Lindgren, Nils and Christensen, Pernilla and Nilsson, Björn and Åkerholm, Marianne and Allard, Anna and Reese, Heather and Olsson, Håkan
(2015).
Using optical satellite data and airborne lidar data for a nationwide sampling survey.
Remote sensing. 7
:4
, 4253-4267
[Journal article]
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PDF
- Published Version
Available under License Creative Commons Attribution. 4MB |
Official URL: http://dx.doi.org/10.3390/rs70404253
Abstract
A workflow for combining airborne lidar, optical satellite data and National Forest Inventory (NFI) plots for cost efficient operational mapping of a nationwide sample of 5x 5 km squares in the National Inventory of Landscapes in Sweden (NILS) landscape inventory in Sweden is presented. Since the areas where both satellite data and lidar data have a common data quality are limited, and impose a constraint on the number of available NFI plots, it is not feasible to perform classifications in a single step. Instead a stratified approach where canopy cover and canopy height are first predicted from lidar data trained with NFI plots is proposed. From the lidar predictions a forest stratum is defined as grid cells with more than 3m mean tree height and more than 10% vertical canopy cover, the remaining grid cells are defined as open land. Both forest and open land are then classified into broad vegetation classes using optical satellite data. The classification of open land is trained with aerial photo interpretation and the classification of the forest stratum is trained with a new set of NFI plots. The result is a rational procedure for nationwide sample based vegetation characterization.
Authors/Creators: | Lindgren, Nils and Christensen, Pernilla and Nilsson, Björn and Åkerholm, Marianne and Allard, Anna and Reese, Heather and Olsson, Håkan | ||||||
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Title: | Using optical satellite data and airborne lidar data for a nationwide sampling survey | ||||||
Series Name/Journal: | Remote sensing | ||||||
Year of publishing : | 2015 | ||||||
Depositing date: | 23 December 2015 | ||||||
Volume: | 7 | ||||||
Number: | 4 | ||||||
Page range: | 4253-4267 | ||||||
Number of Pages: | 15 | ||||||
Publisher: | Molecular Diversity Preservation International | ||||||
ISSN: | 2072-4292 | ||||||
Language: | English | ||||||
Publication Type: | Journal article | ||||||
Refereed: | Yes | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Copyright: | Creative Commons: Attribution 4.0 | ||||||
Full Text Status: | Public | ||||||
Agris subject categories.: | E Economics, development, and rural sociology > E11 Land economics and policies K Forestry > K10 Forestry production | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing | ||||||
Agrovoc terms: | remote sensing, forest inventories, forest surveys, data collection, classification, satellites | ||||||
Keywords: | lidar, operational, Landsat, nationwide, sampling, mapping | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-e-3151 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-3151 | ||||||
Additional ID: |
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ID Code: | 12929 | ||||||
Faculty: | NJ - Fakulteten för naturresurser och jordbruksvetenskap S - Faculty of Forest Sciences | ||||||
Department: | (S) > Dept. of Forest Resource Management (NL, NJ) > Dept. of Forest Resource Management | ||||||
Deposited By: | SLUpub Connector | ||||||
Deposited On: | 23 Dec 2015 08:02 | ||||||
Metadata Last Modified: | 09 Sep 2020 14:17 |
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