suggest that, as generalized climatic index, sponge is particularly appropriate for large-area and global vegetation monitoring. The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge and AVHRR data was initiated. Along an east-west Texas gradient, vegetation, sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values along the Texas gradient suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.
Greegor, D.↗
A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect
A new experimental climatological model/variable termed the sponge, a measure of moisture availability based on daily temperature maxima and minima and precipitation, is tested for potential biogeographic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic from, suggest that, as a generalized climatic index, sponge's simplicity and sensitivity make particularly appropriate for trans-regional biogeographic studies (e.g., large-area and global vegetation monitoring). The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.
Greegor, D. H.↗
Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base
In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).
Clark, J.↗
Radar reflectivities and satellite imagery of severe storms 20 May 1977
Storms on 20 May 1977 generated a vast cirrus deck. Disturbed areas at storm top had equivalent black-body temperatures (T sub BB) much lower than the tropopause temperature, indicative of overshooting tops. The area of T sub BB not greater than -71 C represents the area of convective activity penetrating 2 km above the tropopause. This area was relatively large after cloud tops and radar reflectivities reached their maximum heights. It became much smaller during tornadoes when reflectivities were decreasing. T sub BB was at a minimum at the time of mesocyclone formation. The Del City storm had two periods of growth, as indicated both by reflectivities and the T sub BB areas. The mesocyclone was first detected during the second less intense period of growth; the tornado occurred during decreasing reflectivities. The maintenance of large areas of relatively low T sub BB after tornado dissipation is ascribed to continued convection on the flanks of the storm and to residual updrafts in a thick anvil cloud.
Wexler, R.↗
Assessment of radar resolution requirements for soil moisture estimation from simulated satellite imagery
Radar simulations were performed at five-day intervals over a twenty-day period and used to estimate soil moisture from a generalized algorithm requiring only received power and the mean elevation of a test site near Lawrence, Kansas. The results demonstrate that the soil moisture of about 90% of the 20-m by 20-m pixel elements can be predicted with an accuracy of + or - 20% of field capacity within relatively flat agricultural portions of the test site. Radar resolutions of 93 m by 100 m with 23 looks or coarser gave the best results, largely because of the effects of signal fading. For the distribution of land cover categories, soils, and elevation in the test site, very coarse radar resolutions of 1 km by 1 km and 2.6 km by 3.1 km gave the best results for wet moisture conditions while a finer resolution of 93 m by 100 m was found to yield superior results for dry to moist soil conditions.
Ulaby, F. T.↗
Vegetation classification based on Advanced Very High Resolution Radiometer /AVHRR/ satellite imagery
Data from the NOAA-6 spacecraft Advanced Very High Resolution Radiometer (AVHRR) were tested for effectiveness for vegetation classification. Vegetation, climatological, and meteorological data were gathered for three days over 12 locations, and the normalized differences between the AVHRR bands 1 and 2 were determined. A vegetative greenness index was compared with a hydrologic factor and vegetation characteristics as measured by ground truth. A multivariate vegetation gradient model was formulated, incorporating AVHRR and climatological data. The hydrologic factor was calculated in terms of the precipitation, evaporation, maximum and minimum temperatures, and the hydrologic capacity. The observations were taken over Texas, which has a wide range of climates. A high correlation was found in the vegetation-HF index. The AVHRR data are concluded to be an effective tool for analysis of vegetation/climate relationships.
Norwine, J.↗
Automated mesoscale wind fields derived from GOES satellite imagery
A new multispectral image-processing system for extracting mesoscale wind fields automatically from sequences of GOES imagery is described. This system can produce equivalent or superior cloud-wind estimates compared to the time-consuming manual methods used on various interactive meteorological processing systems. Analysis of automated mesoscale cloud winds yield an estimated random error value of less than 1 m/s and produces both regional and mesoscale vector wind-field structure and divergence patterns that are consistent in time and highly correlated with subsequent severe thunderstorm development. As an example, the system is here applied to SMS II five-minute imagery from April 24, 1975 and the results are compared with manually obtained ones.
Wilson, G. S.↗
The development of an MSS satellite imagery classification expert system
Unsupervised image classification of Landsat MSS imagery entails a significant part of the remote sensing, image analysis effort. Expert systems, a technology developed in the field of artificial intelligence, offers the potential to automate this process, thus greatly increasing the efficiency with which an analyst can perform unsupervised image classification and making the knowledge of the image analyst available to a community of nonexperts. Such a system, under development at the NASA/Ames Research Center, is described and planned enhancements are discussed.
