Uncertainty in forest net present value estimations

Peer reviewe

Investigation to develop a multistage forest sampling inventory system using ERTS-1 imagery

The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data

Socio-Economic Evaluation of the Potential for Australian Tree Species in the Philippines

Crop Production/Industries,

VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

Valuation of timberland under price uncertainty

In the first essay, a critical examination of three commonly used stochastic price processes is presented. Each process is described and rejected as a possible model of lumber futures prices. A mean reverting generalized autoregressive conditional heteroskedasticity (GARCH) model, developed by Bollerslev (1986), is proposed as a stochastic process for lumber futures prices. The essay provides the steps that should be taken to ensure that a proper price process is used in each application. In the second essay, a flexible harvesting strategy known as the reservation price strategy is presented. When the current price is below the reservation price, the forest owner delays the harvest. An optimal stopping model is used to derive an expression for the optimal sequence of reservation prices under price uncertainty. A solution method using a Monte Carlo backward recursion algorithm is presented. The Monte Carlo simulation procedure may be applied when analytical solutions are difficult or intractable. In the third essay, a simulation model is used to estimate the per acre value of land devoted to timber production under different harvesting strategies, stumpage price processes, and site qualities. By following the reservation price strategy, forest owners can increase the expected prots from timber harvesting and reduce the variability in profits from timber harvesting relative to a fixed rotation strategy. For an estimated mean reverting GARCH process, the reservation price strategy increases the value of timberland by 33.0 percent for a site index of 90 and by 22.1 percent for a site index of 60 relative to a fixed rotation strategy

Interpreting Housing Prices with a MultidisciplinaryApproach Based on Nature-Inspired Algorithms and Quantum Computing

Current technology still does not allow the use of quantum computers for broader and individual uses; however, it is possible to simulate some of its potentialities through quantum computing. Quantum computing can be integrated with nature-inspired algorithms to innovatively analyze the dynamics of the real estate market or any other economic phenomenon. With this main aim, this study implements a multidisciplinary approach based on the integration of quantum computing and genetic algorithms to interpret housing prices. Starting from the principles of quantum programming, the work applies genetic algorithms for the marginal price determination of relevant real estate characteristics for a particular segment of Naples’ real estate market. These marginal prices constitute the quantum program inputs to provide, as results, the purchase probabilities corresponding to each real estate characteristic considered. The other main outcomes of this study consist of a comparison of the optimal quantities for each real estate characteristic as determined by the quantum program and the average amounts of the same characteristics but relative to the real estate data sampled, as well as the weights of the same characteristics obtained with the implementation of genetic algorithms. With respect to the current state of the art, this study is among the first regarding the application of quantum computing to interpretation of selling prices in local real estate markets