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D. J. Meyer

Publications and source records attributed to D. J. Meyer.

12 recordsLinked to original sources
USGS2010

Water vapour correction of the daily 1 km AVHRR global land dataset: Part I validation and use of the Water Vapour input field

An atmospheric correction algorithm developed for the 1 km Advanced Very High Resolution Radiometer (AVHRR) global land dataset was modified to include a near real-time total column water vapour data input field to account for the natural variability of atmospheric water vapour. The real-time data input field used for this study is the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A global total column water vapour dataset. It was validated prior to its use in the AVHRR atmospheric correction process using two North American AVHRR scenes, namely 13 June and 28 November 1996. The validation results are consistent with those reported by others and entail a comparison between TOVS, radiosonde, experimental sounding, microwave radiometer, and data from a hand-held sunphotometer. The use of this data layer as input to the AVHRR atmospheric correction process is discussed.

International Journal of Remote Sensing↗
USGS2010

Study of high SAR backscattering caused by an increase of soil moisture over a sparsely vegetated area: Implications for characteristics of backscattering

We used interferometric methods on a pair of repeat-pass ERS-1 synthetic aperture radar (SAR) images to study soil moisture changes over sparsely vegetated targets. The intensity of the SAR image acquired at one time was higher than that of an image acquired at an earlier time. We used a correlation image computed from the SAR image pair to study the cause of the observed changes in SAR intensity. Because a reduction of correlation over areas with intensity changes was not observed, we interpreted the intensity changes as not being caused by changes in roughness/structure, but by a change in soil moisture owing to rainfall. An increase in soil moisture ranging from 5% to 20% is the most likely explanation for the increase of intensity. These analyses imply that both intensity and phase information should be used in SAR change detection applications.

International Journal of Remote Sensing↗
USGS2008

The effect of variations in relative spectral response on the retrieval of land surface parameters from multiple sources of remotely sensed imagery

Airborne visible infrared imaging spectrometer (AVIRIS) images, collected over Sioux Falls, South Dakota, were used to quantify the effect of spectral response on different surface materials and to develop spectral "figures-of-merit" for spectral responses covering similar, but not identical spectral bands. In this simulation, AVIRIS images were converted to radiance, then spectrally resampled to six wavelength bands commonly used for terrestrial observation. Preliminary results indicate that differences between the simulations can be attributed to variations in surface reflectance within spectral bands, and suggest influences due to water vapor absorption. Radiance simulated from the spectrally narrow Moderate Resolution Imaging Spectroradiometer (MODIS) relative spectral responses (RSR) was generally higher than that using the broader Enhanced Thematic Mapper Plus (ETM+) RSRs over most targets encountered over the test area. This is consistent with many MODIS bands being biased toward shorter wavelengths compared to corresponding ETM+ bands when viewing targets whose radiance decreases with wavelength. In some cases the higher radiance values appeared to occur where the MODIS RSR is better situated over peak reflected wavelengths. Simulation differences between MODIS & ETM+ bands in the near-infrared indicated higher MODIS radiance values that suggest the influence of water vapor absorption at 820 nanometers. This result agreed with water vapor values retrieved from the AVIRIS images themselves at around 2.7 cm precipitable water, and measurements made at a nearby AERONET node at around 2.8 cm during the AVIRIS overflight.

Conference Paper↗
USGS2007

Estimating the effective spatial resolution of an AVHRR time series

A method is proposed to estimate the spatial degradation of geometrically rectified AVHRR data resulting from misregistration and off-nadir viewing, and to infer the cumulative effect of these degradations over time. Misregistrations are measured using high resolution imagery as a geometric reference, and pixel sizes are computed directly from satellite zenith angles. The influence or neighbouring features on a nominal 1 km by 1 km pixel over a given site is estimated from the above information, and expressed as a spatial distribution whose spatial frequency response is used to define an effective field-of-view (EFOV) for a time series. In a demonstration of the technique applied to images from the Conterminous U.S. AVHRR data set, an EFOV of 3·1km in the east-west dimension and 19 km in the north-south dimension was estimated for a time series accumulated over a grasslands test site.

