Automate generation of DEM from DSM in Forest Area using artificial neural networks (Record no. 10111)

MARC details
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005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260817170900.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190614s2011 th ad ||| 000 0 eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b12133991
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT Diss. no.RS-11-05
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bandara, K. R. M. U.
245 10 - TITLE STATEMENT
Title Automate generation of DEM from DSM in Forest Area using artificial neural networks
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Pathum Thani :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 2011
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (51 leaves) :
Other physical details ill., charts
490 1# - SERIES STATEMENT
Series statement Dissertation ;
Volume/sequential designation no. RS-11-05
500 ## - GENERAL NOTE
General note A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Remote Sensing and Geographic Information Systems
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D.) - Asian Institute of Technology, 2011
520 ## - SUMMARY, ETC.
Summary, etc. Thisresearch was carried out touse the Digital Surface Model (DSM) to obtain a Digital Terrain Model (DEM) in a forest area by using Artificial Neural Networks (ANN) instead of removing DSM point clouds and then interpolation the formed hollow area using surrounding DEMpoints. The study was carried out for one of the dense forest areas ofMeegahakivula in Badulla District, Sri Lanka wherethe elevation is varying from 230 m to 403 m with approximately 16 m mean heights of trees. Initially, onlythe perimeter DEMdata was used to train the ANN and secondly, the training was done using only nine well distributed DEMpoints inside the forest area. An application oriented ANN software module was designed with the facilities to use all relevant parameters and it can be used to trainand use for any coordinate system transformations. The developed application oriented ANN was trained by using sample data. It was trained to 1.5 m accuracy for 172 points of the perimeter and 3.9 m for the nine points. By using trained ANN, the whole DSMdata of the area and the extracted DSM with the range of [min, max] and [mean {u2013}standard deviation, mean + standard deviation] of the used sample data sets were projected to DEM. The above projected DEMwith the two ranges were interpolated using severalinterpolation methods. All ANN projected DEMs were compared with the reference DEM to check the fitness of the ANN projected DEMsand obtained the RMSE as the deviation of projected DEMs with reference DEM. The highest accuracy as the lowest overall deviation (lowest RMSE)was obtained by the [min, max] range DSM projection with the nine points trained ANN and by Topo to Raster interpolation method and it was 1.240 m. Other DEMaccuracies were also closer to this and it was proven that the ability to project DSM to DEMwith ANN.DEM projected by ANN can be used to slope determination, landslide monitoring, soil erosion monitoring, orthophoto generation, eliminate of foreshortening and layover of SAR images, etc. according to the accuracy obtained presently, but has to be validated with different forest areas as well as all other areas separately. Further, the developed program has to be improved for mini-batch processing as well as to use for other applications.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Remote-sensing images
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Forests and forestry
General subdivision Remote sensing
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Lal Lamarakoon,
Relator term Chairperson
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name kamiya, Yoshikazu,
Relator term Examination Committee
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Shrestha, Rajendra Prasad,
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Geoinformatics Center, Asian Institute of Technology,
Relator term Scholarship Donor
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element North {u2013}South Center, Zurich, Switzerland,
Relator term Scholarship Donor
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Institute of Photogrammetry & Remote Sensing, ETH, Hoenggerburg, Zurich, Switzerland,
Relator term Scholarship Donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Dissertation ;
Volume/sequential designation no. RS-11-05
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/detail.php?q=B00757">http://203.159.5.9/ait-thesis/detail.php?q=B00757</a>
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998 ## - LOCAL CONTROL INFORMATION (RLIN)
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Cataloger's initials, CIN (RLIN) 140619
First date, FD (RLIN) m
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945 ## - LOCAL PROCESSING INFORMATION (OCLC)
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Koha item type 20-AIT Publication
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      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 17/08/2026 50.00   AIT Diss. no.RS-11-05 30050120555858 17/08/2026 1 17/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 17/08/2026 50.00   AIT Diss. no.RS-11-05 30050120555825 17/08/2026 2 17/08/2026 20-AIT Publication
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 17/08/2026     AIT Diss. no.RS-11-05 30050160000963 17/08/2026   17/08/2026 40-Archives
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 17/08/2026     AIT Diss. no.RS-11-05 30050120993208 17/08/2026 3 17/08/2026 20-AIT Publication
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