scholarly journals IMPROVE THE ZY-3 HEIGHT ACCURACY USING ICESAT/GLAS LASER ALTIMETER DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 37-42 ◽  
Author(s):  
Guoyuan Li ◽  
Xinming Tang ◽  
Xiaoming Gao ◽  
Chongyang Zhang ◽  
Tao Li
Keyword(s):  
High Resolution ◽  
Bundle Adjustment ◽  
Experimental Result ◽  
Altimeter Data ◽  
Surface Model ◽  
Laser Altimetry ◽  
Laser Altimeter ◽  
Ice Cloud ◽  
Elevation Data ◽  
Polar Ice Sheets

ZY-3 is the first civilian high resolution stereo mapping satellite, which has been launched on 9th, Jan, 2012. The aim of ZY-3 satellite is to obtain high resolution stereo images and support the 1:50000 scale national surveying and mapping. Although ZY-3 has very high accuracy for direct geo-locations without GCPs (Ground Control Points), use of some GCPs is still indispensible for high precise stereo mapping. The GLAS (Geo-science Laser Altimetry System) loaded on the ICESat (Ice Cloud and land Elevation Satellite), which is the first laser altimetry satellite for earth observation. GLAS has played an important role in the monitoring of polar ice sheets, the measuring of land topography and vegetation canopy heights after launched in 2003. Although GLAS has ended in 2009, the derived elevation dataset still can be used after selection by some criteria. <br><br> In this paper, the ICESat/GLAS laser altimeter data is used as height reference data to improve the ZY-3 height accuracy. A selection method is proposed to obtain high precision GLAS elevation data. Two strategies to improve the ZY-3 height accuracy are introduced. One is the conventional bundle adjustment based on RFM and bias-compensated model, in which the GLAS footprint data is viewed as height control. The second is to correct the DSM (Digital Surface Model) straightly by simple block adjustment, and the DSM is derived from the ZY-3 stereo imaging after freedom adjustment and dense image matching. The experimental result demonstrates that the height accuracy of ZY-3 without other GCPs can be improved to 3.0 meter after adding GLAS elevation data. What’s more, the comparison of the accuracy and efficiency between the two strategies is implemented for application.

scholarly journals IMPROVE THE ZY-3 HEIGHT ACCURACY USING ICESAT/GLAS LASER ALTIMETER DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 37-42
Author(s):  
Guoyuan Li ◽  
Xinming Tang ◽  
Xiaoming Gao ◽  
Chongyang Zhang ◽  
Tao Li
Keyword(s):  
High Resolution ◽  
Bundle Adjustment ◽  
Experimental Result ◽  
Altimeter Data ◽  
Surface Model ◽  
Laser Altimetry ◽  
Laser Altimeter ◽  
Ice Cloud ◽  
Elevation Data ◽  
Polar Ice Sheets

ZY-3 is the first civilian high resolution stereo mapping satellite, which has been launched on 9th, Jan, 2012. The aim of ZY-3 satellite is to obtain high resolution stereo images and support the 1:50000 scale national surveying and mapping. Although ZY-3 has very high accuracy for direct geo-locations without GCPs (Ground Control Points), use of some GCPs is still indispensible for high precise stereo mapping. The GLAS (Geo-science Laser Altimetry System) loaded on the ICESat (Ice Cloud and land Elevation Satellite), which is the first laser altimetry satellite for earth observation. GLAS has played an important role in the monitoring of polar ice sheets, the measuring of land topography and vegetation canopy heights after launched in 2003. Although GLAS has ended in 2009, the derived elevation dataset still can be used after selection by some criteria. <br><br> In this paper, the ICESat/GLAS laser altimeter data is used as height reference data to improve the ZY-3 height accuracy. A selection method is proposed to obtain high precision GLAS elevation data. Two strategies to improve the ZY-3 height accuracy are introduced. One is the conventional bundle adjustment based on RFM and bias-compensated model, in which the GLAS footprint data is viewed as height control. The second is to correct the DSM (Digital Surface Model) straightly by simple block adjustment, and the DSM is derived from the ZY-3 stereo imaging after freedom adjustment and dense image matching. The experimental result demonstrates that the height accuracy of ZY-3 without other GCPs can be improved to 3.0 meter after adding GLAS elevation data. What’s more, the comparison of the accuracy and efficiency between the two strategies is implemented for application.

