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Goward, S. N.

Publications and source records attributed to Goward, S. N..

Characterizing the LANDSAT Global Long-Term Data Record

The effects of global climate change are fast becoming politically, sociologically, and personally important: increasing storm frequency and intensity, lengthening cycles of drought and flood, expanding desertification and soil salinization. A vital asset in the analysis of climate change on a global basis is the 34-year record of Landsat imagery. In recognition of its increasing importance, a detailed analysis of the Landsat observation coverage within the US archive was commissioned. Results to date indicate some unexpected gaps in the US-held archive. Fortunately, throughout the Landsat program, data have been downlinked routinely to International Cooperator (IC) ground stations for archival, processing, and distribution. These IC data could be combined with the current US holdings to build a nearly global, annual observation record over this 34-year period. Today, we have inadequate information as to which scenes are available from which IC archives. Our best estimate is that there are over four million digital scenes in the IC archives, compared with the nearly two million scenes held in the US archive. This vast pool of Landsat observations needs to be accurately documented, via metadata, to determine the existence of complementary scenes and to characterize the potential scope of the global Landsat observation record. Of course, knowing the extent and completeness of the data record is but the first step. It will be necessary to assure that the data record is easy to use, internally consistent in terms of calibration and data format, and fully accessible in order to fully realize its potential.

Arvidson, T.↗

Evapotranspiration from combined reflected solar and emitted terrestrial radiation - Preliminary FIFE results from AVHRR data

The relation between remotely sensed spectral vegetation indices and thermal IR measurements is studied. Land surface evapotranspiration is evaluated based on this relationship. Analysis of the AVHRR data, obtained in Kansas in 1987, reveal a strong correlation between the spectral vegetation indices and surface temperature and this relation covaries with surface moisture conditions. It is noted that the relation between remotely sensed measurements of canopy green foliage and surface temperature is useful for examining variations in the interface thermal inertia and energy balance Bowen ratio.

Goward, S. N.↗

Quantifying spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains

Spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains are quantified in terms of vegetation and soil wetness. The brightness temperatures (TB) are the daytime observations from April to October for five years (1979 to 1983) obtained by the Nimbus-7 Scanning Multichannel Microwave Radiometer at 6.6 GHz frequency, horizontal polarization. The spatial and temporal variabilities of vegetation are assessed using visible and near-infrared observations by the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR), while an Antecedent Precipitation Index (API) model is used for soil wetness. The API model was able to account for more than 50 percent of the observed variability in TB, although linear correlations between TB and API were generally significant at the 1 percent level. The slope of the linear regression between TB and API is found to correlate linearly with an index for vegetation density derived from AVHRR data.

Choudhury, B. J.↗

Remote sensing from space; Proceedings of Symposium 3, Workshop V, and Topical Meeting A2 of the Twenty-sixth COSPAR Plenary Meeting, Toulouse, France, June 30-July 11, 1986

Various papers on remote sensing from space are presented. The use of such remote sensing to study terrestrial patterns and processes is examined, including the relevant processes and theories, observed vegetation and surface climate parameters, derived terrestrial processes, atmospheric effects, and new sensors. Quantitative radar remote sensing of land and oceanic surface features is addressed, including systems, calibration, simulation, data evaluation for vegetational studies, altimetry, sea ice monitoring, and oil slick detection. The use of satellite observations for weather prediction is discussed.

Goward, S. N.↗

Observed relation between thermal emission and reflected spectral radiance of a complex vegetated landscape

An investigation is conducted, for a complex vegetated land area, into the statistical relationship between remotely sensed thermal emissions and reflected spectral radiance. The Kauth-Thomas Tasseled Cap transformation is employed to infer the albedo and amount of green vegetation present from Landsat multispectral scanner (MSS) observations. Reflective data and thermal infrared data were acquired from the Heat Capacity Mapping Mission (HCMM) satellite along with reflective data from the Landsat 3 MSS for a site near Hartford, CT on a single date. Results are presented which indicate that thermal emissions had the greatest association with the amount of vegetation as indicated by a multispectral index, while albedo did not exhibit any substantial relationship with these emissions. These findings are explained in terms of the enhanced latent heat flux to the atmosphere associated with actively transpiring vegetation.

