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At least 289 records · Page 16

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗

Horizon Based Orientation Estimation for Planetary Surface Navigation

Planetary rovers navigate in extreme environments for which a Global Positioning System (GPS) is unavailable, maps are restricted to relatively low resolution provided by orbital imagery, and compass information is often lacking due to weak or not existent magnetic fields. However, an accurate rover localization is particularly important to achieve the mission success by reaching the science targets, avoiding negative obstacles visible only in orbital maps, and maintaining good communication connections with ground. This paper describes a horizon solution for precise rover orientation estimation. The detected horizon in imagery provided by the on board navigation cameras is matched with the horizon rendered over the existing terrain model. The set of rotation parameters (roll, pitch yaw) that minimize the cost function between the two horizon curves corresponds to the rover estimated pose.

localization↗

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Disaggregation - 3

This is a followup on the preceding presentation by Crosson and Schamschula. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to disaggregate the microwave measurements to allow comparison with outputs from the hydrological models. Weighted interpolation and Bayesian methods are proposed to facilitate the comparison. While remote measurements occur at a large scale, they reflect underlying small-scale features. We can give continuing estimates of the small scale features by correcting the simple 0th-order, starting with each small-scale model with each large-scale measurement using a straightforward method based on Kalman filtering.

Caulfield, John↗

Estimates of oceanic surface wind speed and direction using orthogonal beam scatterometer measurements and comparison of recent sea scattering theories

The wind direction properties of radar backscatter from the sea were empirically modelled using a cosine Fourier series through the 4th harmonic in wind direction (referenced to upwind). A comparison with 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data, at incidence angles of 40 and 65, indicates that effects to third and fourth harmonics are negligible. Another important result is that the Fourier coefficients through the second harmonic are related to wind speed by a power law expression. A technique is also proposed to estimate the wind speed and direction over the ocean from two orthogonal scattering measurements. A comparison between two different types of sea scatter theories, one type presented by the work of Wright and the other by that of Chan and Fung, was made with recent scatterometer measurements. It demonstrates that a complete scattering model must include some provisions for the anisotropic characteristics of the sea scatter, and use a sea spectrum which depends upon wind speed.

Moore, R. K.↗

Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

polar-orbiting↗

Senegalese land surface change analysis and biophysical parameter estimation using NOAA AVHRR spectral data

Surface biophysical estimates were derived from analysis of NOAA Advanced Very High Spectral Resolution (AVHRR) spectral data of the Senegalese area of west Africa. The parameters derived were of solar albedo, spectral visible and near-infrared band reflectance, spectral vegetative index, and ground temperature. Wet and dry linked AVHRR scenes from 1981 through 1985 in Senegal were analyzed for a semi-wet southerly site near Tambacounda and a predominantly dry northerly site near Podor. Related problems were studied to convert satellite derived radiance to biophysical estimates of the land surface. Problems studied were associated with sensor miscalibration, atmospheric and aerosol spatial variability, surface anisotropy of reflected radiation, narrow satellite band reflectance to broad solar band conversion, and ground emissivity correction. The middle-infrared reflectance was approximated with a visible AVHRR reflectance for improving solar albedo estimates. In addition, the spectral composition of solar irradiance (direct and diffuse radiation) between major spectral regions (i.e., ultraviolet, visible, near-infrared, and middle-infrared) was found to be insensitive to changes in the clear sky atmospheric optical depth in the narrow band to solar band conversion procedure. Solar albedo derived estimates for both sites were not found to change markedly with significant antecedent precipitation events or correspondingly from increases in green leaf vegetation density. The bright soil/substrate contributed to a high albedo for the dry related scenes, whereas the high internal leaf reflectance in green vegetation canopies in the near-infrared contributed to high solar albedo for the wet related scenes. The relationship between solar albedo and ground temperature was poor, indicating the solar albedo has little control of the ground temperature. The normalized difference vegetation index (NDVI) and the derived visible reflectance were more sensitive to antecedent rainfall amounts and green vegetation changes than were near-infrared changes. The information in the NDVI related to green leaf density changes primarily was from the visible reflectance. The contribution of the near-infrared reflectance to explaining green vegetation is largely reduced when there is a bright substrate.

Vukovich, Fred M.↗

Sea Surface Temperature Gradients Estimation Using Top-of-Atmosphere Observations from the ESA Earth Explorer 10 Harmony Mission: Preliminary Studies