Error identification in orbital laser altimeter data by machine learning

2021 ◽  
Author(s):  
Oliver Stenzel ◽  
Robin Thor ◽  
Martin Hilchenbach
Keyword(s):  
Machine Learning ◽  
High Performance ◽  
Space Science ◽  
Altimeter Data ◽  
Laser Altimetry ◽  
Error Identification ◽  
Laser Altimeter ◽  
Data Set ◽  
Baseline Design ◽  
Solar System Bodies

&lt;p&gt;Orbital Laser altimeters deliver a plethora of data that is used to map planetary surfaces [1] and to understand interiors of solar system bodies [2]. Accuracy and precision of laser altimetry measurements depend on the knowledge of spacecraft position and pointing and on the instrument. Both are important for the retrieval of tidal parameters. In order to assess the quality of the altimeter retrievals, we are training and implementing an artificial neural network (ANN) to identify and exclude scans from analysis which yield erroneous data. The implementation is based on the PyTorch framework [3]. We are presenting our results for the MESSENGER Mercury Laser Altimeter (MLA) data set [4], but also in view of future analysis of the BepiColombo Laser Altimeter (BELA) data, which will arrive in orbit around Mercury in 2025 on board the Mercury Planetary Orbiter [5,6]. We further explore conventional methods of error identification and compare these with the machine learning results. Short periods of large residuals or large variation of residuals are identified and used to detect erroneous measurements. Furthermore, long-period systematics, such as those caused by slow variations in instrument pointing, can be modelled by including additional parameters.&lt;br&gt;[1] Zuber, Maria T., David E. Smith, Roger J. Phillips, Sean C. Solomon, Gregory A. Neumann, Steven A. Hauck, Stanton J. Peale, et al. &amp;#8216;Topography of the Northern Hemisphere of Mercury from MESSENGER Laser Altimetry&amp;#8217;. Science 336, no. 6078 (13 April 2012): 217&amp;#8211;20. https://doi.org/10.1126/science.1218805.&lt;br&gt;[2] Thor, Robin N., Reinald Kallenbach, Ulrich R. Christensen, Philipp Gl&amp;#228;ser, Alexander Stark, Gregor Steinbr&amp;#252;gge, and J&amp;#252;rgen Oberst. &amp;#8216;Determination of the Lunar Body Tide from Global Laser Altimetry Data&amp;#8217;. Journal of Geodesy 95, no. 1 (23 December 2020): 4. https://doi.org/10.1007/s00190-020-01455-8.&lt;br&gt;[3] Paszke, Adam, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, et al. &amp;#8216;PyTorch: An Imperative Style, High-Performance Deep Learning Library&amp;#8217;. Advances in Neural Information Processing Systems 32 (2019): 8026&amp;#8211;37.&lt;br&gt;[4] Cavanaugh, John F., James C. Smith, Xiaoli Sun, Arlin E. Bartels, Luis Ramos-Izquierdo, Danny J. Krebs, Jan F. McGarry, et al. &amp;#8216;The Mercury Laser Altimeter Instrument for the MESSENGER Mission&amp;#8217;. Space Science Reviews 131, no. 1 (1 August 2007): 451&amp;#8211;79. https://doi.org/10.1007/s11214-007-9273-4.&lt;br&gt;[5] Thomas, N., T. Spohn, J. -P. Barriot, W. Benz, G. Beutler, U. Christensen, V. Dehant, et al. &amp;#8216;The BepiColombo Laser Altimeter (BELA): Concept and Baseline Design&amp;#8217;. Planetary and Space Science 55, no. 10 (1 July 2007): 1398&amp;#8211;1413. https://doi.org/10.1016/j.pss.2007.03.003.&lt;br&gt;[6] Benkhoff, Johannes, Jan van Casteren, Hajime Hayakawa, Masaki Fujimoto, Harri Laakso, Mauro Novara, Paolo Ferri, Helen R. Middleton, and Ruth Ziethe. &amp;#8216;BepiColombo&amp;#8212;Comprehensive Exploration of Mercury: Mission Overview and Science Goals&amp;#8217;. Planetary and Space Science, Comprehensive Science Investigations of Mercury: The scientific goals of the joint ESA/JAXA mission BepiColombo, 58, no. 1 (1 January 2010): 2&amp;#8211;20. https://doi.org/10.1016/j.pss.2009.09.020.&lt;/p&gt;

