A bibliography of geomorphometry, the quantitative representation of topography; supplement 3.0

Pike, Richard J.

doi:10.3133/ofr99140

Cited by 13 publications

(3 citation statements)

References 37 publications

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“…The results of the classification of geomorphometric units in north-central Crete have further demonstrated the possibility of an automated extraction of geomorphometrical properties from a DEM (Pike, 1993(Pike, , 1999. Generally, in order to draw conclusions regarding the relief evolution we have to classify the geomorphic characteristics of an area by taking into consideration geotectonic, climatic and hydrological parameters together with geomorphologic indexes (drainage density, drainage frequency, basin elongation, etc.).…”

Section: Discussionmentioning

confidence: 98%

“…In the past, attempts at defining geomorphometry have concentrated on the geometry of the landscape, but new technical advances in electronic computers, analytical algorithms, input/output devices and large sets of topographic data have reoriented geomorphometry (Pike, 1993(Pike, , 1999. The computer implementation of morphometry provides geomorphologists with a digital representation of landforms that is now essential to process modeling (Dikau, 1998;Dehn et al, 2001) at all levels of generalization.…”

Section: Introductionmentioning

confidence: 98%

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Computer-assisted discrimination of morphological units on north-central Crete (Greece) by applying multivariate statistics to local relief gradients

et al. 2004

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Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Computer-assisted discrimination of morphological units on north-central Crete (Greece) by applying multivariate statistics to local relief gradients

et al. 2004

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“…Geomorphometry and relief shading techniques overlap in many aspects in that they are both areas of geographic rendering that make use of digital elevation models and other similar datasets for cartographic representation (Pike et al 2009). Both branches of topographical representation pre-date computerized mapping, yet have been revolutionized with the growth of computer processing, thus routinizing their implementations (Pike 1999). However, since geomorphometric applications parameterize complex geomorphological influences for quantitative topographical analysis, many differences exist between geomorphometric models, such as predictive vegetation modeling and our proposed standard elevation models.…”

mentioning

confidence: 99%

Standard elevation models for evaluating terrain representation

Kennelly

Patterson

Tait

et al. 2019

Abstr. Int. Cartogr. Assoc.

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Standard Elevation ModelsWe propose the use of standard elevation models to evaluate and compare the quality of various relief shading and other terrain rendering techniques. These datasets will cover various landforms, be available at no cost to the user, and be free of common data imperfections such as missing data values, resampling artifacts, and seams. Datasets will be available at multiple map scales over the same geographic area for multi-scale analysis.Utilizing a standard data model for testing and comparing methods is a common practice among many disciplines. Furthermore, the use of digital models to test rendering techniques based on qualitative visual production has been well established for decades. Following the generation of the first digital image in 1957, image processing and analysis required standard test images upon which methods could be tested and compared. During the 1960s and 1970s, many well-known standard test images emerged from this need for a comparative technique model. Today, institutions like the University of Southern California's Signal and Image Processing Institute maintain digital image databases for the primary purpose of supporting image processing and analysis research, including geographic imaging processes.

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Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

Giano

Danese²,

Gioia³

et al. 2020

Lecture Notes in Computer Science

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Recent advances in spatial methods of digital elevation model (DEMs) analysis have addressed many research topics on the assessment of morphometric parameters of the landscape. Development of computer algorithms for calculating the geomorphometric properties of the Earth's surface has allowed for expanding of some methods in the semi-automatic recognition and classification of landscape features. In such a way, several papers have been produced, documenting the applicability of the landform classification based on map algebra. The Topographic Position Index (TPI) is one of the most widely used parameters for semi-automated landform classification using GIS software. The aim was to apply the TPI classes for landform classification in the Basilicata Region (Southern Italy). The Basilicata Region is characterized by an extremely heterogeneous landscape and geological features. The automated landform extraction, starting from two different resolution DEMs at 20 and 5 m-grids, has been carried out by using three different GIS software: Arcview, Arcmap, and SAGA. Comparison of the landform maps resulting from each software at a different scale has been realized, furnishing at the end the best landform map and consequently a discussion over which is the best software implementation of the TPI method.

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A bibliography of geomorphometry, the quantitative representation of topography; supplement 3.0

Cited by 13 publications

References 37 publications

Computer-assisted discrimination of morphological units on north-central Crete (Greece) by applying multivariate statistics to local relief gradients

Computer-assisted discrimination of morphological units on north-central Crete (Greece) by applying multivariate statistics to local relief gradients

Standard elevation models for evaluating terrain representation

Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

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