Sebastian Schnell

Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation

This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes design-based and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data..We review studies on large-area forest surveys based on model-assisted, model-based, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters.

Estimating forest edge length from forest inventory sample dataThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.

Forest edge length is important for landscape ecological analysis, including the analysis of fragmentation. In this paper, we estimate forest edge length using field sample data from the German National Forest Inventory as an example. The complex plot design of many large-area forest inventories allows for the estimation of forest edge length at different spatial resolutions. As expected, estimates depend on the spatial resolution: longer estimated edge lengths resulted from observations at finer spatial resolutions. From the comparison of estimated edge lengths at different spatial resolutions, conclusions about the irregularity of forest edges can be drawn: more irregular forest boundaries resulted in greater differences between the estimated lengths for different spatial resolutions. One conclusion is of particular relevance: reported forest edge length values are meaningless unless their spatial resolution is also reported. The analysis presented is an add-on to the standard estimations from a forest ...

Hierarchical model-based inference for forest inventory utilizing three sources of information

Abstract∙ Key messageThe study presents novel model-based estimators for growing stock volume and its uncertainty estimation, combining a sparse sample of field plots, a sample of laser data, and wall-to-wall Landsat data. On the basis of our detailed simulation, we show that when the uncertainty of estimating mean growing stock volume on the basis of an intermediate ALS model is not accounted for, the estimated variance of the estimator can be biased by as much as a factor of three or more, depending on the sample size at the various stages of the design.∙ ContextThis study concerns model-based inference for estimating growing stock volume in large-area forest inventories, combining wall-to-wall Landsat data, a sample of laser data, and a sparse subsample of field data.∙ AimsWe develop and evaluate novel estimators and variance estimators for the population mean volume, taking into account the uncertainty in two model steps.∙ Methods Estimators and variance estimators were derived for two main methodological approaches and evaluated through Monte Carlo simulation. The first approach is known as two-stage least squares regression, where Landsat data were used to predict laser predictor variables, thus emulating the use of wall-to-wall laser data. In the second approach laser data were used to predict field-recorded volumes, which were subsequently used as response variables in modeling the relationship between Landsat and field data.Results∙ The estimators and variance estimators are shown to be at least approximately unbiased. Under certain assumptions the two methods provide identical results with regard to estimators and similar results with regard to estimated variances.∙ Conclusion We show that ignoring the uncertainty due to one of the models leads to substantial underestimation of the variance, when two models are involved in the estimation procedure.

Monitoring trees outside forests: a review

Trees outside forests (TOFs) are an important natural resource that contributes substantially to national biomass and carbon stocks and to the livelihood of people in many regions. Over the last decades, decision makers have become increasingly aware of the importance of TOF, and as a consequence, this tree resource is nowadays often considered in forest monitoring systems. Our review shows that in many cases, TOF are included in national forest inventories, applying traditional methodologies with relatively sparse networks of field sample plots. Only in some countries, such as India, the design of the inventories has considered the special features of how TOFs occur in the landscape. Several research studies utilising remote sensing for monitoring TOF have been conducted lately, but very few studies include comparative studies to optimise sampling strategies for TOF. Our review indicates that methods combining remote sensing and field surveys appear to be very promising, especially when remote sensing techniques that assess both the horizontal and vertical structures of tree resources are applied. For example, two-phase sampling strategies with laser scanning in the first phase and a field survey in the second phase appear to be effective for assessing TOF resources. However, TOFs often exhibit different characteristics than forest trees. Thus, to improve TOF monitoring, there is often a need to develop models, e.g. for biomass assessment, that are specifically adapted to this tree resource. Alternatively, field-based remote sensing methods that provide structural information about individual trees, notably terrestrial laser scanning, could be further developed for TOF monitoring applications. This also would have a potential to reduce the problem of accessing TOF during field surveys, which is a problem, for example, in countries where TOF are present on intensively utilised private grounds like gardens and agricultural fields.

Stand Density Management Diagrams for Three Exotic Tree Species in Smallholder Plantations in Vietnam

When smallholder farmers establish tree plantations to sell wood to the wood industry, they may run into problems when the plantations are mature and to be marketed because these farmers usually (1) do not know how to estimate the growing stock and (2) do not have sufficient knowledge of the wood markets. In this study, we tackle problem (1) and present stand density management diagrams (SDMDs) as a simple tool that allows rapid estimation of standing volume from data that stem from very basic inventory. Our data come from smallholder plantations in Vietnam, from four communes in the provinces of Binh Dinh and Phu Tho. Immense afforestation activities have been taken place in the country during the past two decades and it is special to Vietnam that a large share of these afforestations are under smallholder management with the goal to generate an additional source of income for these rural poor. A certain type of SDMDs is elaborated for three important exotic tree species commonly used for establishing industrial tree plantations (Acacia hybrid, Acacia mangium and Eucalyptus urophylla). They can be used for volume estimation and are also a tool to guide stand management and silvicultural treatments in general. Both implementation of the inventory and usage of the SDMDs are straightforward and simple so that this tool may be well suited to support smallholders in a better informed marketing of their wood, as well as, a better informed silvicultural management of their plantations.