scholarly journals POINTING ANGLE CALIBRATION OF ZY3-02 SATELLITE LASER ALTIMETER USING TERRAIN MATCHING

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 205-210 ◽  
Author(s):  
G. Li ◽  
X. Tang ◽  
X. Gao ◽  
J. P. Huang ◽  
J. Chen ◽  
...  
Keyword(s):  
Altimetry Data ◽  
Laser Altimetry ◽  
Angle Error ◽  
Laser Altimeter ◽  
Geometric Calibration ◽  
Pointing Error ◽  
The Public ◽  
Ice Cloud ◽  
Laser Data ◽  
Terrain Matching

After GLAS (Geo-science Laser Altimeter System) loaded on the ICESat (Ice Cloud and land Elevation Satellite), satellite laser altimeter attracts more and more attention. ZY3-02 equipped with the Chinese first satellite laser altimeter has been successfully launched on 30<sup>th</sup> May, 2016. The geometric calibration is an important step for the laser data processing and application. The method to calculate the laser pointing angle error based on existed reference terrain data is proposed in this paper. The public version terrain data, such as 90m-SRTM and 30m-AW3D30, can be used to estimate the pointing angle of laser altimeter. The GLAS data with simulated pointing error and actual ZY3-02 laser altimetry data is experimented to validate the algorithm. The conclusion will be useful for the future domestic satellite laser altimeter.

scholarly journals Interannual changes of the floating ice shelf of Petermann Gletscher, North Greenland, from 2000 to 2012

2014 ◽  
Vol 60 (221) ◽  
pp. 489-499 ◽  
Author(s):  
Andreas Münchow ◽  
Laurie Padman ◽  
Helen A. Fricker
Keyword(s):  
Mass Loss ◽  
Three Dimensional ◽  
Greenland Ice Sheet ◽  
Altimeter Data ◽  
Ice Shelf ◽  
Laser Altimetry ◽  
Laser Altimeter ◽  
Airborne Laser ◽  
Tracking Surface ◽  
Basal Melting

AbstractPetermann Gletscher, northwest Greenland, drains 4% of the Greenland ice sheet into Nares Strait. Its floating ice shelf retreated from 81 to 48 km in length during two large calving events in 2010 and 2012. We document changes in the three-dimensional ice-shelf structure from 2000 to 2012, using repeated tracks of airborne laser altimetry and ice radio-echo sounding, ICESat laser altimetry and MODIS visible imagery. The recent ice-shelf velocity, measured by tracking surface features between flights in 2010 and 2011, is ~1.25 km a−1, ~15–30% faster than estimates made before 2010. The steady- state along-flow ice divergence represents 6.3 Gta−1 mass loss through basal melting (~5Gta−1) and surface melting and sublimation (~1.0Gta−1). Airborne laser altimeter data reveal thinning, both along a thin central channel and on the thicker ambient ice shelf. From 2007 to 2010 the ice shelf thinned by ~5 m a−1, which represents a non-steady mass loss of ~4.1 Gta−1. We suggest that thinning in the basal channels structurally weakened the ice shelf and may have played a role in the recent calving events.

scholarly journals Urban Density Indices Using Mean Shift-Based Upsampled Elevetion Data

