AROP

Metadata Updated: February 21, 2020

Accurate geo-referencing information is a basic requirement for combining remote satellite imagery with other geographic information. To detect changes in time-series satellite images, it is extremely important for the images to be precisely co-registered and orthorectified, so that images acquired from different sensors and dates can be compared directly. Precise registration relates satellite images to the ground reference based on carefully selected ground control points between the image and corresponding ground objects. Co-registration matches two images based on the tie points in the images. The topographical variations of the earth’s surface and the satellite view zenith angle affect the pixel’s distance projected onto the satellite image. The distortion inherent in the image is determined by topographical elevation. The orthorectification process is used to correct the pixel displacement caused by the topographical variations at the off-nadir viewing and to make the image orthographic, with every pixel in its correct location regardless of elevation and viewing direction. The automated registration and orthorectification package (AROP) uses precisely registered and orthorectified Landsat data (e.g., GeoCover or recently released free Landsat Level 1T data from the USGS EROS data center) as the base image to co-register, orthorectify and reproject (if needs) the warp images from other data sources, and thus make geo-referenced time-series images consistent in the geographic extent, spatial resolution, and projection. The co-registration, orthorectification and reprojection processes were integrated and thus image is only resampled once. This package has been tested on the Landsat Multi-spectral Scanner (MSS), TM, Enhanced TM Plus (ETM+) and Operational Land Imager (OLI), Terra ASTER, CBERS CCD, IRS-P6 AWiFS, and Sentinel-2 Multispectral Instrument (MSI) data. The development of the AROP package was supported by the U.S. Geological Survey (USGS) Landsat Science Team project and the NASA EOS project. The package was initially developed at the NASA Goddard Space Flight Center by Dr. Feng Gao (from September 2005 to June 2011). Further improvement and continuous maintenance are now being undertaken in the Hydrology and Remote Sensing Laboratory, Agricultural Research Service, U.S. Department of Agriculture (USDA) by Dr. Feng Gao.

Access & Use Information

Public: This dataset is intended for public access and use. License: Creative Commons CCZero

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Dates

Metadata Created Date February 21, 2020
Metadata Updated Date February 21, 2020

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date February 21, 2020
Metadata Updated Date February 21, 2020
Publisher Agricultural Research Service
Unique Identifier 9244748f-d9e0-4243-9863-07b282bbc52b
Maintainer
Gao, Feng
Maintainer Email
Public Access Level public
Bureau Code 005:18
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id ce6f45c6-ae96-47c8-94ed-b165570ef0d1
Harvest Source Id 50ca39af-9ddb-466d-8cf3-84d67a204346
Harvest Source Title USDA JSON
License https://creativecommons.org/publicdomain/zero/1.0/
Data Last Modified 2019-08-05
Program Code 005:040
Source Datajson Identifier True
Source Hash 5f18100b527e442336eaba2e2559762e9a6dc4a1
Source Schema Version 1.1

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