International Journal of Remote Sensing↗
USGS2007

Cross-calibration of the Terra MODIS, Landsat 7 ETM+ and EO-1 ALI sensors using near-simultaneous surface observation over the Railroad Valley Playa, Nevada, test site

A cross-calibration methodology has been developed using coincident image pairs from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS), the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Earth Observing EO-1 Advanced Land Imager (ALI) to verify the absolute radiometric calibration accuracy of these sensors with respect to each other. To quantify the effects due to different spectral responses, the Relative Spectral Responses (RSR) of these sensors were studied and compared by developing a set of "figures-of-merit." Seven cloud-free scenes collected over the Railroad Valley Playa, Nevada (RVPN), test site were used to conduct the cross-calibration study. This cross-calibration approach was based on image statistics from near-simultaneous observations made by different satellite sensors. Homogeneous regions of interest (ROI) were selected in the image pairs, and the mean target statistics were converted to absolute units of at-sensor reflectance. Using these reflectances, a set of cross-calibration equations were developed giving a relative gain and bias between the sensor pair.

Conference Paper↗
USGS2004

A geometric performance assessment of the EO-1 advanced land imager

The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2004

Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor

As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2002

Satellite mapping of surface biophysical parameters at the biome scale over the North American grasslands: A case study

Quantification of biophysical parameters is needed by terrestrial process modeling and other applications. A study testing the role of multispectral data for monitoring biophysical parameters was conducted over a network of grassland field sites in the Great Plains of North America. Grassland biophysical parameters [leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fPAR), and biomass] and their relationships with ground radiometer normalized difference vegetation index (NDVI) were established in this study ( r 2 =.66–.85) from data collected across the central and northern Great Plains in 1995. These spectral/biophysical relationships were compared to 1996 field data from the Tallgrass Prairie Preserve in northeastern Oklahoma and showed no consistent biases, with most regression estimates falling within the respective 95% confidence intervals. Biophysical parameters were estimated for 21 “ground pixels” (grids) at the Tallgrass Prairie Preserve in 1996, representing three grazing/burning treatments. Each grid was 30×30 m in size and was systematically sampled with ground radiometer readings. The radiometric measurements were then converted to biophysical parameters and spatially interpolated using geostatistical kriging. Grid-based biophysical parameters were monitored through the growing season and regressed against Landsat Thematic Mapper (TM) NDVI ( r 2 =.92–.94). These regression equations were used to estimate biophysical parameters for grassland TM pixels over the Tallgrass Prairie Preserve in 1996. This method maintained consistent regression development and prediction scales and attempted to minimize scaling problems associated with mixed land cover pixels. A method for scaling Landsat biophysical parameters to coarser resolution satellite data sets (1 km 2 ) was also investigated.

Remote Sensing of Environment↗
USGS1992

Evaluation of terrain models for the geocoding and terrain correction, of synthetic aperture radar (SAR) images

The variability of the resolutions and the presence of artifacts cause inaccurate correction of the terrain-induced geometric distortions in synthetic-aperture radar (SAR) images. To quantify the effects of these inaccuracies on SAR terrain correction, corrections of a Seasat SAR image were performed using a 1 degrees US Geological Survey (USGS) terrain model, a 7.5-min USGS terrain model, and a terrain model derived from stereoimagery acquired from SPOT. Geometric verifications of the corrected imagery showed that the resolution of the 1 degrees terrain model is not adequate to resolve many features in the Seasat image. Geometric verifications of images corrected with the two higher resolution terrain models showed localized errors as large as 52 m for mountain peaks. However, comparison of data corrected with those models shows that both produce results that differ by less than the resolution of either of them. Periodic artifacts observed in the terrain models translated to ground range differences of 18 m, which are well below the resolution of the SAR imagery.

IEEE Transactions on Geoscience and Remote Sensing↗