David S. Simonett

Radar detection of flooding beneath the forest canopy - A review

Abstract Synthetic aperture radar remote sensing is a promising tool for detection of flooding on forested floodplains. The bright appearance of flooded forests on radar images results from double-bounce reflections between smooth water surfaces and tree trunks or branches. Enhanced back scattering at L-band has been shown to occur in a wide variety of forest types, including cypress-tupelo swamps, temperate bottomland hardwoods, spruce bogs, mangroves and tropical floodplain forests. Lack of enhancement is a function of both stand density and branching structure. According to models and measurements, the magnitude of the enhancement is about 3 to 10 dB. Steep incidence angles (20°-30°) are optimal for detection of flooding, since some forest types exhibit bright returns only at steeper angles. P-band should prove useful for floodwater mapping in dense stands, and multifrequency polarimetric analysis should allow flooded forests to be distinguished from marshes.

L-Band Radar Backscatter Modeling of Forest Stands

An L-band HH radar backscatter model of a coniferous forest stand is described and compared with SIR-B L-band image data of the Mount Shasta region of northern California. Being based upon an identification and implementation of the expected major components of forest backscattering, the model is simple in form and thus fast computationally, making possible extensive simulations of forest stands. A particularly important component in the model relates to representing the specular reflections expected from tree trunks to the ground and then back to the sensor. These are strong returns and are seen to be necessary to explain both the forest measurements made by the authors and the observations of others. Although the experimental data is limited in quantity and quality, agreement between available experimental and simulated values of forest backscatter is better than the residual uncertainty and relative calibration error of the experimental data, provided the model and experiment are matched initially at one set of parameter values.

The effect of changing environmental conditions on microwave signatures of forest ecosystems: preliminary results of the March 1988 Alaskan aircraft SAR experiment

Abstract In preparation for the first European Space Agency (ESA) Remote Sensing(ERS-I) mission,a series of multitemporal, multifrequency, multipolarization aircraft synthetic aperture radar (SAR) data sets were acquired over the Bonanza Creek Experimental Forest near Fairbanks, Alaska in March, 1988. P-, L- and C-band data were acquired with the NASA/JPL Airborne SAR on five differentdays over a period of two weeks. The airborne data were augmented with intensiveground calibration data as well as detailed, simultaneous in situ measurements of the geometric, dielectric and moisture properties of the snow and forest canopy. During the time period over which the SAR data were collected, the environmental conditions changed significantly; temperatures ranged from unseasonably warm (I to 9°C) to well below freezing (-8 to - 15°C), and the moisture content of the snow and trees changed from a liquid to a frozenstate. The SAR data clearly indicate the radar return is sensitive to these changing environmental fa...

A radar backscatter model for discontinuous coniferous forests

A radar backscattering model for low-to-medium-density woodland in which each tree is treated as an individual backscatterer is described. A forest stand viewed by radar is then an assemblage of scatterers standing on a background in a certain spatial pattern. The backscattering components arising from the various intersections of radar beams with the forest stand are calculated separately, and their Stokes matrices are then added together to achieve the Stokes matrix for total backscattering. Probabilities of radar beams intersecting tree crowns are introduced into the model. >

Simulation of L-band and HH microwave backscattering from coniferous forest stands A comparison with SIR-B data

Abstract Shuttle Imaging Radar-B (SIR-B) images of coniferous forest stands dominated by Ponderosa pine in the Mt. Shasta region of northern California were used to evaluate a composite L-band HH backscattering model of coniferous forest stands. Eight forest stands were employed to describe the relative trend and distribution of backscattering coefficients. It was found that (1) both SIR-B and simulated backscattering coefficients for the eight stands have similar trends and relations to average tree height and average number of trees per pixel and (2) the dispersion and distribution of simulated backscattering coefficients from each stand broadly matched SIR-B data from the same stand. Although it is difficult to draw any strong conclusions from the comparisons because the experimental data arc limited in both quantity and quality and are also undersampled, the comparisons indicate that a stand-based L-band HH composite model seems promising for explaining backscattering features. The means of the backsc...

