This review attempts, from a critical perspective, to put 25 years of satellite remote sensing research into the context of forestry planning. It is limited to temperate and boreal regions and to remote sensing in the visible and near infra‐red spectra. It is structured as follows: firstly, the forestry planning problem is defined and information requirements are identified; secondly, the attempts to use satellite remote sensing as an information source for forestry planning are reviewed, divided into the topics inventory and monitoring; and, finally, the methods for extracting forest information from satellite images are re‐examined, and their inherent limitations and methodological weaknesses are discussed. It is concluded that satellite images seldom contain enough information to support the decision process in applied forestry. Although regional level applications may be useful, few successful and reliable applications for local forest inventory, planning or damage monitoring have evolved. Stratificat...

Satellite remote sensing for forestry planning—A review

Evaluations of inventory methods usually end when precision and bias are quantified. Additional information on the appropriateness of a method may be provided through cost-plus-loss analyses, where the total costs are calculated as the sum of net present value (NPV) losses, i.e. expected economic losses as a result of future incorrect decisions due to errors in measurements, and inventory costs. The aim of the study was to compare inventories of basal area, dominant height and number of trees per hectare based on photo-interpretation and laser scanning from two sites in Norway by means of cost-plus-loss analyses. In general, more precise estimates were found for laser scanning than for photo-interpretation, while the biases were about equally distributed between the two methods. On average for the two sites, the inventory costs, NPV losses and total costs for photo-interpretation were about 6, 49 and 54 euros ha−1, respectively, while they were 11, 13 and 25 euros ha−1 for laser scanning. The data used fo...

Comparing stand inventories for large areas based on photo-interpretation and laser scanning by means of cost-plus-loss analyses

Ecologists working in conservation and resource management are discovering the importance of using Bayesian analytic methods to deal explicitly with uncertainty in data analyses and decision making. However, Bayesian procedures require, as inputs and outputs, an idea that is problematic for the human brain: the probability of a hypothesis (\"single−event probability\"). I describe several cognitive concepts closely related to single−event probabilities, and discuss how their interchangeability in the human mind results in \"cognitive illusions,\" apparent deficits in reasoning about uncertainty. Each cognitive illusion implies specific possible pitfalls for the use of single−event probabilities in ecology and resource management. I then discuss recent research in cognitive psychology showing that simple tactics of communication, suggested by an evolutionary perspective on human cognition, help people to process uncertain information more effectively as they read and talk about probabilities. In addition, I suggest that carefully considered standards for methodology and conventions for presentation may also make Bayesian analyses easier to understand.

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Embracing Uncertainty: The Interface of Bayesian Statistics and Cognitive Psychology

The Nordic countries have long traditions in forest inventory and remote sensing (RS). In sample-based national forest inventories (NFIs), utilization of aerial photographs started during the 1960s, satellite images during the 1980s, laser scanning during the 2000s, and photogrammetric point clouds during the 2010s. In forest management inventories (FMI), utilization of aerial photos started during the 1940s and laser scanning during the 2000s. However, so far, RS has mostly been used for map production and research rather than for estimation of regional parameters or inference on their accuracy. In recent years, the RS technology has been developing very fast. At the same time, the needs for information are constantly increasing. New technologies have created possibilities for cost-efficient production of accurate, large area forest data sets, which also will change the way forest inventories are done in the future. In this study, we analyse the state-of-the-art both in the NFIs and FMIs in the N...

https://www.tandfonline.com/doi/pdf/10.1080/02827581.2017.1416666

Remote sensing and forest inventories in Nordic countries – roadmap for the future

Uncertainty in long-term timber production analyses usually focus success of regeneration, growth/mortality of trees and future fluctuations of timber prices/harvest costs, while uncertainty related to inventory data is paid less attention. At the same time, evaluations of inventory methods usually stop when the error level is stated, while the uncertainty accompanied by using the data is seldom considered. The present work addresses uncertain inventory data in long-term timber production analyses. Final harvest decisions, i.e. possible outcome intervals with respect to timing and expected net present value-losses due to incorrect timing, were considered. A case study was presented where inventory data errors according to different error levels were generated randomly. The selected error levels were based on observations from practical forest inventories in Norway. The analysis tool was GAYA-JLP. The impact of errors on decisions was derived through repeated computations of management strategies maximising net present value without harvest path constraints. A real rate of discount of 3 % and an error level of 15 % resulted in expected net present value-losses of 1 NOK ha–1 for basal area, 63 NOK ha–1 for mean height, 210 NOK ha–1 for site quality, 240 NOK ha–1 for stand age, and 499 NOK ha–1 when random errors occurred simultaneously for all these variables. The expected net present valuelosses varied considerably. The largest losses appeared for stands with ages around optimal economical rotation ages. The losses were also relatively large for young stands, while they were relatively low for overmature stands. The experiences from the case study along with considerations related to other sources of uncertainty may help us to get a more realistic attitude to the reliability of long-term timber production analyses. The results of the study may also serve as a starting point in a decision oriented inventory planning concept, in which alternatives for inventory design and intensity are based on considerations with respect to inventory costs as well as net present value-losses.

L. Bondesson

Papers

A method to determine optimal stand data acquisition policies.