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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation and Soil Salinity

The Dry Chaco in South America is a semi-arid ecoregion prone to dryland salinization. In this region, we investigated coarse-scale surface soil moisture (SM), soil temperature, soil salinity and vegetation, using L-band microwave brightness temperature (TB) observations and retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions, Catchment Land Surface Model (CLSM) simulations, and in situ measurements within 26 sampled satellite pixels. Across these 26 sampled pixels, the satellite-based SM outperformed CLSM SM compared to field data, and forward L-band TB simulations derived from in situ SM and temperature performed better than those derived from CLSM estimates relative to SMOS TB observations. The surface salinity for the sampled pixels was on average only 4 mg/g and only locally influenced the TB simulations, when including salinity in the dielectric mixing model of the forward radiative transfer model (RTM) simulations. To explore the potential of retrieving salinity together with other RTM parameters to optimize TB simulations over the entire Dry Chaco, the RTM was inverted using 10 years of multi-angular SMOS TB data and constraints of CLSM SM and temperature. However, the latter modeled SM was not sufficiently accurate and factors such as open surface water were missing in the background constraints, so that the salinity retrievals effectively represented a bulk correction of the dielectric constant, rather than salinity per se. However, the retrieval of vegetation, scattering albedo and surface roughness resulted in realistic values.

L-Band↗
NASA NTRS1993

Spatial and temporal variability of soil temperature, moisture and surface soil properties

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

Hajek, B. F.↗
NASA NTRS1981

A parameterization of effective soil temperature for microwave emission

A parameterization of effective soil temperature is discussed, which when multiplied by the emissivity gives the brightness temperature in terms of surface (T sub o) and deep (T sub infinity) soil temperatures as T = T sub infinity + C (T sub o - T sub infinity). A coherent radiative transfer model and a large data base of observed soil moisture and temperature profiles are used to calculate the best-fit value of the parameter C. For 2.8, 6.0, 11.0, 21.0 and 49.0 cm wavelengths. The C values are respectively 0.802 + or - 0.006, 0.667 + or - 0.008, 0.480 + or - 0.010, 0.246 + or - 0.009, and 0,084 + or - 0.005. The parameterized equation gives results which are generally within one or two percent of the exact values.

Choudhury, B. J.↗
NASA NTRS1982

A numerical simulation of soil temperature and moisture variations for a bare field

The diurnal variations of soil temperature and moisture content were simulated for a bare agricultural field in the San Joaquin Valley in California. The simulation pertained to the first 72 hours of drying, from saturation, of a sandy, clay loam soil. The results were compared with measurements of soil temperature and moisture content made at the field. Calculated and measured values of soil temperature trends agreed in general, but model results of moisture trends did not replicate observed diurnal effects evident at depths 4 centimeters or more below the surface.

Schieldge, J. P.↗
NASA NTRS2007

Estimating the Soil Temperature Profile from a Single Depth Observation: A Simple Empirical Heatflow Solution

Two data sets of experimental field observations with a range of meteorological conditions are used to investigate the possibility of modeling near-surface soil temperature profiles in a bare soil. It is shown that commonly used heat flow methods that assume a constant ground heat flux can not be used to model the extreme variations in temperature that occur near the surface. This paper proposes a simple approach for modeling the surface soil temperature profiles from a single depth observation. This approach consists of two parts: 1) modeling an instantaneous ground flux profile based on net radiation and the ground heat flux at 5cm depth; 2) using this ground heat flux profile to extrapolate a single temperature observation to a continuous near surface temperature profile. The new model is validated with an independent data set from a different soil and under a range of meteorological conditions.

Holmes, Thomas↗
NASA NTRS1983

Soil temperature investigations using satellite acquired thermal-infrared data in semi-arid regions

Thermal-infrared data from the Heat Capacity Mapping Mission satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures (MAST) and annual surface temperature amplitudes (AMP) in semi-arid east central Utah. Diurnal data with minimal snow and cloud cover were selected for five dates throughout a yearly period and geometrically co-registered. Rubber-sheet stretching was aided by the WARP program which allowed preview of image transformations. Daytime maximum and nighttime minimum temperatures were averaged to generation average daily temperature (ADT) data set for each of the five dates. Five ADT values for each pixel were used to fit a sine curve describing the theoretical annual surface temperature response as defined by a solution of a one-dimensinal heat flow equation. Linearization of the equation produced estimates of MAST and AMP plus associated confidence statistics. MAST values were grouped into classes and displayed on a color video screen. Diurnal surface temperatures and MAST were primarily correlated with elevation.

Day, R. L.↗
NASA NTRS1981

AgRISTARS: Early warning and crop condition assessment. Plant cover, soil temperature, freeze, water stress, and evapotranspiration conditions

Emissive (10.5 to 12.5 microns) and reflective (0.55 to 1.1 microns) data for ten day scenes and infrared data for six night scenes of southern Texas were analyzed for plant cover, soil temperature, freeze, water stress, and evapotranspiration. Heat capacity mapping mission radiometric temperatures were: within 2 C of dewpoint temperatures, significantly correlated with variables important in evapotranspiration, and related to freeze severity and planting depth soil temperatures.

