Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Forest inventory information needs in Northwest Russia

This thesis applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The thesis recommends strategic options for LiDAR technology’s value enhancement in Russian forestry.

Forest inventory information needs in Northwest Russia

This research report applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The report recommends strategic options for LiDAR technology’s value enhancement in Russian forestry. This work has been conducted as a part of the project ‘Finnish-Russian Forest Academy 2 - Exploiting and Piloting’, which has been supported financially by the South-East Finland- Russia ENPI CBC 2007-2014 Programme.

Suitability of LiDAR technology for forest inventory in Russia

LiDAR is an advanced remote sensing technology with many applications, including forest inventory. The most common type is ALS (airborne laser scanning). The method is successfully utilized in many developed markets, where it is replacing traditional forest inventory methods. However, it is innovative for Russian market, where traditional field inventory dominates. ArboLiDAR is a forest inventory solution that engages LiDAR, color infrared imagery, GPS ground control plots and field sample plots, developed by Arbonaut Ltd. This study is an industrial market research for LiDAR technology in Russia focused on customer needs. Russian forestry market is very attractive, because of large growing stock volumes. It underwent drastic changes in 2006, but it is still in transitional stage. There are several types of forest inventory, both with public and private funding. Private forestry enterprises basically need forest inventory in two cases – while making coupe demarcation before timber harvesting and as a part of forest management planning, that is supposed to be done every ten years on the whole leased territory. The study covered 14 companies in total that include private forestry companies with timber harvesting activities, private forest inventory providers, state subordinate companies and forestry software developer. The research strategy is multiple case studies with semi-structured interviews as the main data collection technique. The study focuses on North-West Russia, as it is the most developed Russian region in forestry. The research applies the Voice of the Customer (VOC) concept to elicit customer needs of Russian forestry actors and discovers how these needs are met. It studies forest inventory methods currently applied in Russia and proposes the model of method comparison, based on Multi-criteria decision making (MCDM) approach, mainly on Analytical Hierarchy Process (AHP). Required product attributes are classified in accordance with Kano model. The answer about suitability of LiDAR technology is ambiguous, since many details should be taken into account.

Materiaalitoimintojen kehittäminen kokoonpano-osastolla

Työn tavoitteena oli yhtenäisen toimintamallin luominen kohdeyrityksen materiaalitoiminnoille tuotannon kokoonpano-osastolla ja kokoonpanoa palvelevissa varastoissa. Toimintamallin tuli kattaa nimikkeiden siirrot ja siirtoihin liittyvät toimet toiminnanohjausjärjestelmässä. Lisäksi toimintamallin tuli vähentää saldovirheitä ja niistä johtuvia osapuutteita ja inventaarioepäselvyyksiä. Nykytilan kartoituksella yksilöitiin oleellisimmat kehityskohteet saldovirheiden eliminoimiseksi. Myös yrityksen lean-implementoinnin vaatimukset materiaalitoimintojen luotettavuudelle oli huomioitava. Kehityskohteiden tehostustoimista luotiin materiaalitoimintojen malli, joka yhtenäistää käytäntöjä ja vähentää operatiivisia saldojen hallinnan haasteita.

ESTIMATION OF CORK PRODUCTION USINGAERIAL IMAGERY1

ABSTRACT Inventory and prediction of cork harvest over time and space is important to forest managers who must plan and organize harvest logistics (transport, storage, etc.). Common field inventory methods including the stem density, diameter and height structure are costly and generally point (plot) based. Furthermore, the irregular horizontal structure of cork oak stands makes it difficult, if not impossible, to interpolate between points. We propose a new method to estimate cork production using digital multispectral aerial imagery. We study the spectral response of individual trees in visible and near infrared spectra and then correlate that response with cork production prior to harvest. We use ground measurements of individual trees production to evaluate the model’s predictive capacity. We propose 14 candidate variables to predict cork production based on crown size in combination with different NDVI index derivates. We use Akaike Information Criteria to choose the best among them. The best model is composed of combinations of different NDVI derivates that include red, green, and blue channels. The proposed model is 15% more accurate than a model that includes only a crown projection without any spectral information.