The Harmony satellite mission was recently approved as the next European Space Agency (ESA) Earth Explorer 10. The mission science objectives cover several applications related to solid earth, the cryosphere, upper-ocean dynamics and air–sea interactions. The mission consists of a constellation of two satellites, flying with the Copernicus Sentinel 1 (C or D) spacecraft, each hosting a C-band receive-only radar and a thermal infrared (TIR) payload. From an ocean dynamics/air–sea interaction perspective, the mission will provide the unique opportunity to observe simultaneously the signature of submesoscale upper-ocean processes via synthetic aperture radar and TIR imagery. The TIR imager is based on microbolometer technology and its acquisitions will rely on four channels: three narrow-band channels yielding observations at a ≃1 km spatial sampling distance (SSD) and a panchromatic (PAN, 8–12 μm) channel characterized by a ≃300 m SSD. Our study investigates the potential of Harmony in retrieving spatial features related to sea surface temperature (SST) gradients from the high-resolution PAN channel, relying on top-of-atmosphere (TOA) observations. Compared to a standard SST gradient retrieval, our approach does not require atmospheric correction, thus avoiding uncertainties due to inter-channel co-registration and radiometric consistency, with the possibility of exploiting the higher resolution of the PAN channel. The investigations were carried out simulating the future Harmony TOA radiances (TARs), as well as relying on existing state-of-the-art level 1 satellite products. Our approach enables the correct description of SST features at the sea surface avoiding the generation of spurious features due to atmospheric correction and/or instrumental issues. In addition, analyses based on existing satellite products suggest that the clear-sky TOA observations, in a typical mid-latitude scene, allow the reconstruction of up to 85% of the gradient magnitudes found at the sea-surface level. The methodology is less efficient in tropical areas, suffering from smoothing effects due to the high concentrations of water vapor.

sea surface temperature (SST)↗

Interannual Variability of Tropical Ocean Evaporation: A Comparison of Microwave Satellite and Assimilation Results

Remote sensing methodologies for turbulent heat fluxes over oceans depend on driving bulk formulations of fluxes with measured surface winds and estimated near surface thermodynamics from microwave sensors of the Special Sensor Microwave Imager (SSM/I) heritage. We will review recent work with a number of SSM/I-based algorithms and investigate the ability of current data sets to document global, tropical ocean-averaged evaporation changes in association with El Nino and La Nina SST changes. We show that in addition to interannual signals, latent heat flux increases over the period since late 1987 range from approx. .1 to .6 mm/ day are present; these represent trends 2 to 3 times larger than the NCEP Reanalysis. Since atmospheric storage cannot account for the difference, and since compensating evapotranspiration changes over land are highly unlikely to be this large, these evaporation estimates cannot be reconciled with ocean precipitation records such as those produced by the Global Precipitation Climatology Project, GPCP. The reasons for the disagreement include less than adequate intercalibration between SSM/I sensors providing winds and water vapor for driving the algorithms, biases due to the assumption that column integrated water vapor mirrors near surface water vapor variations, and other factors as well. The reanalyses have their own problems with spin-up during assimilation, lack of constraining input data at the ocean surface, and amplitude of synoptic transients.

Robertson, Franklin R.↗

Estimation of sea surface temperature from remote measurements in the 11-13 micron window region

The Nimbus-4 IRIS data was examined in the spectral region 775 to 1250/cm (8-13 microns) for useful information to determine the sea surface temperature. The high spectral resolution data of IRIS was degraded to low resolution by averaging to simulate a multi-channel radiometer in the window region. These simulated data show that within the region 775-975/cm (12.9-10.25 microns) the brightness temperatures are linearly related to the absorption parameters. Such a linear relationship is observed over cloudy as well as clear regions and over a wide range of latitudes. From this linear relationship it is feasible to correct for the atmospheric attenuation and get the sea surface temperature, accurate to within 1 K, in a cloud free field of view. The information about the cloud cover is taken from the TV pictures and BUV albedo measurements on board the Nimbus-4 satellite.

Prabhakara, C.↗

Bistatic-radar estimation of surface-slope probability distributions with applications to the moon.

A method for extracting surface-slope frequency distributions from bistatic-radar data has been developed and applied to the lunar surface. Telemetry transmissions from orbiting Apollo spacecraft were received on the earth after reflection from the lunar surface. The echo-frequency spectrum was related analytically to the probability distribution of lunar slopes. Standard regression techniques were used to solve the inverse problem of finding slope distributions from observed echo-frequency spectra. Data taken simultaneously at two wavelengths, 13 and 116 cm, have yielded diverse slope statistics.

Parker, M. N.↗

Estimation of sea surface temperature from remote sensing in the 11-13 micron window region

The Nimbus 3 and 4 IRIS spectral data in the 11-13 micron water vapor window region are analyzed to determine the sea surface temperature (SST). The high spectral resolution data of IRIS are averaged over approximately 1 micron wide intervals to simulate channels of a radiometer to measure the SST. Three channels are utilized to measure SST over cloud-free oceans. However, two of these channels are sufficient in routine SST determination. The differential absorption properties of water vapor in the two channels enable one to determine the water vapor absorption correction without detailed knowledge of the vertical profiles of temperature and water vapor. The feasibility of determining the SST is demonstrated globally with Nimbus 3 data where cloud-free areas can be selected with the help of albedo data from the MRIR experiment on board the same satellite.