Engle, S. W.↗
Detection of rotating thunderstorms using satellite imagery
In the case of the Carolina tornadoes, researchers prepared visible and IR GOES imagery covering the period 2000 Z when the storm entered South Carolina from Georgia until it exited North Carolina at 0200 Z into Virginia. The GOES IR imagery clearly demonstrated that this storm was imbedded in a continuously propagating mesolow with a well defined cold dome. The ground damage track paralleled exactly with the cold dome throughout the storm's life across the Carolinas. There were no advanced very high resolution radiometer (AVHRR) data during the period to allow researchers to inspect the cloud top for warm temperature anomalies. The Carolina storm did exhibit rightward deviating outflow which was oriented about 60 degrees to the 300 mb streamlines. The tornadoes of April 27, 1984 were part of a tornado producing cold front which stretched from Oklahoma to Minnesota. As the front moved eastward it touched off numerous tornadoes in eastern Wisconsin. GOES imagery for this data was prepared and it was strikingly clear that all along the North-South oriented squall line, the individual tunderstorms had cirrus plumes which had remarkable right deviation to the upper air flow. Unlike the Carolina long track supercell cell-mesolow system, these storms were isolated individual thunderstorms which touched off at least 16 tornadoes in eastern Wisconsin stretching from the Milwaukee area on the south to Vilas County in the north. The monster tornado of June 8, 1984 which leveled 90 percent of the village of Barneveld, Wisconsin and killed 9 persons is also discussed.
Anderson, C. E.↗
A dynamic threshold method for obtaining cloud cover from satellite imagery data
Errors in cloud cover derived by using a fixed threshold applied to imagery data depend not only on the fractional cover but also on cloud size. As a result, a fixed threshold applied to two scenes having the same cloud cover will produce different estimates of the cover when the clouds in the two scenes have different sizes. To allow for this influence due to cloud size, a dynamic threshold method is presented. In this method an infrared threshold is adjusted to achieve the highest correlation between the threshold-derived cloud cover and the mean emitted radiance for mesoscale-sized subregions within the scene. For single-layered cloud systems this threshold achieves a cancellation of errors in the cloud cover for the subregions so that the resulting cloud cover for the region and the associated estimates of cloud properties are in fair agreement with estimates obtained using the spatial coherence method. The agreement illustrates the validity of the layered cloud model used in different ways by the two methods. The performance of the dynamic threshold method is contrasted with that of a fixed threshold applied to the same data in order to illustrate the merits of applying a scene-dependent threshold.
Coakley, James A., Jr.↗
The combined use of diagnosed mesoscale frontogenesis and satellite imagery in forecasting squall line formation
The appearance of a line of small cumulus congestus clouds along a cold front in conjunction with developing mesoscale clear zone immediately behind the front was used to infer the existence of a meso-Beta-scale frontogenetical circulation capable of squall line initiation. The very short-range forecasting (2 to 6 hr) capabilities of synthesizing GOES imagery with diagnostic frontogenesis analyses of conventional surface data to predict the precise location and time of formation of such convective activity is demonstrated. The observations support the frontogenesis hypothesis postulated by Koch (1984).
Dorian, Paul↗
Cloud cover determination in polar regions from satellite imagery
A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.
Barry, R. G.↗
Cloud cover determination in polar regions from satellite imagery
The principal objectives of this project are: to develop suitable validation data sets to evaluate the effectiveness of the ISCCP operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers: and to compare synoptic cloud data from a control run experiment of the Goddard Institute for Space Studies (GISS) climate model 2 with typical observed synoptic cloud patterns. Current investigations underway are listed and the progress made to date is summarized.
Barry, R. G.↗
Variability of pigment biomass in the California Current system as determined by satellite imagery. I - Spatial variability
Spatial variability of chlorophyll in the California Current system was analyzed using Coastal Zone Color Scanner (CZCS) imagery. A total of 48 images were analyzed to produce seasonal averages and variances, gradients, and power spectra. Roughly one third to one half of the variance in pigment biomass can be explained by consistent, large-scale gradients. In general, biomass is higher in the north and in nearshore areas. Nearshore areas also have proportionally more small-scale variability than the areas offshore. Slopes of the power spectra for nearshore areas are about -2.2 (for spatial scales of 10-100 km), while slopes for offshore areas are about -3. In addition, the power spectra show evidence of a change in slope at about 10 km, with slopes of about -1 for shorter-length scales. This may indicate that biological processes dominate the smaller scales, while mesoscale eddies and geostrophic currents dominate the larger scales.
Smith, Raymond C.↗
Progress of research to identify rotating thunderstorms using satellite imagery
The possibility of detecting potentially tornadic thunderstorm cells from geosynchronous satelite imagery is determined. During the life of the contract, we examined eight tornado outbreak cases which had a total of 124 individual thunderstorm cells, 37 of which were tornadic.These 37 cells produced a total of 119 tornadoes. The outflow characteristics of all the cells were measured. Through the use of a 2-D flow field model, we were able to simulate the downstream developmemt of an anvil cloud plume which was emitted by the storm updraft at or near the tropopause. We used two parameters to characterize the anvil plume behavior: its speed of downstream propagation (U max) and the clockwise deviation of the centerline of the anvil plume from the storm relative ambient wind at the anvil plume outflow level (MDA). U max was the maximum U-component of the anvil wind parameter required to successfully maintain an envelope of translating particles at the tip of the expanding anvil cloud. MDA was the measured deviation angle acquired from McIDAS, between the storm relative ambient wind direction and the storm relative anvil plume outflow direction; tha latter being manipulated by controlling a tangential wind component to force the envelope of particles to maintain their position of surrounding the expanding outflow cloud.
Anderson, Charles E.↗