A custom EASE-Grid SSM/I processing system

Kim, E.J.; O'Kray, Chad; Hinds, Nigel; England, Anthony W.; Brodzik, M. J.; Knowles, K.; Hardman, M.

doi:10.1109/igarss.1998.699689

Cited by 6 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For polar applications, this simple operation is much easier than area calculations on the common alternative polar stereographic grids, where grid cell area is a function of latitude. Data set producers also take advantage of the EASE-Grid "scalability" feature by defining custom grid resolutions and areal coverages to suit specific applications [11]. Figure 2.…”

mentioning

confidence: 99%

EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

Brodzik

Billingsley

Haran

et al. 2012

IJGI

386

261

View full text Add to dashboard Cite

Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid) was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to understand, EASE-Grid suffers from limitations that make it impossible to format in the widely popular GeoTIFF convention without reprojection. Importing EASE-Grid data into standard mapping software packages is nontrivial and error-prone. This article defines a standard for an improved EASE-Grid 2.0 definition, addressing how the changes rectify issues with the original grid definition. Data distributed using the EASE-Grid 2.0 standard will be easier for users to import into standard software packages and will minimize common reprojection errors that users had encountered with the original EASE-Grid definition.Keywords: EASE-Grid 2.0; EASE-Grid; WGS 84; equal-area projections; Earth-gridded EASE-Grid History and AttributesDefined in the early 1990s as part of the NOAA/NASA Polar Pathfinder Program for gridded, satellite-derived passive microwave brightness temperatures, the Equal-Area SSM/I Earth Grid (EASE-Grid) was simple to use and understand. The original definition [1,2] specified three ISPRS Int. J. Geo-Inf. 2012, 1 33 projections together with the Backus-Gilbert interpolation method used for the SSM/I (Special Sensor Microwave/Imager) Pathfinder data set [3]. The EASE-Grid projection and gridding scheme was quickly adopted and used with different interpolation methods by the SMMR, AVHRR and TOVS Polar Pathfinder projects, and has been used in the production of numerous other data sets since then. Over time, the authors realized that the projection and gridding scheme had become so widely used that the SSM/I in the original name was a misnomer, since there was nothing SSM/I-specific about the projection and grid definitions. By 2002, Brodzik and Knowles [4] decided to retain the acronym but changed the meaning to "Equal-Area Scalable Earth-Grid", to emphasize the versatility of applications it enjoyed. Today, the term EASE-Grid refers to the three original projections and associated gridding scheme, but does not include prescriptions for binning or interpolation methods.The EASE-Grid definition [4] specifies a set of three equal-area projections together with an infinite set of potential grid (spatial resolution and coverage) definitions. The EASE-Grid projections comprise polar aspect Lambert azimuthal equal-area projections (Figure 1) for Northern or Southern Hemisphere, and a cylindrical equal-area projection with standard parallels at ±30• (Figure 2) for applications in midand low-latitude regions. The first EASE-Grids, defined for SSM/I gridded brightness temperatures at 25-km resolution, spanned the full Northern and Southern Hemispheres in the azimuthal aspects and the global projection to a latitude of ±86.72• . This poleward extent was inside the data area near the pole for SSM/I, where no data were collected by the sensor due to orbital inclina...

show abstract

mentioning

confidence: 99%

EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

Brodzik

Billingsley

Haran

et al. 2012

IJGI

386

261

View full text Add to dashboard Cite

show abstract

“…NSIDC's operational EASE-Grid processor (referred to here as the ''standard'' processor) is not configured to operate in this mode. A ''custom'' EASE-Grid processor was created in cooperation with NSIDC [Kim et al, 1998]. The custom processor splits full orbits into individual ascending and descending orbit segments prior to processing so that no overlapping data is discarded [O'Kray, 1998].…”

Section: Appendix A: Ease-grid Processing Detailsmentioning

confidence: 99%

A yearlong comparison of plot‐scale and satellite footprint‐scale 19 and 37 GHz brightness of the Alaskan North Slope

Kim

England

2003

J. Geophys. Res.

View full text Add to dashboard Cite

[1] Subpixel heterogeneity remains a key issue in the estimation of land parameters using satellite passive microwave sensors; the scales of spatial variability on land are typically much smaller than sensor footprints (tens of km). Disaggregation is a necessary component of any successful assimilation or retrieval scheme attempting to exploit satellite passive microwave observations to estimate parameters at the local scale. This paper quantifies the similarity between ground-based brightness and satellite brightness observations at 19 and 37 GHz for Arctic tundra on the North Slope of Alaska, identifying and quantifying sources of the differences. To the extent that this very homogeneous area represents a limiting case, the impact of subpixel heterogeneity in less homogeneous areas may be gauged. The ground-based radiobrightness observations were collected during the Radiobrightness Energy Balance Experiment 3 (REBEX-3) conducted on the North Slope in 1994-1995. A comparison was made of 381 days of brightness observations from a tower-mounted Special Sensor Microwave Imager (SSM/I) simulator representing the full range of annual conditions with coincident satellite SSM/I observations. Issues such as instrument stability, the effects of atmospheric radiative transfer, and consistency of satellite pixel locations are considered. Linear correlations between tower-based and SSM/I brightness observations of 0.93, 0.94, 0.93, and 0.92 were observed for the 19V, 19H, 37V, and 37H channels, respectively. Footprint sizes were 2 Â 4 m for the tower-based observations and 43 Â 69 km for the resampled SSM/I observations. Atmospheric, topographic, and time-ofobservation effects can account for the differences between the best fit lines and the 1:1 lines, with calibration errors accounting for the residual differences.

show abstract

A multi-pass median filter technique to remove ambiguities in retrieved wind fields from spaceborne scatterometer data

Pak

Kim

Callahan

et al. 1998

IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings.

View full text Add to dashboard Cite

An automated median filter-based ambiguity removal algorithm is used because of its simplicity and computational efficiency. The algorithm requires an initial wind field. Consequently the performance of the algorithm depends largely on the accuracy of the initial wind field compared to the true wind field. Usually, an initial wind field consisting of the highest ranked retrieved wind vectors is used. However, we found that this does not result in the best performance. In this paper we present a technique called the multi-pass median filter algorithm. The technique gives superior performance to the conventional median filter algorithm by generating a better initial wind field.

show abstract

A custom EASE-Grid SSM/I processing system

Cited by 6 publications

References 4 publications

EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

A yearlong comparison of plot‐scale and satellite footprint‐scale 19 and 37 GHz brightness of the Alaskan North Slope

A multi-pass median filter technique to remove ambiguities in retrieved wind fields from spaceborne scatterometer data

Contact Info

Product

Resources

About