Wiegand, C. L.↗
NASA NTRS1982

Delineation of soil temperature regimes from HCMM data

Average daily temperatures (ADT) were calculated for five Heat Capacity Mapping Mission scenes by averaging raw daytime temperature and nighttime temperature values using the SUBTRAN program. Mean annual soil temperatures (MAST) were calculated using ADT as input into a linearized one-dimensional heat flow equation describing the theoretical temperature response curve at the Earth's surface. The annual amplitude (AMP) of the response curve was also calculated. Finally, versatec plots of MAST and AMP were generated showing their spatial distribution.

Day, R. L.↗
NASA NTRS1984

Soil temperature extrema recovery rates after precipitation cooling

From a one dimensional view of temperature alone variations at the Earth's surface manifest themselves in two cyclic patterns of diurnal and annual periods, due principally to the effects of diurnal and seasonal changes in solar heating as well as gains and losses of available moisture. Beside these two well known cyclic patterns, a third cycle has been identified which occurs in values of diurnal maxima and minima soil temperature extrema at 10 cm depth usually over a mesoscale period of roughly 3 to 14 days. This mesoscale period cycle starts with precipitation cooling of soil and is followed by a power curve temperature recovery. The temperature recovery clearly depends on solar heating of the soil with an increased soil moisture content from precipitation combined with evaporation cooling at soil temperatures lowered by precipitation cooling, but is quite regular and universal for vastly different geographical locations, and soil types and structures. The regularity of the power curve recovery allows a predictive model approach over the recovery period. Multivariable linear regression models alloy predictions of both the power of the temperature recovery curve as well as the total temperature recovery amplitude of the mesoscale temperature recovery, from data available one day after the temperature recovery begins.

Welker, J. E.↗
NASA NTRS1986

Biologically relevant physical measurements in the ice-free valleys of southern Victoria Land: soil temperature profiles and ultraviolet radiation

As part of the ongoing comprehensive study of the cryptoendolithic microbial community in the ice-free valleys of southern Victoria Land, thermal properties of the soil and the ultraviolet radiation regime were measured. Although soil temperature profiles have been measured in the ice-free valleys (e.g., Cameron et al. 1970; Cameron 1972), these are the first such data from higher elevations. This is apparently the first time the ultraviolet radiation regime has been measured in the Antarctic.

NASA Program Exobiology↗
NASA NTRS1991

A case study demonstration of the soil temperature extrema recovery rates after precipitation cooling at 10-cm soil depth

Since the invention of maximum and minimum thermometers in the 18th century, diurnal temperature extrema have been taken for air worldwide. At some stations, these extrema temperatures were collected at various soil depths also, and the behavior of these temperatures at a 10-cm depth at the Tifton Experimental Station in Georgia is presented. After a precipitation cooling event, the diurnal temperature maxima drop to a minimum value and then start a recovery to higher values (similar to thermal inertia). This recovery represents a measure of response to heating as a function of soil moisture and soil property. Eight different curves were fitted to a wide variety of data sets for different stations and years, and both power and exponential curves were fitted to a wide variety of data sets for different stations and years. Both power and exponential curve fits were consistently found to be statistically accurate least-square fit representations of the raw data recovery values. The predictive procedures used here were multivariate regression analyses, which are applicable to soils at a variety of depths besides the 10-cm depth presented.

Welker, Jean Edward↗
NASA NTRS2000

BOREAS TF-3 NSA-OBS Tower Flux, Meteorological, and Soil Temperature Data

The BOReal Ecosystem-Atmosphere Study Tower Flux (BOREAS TF-3) team collected tower flux, surface meteorological, and soil temperature data at the BOREAS Northern Study Area-Old Black Spruce (NSA-OBS) site continuously from the March 1994 through October 1996. The data are available in tabular ASCII files.

Wofsy, Steven↗
NASA NTRS1981

Plant cover, soil temperature, freeze, water stress, and evapotranspiration conditions

Emissive and reflective data for 10 days, and IR data for 6 nights in south Texas scenes were analyzed after procedures were developed for removing cloud-affected data. HCMM radiometric temperatures were: within 2 C of dewpoint temperatures on nights when air temperature approached dewpoint temperatures; significantly correlated with variables important in evapotranspiration; and, related to freeze severity and planting depth soil temperatures. Vegetation greenness indexes calculated from visible and reflective IR bands of NOAA-6 to -9 meteorological satellites will be useful in the AgRISTARS program for seasonal crop development, crop condition, and drought applications.

