scholarly journals Aerial Orthophoto and Airborne Laser Scanning as Monitoring Tools for Land Cover Dynamics: A Case Study from the Milicz Forest District (Poland)

2013 ◽  
Vol 171 (6) ◽  
pp. 857-866 ◽  
Author(s):  
Marta Szostak ◽  
Piotr Wezyk ◽  
Piotr Tompalski
Keyword(s):  
Land Cover ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Monitoring Tools ◽  
Land Cover Dynamics ◽  
Forest District

scholarly journals TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

2016 ◽  
Vol XLI-B7 ◽  
pp. 161-169 ◽  
Author(s):  
K. Bakuła ◽  
P. Kupidura ◽  
Ł. Jełowicki
Keyword(s):  
Land Cover ◽  
Laser Scanning ◽  
Near Infrared ◽  
Airborne Laser Scanning ◽  
Surface Model ◽  
Digital Surface Model ◽  
Airborne Laser ◽  
Laser Reflectance ◽  
Elevation Data ◽  
Intensity Images

Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud) acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images), spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and last return numbers slightly improved the results.

scholarly journals TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

2016 ◽  
Vol XLI-B7 ◽  
pp. 161-169 ◽  
Author(s):  
K. Bakuła ◽  
P. Kupidura ◽  
Ł. Jełowicki
Keyword(s):  
Land Cover ◽  
Laser Scanning ◽  
Near Infrared ◽  
Airborne Laser Scanning ◽  
Surface Model ◽  
Digital Surface Model ◽  
Airborne Laser ◽  
Laser Reflectance ◽  
Elevation Data ◽  
Intensity Images

Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud) acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images), spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and last return numbers slightly improved the results.

scholarly journals A Swedish case study on the prediction of detailed product recovery from individual stem profiles based on airborne laser scanning

2014 ◽  
Vol 72 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Andreas Barth ◽  
Johan J. Möller ◽  
Lars Wilhelmsson ◽  
John Arlinger ◽  
Rikard Hedberg ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Product Recovery ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals WIDE-AREA MAPPING OF FOREST WITH NATIONAL AIRBORNE LASER SCANNING AND FIELD INVENTORY DATASETS

2016 ◽  
Vol XLI-B8 ◽  
pp. 727-731 ◽  
Author(s):  
J.-M. Monnet ◽  
C. Ginzler ◽  
J.-C. Clivaz
Keyword(s):  
Laser Scanning ◽  
Prediction Models ◽  
Basal Area ◽  
National Forest Inventory ◽  
Airborne Laser Scanning ◽  
Stem Volume ◽  
Stem Density ◽  
Maximum Height ◽  
Airborne Laser

Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R<sup>2</sup> = 0.61 with a root mean square error of 47 %) and basal area (respectively 0.51 and 45 %) while height variables had an error lower than 19%. This case study shows that the use of nationwide ALS and field datasets for forest resources mapping is cost efficient, but additional investigations are required to handle the limitations of the input data and optimize the accuracy.

scholarly journals TOWARDS AUTOMATIC SINGLE-SENSOR MAPPING BY MULTISPECTRAL AIRBORNE LASER SCANNING

2016 ◽  
Vol XLI-B3 ◽  
pp. 155-162 ◽  
Author(s):  
E. Ahokas ◽  
J. Hyyppä ◽  
X. Yu ◽  
X. Liang ◽  
L. Matikainen ◽  
...  
Keyword(s):  
Land Cover ◽  
Tree Species ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Ground Surface ◽  
Airborne Laser Scanning ◽  
Forest Mapping ◽  
Airborne Laser Scanner ◽  
Airborne Laser

This paper describes the possibilities of the Optech Titan multispectral airborne laser scanner in the fields of mapping and forestry. Investigation was targeted to six land cover classes. Multispectral laser scanner data can be used to distinguish land cover classes of the ground surface, including the roads and separate road surface classes. For forest inventory using point cloud metrics and intensity features combined, total accuracy of 93.5% was achieved for classification of three main boreal tree species (pine, spruce and birch).When using intensity features – without point height metrics - a classification accuracy of 91% was achieved for these three tree species. It was also shown that deciduous trees can be further classified into more species. We propose that intensity-related features and waveform-type features are combined with point height metrics for forest attribute derivation in area-based prediction, which is an operatively applied forest inventory process in Scandinavia. It is expected that multispectral airborne laser scanning can provide highly valuable data for city and forest mapping and is a highly relevant data asset for national and local mapping agencies in the near future.

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