Automated mapping of linear dunefield morphometric parameters from remotely-sensed data

Telfer, Matt W.; Fyfe, Ralph; Lewin, Shaun

doi:10.1016/j.aeolia.2015.03.001

Cited by 27 publications

(37 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 2 shows that the unrealistic land-use types (which we have classified as "N/A") rarely exist: "paddy on flat sandy land" and "paddy on sand dunes". Until recently, the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) version 2, which has 30 m spacing and less than 12 m height accuracy (RMSE) [38], had been used as the highest-resolution, freely-available global elevation dataset for the spatial analysis of dune topography [39,40]. In April 2016, ALOS World 3D version 1 was released as a new global elevation dataset without [41].…”

Section: Depiction Of Local Land-use Typesmentioning

confidence: 99%

Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China

et al. 2016

View full text Add to dashboard Cite

Previous field research on the Horqin Sandy Land (China), which has suffered from severe desertification during recent decades, revealed how land use on a sand-dune topography affects both land degradation and restoration. This study aimed to depict the spatial distribution of local land use in order to shed more light on previous field findings regarding policies on a broader scale. We performed the following analyses with Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) images of Advanced Land Observing Satellite (ALOS): (1) object-based classification to discriminate preliminary classification of land-use types that were approximately differentiated by ordinary pixel-based analysis with spectral information; (2) digital photogrammetry to generate a digital surface model (DSM) with adequately high accuracy to represent undulating sand-dune topography; (3) geographic information system (GIS) analysis to classify major topographic types with the digital surface model (DSM); and (4) overlay of the two classification results to depict the local land-use types. The overall accuracies of the object-based and GIS-based classifications were high, at 93% (kappa statistic: 0.84) and 89% (kappa statistic: 0.81), respectively. The resultant local land-use map represents areas covered in previous field studies, showing where and how land degradation and restoration are likely to occur. This research can contribute to future environmental surveys, models, and policies in the study area.

show abstract

Section: Depiction Of Local Land-use Typesmentioning

confidence: 99%

Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Within the aeolian analysis environment these used to define slip faces and other features with well-defined upper edges, and indirectly used to define valleys or interdune areas which are less distinct on all sides. Within the aeolian analysis environment these secondary bonified subfeatures, are termed defects with splits and crest ends identified as Y-junctions and terminations respectively [3,5,6,[21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Trace Evidence from Mars’ Past: Fingerprinting Transverse Aeolian Ridges

2019

View full text Add to dashboard Cite

Linear dunes and human fingerprints share many characteristics. Both have ridges, valleys, and defects (minutiae) in the form of bifurcations and termination of ridgeline features. For dunes, determining how defects vary across linear and transverse dunefields is critical to understanding the physics of their formative processes and the physical forcing mechanisms that produce dunefields. Unfortunately, manual extraction of defect locations and higher order characteristics (type, orientation, and quality) from remotely sensed imagery is both time-consuming and inconsistent. This problem is further exacerbated when, in the case of imagery from sensors in orbit around Mars, we are unable to field check interpretations. In this research, we apply a novel technique for extracting defects from multiple imagery sources utilizing a robust and well-documented fingerprint minutiae detection and extraction software (MINDTCT: MINutiae DecTeCTion) developed by the National Institute of Standards and Technology (NIST). We apply our ‘fingerprinting’ approach to Transverse Aeolian Ridges (TARs), relict aeolian features commonly seen on the surface of Mars, whose depositional and formative processes are poorly understood. Our algorithmic approach demonstrates that automating the rapid extraction of defects from orbitally-derived high-resolution imagery of Mars is feasible and produces maps that allow the quantification and analysis of these features.

show abstract

“…Previous examples of automatic characterization of aeolian features from remote sensing data include the monitoring of dune migration (Vermeesch and Drake, 2008;Necsoiu et al, 2009), detection and delimitation of dunes on Mars Orbiter Camera (MOC) data (Bandeira et al, 2011), and mapping and characterization of ripple patterns on Mars using HiRISE (High Resolution Imaging Science Experiment) data (Silvestro et al, 2013;. With the purpose of mapping automatically the crests of linear dunes from Landsat imagery, Telfer et al (2015) used a Sobel operator for performing edge detection. Using SAR data, the trends of dune fields on Titan were surveyed using a linear segment detection algorithm (von Gioi et al, 2012;Lucas et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Object-based Dune Analysis: Automated dune mapping and pattern characterization for Ganges Chasma and Gale crater, Mars

et al. 2015

View full text Add to dashboard Cite

A method that enables the automated mapping and characterization of dune fields on Mars is described. Using CTX image mosaics, the introduced Object-based Dune Analysis (OBDA) technique produces an objective and reproducible mapping of dune morphologies over extensive areas. The data set thus obtained integrates a large variety of data, allowing a simple cross-analysis of dune patterns, spectral and morphometric information, and mesoscale wind models. Two dune fields, located in Gale crater and Ganges Chasma, were used to test and validate the methodology. The segmentation of dune-related morphologies is highly efficient, reaching overall accuracies of 95%. In addition, we show that the automated segmentation of slipface traces is also possible with expected accuracies of 85-90%. A qualitative and quantitative comparison of the final outputs with photointerpretations is performed, and the precision of the directional characterization of the dune patterns is evaluated. We demonstrate a good agreement between the OBDA outputs and the photointerpreted dune morphologies, with local trend deviations below 45°f or 80-95% of the mapped areas. Because the developed algorithm is tuned for the recognition of linear features from the imagery, the slipfaces of small barchans can be preferentially overlooked owing to their small extent at the spatial resolution of the CTX mosaics. Dune types composed of longer linear morphologies are much better represented, including correct mapping of secondary structures. Having proved the effectiveness and accuracy of the mapping procedure, we discuss its future applications for the improvement of dune catalogs on Mars.

show abstract

Automated mapping of linear dunefield morphometric parameters from remotely-sensed data

Cited by 27 publications

References 30 publications

Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China

Classification of Land Use on Sand-Dune Topography by Object-Based Analysis, Digital Photogrammetry, and GIS Analysis in the Horqin Sandy Land, China

Trace Evidence from Mars’ Past: Fingerprinting Transverse Aeolian Ridges

Object-based Dune Analysis: Automated dune mapping and pattern characterization for Ganges Chasma and Gale crater, Mars

Contact Info

Product

Resources

About