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Vegetation and soils field research data base: Experiment summaries

Understanding of the relationships between the optical, spectral characteristics and important biological-physical parameters of earth-surface features can best be obtained by carefully controlled studies over fields and plots where complete data describing the condition of targets are attainable and where frequent, timely spectral measurement can be obtained. Development of a vegetation and soils field research data base was initiated in 1972 at Purdue University's Laboratory for Applications of Remote Sensing and expanded in the fall of 1974 by NASA as part of LACIE. Since then, over 250,000 truck-mounted and helicopter-borne spectrometer/multiband radiometer observations have been obtained of more than 50 soil series and 20 species of crops, grasses, and trees. These data are supplemented by an extensive set of biophysical and meteorological data acquired during each mission. The field research data form one of the most complete and best-documented data sets acquired for agricultural remote sensing research. Thus, they are well-suited to serve as a data base for research to: (1) quantiatively determine the relationships of spectral and biophysical characteristics of vegetation, (2) define future sensor systems, and (3) develop advanced data analysis techniques.

Biehl, L. L.↗

Remote sensing of soils in the eastern Palouse region with Landsat Thematic Mapper

Soils of the Palouse region of eastern Washington State were investigated using Landsat Thematic Mapper (TM) band ratios to discriminate areas where erosion has caused paleosols to be exposed. Ratioed data were clustered and plotted to show soil lines which could be subdivided into various levels of organic matter and iron oxides. Successfully classified scenes of a summer fallow (bare soil) field were obtained with band ratios 1/4, 3/4, and 5/4 to map organic carbon and 3/4, 5/4, and 5/3 for the iron/carbon ratio indicator of erosion. Regression models were made with 5/4 data and organic carbon and 5/3 data and the iron/carbon ratio. Based on this analysis, 21 percent of the test field soils are exposed or nearly exposed paleosols.

Frazier, B. E.↗

Mapping Soil pH Buffering Capacity of Selected Fields

Soil pH buffering capacity, since it varies spatially within crop production fields, may be used to define sampling zones to assess lime requirement, or for modeling changes in soil pH when acid forming fertilizers or manures are added to a field. Our objective was to develop a procedure to map this soil property. One hundred thirty six soil samples (0 to 15 cm depth) from three Georgia Coastal Plain fields were titrated with calcium hydroxide to characterize differences in pH buffering capacity of the soils. Since the relationship between soil pH and added calcium hydroxide was approximately linear for all samples up to pH 6.5, the slope values of these linear relationships for all soils were regressed on the organic C and clay contents of the 136 soil samples using multiple linear regression. The equation that fit the data best was b (slope of pH vs. lime added) = 0.00029 - 0.00003 * % clay + 0.00135 * % O/C, r(exp 2) = 0.68. This equation was applied within geographic information system (GIS) software to create maps of soil pH buffering capacity for the three fields. When the mapped values of the pH buffering capacity were compared with measured values for a total of 18 locations in the three fields, there was good general agreement. A regression of directly measured pH buffering capacities on mapped pH buffering capacities at the field locations for these samples gave an r(exp 2) of 0.88 with a slope of 1.04 for a group of soils that varied approximately tenfold in their pH buffering capacities.

Weaver, A. R.↗

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Kim, Edward↗

Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

Li, Bailing↗

Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature

The global fields of normal monthly soil moisture and land surface evapotranspiration are derived with a simple water budget model that has precipitation and potential evapotranspiration as inputs. The precipitation is observed and the potential evapotranspiration is derived from the observed surface air temperature with the empirical regression equation of Thornthwaite (1954). It is shown that at locations where the net surface radiation flux has been measured, the potential evapotranspiration given by the Thornthwaite equation is in good agreement with those obtained with the radiation-based formulations of Priestley and Taylor (1972), Penman (1948), and Budyko (1956-1974), and this provides the justification for the use of the Thornthwaite equation. After deriving the global fields of soil moisture and evapotranspiration, the assumption is made that the potential evapotranspiration given by the Thornthwaite equation and by the Priestley-Taylor equation will everywhere be about the same; the inverse of the Priestley-Taylor equation is used to obtain the normal monthly global fields of net surface radiation flux minus ground heat storage. This and the derived evapotranspiration are then used in the equation for energy conservation at the surface of the earth to obtain the global fields of normal monthly sensible heat flux from the land surface to the atmosphere.