Prabhakara, C.↗

Estimation of sea surface temperature from remote sensing in the 11to 13-micron window region

The Nimbus 3 and 4 Iris spectral data in the 11- to 13-micron water vapor window region are analyzed to determine the sea surface temperature (SST). The high spectral resolution data of Iris are averaged over approximately 1-micron-wide intervals to simulate channels of a radiometer to measure the SST. In the present exploratory study, three such channels in the 775- to 960-per cm (12.9-10.5 micron) region are utilized to measure the SST over cloud-free oceans. However, two of these channels are sufficient in routine SST determination. The differential absorption properties of water vapor in the two channels make it possible to determine the water vapor absorption correction without detailed knowledge of the vertical profiles of temperature and water vapor. The feasibility of determining the SST is demonstrated globally with Nimbus 3 data, where cloud-free areas can be selected with the help of albedo data from the medium-resolution infrared radiometer experiment on board the same satellite. The SST derived from this technique agrees with the measurements made by ships to about 1 C.-

Prabhakara, C.↗

Remote estimation of the surface characteristics and energy balance over an urban-rural area and the effects of surface heat flux on plume spread and concentration

A one dimensional boundary layer model was used in conjunction with satellite derived infrared surface temperatures to deduce values of moisture availability, thermal inertia, heat and evaporative fluxes. The Penn State satellite image display system, a sophisticated image display facility, was used to remotely sense these various parameters for three cases: St. Louis, Missouri; the Land Between the Lakes, Kentucky; and Clarksville, Tennessee. The urban centers displayed the maximum daytime surface temperatures which correspond to the minimum values of moisture availability. The urban center of St. Louis and the bodies of water displayed the maximum nighttime surface temperatures which correspond to the maximum thermal inertia values. It is shown that moisture availability and thermal inertia are very much responsible for the formation of important temperature variations over the urban rural complex.

Dicristofaro, D. C.↗

Satellite estimation of the surface energy balance, moisture availability and thermal inertia

A method for inferring the distribution of surface heat and evaporative fluxes and the ground moisture availability and thermal inertia (ground conductive capacity) is used to analyze two urbanized areas, Los Angeles and St. Louis. The technique employs infrared satellite temperature measurements in conjunction with a one-dimensional boundary-layer model. Results show that there is a marked reduction of evaporation and moisture availability and a corresponding elevation of sensible heat flux over urbanized areas and over cropped areas with low vegetative cover. Conversely, low heat flux and high evaporation characterize vegetated and, especially, forested areas. Warm urban centers appear directly related to a reduction in vegetation, which normally allows for a greater fraction of available radiant energy to be converted into latent heat flux. The distribution of thermal inertia was surprisingly ill-defined and its variation between urban and rural areas was quite small. Thus, the increased heat storage within the urban fabric, which has been proposed as the underlying cause of the nocturnal heat island, may be caused mainly by enhanced daytime surface heating which occurs because of surface dryness, rather than by large spatial variations in the conductivity of the surface.

Carlson, T. N.↗

Satellite-derived surface energy balance estimates in the Alaskan sub-Arctic

The capabilities of the heat capacity mapping mission (HCMM) satellite are described, together with the numerical model used for data analysis. The HCMM carries the HCM radiometer for remote sensing in the visible and 0.55-1.1 micron wavelength regions, as well as in the 10.5-12.5 micron interval, with the swath being 720 km and each pixel being a square 500 m on a side. The HCMM is intended to aid in hydrological studies of soil moisture, runoff, and evapotranspiration estimates. Data are taken of the albedos and temperatures of vegetation, assuming that all reflection is diffuse. Corrections are made in the algorithm to account for sun angle and the spacecraft distance from the earth. Sample calculations are provided from scans of a coastal plain, mountains, and plateaus of Alaska.

Gurney, R. J.↗

Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data

Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. The hypothesis that the relationship between surface temperature and canopy density is sensitivite to seasonal changes in canopy resistance of conifer forests is presently tested. Surface temperature and canopy density were computed for a 20 x 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance for the same period. For all eight days, surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index, implying that latent heat exchange is the major cause of spatial variations in surface radiant tmeperatures.

Nemani, Ramakrishna R.↗

Determination of surface reflectance and estimates of atmospheric optical depth and single scattering albedo from Landsat Thematic Mapper data

Groound-reflectance data on selected targets for calbiration of a Landsat TM image of Wind River Basin, Wyoming, acquired November 21, 1982 were examined. Field-derived calibration relationships together with Landsat radiometric calibration data are used to convert scanner DN values to spectral radiance for the TM bands and (together with a simplified homogeneous atmospheric model) to obtain estimates of single-scattering albedo and optical depth consistent with the derived path radiance and transmission properties of the atmosphere. These estimates are used to study the problems of evaluation of the magnitude of adjacency effects for reference targets, the assumption of isotropic properties, and the aggregate magnitude of multiple reflections between sky and ground. The radiance calibration equations are also used together with preflight measured signal/noise properties of the TM-4 system to estimate the noise-equivalent reflectance recoverable in practice from the system.

Conel, James E.↗