scholarly journals Airborne Laser Scanning Based Forest Inventory: Comparison of Experimental Results for the Perm Region, Russia and Prior Results from Finland

Forests ◽  
2017 ◽  
Vol 8 (3) ◽  
pp. 72 ◽  
Author(s):  
Tuomo Kauranne ◽  
Sergey Pyankov ◽  
Virpi Junttila ◽  
Alexander Kedrov ◽  
Andrey Tarasov ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Experimental Results ◽  
Airborne Laser ◽  
Perm Region

scholarly journals Mapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Johannes Schumacher ◽  
Marius Hauglin ◽  
Rasmus Astrup ◽  
Johannes Breidenbach
Keyword(s):  
Forest Inventory ◽  
Regression Models ◽  
Laser Scanning ◽  
Site Index ◽  
National Forest Inventory ◽  
Airborne Laser Scanning ◽  
National Forest ◽  
Practical Applications ◽  
Airborne Laser ◽  
Sentinel 2

Abstract Background The age of forest stands is critical information for forest management and conservation, for example for growth modelling, timing of management activities and harvesting, or decisions about protection areas. However, area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian National Forest Inventory (NFI) distributed over Norway between latitudes 58° and 65° N in an 18.2 Mha study area. Predictor variables were based on airborne laser scanning (ALS), Sentinel-2, and existing public map data. We performed model validation on an independent data set consisting of 63 spruce stands with known age. Results The best modelling strategy was to fit independent linear regression models to each observed site index (SI) level and using a SI prediction map in the application of the models. The most important predictor variable was an upper percentile of the ALS heights, and root mean squared errors (RMSEs) ranged between 3 and 31 years (6% to 26%) for SI-specific models, and 21 years (25%) on average. Mean deviance (MD) ranged between − 1 and 3 years. The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years. Using a mapped SI, which is required for practical applications, RMSE and MD on plot level ranged from 19 to 56 years (29% to 53%), and 5 to 37 years (5% to 31%), respectively. For the validation stands, the RMSE and MD were 12 (22%) and 2 years (3%), respectively. Conclusions Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age. Overall, we obtained good results, especially for stands with high SI. The models could be considered for practical applications, although we see considerable potential for improvements if better SI maps were available.

The shelf-life of airborne laser scanning data for enhancing forest inventory inferences

2018 ◽  
Vol 206 ◽  
pp. 254-259 ◽  
Author(s):  
Ronald E. McRoberts ◽  
Qi Chen ◽  
Dale D. Gormanson ◽  
Brian F. Walters
Keyword(s):  
Shelf Life ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser

scholarly journals Evaluating the accuracy of ALS-based removal estimates against actual logging data

2020 ◽  
Vol 77 (3) ◽  
Author(s):  
Ville Vähä-Konka ◽  
Matti Maltamo ◽  
Timo Pukkala ◽  
Kalle Kärhä
Keyword(s):  
Model Prediction ◽  
Forest Inventory ◽  
Boreal Forests ◽  
Laser Scanning ◽  
Growth Models ◽  
Airborne Laser Scanning ◽  
Inventory Data ◽  
Attribute Data ◽  
Forest Inventory Data ◽  
Airborne Laser

Abstract Key message We examined the accuracy of the stand attribute data based on airborne laser scanning (ALS) provided by the Finnish Forest Centre. The precision of forest inventory data was compared for the first time with operative logging data measured by the harvester. Context Airborne laser scanning (ALS) is increasingly used together with models to predict the stand attributes of boreal forests. The information is updated by growth models. Information produced by remote sensing, model prediction, and growth simulation needs field verification. The data collected by harvesters on logging sites provide a means to evaluate and verify the accuracy of the ALS-based data. Aims This study investigated the accuracy of ALS-based forest inventory data provided by the Finnish Forest Centre at the stand level, using harvester data as the reference. Special interest was on timber assortment volumes where the quality reductions of sawlog are model predictions in ALS-based data and true realized reductions in the logging data. Methods We examined the accuracy of total volume and timber assortment volumes by comparing ALS-based data and operative logging data measured by a harvester. This was done both for clear cuttings and thinning sites. Accuracy of the identification of the dominant tree species of the stand was examined using the Kappa coefficient. Results In clear-felling sites, the total harvest removals based on ALS and model prediction had a RMSE% of 26.0%. In thinning, the corresponding difference in the total harvested removal was 42.4%. Compared to logged volume, ALS-based prediction overestimated sawlog removals in clear cuttings and underestimated pulpwood removals. Conclusion The study provided valuable information on the accuracy of ALS-based stand attribute data. Our results showed that ALS-based data need better methods to predict the technical quality of harvested trees, to avoid systematic overestimates of sawlog volume. We also found that the ALS-based estimates do not accurately predict the volume of trees removed in actual thinnings.

Indirect and direct estimation of forest biomass change using forest inventory and airborne laser scanning data

2015 ◽  
Vol 164 ◽  
pp. 36-42 ◽  
Author(s):  
Ronald E. McRoberts ◽  
Erik Næsset ◽  
Terje Gobakken ◽  
Ole Martin Bollandsås
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Forest Biomass ◽  
Airborne Laser Scanning ◽  
Direct Estimation ◽  
Airborne Laser

scholarly journals The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

Forests ◽  
2013 ◽  
Vol 4 (3) ◽  
pp. 518-536 ◽  
Author(s):  
Joanne White ◽  
Michael Wulder ◽  
Mikko Vastaranta ◽  
Nicholas Coops ◽  
Doug Pitt ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Airborne Laser
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