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Colorado State University
1.
Ha, Anh Quang.
Sampling strategies for forest aerial detection survey in Colorado.
Degree: PhD, Forest and Rangeland Stewardship, 2016, Colorado State University
URL: http://hdl.handle.net/10217/170372 
► Aerial detection survey (ADS) has been commonly employed in forest surveys in the United States for detecting forest damage and monitoring forest health. In Colorado,…
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▼ Aerial detection survey (ADS) has been commonly employed in forest surveys in the United States for detecting forest damage and monitoring forest health. In Colorado, ADS by USDA Forest Service has conducted annual 100% census of government forested land for more than 20 years with the goal of achieving information about forest damage due to different causal agents and disorders. Sketchmapping has been commonly employed in ADS with the goal of detecting and documenting on maps mortality, defoliation and other visible forest change from aircraft. At medium and large scale, sketchmapping is a suitable technique for forest monitoring that provides valuable information in forest health. This dissertation deals with data of forest area damaged by five causal agents mountain pine beetle, spruce beetle, western spruce budworm, pin engraver, and Douglas fir beetle and two disorders subalpine fir mortality and sudden aspen decline. The combined areas damaged by all causes were also considered. Data were downloaded from ADS in Colorado from 1994 to 2013 as polygon shapefiles with associated information such as causal agents or disorders, area damaged, and type of forest. The goal of my dissertation was to identify an appropriate sampling strategies to archive good estimates of total area damaged, to decrease survey
cost, and to increase safety by reducing the amount of flights. To approach this goal, four sample designs for estimating total area damaged caused by various causal agent were evaluated: simple random sampling, stratified random sampling, probability proportional to size, and non-alignment systematic sampling. A GIS layer of 150 transects covering Colorado’s forestlands was developed and represented the sample unit for my study. Each transect was 3.2 km wide and 625 km long and was numbered from 1 to 150 from south to north. Each sample design was evaluated using eight sample sizes (10, 15, 20, 25,30, 35, 50, and 70) and applied to the seven damages and the combined damaged area. The statistical properties were evaluated to determine the optimal sample design for estimating area damaged caused by different causal agents. The spatio-temporal characteristics of area damaged that influence precision and accuracy of estimate were considered. Most of the damaged forest areas by single causal agents and disorders showed aggregated spatial patterns; whereas the combined damaged areas were uniformly distributed across the landscape. A
loss plus cost function was employed to determine the optimal sample size for each sample design and analyzed for the
cost advantage of alternative sample designs. We found that stratified random sampling was the most optimal sample design by producing the highest percentage of unbiased estimates of total area damaged and the smallest variances. The next best sampling designs were simple random sampling and probability proportional to size. The non-alignment systematic sampling was the worst for estimating total area damaged both for individual causal agents and disorders and all causal…
Advisors/Committee Members: Reich, Robin M. (advisor), Jacobi, William R. (committee member), Lundquist, John E. (committee member), Khosla, Rajiv (committee member).
Subjects/Keywords: Colorado forests; forest insects and diseases; loss plus cost analysis; sampling strategies
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APA (6th Edition):
Ha, A. Q. (2016). Sampling strategies for forest aerial detection survey in Colorado. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/170372
Chicago Manual of Style (16th Edition):
Ha, Anh Quang. “Sampling strategies for forest aerial detection survey in Colorado.” 2016. Doctoral Dissertation, Colorado State University. Accessed December 05, 2019.
http://hdl.handle.net/10217/170372.
MLA Handbook (7th Edition):
Ha, Anh Quang. “Sampling strategies for forest aerial detection survey in Colorado.” 2016. Web. 05 Dec 2019.
Vancouver:
Ha AQ. Sampling strategies for forest aerial detection survey in Colorado. [Internet] [Doctoral dissertation]. Colorado State University; 2016. [cited 2019 Dec 05].
Available from: http://hdl.handle.net/10217/170372.
Council of Science Editors:
Ha AQ. Sampling strategies for forest aerial detection survey in Colorado. [Doctoral Dissertation]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/170372
Swedish University of Agricultural Sciences
2.
Roberge, Cornelia.
Inventory strategies for monitoring and evaluation of forest damage.