Wiegand, C. L.↗
NASA NTRS2000

BOREAS TF-9 SSA-OBS Tower Flux, Meteorological, and Soil Temperature Data

The BOREAS TF-9 team collected energy, carbon dioxide, and water vapor flux data at the BOREAS SSA-OBS site during the growing season of 1994 and most of the year for 1996. From the winter of 1995 to 1996, soil temperature data were also collected and provided. The data are available in tabular ASCII files.

Hall, Forrest G.↗
NASA NTRS1982

Delineation of soil temperature regimes from HCMM data

The subsetting of HCMM data into ORSER format was completed for four dates using a modified SUBSET program. Large areas (approximately 2500 scan lines, 1680 elements) were selected to increase the occurrence of suitable control points for registration. Average daily temperatures (ADT) were calculated for each date. The MERGE program combined registered daytime temperature (DAY-IR) with nighttime temperature (NIGHT-IR) to form a separate two-channel data set. The SUBTRAN program averaged the DAY-IR and NIGHT-IR creating a third ADT channel. Registration equations for the four ADT data sets were generated. A one dimensional soil heat flow equation was modified to allow for mean annual soil temperature predictions using merged ADT data sets.

Day, R. L.↗
NASA NTRS2019

Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S

Seasonal freeze-thaw (FT) affects over half the northern hemisphere and impacts many key processes of the Earth System such as energy exchange, hydrology and vegetation. Nearly all past studies using spaceborne FT retrievals have focused on characterizing FT specifically for natural environments. FT in the built environment is also routinely studied and a topic of great interest, especially with regards to transportation infrastructure. Whereas natural FT process are frequently investigated using spaceborne observations, FT studies of roads are often limited to local scales, using in situ or nearby weather station data only. Comparisons between FT retrievals obtained from NASA's Soil Moisture Active Passive (SMAP) satellite and roads in Alaska (AK) and the Contiguous United States (CONUS) showed that spaceborne FT retrievals had good agreement with road data. But those results also indicated that NASA FT retrievals in CONUS were relatively too warm compared to road data. If SMAP FT retrievals were to be used for identifying FT transition timing for applications by the transportation community, it is also important for frozen conditions to be identified more accurately. This work is primarily concerned with improving frozen retrievals made in CONUS by calculating new Normalized Polarization Ratio (NPR) thresholds as compared to those currently used in SMAP FT. We found that focusing on a temporal subset of October through May for comparisons greatly improved the correlation between NPR and effective soil temperature (Teff, one of SMAP's ancillary datasets), often from about zero to 0.6. We then applied linear regression between NPR and Teff to obtain new NPR thresholds resulting in the FT-Roads (FT-R) product. NASA FT and FT-R were evaluated against road data at about 1000 locations in CONUS and a battery of different tests indicated that FT-R performed better under nearly all conditions compared to NASA FT. Overall, NASA FT accuracies were 69% and 80% for 6 am and 6 pm SMAP retrievals, while FT-R achieved accuracies of 79% and 82%. We also investigated the potential for using Teff for road FT (6 am, only) and found that those comparisons were even more accurate (84%). We've also quantified inter- and intraregional differences of SMAP FT performance and found that accuracy metrics vary over twice as much between geographic subdivisions (9%) as compared to between the states within a subdivision (4%). Most importantly, the main goal of improving the detection of in situ frozen conditions in CONUS was realized, with FT-R accurately detecting frozen conditions >50% more frequently than NASA FT.

Passive microwave↗
NASA NTRS1981

Delineation of soil temperature regimes from HCMM data

Evaluation of LANDSAT and Heat Capacity Mapping Mission (HCMM) data as input into National Cooperative Soil Survey is discussed. Signature classification techniques were applied to 13 May 76 LANDSAT data. LANDSAT data was overlaid with HCMM data, revealing registration problems caused by a shortage of control points in LANDSAT data, and the WARP program developed to improve registration accuracy. Initial images for control point selection were produced using digital terrain elevation data. Statistical procedures for evaluating data classification and to describe spatial distribution of surface temperature and its correlation with soil surface conditions were investigated.

Day, R. L.↗
NASA NTRS1992

A model for inferring canopy and underlying soil temperatures from multi-directional measurements

A model is presented of thermal emission from a canopy/soil surface, where the soil and the leaves are at different temperatures, Tg and Tc, respectively. The temperature Tm corresponding to a radiometer reading is given by B sub lambda(Tm) = chi-B sub lambda(Tg) + (1-chi)B sub lambda(Tc), where B sub lambda denotes the Planck blackbody function at wavelength lambda, chi specifies the fraction of the field of view occupied by the soil at a given view direction, and an emissivity of 1.0 is assumed for the plants and the soil. It is observed that at large view zenith angles, only the plants are effectively seen, and therefore Tc can be determined from the observations a large zenith angles, to the extent that such observations are practical. Water stress can produce an increase of chi and thus tends to produce an exaggerated increase in the observed temperature compared to the actual increase in canopy temperature. These effects are analyzed for a simulated soybean canopy.

Otterman, J.↗