Bounding the role of black carbon in the climate system: a scientific assessment

Black carbon aerosol plays a unique and important role in Earth’s climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr�-1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m�-2 with 90% uncertainty bounds of (+0.08, +1.27)Wm�-2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m�-2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m�-2 with 90% uncertainty bounds of +0.17 to +2.1 W m�-2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m�-2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (�-0.50 to +1.08) W m-�2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (�-0.06 W m�-2 with 90% uncertainty bounds of �-1.45 to +1.29 W m�-2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

Comparing simulation methods for modelling the errors of stand inventory data

Abstract

Uncertainty methods inactivation and inventory calculations

For a number of important nuclides, complete activation data libraries with covariance data will be produced, so that uncertainty propagation in fuel cycle codes (in this case ACAB,FISPIN, ...) can be developed and tested. Eventually, fuel inventory codes should be able to handle the complete set of uncertainty data, i.e. those of nuclear reactions (cross sections, etc.), radioactive decay and fission yield data. For this, capabilities will be developed both to produce covariance data and to propagate the uncertainties through the inventory calculations.

Methods for reducing large speed differences in traffic streams. Volume I - inventory of methods. Task A report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, Washington, D.C.

Data collection methods for sand inventory-type surveys /

"March 1980."

Further psychometric study of the Beck Anxiety Inventory including factorial analysis and social anxiety disorder screening

Objective. To analyze the psychometric properties of the Brazilian Portuguese version of the Beck Anxiety Inventory (BAI) in terms of its internal consistency, scores distribution, concurrent and discriminant validity, and factorial analysis in a sample of university students and social anxiety disorder (SAD) cases and non-cases. Methods. A sample of Brazilian university students from the general population (N = 2314) and a sample of university students identified as cases (N = 88) and non-cases (N = 90) of SAD were assessed, using as a parameter the Structured Clinical Interview for the DSM-IV. The different instruments were completed individually in the presence of an experienced rater. Results. The BAI showed adequate internal consistency (0.88-0.92) and discriminant validity, with 0.74 sensitivity and 0.71 specificity for a cut-off score of 10. The factorial analysis suggested a three-factor solution to be the most adequate. Conclusions. The version of the BAI studied is quite adequate to be used in the context of Brazilian university students, identifying the presence of anxiety indicators. However, its usefulness to screen for SAD seems limited.

Evaluation of the psychometric properties of the Social Phobia Inventory in university students

Objective: The aim of the study was to study the psychometric properties of the Social Phobia Inventory (SPIN) in its version for the context of Brazilian adults. Methods: A sample of Brazilian university students from the general population (n = 2314) and a sample of university students identified as cases (n = 88) and noncases (n = 90) of social phobia were assessed, using as a parameter the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. The different instruments were applied individually in the presence of a rater. Results: The SPIN showed adequate internal consistency (.63-.90) and concurrent validity with different instruments of auto- and hetero-evaluation of social phobia. Discriminative validity showed 0.84 to 0.86 sensitivity and 0.84 to 0.87 specificity for cutoff notes between 19 and 21. Factorial analysis showed the presence of a variable number of factors as a function of the different samples. Conclusions: The version of the SPIN studied is quite adequate for use in the context of Brazilian university students, favoring the screening of social phobia. However, further studies using more diverse samples are needed. (C) 2010 Elsevier Inc. All rights reserved.

Factorial validity of the Maslach Burnout Inventory (MBI-HSS) among Spanish professionals

OBJECTIVE: To assess the factorial validity and internal consistency of the Maslach Burnout Inventory (MBI-HSS). METHODS: In a sample consisting of 705 Spanish professionals from diverse occupational sectors (health, education, police and so one), seven plausible factorial models hypothesized were compared using LISREL 8. RESULTS: The four-factor oblique solution and the three-factor oblique solution showed the best and similar fit. Deletion of Item 12 and Item 16, taking into consideration the suggestions in the manual, improved the goodness of fit for both models. The four-factor oblique model suggests that, in addition to Emotional Exhaustion (EE) and Depersonalization (DP), Personal Accomplishment (PA) consists of two components labeled here Self-Competence (Items 4, 7, 17, and 21) and the Existential Component (Items 9, 12, 18, and 19). However, the alpha coefficient was relatively low for the Self-Competence component, suggesting that it is more suitable to estimate the syndrome as a threedimensional construct. The Cronbach's alpha was satisfactory for PA (alpha =.71) and EE (alpha =.85), and moderate for DP (alpha =.58). CONCLUSIONS: The results show that the MBI-HSS offers factorial validity and its scales present internal consistency to evaluate the quality of working life for Spanish professionals.

A new frontier in biodiversity inventory: a proposal for estimators of phylogenetic and functional diversity

Copyright © 2014 The Authors. Methods in Ecology and Evolution © 2014 British Ecological Society.