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1353-1357
Author(s):  
E. Charou ◽  
S. Gyftakis ◽  
E. Bratsolis ◽  
T. Tsenoglou ◽  
Th. D. Papadopoulou ◽  
...  
Keyword(s):  
High Resolution ◽  
Mean Shift ◽  
Urban Land ◽  
Optical Data ◽  
Surface Model ◽  
Land Classification ◽  
Urban Density ◽  
Coverage Ratio ◽  
Area Of Interest ◽  
Elevation Data

Urban density is an important factor for several fields, e.g. urban design, planning and land management. Modern remote sensors deliver ample information for the estimation of specific urban land classification classes (2D indicators), and the height of urban land classification objects (3D indicators) within an Area of Interest (AOI). In this research, two of these indicators, Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) are numerically and automatically derived from high-resolution airborne RGB orthophotos and LiDAR data. In the pre-processing step the low resolution elevation data are fused with the high resolution optical data through a mean-shift based discontinuity preserving smoothing algorithm. The outcome is an improved normalized digital surface model (nDSM) is an upsampled elevation data with considerable improvement regarding region filling and “straightness” of elevation discontinuities. In a following step, a Multilayer Feedforward Neural Network (MFNN) is used to classify all pixels of the AOI to building or non-building categories. For the total surface of the block and the buildings we consider the number of their pixels and the surface of the unit pixel. Comparisons of the automatically derived BCR and FAR indicators with manually derived ones shows the applicability and effectiveness of the methodology proposed.

scholarly journals Performance Assessment of ICESat-2 Laser Altimeter Data for Water-Level Measurement over Lakes and Reservoirs in China

2020 ◽  
Vol 12 (5) ◽  
pp. 770 ◽  
Author(s):  
Cui Yuan ◽  
Peng Gong ◽  
Yuqi Bai
Keyword(s):  
Measurement Uncertainty ◽  
Large Scale ◽  
Temporal Frequency ◽  
Altimeter Data ◽  
Profile Measurement ◽  
Accuracy Evaluation ◽  
Radar Altimeter ◽  
Laser Altimeter ◽  
Ice Cloud ◽  
Lakes And Reservoirs

Although the Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was primarily designed for glacier and sea-ice measurement, it can also be applied to monitor lake surface height (LSH). However, its performance in monitoring lakes/reservoirs has rarely been assessed. Here, we report an accuracy evaluation of the ICESat-2 laser altimetry data over 30 reservoirs in China using gauge data. To show its characteristics in large-scale lake monitoring, we also applied an advanced radar altimeter SARAL (Satellite for ARgos and ALtika) and the first laser altimeter ICESat (Ice, Cloud and land Elevation Satellite) to investigate all lakes and reservoirs (>10 km2) in China. We found that the ICESat-2 has a greatly improved altimetric capability, and the relative altimetric error was 0.06 m, while the relative altimetric error was 0.25 m for SARAL. Compared with SARAL and ICESat data, ICESat-2 data had the lowest measurement uncertainty (the standard deviation of along-track heights; 0.02 m vs. 0.17 m and 0.07 m), the greatest temporal frequency (3.43 vs. 1.35 and 1.48 times per year), and the second greatest lake coverage (636 vs. 814 and 311 lakes). The precise LSH profiles derived from the ICESat-2 data showed that most lakes (90% of 636 lakes) had a quasi-horizontal LSH profile (measurement uncertainty <0.05 m), and special methods are needed for mountainous lakes or shallow lakes to extract precise LSHs.

scholarly journals High-Resolution Elevation Model of Lop Nur Playa Derived from TanDEM-X

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Yuyang Geng ◽  
Yun Shao ◽  
Tingting Zhang ◽  
Huaze Gong ◽  
Lan Yang
Keyword(s):  
High Resolution ◽  
Least Square ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Relative Height ◽  
Laser Altimeter ◽  
Ice Cloud ◽  
Digital Elevation ◽  
Lop Nur ◽  
Elevation Model

In this paper, a digital elevation model (DEM) was produced for Lop Nur playa produced with the data from TanDEM-X mission. The spatial resolution is 10 m. It covers an area of 38,000 km2 for orthometric height from 785 m to 900 m above sea level, which is composed of 42 interferometric synthetic aperture radar (InSAR) scenes. A least-square adjustment approach was used to reduce the systematic errors in each DEM scene. The DEM produced was validated with data from other sensors including Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) and aerial Structure-from-Motion (SfM) DEM. The results show that global elevation root mean square error to GLAS is 0.57 m, and the relative height error to SfM DEM in complicated terrain is 3 m. The excellent height reliability of TanDEM InSAR DEM in Lop region was proved in this paper. A reliable high-resolution basic topographic dataset for researches of Lop Nur was provided.

