Mapping Accuracy Assessment

ExoMars is the flagship mission of the European Space Agency (ESA) Aurora Programme. The mobile scientific platform, or rover, will carry a drill and a suite of instruments dedicated to exobiology and geochemistry research. As the ExoMars rover is designed to travel kilometres over the Martian surface, high-precision rover localization and topographic mapping will be critical for traverse path planning and safe planetary surface operations. For such purposes, the ExoMars rover Panoramic Camera system (PanCam) will acquire images that are processed into an imagery network providing vision information for photogrammetric algorithms to localize the rover and generate 3-D mapping products. Since the design of the ExoMars PanCam will influence localization and mapping accuracy, quantitative error analysis of the PanCam design will improve scientists’ awareness of the achievable level of accuracy, and enable the PanCam design team to optimize its design to achieve the highest possible level of localization and mapping accuracy. Based on photogrammetric principles and uncertainty propagation theory, we have developed a method to theoretically analyze how mapping and localization accuracy would be affected by various factors, such as length of stereo hard-baseline, focal length, and pixel size, etc.

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CAMERA CALIBRATION ACCURACY AT DIFFERENT UAV FLYING HEIGHTS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w3-595-2017 ◽

2017 ◽

Vol XLII-2/W3 ◽

pp. 595-600 ◽

Cited By ~ 3

Author(s):

A. R. Yusoff ◽

M. F. M. Ariff ◽

K. M. Idris ◽

Z. Majid ◽

A. K. Chong

Keyword(s):

Camera Calibration ◽

Accuracy Assessment ◽

Low Cost ◽

Digital Camera ◽

Bundle Adjustment ◽

Digital Cameras ◽

Mapping Accuracy ◽

Image Mapping ◽

Object Distance ◽

Uav Image

Unmanned Aerial Vehicles (UAVs) can be used to acquire highly accurate data in deformation survey, whereby low-cost digital cameras are commonly used in the UAV mapping. Thus, camera calibration is considered important in obtaining high-accuracy UAV mapping using low-cost digital cameras. The main focus of this study was to calibrate the UAV camera at different camera distances and check the measurement accuracy. The scope of this study included camera calibration in the laboratory and on the field, and the UAV image mapping accuracy assessment used calibration parameters of different camera distances. The camera distances used for the image calibration acquisition and mapping accuracy assessment were 1.5&thinsp;metres in the laboratory, and 15 and 25&thinsp;metres on the field using a Sony NEX6 digital camera. A large calibration field and a portable calibration frame were used as the tools for the camera calibration and for checking the accuracy of the measurement at different camera distances. Bundle adjustment concept was applied in Australis software to perform the camera calibration and accuracy assessment. The results showed that the camera distance at 25&thinsp;metres is the optimum object distance as this is the best accuracy obtained from the laboratory as well as outdoor mapping. In conclusion, the camera calibration at several camera distances should be applied to acquire better accuracy in mapping and the best camera parameter for the UAV image mapping should be selected for highly accurate mapping measurement.

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Mapping Chestnut Stands Using Bi-Temporal VHR Data

Remote Sensing ◽

10.3390/rs11212560 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2560 ◽

Cited By ~ 2

Author(s):

Francesca Marchetti ◽

Björn Waske ◽

Manuel Arbelo ◽

Jose Moreno-Ruíz ◽

Alfonso Alonso-Benito

Keyword(s):

Spatial Information ◽

Accuracy Assessment ◽

Temporal Data ◽

Mapping Accuracy ◽

The Public ◽

Tenerife Island ◽

Complex Landscape ◽

The Impact ◽

Very High ◽

Phenological Phases

This study analyzes the potential of very high resolution (VHR) remote sensing images and extended morphological profiles for mapping Chestnut stands on Tenerife Island (Canary Islands, Spain). Regarding their relevance for ecosystem services in the region (cultural and provisioning services) the public sector demand up-to-date information on chestnut and a simple straight-forward approach is presented in this study. We used two VHR WorldView images (March and May 2015) to cover different phenological phases. Moreover, we included spatial information in the classification process by extended morphological profiles (EMPs). Random forest is used for the classification process and we analyzed the impact of the bi-temporal information as well as of the spatial information on the classification accuracies. The detailed accuracy assessment clearly reveals the benefit of bi-temporal VHR WorldView images and spatial information, derived by EMPs, in terms of the mapping accuracy. The bi-temporal classification outperforms or at least performs equally well when compared to the classification accuracies achieved by the mono-temporal data. The inclusion of spatial information by EMPs further increases the classification accuracy by 5% and reduces the quantity and allocation disagreements on the final map. Overall the new proposed classification strategy proves useful for mapping chestnut stands in a heterogeneous and complex landscape, such as the municipality of La Orotava, Tenerife.

