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Deriving DSMs from LiDAR data with kriging

Lloyd, C.D. and Atkinson, P.M. (2002) Deriving DSMs from LiDAR data with kriging International Journal of Remote Sensing, 23, (12), pp. 2519-2524. (doi:10.1080/01431160110097998).

Record type: Article


Light Detection And Ranging (LiDAR) is becoming a widely used source of digital elevation data. LiDAR data are obtained on a point support and it is necessary to interpolate to a regular grid if a digital surface model (DSM) is required. When the data are numerous, and close together in space, simple linear interpolation algorithms are usually considered sufficient. In this letter, inverse distance weighting (IDW), ordinary kriging (OK) and kriging with a trend model (KT) are assessed for the construction of DSMs from LiDAR data. It is shown that the advantages of KT become more apparent as the number of data points decrease (and the sample spacing increases). It is argued that KT may be advantageous in some instances where the desire is to derive a DSM from LiDAR point data but in many cases a simpler approach, such as IDW, may suffice

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Published date: 2002


Local EPrints ID: 14953
ISSN: 0143-1161
PURE UUID: 439af97e-33ad-4f5b-8ded-33a65e47319d

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Date deposited: 10 Mar 2005
Last modified: 17 Jul 2017 16:52

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Author: C.D. Lloyd
Author: P.M. Atkinson

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