Mintz, Y.↗

Microwave emission from smooth bare fields and soil moisture sampling depth

This paper studies the depth to which soil moisture can be directly estimated with microwave measurements over smooth bare fields. The analyses are based on both theoretical and experimental considerations at the frequencies of 1.4, 5.0, and 10.7 GHz. Radiative transfer calculations of microwave emissivities at these frequencies are performed with a number of moisture profiles measured for two soils. The calculated emissivities are compared with those derived from the Fresnel equation to deduce the microwave sampling depth in soils. The data acquired from the ground-level radiometric measurements during the summers of 1979-1981 are examined and compared with the theoretical analysis. Both theoretical and experimental analyses lead to the conclusion that the microwave samplinhg depth in soils is about one tenth of the wavelength of observation. It is shown that the moisture content at any depth near the surface of a smooth soil can be estimated, in principle, by a combination of a radiometric measurement and a curve generated by the Fresnel equation at an appropriate frequency, provided that the texture of the soil is known.

Wang, James R.↗

Landsat thematic mapper (TM) soil variability analysis over Webster County, Iowa

Thematic mapper simulator (TMS) data acquired June 7, June 23, and July 31, 1982, and Landsat thematic mapper (TM) data acquired August 2, September 3, and October 21, 1982, over Webster County, Iowa, were examined for within-field soil effects on corn and soybean spectral signatures. It was found that patterns displayed on various computer-generated map products were in close agreement with the detailed soil survey of the area. The difference in spectral values appears to be due to a combination of subtle soil properties and crop growth patterns resulting from the different soil properties. Bands 4 (0.76-.90 micron), 5 (1.55-1.75 micron), and 7 (2.08-2.35 micron) were found to be responding to the within-field soil variability even with increasing ground cover. While these results are preliminary, they do indicate that the soil influence on the vegetation is being detected by TM and should provide improved information relating to crop and soil properties.

Thompson, D. R.↗

Soil moisture ground truth, Lafayette, Indiana, site; St. Charles Missouri, site; Centralia, Missouri, site

The soil moisture ground-truth measurements and ground-cover descriptions taken at three soil moisture survey sites located near Lafayette, Indiana; St. Charles, Missouri; and Centralia, Missouri are given. The data were taken on November 10, 1975, in connection with airborne remote sensing missions being flown by the Environmental Research Institute of Michigan under the auspices of the National Aeronautics and Space Administration. Emphasis was placed on the soil moisture in bare fields. Soil moisture was sampled in the top 0 to 1 in. and 0 to 6 in. by means of a soil sampling push tube. These samples were then placed in plastic bags and awaited gravimetric analysis.

Jones, E. B.↗

Spectral characteristics and the extent of paleosols of the Palouse formation

The objective of this study is to test the hypothesis that TM data is adequate in band selection and width and in spatial resolution to distinguish soil organic matter, iron oxide, and lime-silica contents to map several severity classes of erosion in soils of the Palouse region. The methodology used is as follows: (1) To develop spectral relationships from TM data that define the spatial distribution of soil areas by levels of (1) organic matter in the surface soil, (2) iron oxide and clay in exposed paleosol B horizons, and (3) lime-silica accumulations in exposed paleosol B horizons; (2) To compare areas determined by the method outlined in 1 to patterns interpreted from color aerial photos, and to ground observations on bare-soil fields; and (3) To define, on the basis of results of 1 and 2 to the extent possible, where exposed paleosols exist within fields that are not bare, but have a crop cover, and the distribution of desirable and undesirable soil properties in each field.

Frazier, B. E.↗

Extension of laboratory-measured soil spectra to field conditions

Spectral responses of two glaciated soils, Chalmers silty clay loam and Fincastle silt loam, formed under prairie grass and forest vegetation, respectively, were measured in the laboratory under controlled moisture equilibria using an Exotech Model 20C spectroradiometer to obtain spectral data in the laboratory under artificial illumination. The same spectroradiometer was used outdoors under solar illumination to obtain spectral response from dry and moistened field plots with and without corn residue cover, representing the two different soils. Results indicate that laboratory-measured spectra of moist soil are directly proportional to the spectral response of that same field-measured moist bare soil over the 0.52 micrometer to 1.75 micrometer wavelength range. The magnitudes of difference in spectral response between identically treated Chalmers and Fincastle soils are greatest in the 0.6 micrometers to 0.8 micrometer transition region between the visible and near infrared, regardless of field condition or laboratory preparation studied.