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An evaluation of DEMs derived from LiDAR and photogrammetry for wetland mapping

The Forestry Chronicle ◽

10.5558/tfc84840-6 ◽

2008 ◽

Vol 84 (6) ◽

pp. 840-849 ◽

Cited By ~ 19

Author(s):

A R Hogg ◽

J. Holland

Keyword(s):

Accuracy Assessment ◽

Light Detection And Ranging ◽

Qualitative Assessment ◽

Wetland Mapping ◽

Aerial Photo ◽

Mapping Accuracy ◽

Digital Elevation ◽

Wetland Identification ◽

Lidar Dem ◽

Topographic Relief

The Ontario Ministry of Natural Resources (OMNR) and Ducks Unlimited Canada (DUC) have been engaged in developing an efficient and accurate methodology for inventorying wetlands. Their progress in this area has demonstrated that Digital Elevation Models (DEMs) are crucial input for wetland identification and boundary delineation. The provincial DEM, however, has known precision limitations in areas of minimal topographic relief that cause considerable mapping error. This study explored whether wetland mapping derived from bare-earth light detection and ranging (LiDAR) data would overcome the limitations of the provincial DEM. An automated wetland mapping approach was applied to the 2 elevation datasets and the results were compared using 2 methods of validation. One hundred aerial-photo-interpreted sample plots were used to quantitatively measure the ability of each source to separate upland from wetland. An overlay of wetland maps created from the 2 DEM sources was then qualitatively assessed to further clarify the magnitude of discrepancy between the 2 mapping sources. The study concluded that LiDAR showed a significant improvement at p = 0.05 over the provincial DEM for mapping wetlands, improving overall mapping accuracy from 76% to 84%. However, an overlay analysis and qualitative assessment showed the magnitude of this reported improvement is greater than was quantified by the accuracy assessment and that an assessment scheme with different sample units may further elucidate this discrepancy. Key words: LiDAR, DEM, wetland, mapping

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An accuracy assessment of the MTBS burned area product for shrub–steppe fires in the northern Great Basin, United States

International Journal of Wildland Fire ◽

10.1071/wf14131 ◽

2015 ◽

Vol 24 (1) ◽

pp. 70 ◽

Cited By ~ 35

Author(s):

Aaron M. Sparks ◽

Luigi Boschetti ◽

Alistair M. S. Smith ◽

Wade T. Tinkham ◽

Karen O. Lannom ◽

...

Keyword(s):

Great Basin ◽

Accuracy Assessment ◽

Burned Area ◽

Arid Environments ◽

Visual Interpretation ◽

Mapping Accuracy ◽

Commission Errors ◽

Shrub Steppe ◽

Area Product ◽

Steppe Fires

Although fire is a common disturbance in shrub–steppe, few studies have specifically tested burned area mapping accuracy in these semiarid to arid environments. We conducted a preliminary assessment of the accuracy of the Monitoring Trends in Burn Severity (MTBS) burned area product on four shrub–steppe fires that exhibited varying degrees of within-fire patch heterogeneity. Independent burned area perimeters were derived through visual interpretation and were used to cross-compare the MTBS burned area perimeters with classifications produced using set thresholds on the Relativised differenced Normalised Burn Index (RdNBR), Mid-infrared Burn Index (MIRBI) and Char Soil Index (CSI). Overall, CSI provided the most consistent accuracies (96.3–98.6%), with only small commission errors (1.5–4.4%). MIRBI also had relatively high accuracies (92.2–97.9%) and small commission errors (2.1–10.8%). The MTBS burned area product had higher commission errors (4.3–15.5%), primarily due to inclusion of unburned islands and fingers within the fire perimeter. The RdNBR burned area maps exhibited lower accuracies (92.9–96.0%). However, the different indices when constrained by the MTBS perimeter provided variable results, with CSI providing the highest and least variable accuracies (97.4–99.1%). Studies seeking to use MTBS perimeters to analyse trends in burned area should apply spectral indices to constrain the final burned area maps. The present paper replaces a former paper of the same title (http://dx.doi.org/10.1071/WF13206), which was withdrawn owing to errors discovered in data analysis after the paper was accepted for publication.

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