High-Resolution Ground-Based GPS Measurements Show Intercampaign Bias in ICESat Elevation Data Near Summit, Greenland

2011 ◽  
Vol 49 (6) ◽  
pp. 3393-3400 ◽  
Author(s):  
Matthew R. Siegfried ◽  
Robert L. Hawley ◽  
John F. Burkhart
Keyword(s):  
Ground Truth ◽  
Laser Altimeter ◽  
Ice Cloud ◽  
Ice Surface ◽  
Salt Flats ◽  
Laser Signal ◽  
Elevation Data ◽  
Elevation Changes ◽  
Validation Experiments

The Geoscience Laser Altimeter System (GLAS) aboard the National Aeronautics and Space Administration's Ice, Cloud, and land Elevation Satellite (ICESat) collected data from early 2003 to late 2009 with the specific goal of measuring ice-surface elevation changes. While the precision of GLAS instrumentation has been studied over its intended target (ice), its accuracy has only been robustly estimated using independent (terrestrial nonlaser) methods over salt flats. Here, we perform repeat high-precision Global Positioning System (GPS) surveys under four passes of ICESat track 0412 (campaigns L3I, L3J, L2D, and L2E) to compare directly GLAS elevation data footprints to a coincident GPS ground truth near Summit, Greenland. Analysis and comparison of GLAS data with GPS data show a campaign-dependent elevation bias ranging from -0.112 &#x00B1;0.030 m (L3J) to 0.121 &#x00B1; 0.071 m (L2E). Although uncorrected reflectance values and field observations both indicate that forward scattering of the laser signal through the atmosphere accounts for the anomalously negative L3J bias, the biases of all campaigns studied are within the instrument's goal accuracy of &#x00B1;0.15 m. However, our analysis shows a campaign dependence in the bias, which may propagate through estimates of mass balance. The error introduced from intercampaign biases illustrates the importance of long-term independent validation experiments of satellite altimetry data over ice sheets.

scholarly journals TOPOGRAPHIC MAPPING OF THE MOON IN THE 21ST CENTURY: FROM HECTOMETER TO MILLIMETER SCALES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1117-1124
Author(s):  
K. Di ◽  
J. Oberst ◽  
I. Karachevtseva ◽  
B. Wu
Keyword(s):  
21St Century ◽  
Multiple Scale ◽  
Shape From Shading ◽  
Altimeter Data ◽  
Topographic Mapping ◽  
Data Mapping ◽  
Laser Altimeter ◽  
Landing Sites ◽  
Elevation Data ◽  
Mapping Techniques

Abstract. This paper presents a review of lunar topographic mapping in the two decades of the 21st century, including descriptions of lunar exploration missions, relevant payloads and data, mapping techniques, as well as global and regional mapping products. Various lunar photogrammetric mapping techniques such as construction of geometric models of lunar orbital images, block adjustments, shape from shading, co-registration of lunar orbital image and elevation data have been developed to process lunar orbital images and generate mapping products. Global topographic products at hectometer and decameter scales have been produced from orbital images and/or laser altimeter data. Regional topographic maps of the landing sites and other sites of interest have been generated at meter-scale using the sub-meter to meter resolution orbital images. Detailed local topographic products at centimeter to millimeter scales of the landing sites and rover traverse areas have been produced using descent images acquired by the landers and stereo images acquired by the rovers. These multiple-scale topographic mapping products have been extensively used to support various science applications, as well as engineering applications such as surface operations of the rovers.

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