Stoner, E. R.↗

Spatial variability of soil hydraulics and remotely sensed soil parameters

The development of methods to correctly interpret remotely sensed information about soil moisture and soil temperature requires an understanding of water and energy flow in soil, because the signals originate from the surface, or from a shallow surface layer, but reflect processes in the entire profile. One formidable difficulty in this application of soil physics is the spatial heterogeneity of natural soils. Earlier work has suggested that the heterogeneity of soil hydraulic properties may be described by the frequency distribution of a single scale factor. The sensitivity of hydraulic and energetic processes to the variation of this scale factor is explored with a suitable numerical model. It is believed that such an analysis can help in deciding how accurately and extensively basic physical properties of field soils need to be known in order to interpret thermal or radar waveband signals. It appears that the saturated hydraulic conductivity needs to be known only to its order of magnitude, and that the required accuracy of the soil water retention function is about 0.02 volume fraction. Furthermore, the results may be helpful in deciding how the total scene or view field, as perceived through a sensor, is composed from the actual mosaic of transient soil properties, such as surface temperature or surface soil moisture. However, the latter proposition presupposes a random distribution of permanent properties, a condition that may not be met in many instances, and no solution of the problem is apparent.

Lascano, R. J.↗

Photointerpretation of Skylab photography

The author has identified the following significant results. In terms of film grain texture and object definition, the S190B color positive film is distinctly superior to the S190A films, when both are compared in the 9 x 9 inch format. Within the six S190A films, the panchromatic black and white films are superior to the infrared black and white, and the color positive film is superior to the color infrared. Minimum relief differences on the order of 500 to 100 feet could be detected by stereoscopic study, however, it is not possible to determine to what extent vegetation and cultural practices assist in such delineations. Water and wind gaps through major ridges were easily seen. Streams of third order and larger were clearly visible and easy to trace; second order streams were not identified with consistency. Differences in color, tone, and textural patterns rarely supplied clues for differentiating soils or bedrock. The separation of naturally forested areas from areas of cultivation and pasture was effective and a valuable clue to the underlying geology. Suburban and industrial developments were clearly differentiated from urban areas and surrounding agricultural fields. Soil associations could be identified on a regional basis, but no sharp boundary could be drawn separating soil associations.

Mcmurtry, G. J.↗

Radar measurement of soil moisture content

The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4-8 GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system was used to measure the return at 10 frequency points across the 4-8 GHz band, at different look angles, and for all polarization combinations. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear over the range 15%-30% moisture content for all angles, frequencies, polarizations and surface conditions.

Ulaby, F. T.↗

Spectral characteristics and the extent of paleosols of the Palouse formation

Thematic mapping data was analyzed and verified by comparison to previously gathered transect samples and to aerial photographs. A bare-soil field with exposed paleosols characterized by slight enrichment of iron was investigated. Spectral relationships were first investigated statistically by creating a data set with DN values spatially matched as nearly as possible to field sample points. Chemical data for each point included organic carbon, free iron oxide, and amorphous iron content. The chemical data, DN values, and various band ratios were examined with the program package Statistix in order to find the combinations of reflectance data most likely to show a relationship which would dependably separate the exposed paleosols from the other soils. Cluster analysis and Fastclas classification procedures were applied to the most promising of the band ratio combinations.

Frazier, B. E.↗

Radar measurement of soil moisture content

The effect of soil moisture on the radar backscattering coefficient was investigated by measuring the 4- to 8-GHz spectral response from two types of bare-soil fields: slightly rough and very rough, in terms of the wavelength. An FM-CW radar system mounted atop a 75-ft truck-mounted boom was used to measure the return at ten frequency points across the 4- to 8-GHz band, at eight different look angles (0 through 70 deg), and for all polarization combinations. A total of 17 sets of data were collected covering the range from 4 to 36% soil moisture content by weight. The results indicate that the radar response to soil moisture content is highly dependent on the surface roughness, microwave frequency, and look angle. The response seems to be linear, however, over the range from 15 to 30% moisture content for all angles, frequencies, polarizations and surface conditions.

Ulaby, F. T.↗