Validation of Geometric Accuracy of
Global Land Survey (GLS) 2000 Data
Rajagopalan Rengarajan, Aparajithan Sampath, James Storey, and Michael Choate
Abstract
The Global Land Survey (GLS) 2000 data were generated from
Geocover™ 2000 data with the aim of producing a global
data set of accuracy better than 25 m Root Mean Square
Error (RMSE). An assessment and validation of accuracy
of GLS 2000 data set, and its co-registration with Geocov-
er™ 2000 data set is presented here. Since the availability
of global data sets that have higher nominal accuracy than
the GLS 2000 is a concern, the data sets were assessed in
three tiers. In the first tier, the data were compared with the
Geocover™ 2000 data. This comparison provided a means
of localizing regions of higher differences. In the second
tier, the GLS 2000 data were compared with systematical-
ly corrected Landsat-7 scenes that were obtained in a time
period when the spacecraft pointing information was ex-
tremely accurate. These comparisons localize regions where
the data are consistently off, which may indicate regions
of higher errors. The third tier consisted of comparing the
GLS 2000 data against higher accuracy reference data. The
reference data were the Digital Ortho Quads over the United
States, ortho-rectified SPOT data over Australia, and high
accuracy check points obtained using triangulation bundle
adjustment of Landsat-7 images over selected sites around
the world. The study reveals that the geometric errors in
Geocover™ 2000 data have been rectified in GLS 2000 data,
and that the accuracy of GLS 2000 data can be expected to
be better than 25 m RMSE for most of its constituent scenes.
Introduction
The Global Land Survey (
GLS
) 2000 data set is a collection
of images acquired by the Landsat 7
ETM+
sensor, and is the
geodetic reference for all Landsat products archived at the US
Geological Survey Earth Resources and Observation Science
(
EROS
) Center. The goal of this paper is to provide an assess-
ment of the geometric accuracy of the
GLS
2000 data set and
compare its accuracy relative to the Geocover™ 2000 data
set. The Geocover™
™
data sets (1975, 1990, and 2000) were
the predecessor to
GLS
data sets. Studies (Franks
et al
., 2009;
Masek and Covington, 2007) reveal that Geocover™ 2000
data have substantial errors (>100 m) on a per-scene and
per-pixel level (Masek and Covington, 2007). Therefore, the
Geocover™ 2000 data set images were reprocessed using all
available ground control points, Landsat-7 definitive ephem-
eris, and tie points in a block configuration to create the
GLS
2000 reference data set. In addition to the Geocover™ 2000
data set, Geocover™ data sets for 1975 and 1990 were also
reprocessed and registered to the
GLS
2000 data set forming
GLS-
1975 and 1990 data sets. New
GLS
2005 and 2010 data sets
have since been created. The
GLS
data base is freely available
(through EarthExplorer
:
) global
data base selected for each epoch (1975, 1990, 2000, 2005,
and 2010) for minimum cloud cover and at peak greenness.
They are used in a variety of applications needing a global
time series images and provides a baseline for many global
change studies (Gutman
et al
., 2008). The
GLS
2000 data set
is also the geographic reference for Landsat Data Continuity
Mission (
LDCM
) and serves as standard reference data for a
number of satellite data providers around the world (Chander
et al
., 2010; Sampath, 2012). This makes the task of validat-
ing the accuracy of the
GLS
2000 data set very important. The
most commonly used methods of validating the geometric
accuracy of remote sensing data sets involve comparing them
against reference data sets of higher accuracy (Chander
et al
.,
2010; Gianinetto and Scaioni, 2008; Li
et al
., 2007; Sampath,
2012), or using available ground control points (Aguiller
et
al
., 2012; Muller
et al
., 2012). However, the global coverage
of the data sets makes it hard to assess the accuracy, as other
independent data sets of comparable accuracy and coverage,
or ground control points are limited in availability.
To address the challenges presented by the global coverage
of the data, the validation task was divided into three parts. In
the first part (or tier), the
GLS
2000 data were compared with
the Geocover™ 2000 data. In the second tier, the data were
compared with Landsat-7 (
L7
) Level 1G systematic products
(radiometrically and geometrically corrected products, with-
out the use of terrain or ground control) acquired during April
2005 through December 2006 when the gyros of the satellite
performed extremely well; the platform was considered
stable, and the resulting data products were of high accuracy
(Lee
et al
., 2004). The third tier of tests consisted of testing
GLS
2000 data against higher accuracy reference data sets,
wherever they were available. Most of the available ground
control points were used to generate
GLS
2000 data, hence
they were not used in this assessment. The reference data sets
included data from Digital Ortho Quads and
SPOT
ortho-recti-
fied data from Australia’s National Earth Observation Group.
In other parts of the world, the
GLS
2000 data were validated
using a triangulation-based satellite bundle adjustment algo-
rithm. Similar techniques, based on rigorous sensor model-
ing, have been used by many researchers for improving the
accuracy of satellite data (Lutes and Grodecki, 2004; Li
et al
.,
Aparajithan Sampath, James Storey, and Michael Choate
are with
Stinger Ghaffarian Technologies (SGT), Contractor
to US Geological Survey, Earth Resources Observation and
Science (EROS) Center, Mundt Federal Building, 47914 252
nd
Street, Sioux Falls, SD 57198 (
).
Rajagopalan Rengarajan is a Graduate Student at the Roches-
ter Institute of Technology, Rochester, NY 14623.
Photogrammetric Engineering & Remote Sensing
Vol. 81, No. 2, February 2015, pp. 131–141.
0099-1112/15/812–131
© 2014 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.81.2.131
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
February 2015
131
