Abstract
The level of spatial co-registration between airborne laser scanning (ALS) and ground data can determine the goodness of the statistical inference used in forest inventories. The importance of positioning methods in the field can increase, depending on the structural complexity of forests. An area-based approach was followed to conduct forest inventory over seven National Forest Inventory (NFI) forest strata in Spain. The benefit of improving the co-registration goodness was assessed through model transferability using low- and high-accuracy positioning methods. Through the inoptimality losses approach, we evaluated the value of good co-registered data, while assessing the influence of forest structural complexity. When using good co-registered data in the 4th NFI, the mean tree height (HTmean), stand basal area (G) and growing stock volume (V) models were 2.6%, 10.6% and 14.7% (in terms of root mean squared error, RMSE %), lower than when using the coordinates from the 3rd NFI. Transferring models built under poor co-registration conditions using more precise data improved the models, on average, 0.3%, 6.0% and 8.8%, while the worsening effect of using low-accuracy data with models built in optimal conditions reached 4.0%, 16.1% and 16.2%. The value of enhanced data co-registration varied between forests. The usability of current NFI data under modern forest inventory approaches can be restricted when combining with ALS data. As this research showed, investing in improving co-registration goodness over a set of samples in NFI projects enhanced model performance, depending on the type of forest and on the assessed forest attributes.
Highlights
Collecting information on the status of the forest stands is the basis for developing effective strategies to maximize the use of forest resources [1,2]
The standard deviation of the distances showed more variability in the Canary Islands, where National Forest Inventory (NFI) samples located in the Canario forests had higher values than those computed for Extremadura
We evaluated in this paper the implications of improving the co-registration between ground and airborne laser scanning (ALS) data by means of modern plot positioning methods on two regional-scale inventories based on the sampling design from the NFI of Spain
Summary
Collecting information on the status of the forest stands is the basis for developing effective strategies to maximize the use of forest resources [1,2]. The scale of the assessment can turn the process of measuring all existing trees into a prohibitively expensive and time-consuming operation, which explains why sample-based estimates are normally used to conduct forest inventory [3,4]. These sampling schemes aim at collecting trustworthy information, from which one can compute unbiased estimates at different planning scales [5]. The development of the forestry applications using Light Detection and Ranging (LiDAR) data has been focused on the use of airborne laser scanning (ALS) and the implementation of area-based methods (ABA) to estimate forest attributes [9,10]
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