Degree: 2017, Swedish University of Agricultural Sciences
URL: https://pub.epsilon.slu.se/13925/
► Under global change, increasing stresses on forests require strategies for monitoring and mitigation of damages caused by pests and diseases. While the threats to forests…
(more)
▼ Under global change, increasing stresses on forests require strategies for monitoring and mitigation of damages caused by pests and diseases. While the threats to forests increase, so do the possibilities to set up efficient monitoring programmes and detect forest damage by utilising new technologies. This thesis focuses on strategies for forest damage inventories where different auxiliary data are combined to improve information for pest mitigation programmes. First, the efficiency of National Forest Inventories (NFIs; or similar inventories) for detecting and estimating state and change of forest damage across large regions was evaluated. NFIs were found efficient for assessing widely distributed damage, but unable to detect clustered and local outbreaks with adequate precision. Second, targeted forest damage inventories directed to areas with potential or suspected damage were investigated. It was found that two-phase sampling for stratification taking the first phase information from existing NFIs was an efficient strategy. Remotely-sensed auxiliary information and post-stratification was shown to further improve the precision. Third, the use of a new sampling design was evaluated: the local pivotal method (LPM), which spreads the sample in the multi-dimensional space of available auxiliary data. The LPM was found to be more efficient than simple random sampling in all scenarios and, depending on the allocation of the sample and the properties of the auxiliary data, it sometimes outperformed two-phase sampling for stratification. Thus, the LPM may be a valuable tool for practical forest damage inventories. Fourth, the cost-plus-loss method was applied to evaluate inventory strategies in a pest mitigation context. If inventory costs are large, it is especially important to quantify the inventory efforts necessary to evaluate the need for mitigation. The optimal sampling effort necessary for deciding whether or not a defoliator outbreak should be treated was quantified. Double sampling was found to be a cost-effective sampling strategy, i.e. the size of the second phase sample was determined based on the estimates from a small first phase sample. As an overall conclusion, the thesis points out the importance of making use of existing information in setting up effective inventories of forest damage and of using appropriate sampling strategies for making use of the information in the best possible way.
Subjects/Keywords: forest trees; forest pests; forest inventories; forest surveys; sampling; monitoring; population density; evaluation; cost-plus-loss; forest damage; forest inventory; forest pests; Monte-Carlo simulation; survey sampling; target tailored inventories
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APA (6th Edition):
Roberge, C. (2017). Inventory strategies for monitoring and evaluation of forest damage. (Doctoral Dissertation). Swedish University of Agricultural Sciences. Retrieved from https://pub.epsilon.slu.se/13925/
Chicago Manual of Style (16th Edition):
Roberge, Cornelia. “Inventory strategies for monitoring and evaluation of forest damage.” 2017. Doctoral Dissertation, Swedish University of Agricultural Sciences. Accessed December 05, 2019.
https://pub.epsilon.slu.se/13925/.
MLA Handbook (7th Edition):
Roberge, Cornelia. “Inventory strategies for monitoring and evaluation of forest damage.” 2017. Web. 05 Dec 2019.
Vancouver:
Roberge C. Inventory strategies for monitoring and evaluation of forest damage. [Internet] [Doctoral dissertation]. Swedish University of Agricultural Sciences; 2017. [cited 2019 Dec 05].
Available from: https://pub.epsilon.slu.se/13925/.
Council of Science Editors:
Roberge C. Inventory strategies for monitoring and evaluation of forest damage. [Doctoral Dissertation]. Swedish University of Agricultural Sciences; 2017. Available from: https://pub.epsilon.slu.se/13925/
Swedish University of Agricultural Sciences
3.
Duvemo, Karl.
The influence of data uncertainty on planning and decision processes in forest management.
Degree: 2009, Swedish University of Agricultural Sciences
URL: http://pub.epsilon.slu.se/1924/
► This thesis focuses on how uncertainty in forest data affects the outcome of management planning and decision making. In a review article (paper I), previous…
(more)
▼ This thesis focuses on how uncertainty in forest data affects the outcome of management planning and decision making. In a review article (paper I), previous research aiming to evaluate forestry data are described. The methodology used and the results presented were discussed. A general conclusion was that previous studies concerned highly simplified planning situations, leaving some doubts concerning their real world applicability. In papers II and III, two quantitative approaches of data evaluation were applied to data from sample plot imputations. In paper II, a cost plus loss analysis of using the data for forest management decision making is presented. The usefulness of the data in forestry scenario analysis were scrutinized in paper III as errors in the predictions of future forest states, harvest levels and net income flow. In both papers it was concluded that improvements in the methodology of assessing data would be required. In paper IV, an advance of the cost-plus-loss methodology was suggested by developing a simulation system that aims to capture the hierarchical structure and iterative nature of forestry planning. The simulation system included the tactical and operational levels of a continuous planning process at a specific corporate forest owner. It was characterized by annual re-planning with the option to reassess data of selected stands prior to operational planning. The planning simulation system was used in paper V for evaluation of current practice data. It was concluded that high decision losses occurred as a result of errors in the studied data. The introduction of holding level wood-flow considerations and incitements to cluster harvest activities reduced decision losses compared to stand wise planning without such considerations.