Goward, S. N.↗

Analysis of Terrestrial Conditions and Dynamics

An ecological model is developed to estimate annual net primary productivity of vegetation in twelve major North American biomes. Three models are adapted and combined, each addressing a different factor known to govern primary productivity, i.e., photosynthesis, respiration, and moisture availability. Measures of intercepted photosynthetically active radiation (1PAR) for input to the photosynthesis model are derived from spectral vegetation index data. Normalized Difference Vegetation Index (NDVI) data are produced from NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) observations for April 1982 through March 1983. NDVI values are sampled from within the biomes at locations for which climatological data are available. Monthly estimates of Net Primary Productivity (NPP) for each sample location are generated and summed over the twelve month period. These monthly estimates are averaged to produce a single annual estimated NPP value for each biomes. Comparison of estimated NPP values with figures reported in the literature produces a correlation coefficient of 85.

Goward, S. N.↗

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations acquired by the advanced very high resolution radiometer, a sensor on the current series of U.S. National Oceanic and Atmospheric Administration meteorological satellites, may be particularly well suited for global studies of vegetation. Preliminary results from analysis of North American observations, extending from April to November 1982, show that the vegetation index patterns observed correspond to the known seasonality of North American natural and cultivated vegetation. Integration of the observations over the growing season produced measurements that are related to net primary productivity patterns of the major North American natural vegetation formations. Regions of intense cultivation were observed as anomalous areas in the integrated growing season measurements. Significant information on seasonality, annual extent and interannual variability of vegetation photosynthetic activity at continental and global scales can be derived from these satellite observations.

Goward, S. N.↗

Shortwave infrared detection of vegetation

The potential of short wave infrared (SWIR) measurements in vegetation discrimination is further substantiated through a discussion of field studies and an examination of the physical bases which cause SWIR measurements to vary with the vegetation type observed. The research reported herein supported the AGRISTARS program objective to incorporate TM measurements in the analysis of agricultural activity. Field measurements on corn and soybeans in Iowa were conducted, and the mean and variance of canopy reflectance were computed for each observation date. The Suits canopy reflectance model was used to evaluate possible explanations of the observed corn/soybeans reflectance patterns /39/. The SWIR measurements were shown to effectively discriminate corn and soybeans on the basis of leaf absorption properties.

Goward, S. N.↗

Shortwave infrared detection of vegetation

Shortwave infrared sensors were included on the Thematic Mapper (TM) to observe vegetation reflected radiance patterns related to water leaf content. Analysis of field measurements for corn and soybeans throughout the growing season showed that shortwave infrared measurements enhance discrimination between the species, particularly in midseason. A numerical model of the canopy reflectance showed that differential leaf absorptance can produce the observed patterns. Analysis of coincident studies of leaf optical properties were conducted to generalize the results to other types of vegetation.

Goward, S. N.↗

Analysis of terrestrial conditions and dynamics

Land spectral reflectance properties for selected locations, including the Goddard Space Flight Center, the Wallops Flight Facility, a MLA test site in Cambridge, Maryland, and an acid test site in Burlington, Vermont, were measured. Methods to simulate the bidirectional reflectance properties of vegetated landscapes and a data base for spatial resolution were developed. North American vegetation patterns observed with the Advanced Very High Resolution Radiometer were assessed. Data and methods needed to model large-scale vegetation activity with remotely sensed observations and climate data were compiled.

Goward, S. N.↗

Use of the TM tasseled cap transform for interpretation of spectral contrasts in an urban scene

Investigations are being conducted with the objective to develop automated numerical image analysis procedures. In this context, an examination is performed of physically-based multispectral data transforms as a means to incorporate a priori knowledge of land radiance properties in the analysis process. A physically-based transform of TM observations was developed. This transform extends the Landsat MSS Tasseled Cap transform reported by Kauth and Thomas (1976) to TM data observations. The present study has the aim to examine the utility of the TM Tasseled Cap transform as applied to TM data from an urban landscape. The analysis conducted is based on 512 x 512 subset of the Washington, DC November 2, 1982 TM scene, centered on Springfield, VA. It appears that the TM tasseled cap transformation provides a good means to explain land physical attributes of the Washington scene. This result provides a suggestion regarding a direction by which a priori knowledge of landscape spectral patterns may be incorporated into numerical image analysis.

