Flood hazard mapping by integrating airborne laser scanning data, high resolution images and large scale maps

This study considered airborne laser scanning (ALS) based aboveground biomass (AGB) prediction in mountain forests. The study area consisted of a long transect from southern Norway to northern parts of the country with wide ranges of elevation along a long latitudinal gradient (58°N–69°N). This transect was covered by ALS data and field data from 238 plots. AGB was modeled using different types of predictor variables, namely ALS metrics, variables related to growing conditions (elevation, latitude, and climatic variables), and tree species information. Modelling of AGB in the long transect covering diverse mountainous forest conditions was challenging: the RMSE values were rather large (37%–70%). The effects of growing conditions on model predictions were minor. However, species information was essential to improve accuracy. The analysis revealed that when doing inventories of spruce-dominated areas, all plots should be pooled together when the models are developed, whereas if pine or deciduous species dominate the area in question, separate dominant species-wise models should be constructed.

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Airborne Laser Scanning and Very High-Resolution Satellite Data for Geomorphological Mapping in Parts of Elbe River Valley, Germany

Geoinformatics in Applied Geomorphology ◽

10.1201/b10964-3 ◽

2011 ◽

pp. 23-37

Author(s):

Siddan Anbazhagan ◽

Marco Trommler ◽

Elmar Csaplovics

Keyword(s):

High Resolution ◽

Satellite Data ◽

Laser Scanning ◽

River Valley ◽

Airborne Laser Scanning ◽

Elbe River ◽

Geomorphological Mapping ◽

Airborne Laser ◽

Very High

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ANALYSIS OF 3D BUILDING MODELS ACCURACY BASED ON THE AIRBORNE LASER SCANNING POINT CLOUDS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-797-2018 ◽

2018 ◽

Vol XLII-2 ◽

pp. 797-804 ◽

Cited By ~ 4

Author(s):

W. Ostrowski ◽

M. Pilarska ◽

J. Charyton ◽

K. Bakuła

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Large Scale ◽

Point Clouds ◽

3D Models ◽

Airborne Laser Scanning ◽

Aerial Images ◽

Statistical Parameters ◽

Airborne Laser ◽

Building Models

Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term “3D building models” can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model.

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