Subjects/Keywords: forest inventories; planning; decision making; data analysis; Forest inventory; data evaluation; cost plus loss analysis; tactical planning; operational planning; decision support system; simulation of data errors; optimization
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APA ·
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APA (6th Edition):
Duvemo, K. (2009). The influence of data uncertainty on planning and decision processes in forest management. (Doctoral Dissertation). Swedish University of Agricultural Sciences. Retrieved from http://pub.epsilon.slu.se/1924/
Chicago Manual of Style (16th Edition):
Duvemo, Karl. “The influence of data uncertainty on planning and decision processes in forest management.” 2009. Doctoral Dissertation, Swedish University of Agricultural Sciences. Accessed December 05, 2019.
http://pub.epsilon.slu.se/1924/.
MLA Handbook (7th Edition):
Duvemo, Karl. “The influence of data uncertainty on planning and decision processes in forest management.” 2009. Web. 05 Dec 2019.
Vancouver:
Duvemo K. The influence of data uncertainty on planning and decision processes in forest management. [Internet] [Doctoral dissertation]. Swedish University of Agricultural Sciences; 2009. [cited 2019 Dec 05].
Available from: http://pub.epsilon.slu.se/1924/.
Council of Science Editors:
Duvemo K. The influence of data uncertainty on planning and decision processes in forest management. [Doctoral Dissertation]. Swedish University of Agricultural Sciences; 2009. Available from: http://pub.epsilon.slu.se/1924/
Swedish University of Agricultural Sciences
4.
Holmström, Hampus.
Data acquisition for forestry planning by remote sensing based sample plot imputation.
Degree: 2001, Swedish University of Agricultural Sciences
URL: http://pub.epsilon.slu.se/29/
► In forestry planning, accurate description of the state of the forests is essential. Advanced planning models often require input data with high resolution, i.e. data…
(more)
▼ In forestry planning, accurate description of the state of the forests is essential. Advanced planning models often require input data with high resolution, i.e. data at the single-tree level. Field inventory procedures based on sample plot measurements are usually employed. However, such methods are expensive, so cost-efficient alternatives would be attractive. In the work described in this thesis, inventory methods based on imputation of reference sample plot data were evaluated. The reference material consisted of data from previously performed field inventories. The k nearest neighbour (kNN) method was used, in which all variables available at the reference plots were simultaneously estimated for the target areas. The imputations were based on information derived from interpretations of aerial photographs, optical satellite data, radar data (airborne sensor), and existing stand records. To account for differences in the qualities of the different information sources combined in the kNN estimations, distance metrics were defined and applied using regression functions. The utility of various types of forecasted reference material was evaluated. Increasing the length of forecasts of reference sample plot data increased the mean square error (MSE) in stem volume estimates. However, by excluding disturbed plots (due to thinnings) from the reference material, plot data forecasted for up to 25 years could be used without severely decreasing the accuracy of the estimations. Using aerial photo interpretations together with stand records, kNN estimates of stem volume with relative root MSEs (RMSEs) of 14-20% at the stand level were obtained. More accurate estimates were obtained for a northern test site, in comparison with results from southern Sweden. Combining optical satellite data and radar data significantly improved results, giving a RMSE in standwise stem volume estimates of 22%, compared to 30% for the best single-sensor case. Consequences of using kNN estimations in a planning context were evaluated by a cost-plus-loss approach. The total cost of undertaking an inventory was obtained by summing the actual inventory cost and the net present value of expected future losses due to non-optimal decisions caused by erroneous data. Input data obtained by imputation of reference sample plots were compared with traditional field sample plot inventories. Results indicated that the total cost of an inventory could be reduced by 15-50% by integrating different methods; imputation could be applied for some types of stands while more accurate field inventories should be carried out in others. It is not necessarily the most valuable stands that should be inventoried by careful field measurements, but many of those with a treatment impendin
Subjects/Keywords: aerial surveying; cost analysis; evaluation; forest inventories; forestry; methods; photography; planning; remote sensing; forestry; aerial photography; cost-plus-loss analysis; forest assessment; individual tree data; multisource data; nonparametric estimation.
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APA ·
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MLA ·
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CSE |
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Manager
APA (6th Edition):
Holmström, H. (2001). Data acquisition for forestry planning by remote sensing based sample plot imputation. (Doctoral Dissertation). Swedish University of Agricultural Sciences. Retrieved from http://pub.epsilon.slu.se/29/
Chicago Manual of Style (16th Edition):
Holmström, Hampus. “Data acquisition for forestry planning by remote sensing based sample plot imputation.” 2001. Doctoral Dissertation, Swedish University of Agricultural Sciences. Accessed December 05, 2019.
http://pub.epsilon.slu.se/29/.