Reflectance and transmission properties of West African savanna trees from ground radiometer measurements

Abstract Reflectance and transmission properties of savanna trees were measured using a pole-mounted radiometer for four Sahelian and two Sudanian species in West Africa. The measurements showed that canopy spectral components, that is, shadowed and sunlit tree crown and background, have distinct reflectance characteristics in red and infrared wavebands as modelled by Li and Strahler (1985). Sunlit canopy is the greenest component (greatest infrared to red contrast), and sunlit background (consisting mostly of bare soil), the brightest (greatest summed red and infrared reflectance). Shadowed crown, the darkest component, is greener than shadowed background. The field radiometer measurements were used to calculate the normalized difference vegetation index (NDVI), and the spatial integral of the NDVI over the canopy was related to crown volume yielding per species r2 of 075 to 0.81. Measurements of canopy transmission indicated that only 12 to 47 per cent of incoming radiation was absorbed in these wavebands.

L-Band Radar Sensing of Soil Moisture

The objectives of this experiment were to assess the performance of an L-band, 25-cm wavelength imaging synthetic aperture radar (SAR) for soil moisture determination, and to study the temporal variability of radar returns from a number of agricultural fields. A series of three overflights was accomplished during March 1977 over an agricultural test site in Kern County, CA. Soil moisture samples were collected from bare fields at nine sites at depths of 0-2, 2-5, 5-15, and 15-30 cm. These gravimetric measurements were converted to percent of field capacity for correlation to the radar return signal. The initial signal film was optically correlated and scanned to produce image data numbers. These numbers were then converted to relative return power by linear interpolation of the noise power wedge which was introduced in 5-dB steps into the original signal film before and after each data run. Results of correlations between the relative return power and percent of field capacity (%FC) demonstrate that the relative return power from this imaging radar system is responsive to the amount of soil moisture in bare fields. The signal returned from dry (15%FC) and wet (130%FC) fields where furrowing is parallel to the radar beam differs by about 15 dB. Problems remain to be resolved before this technique can be operationally employed. First, adequate calibration of the radar system is required to insure comparability of data both from area to area within a single flight and between different flights.

Impacts of remote sensing on U.S. geography

Abstract This paper examines some impacts of remote sensing on geography. As geographers involved in this new technology, we review and place in context its development; and with a vision of its value to our discipline, we are concerned at its modest impact on major research areas in geography. Even acknowledging that, in a broader view, remote sensings impact on geography has been greater than in other disciplines does not alleviate our concerns that few senior academic geographers have remote sensing research underway; that few economic geographers have examined its potential; that even fewer regional geographers with interests in less-developed countries have remote sensing research interests; and that although there has been growth in the number of remote sensing courses taught in geography, this has not been accompanied by publication in reviewed geographic journals. We ask the questions: What does remote sensing permit the geographer to do better and/or cheaper than he or she could do in the past? What may remote sensing enable future geographers to do which would be significant to professional and academic geography? We then find that the exploitation of the improved or unique information available to the geographer via the application of remote sensing techniques has barely begun. Yet, remote sensing is a reality within geography whose time has come. It is too powerful a tool to be ignored in terms of both its information potential and the logic implicit in the reasoning process employed to analyze the data. We predict it could change our perceptions, our methods of data analysis, our models, and our paradigms.

Side-scan sonar mapping and computer-aided interpretation in the Santa Barbara Channel, California

We have experimented with digital processing of side scan sonar data taken in a 14 sq-km area of continental shelf offshore Southern California. The data were FM tape recorded during the survey and digitized and processed later in the laboratory. The digital image processing included both image correction and image enhancement. Geometric corrections were applied to correct for image distortions due to variable ship position and speed and sonar slant range. Enhancements that were tried included contrast stretching, band-pass filtering, image restoration (inverse filtering), and various edge enhancements such as density slicing and standard deviation filters. Interpretive procedures were also attempted and included digital mosaicking, stereoscopic viewing, and falsecolor display. The most effective processing was geometric correction combined with contrast stretching. Mosaicking proved difficult due to imprecise navigation (±50 m), but was very effective in increasing the understanding of the geologic structure in the survey area.

Radar Modeling Of Tropical Mangal Forest Stands

Radar modeling of mangal forest stands in the Sundarbans area of southern Bangladesh is discussed. The modeling uses radar system parameters with forest data on tree height, spacing, biomass, species combinations, and water content (including slightly conductive water) in leaves and trunks of the mangal. For Sundri and Gewa tropical mangal forests, six model components are proposed; the models are required to explain the contributions of various combinations of forest species in the attenuation and scattering of mangal-vegetated nonflooded or flooded surfaces. Statistical data of simulated images have been compared with those of SIR-B images both to refine the modeling procedures and to characterize the model output appropriately. The possibility of delineation of flooded or nonflooded boundaries is discussed.