Goward, S. N.↗

Collection of in situ forest canopy spectra using a helicopter - A discussion of methodology and preliminary results

An important part of fundamental remote sensing research is based on the measurement and analysis of spectral reflectance from earth surface materials in situ. It has been found that for an effective analysis of the target of interest, different applications of remotely sensed data require spectral measurements from different portions of the electromagnetic spectrum. It is pointed out that the detailed spectral reflectance characteristics of forest vegetation are currently not well understood, particularly in the middle infrared wavelength region. Details regarding the need for in situ forest canopy measurements are examined, taking into account certain difficulties arising in the case of satellite observations. Because of these difficulties, the present paper provides a discussion of methodology and preliminary spectra based on an experiment to use a helicopter as an observing platform for in situ forest canopy spectra measurement.

Williams, D. L.↗

Application of digital analysis of MSS to agro-environmental studies

Topics of investigation include infrared analysis of vegetation canopies, urban/rural albedo studies, analysis of Field Spectrometer System (ESS) observations, geometric and radiometric processing techniques of aircraft MSS data, and the use of LANDSAT MSS observations to map wetlands and snow cover.

Goward, S. N.↗

Enhanced crop discrimination using the mid-IR (1.55-1.75 microns)

Improvements in crop discrimination can be realized by using mid-IR bands (1.55 -1.75 and 2.08 -2.35 microns) which are sensitive to canopy moisture content. Analyses of data from two growing seasons in Webster County, Iowa clearly indicate that corn and soybeans are highly separable in the mid-IR from early season through harvest. This contrasts sharply with visible and near-IR bands where corn and soybeans are confused throughout much of the growing season. The mid-IR temporal reflectance behavior appears to result from differences between C4 monocot and C3 dicot internal leaf structure. If this hypothesis holds, mid-IR observations should improve discrimination in other instances where similar differences in internal leaf structure are present.

Ungar, S. G.↗

Application of digital analysis of MSS data to agro-environmental studies

Progress in the application of digital analysis of multispectral scanner data to agro-environmental studies is described. Simulation of LANDSAT D thematic mapper (TM) observations from aircraft multispectral scanner data and field spectrometer data collected over a corn-soybean agricultural region in Webster County, Iowa during the 1979 growing season in support of the NASA/AgRISTARS program is described. The simulations were analyzed to evaluate the potential utility of the TM (1.55-1.75 micron) mid-infrared observations in corn-soybean discrimination. Current LANDSAT data was analyzed to study snow cover in northern New England and wetlands in Nebraska and Vermont. The application of satellite remote sensor data in additional environmental research areas is described.

Lewis, R. A.↗

Longwave infrared observation of urban landscapes

An investigation is conducted regarding the feasibility to develop improved methods for the identification and analysis of urban landscapes on the basis of a utilization of longwave infrared observations. Attention is given to landscape thermal behavior, urban thermal properties, modeled thermal behavior of pavements and buildings, and observed urban landscape thermal emissions. The differential thermal behavior of buildings, pavements, and natural areas within urban landscapes is found to suggest that integrated multispectral solar radiant reflectance and terrestrial radiant emissions data will significantly increase potentials for analyzing urban landscapes. In particular, daytime satellite observations of the considered type should permit better identification of urban areas and an analysis of the density of buildings and pavements within urban areas. This capability should enhance the utility of satellite remote sensor data in urban applications.

Goward, S. N.↗

Remote sensing research in geographic education: An alternative view

It is noted that within many geography departments remote sensing is viewed as a mere technique a student should learn in order to carry out true geographic research. This view inhibits both students and faculty from investigation of remotely sensed data as a new source of geographic knowledge that may alter our understanding of the Earth. The tendency is for geographers to accept these new data and analysis techniques from engineers and mathematicians without questioning the accompanying premises. This black-box approach hinders geographic applications of the new remotely sensed data and limits the geographer's contribution to further development of remote sensing observation systems. It is suggested that geographers contribute to the development of remote sensing through pursuit of basic research. This research can be encouraged, particularly among students, by demonstrating the links between geographic theory and remotely sensed observations, encouraging a healthy skepticism concerning the current understanding of these data.

Wilson, H.↗