MLA Handbook (7th Edition):
Holmström, Hampus. “Data acquisition for forestry planning by remote sensing based sample plot imputation.” 2001. Web. 05 Dec 2019.
Vancouver:
Holmström H. Data acquisition for forestry planning by remote sensing based sample plot imputation. [Internet] [Doctoral dissertation]. Swedish University of Agricultural Sciences; 2001. [cited 2019 Dec 05].
Available from: http://pub.epsilon.slu.se/29/.
Council of Science Editors:
Holmström H. Data acquisition for forestry planning by remote sensing based sample plot imputation. [Doctoral Dissertation]. Swedish University of Agricultural Sciences; 2001. Available from: http://pub.epsilon.slu.se/29/
Swedish University of Agricultural Sciences
5.
Barth, Andreas.
Spatially comprehensive data for forestry scenario analysis.
Degree: 2007, Swedish University of Agricultural Sciences
URL: http://pub.epsilon.slu.se/1613/
► This thesis focuses on the use of forest data for national level policy making. Three major issues were considered: (i) to determine typical requirements of…
(more)
▼ This thesis focuses on the use of forest data for national level policy making. Three major issues were considered: (i) to determine typical requirements of data in forestry scenario analysis, (ii) to evaluate and further develop methods to determine data requirements, and (iii) to develop methods that improve data usability in forestry scenario analysis. Increasingly, the trend is to use spatially comprehensive data as a basis for forestry scenario analysis. Compared to traditional approaches, often limited to sample data, this allows for a broader scope. This is needed since sustainable forestry today must encompass economical and ecological, as well as social perspectives. Different approaches to linking data acquisition strategies with decisions that typically are based on forestry scenario analyses were used in the determination of data requirements. In Paper I, a qualitative framework was developed and applied. The conclusions were that none of the currently used Swedish data acquisition strategies were able to provide data for adequate multi-resource forestry scenario analysis at national level. In Papers II and III, two quantitative approaches were used for the evaluation of sample-plot imputations; using a decision support system the quantitative consequences of errors and cost-plus-loss with simulations were considered. From Paper II it was clear that traditional approaches to acquiring spatially comprehensive data may lead to severe errors in scenario analyses. Both papers concluded that improvements are required in the methodology of assessing the data. In Paper IV, an analytical cost-plus-loss approach was used to address the issue of decision-making at the national level linked to national forest inventories. The conclusion was that the current level of Swedish national forest inventory is motivated fully by the role of the inventory to provide information for national level timber harvesting planning, whereas the inventory serves many other purposes as well. In Papers V and VI, methods were developed and tested regarding how the usability of spatially comprehensive data for national level forestry scenario analysis can be enhanced. In Paper V an algorithm for spatially consistent imputation within forest stands was developed and found to deliver good results in a case study. In Paper VI, a framework for landscape level imputation aiming at preserving overall composition while enhancing spatial configuration was outlined and tested. A core component of the framework was a restricted imputation algorithm that ensured that the classical imputation problem of data “tending towards the mean” was avoided. Case studies showed promising results, but it is clear that the methodological tool-kit must be further developed before it can be applied in practice.
Subjects/Keywords: forest inventories; planning; decision making; decision support; data collection; data analysis; forest inventory; data acquisition; forest management; decision support systems; forestry scenario analysis; data requirements; national level forest planning; decision-making; policy-making; cost-plus-loss analysis; medium-resolution satellite data; laser scanner data; national forest inventory; data usability; optimisation; imputation
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APA ·
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APA (6th Edition):
Barth, A. (2007). Spatially comprehensive data for forestry scenario analysis. (Doctoral Dissertation). Swedish University of Agricultural Sciences. Retrieved from http://pub.epsilon.slu.se/1613/
Chicago Manual of Style (16th Edition):
Barth, Andreas. “Spatially comprehensive data for forestry scenario analysis.” 2007. Doctoral Dissertation, Swedish University of Agricultural Sciences. Accessed December 05, 2019.
http://pub.epsilon.slu.se/1613/.
MLA Handbook (7th Edition):
Barth, Andreas. “Spatially comprehensive data for forestry scenario analysis.” 2007. Web. 05 Dec 2019.
Vancouver:
Barth A. Spatially comprehensive data for forestry scenario analysis. [Internet] [Doctoral dissertation]. Swedish University of Agricultural Sciences; 2007. [cited 2019 Dec 05].
Available from: http://pub.epsilon.slu.se/1613/.
Council of Science Editors:
Barth A. Spatially comprehensive data for forestry scenario analysis. [Doctoral Dissertation]. Swedish University of Agricultural Sciences; 2007. Available from: http://pub.epsilon.slu.se/1613/
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