scholarly journals Sawtimber Yield Tables for Pennsylvania Forest Management Planning

2010 ◽  
Vol 27 (4) ◽  
pp. 140-150
Author(s):  
Horacio Gilabert ◽  
Phillip J. Manning ◽  
Marc E. McDill ◽  
Steve Sterner
Keyword(s):  
Forest Management ◽  
Forest Type ◽  
Site Class ◽  
Management Planning ◽  
Forest Management Planning ◽  
Ecological Regions ◽  
Continuous Forest ◽  
Planning Project ◽  
Species Groups ◽  
The 1960S

Abstract Models to predict gross and net sawtimber volume per acre for even-aged stands were calibrated for Pennsylvania forests as part of a continuing forest management planning project for Pennsylvania's 2.1 million acres of state forestland. Because of the requirements of the models and limitations of the planning data, the main variable driving the yield models was age. Binary variables were used to shift the sawtimber volume predictions up or down to differentiate yields for 3 site classes, 2 stocking classes, 7 forest types, and 10 ecological regions within the state. The models were fitted using plot-level observations from a continuous forest inventory that has been carried out by the Pennsylvania Department of Conservation and Natural Resources Bureau of Forestry since the 1960s. To apportion the total volume into species groups, proportions were derived of the total sawtimber volume per acre for seven different species groups by forest type and site class for four macro-regions aggregated from the ecological regions within Pennsylvania.

scholarly journals A Levenberg–Marquardt Backpropagation Neural Network for Predicting Forest Growing Stock Based on the Least-Squares Equation Fitting Parameters

Forests ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 757 ◽  
Author(s):  
Ruyi Zhou ◽  
Dasheng Wu ◽  
Luming Fang ◽  
Aijun Xu ◽  
Xiongwei Lou
Keyword(s):  
Forest Management ◽  
Least Squares ◽  
Tree Species ◽  
Backpropagation Neural Network ◽  
Management Planning ◽  
Forest Management Planning ◽  
Growing Stock ◽  
Planning And Design ◽  
Levenberg Marquardt ◽  
Species Groups

Traditional field surveys are expensive, time-consuming, laborious, and difficult to perform, especially in mountainous and dense forests, which imposes a burden on forest management personnel and researchers. This study focuses on predicting forest growing stock, one of the most significant parameters of a forest resource assessment. First, three schemes were designed—Scheme 1, based on the study samples with mixed tree species; Scheme 2, based on the study samples divided into dominant tree species groups; and Scheme 3, based on the study samples divided by dominant tree species groups—the evaluation factors are fitted by least-squares equations, and the non-significant fitted-factors are removed. Second, an overall evaluation indicator system with 17 factors was established. Third, remote sensing images of Landsat Thematic Mapper, digital elevation model, and the inventory for forest management planning and design were integrated in the same database. Lastly, a backpropagation neural network based on the Levenberg–Marquardt algorithm was used to predict the forest growing stock. The results showed that the group estimation precision exceeded 90%, which is the highest standard of total sampling precision of inventory for forest management planning and design in China. The prediction results for distinguishing dominant tree species were better than for mixed dominant tree species. The results also showed that the performance metrics for prediction could be improved by least-squares equation fitting and significance filtering of the evaluation factors.

Advancing forest planning: reflections on the Otway Forest Management Planning Project

1995 ◽  
Vol 58 (2) ◽  
pp. 23-30 ◽  
Author(s):  
J. Dargavel ◽  
J. Holden ◽  
R. P. Brinkman ◽  
B. J. Turner
Keyword(s):  
Forest Management ◽  
Forest Planning ◽  
Management Planning ◽  
Forest Management Planning ◽  
Planning Project

Developing and Implementing Multiple-Use Forest Management Planning in Turkey

2008 ◽  
Vol 42 (1) ◽  
pp. 37-48 ◽  
Author(s):  
Emin Zeki Baskent ◽  
Salih Terzioğlu ◽  
Şağdan Başkaya
Keyword(s):  
Forest Management ◽  
Multiple Use ◽  
Management Planning ◽  
Forest Management Planning

scholarly journals Small Area Estimation of Postfire Tree Density Using Continuous Forest Inventory Data

2021 ◽  
Vol 4 ◽  
Author(s):  
George C. Gaines ◽  
David L. R. Affleck
Keyword(s):  
Forest Inventory ◽  
Mean Squared Error ◽  
Tree Density ◽  
Standard Errors ◽  
Sample Sizes ◽  
Management Planning ◽  
Forest Management Planning ◽  
Continuous Forest ◽  
Sample Data ◽  
Regional Forest

Wildfire activity in the western United States is expanding and many western forests are struggling to regenerate postfire. Accurate estimates of forest regeneration following wildfire are critical for postfire forest management planning and monitoring forest dynamics. National or regional forest inventory programs can provide vegetation data for direct spatiotemporal domain estimation of postfire tree density, but samples within domains of administrative utility may be small (or empty). Indirect domain expansion estimators, which borrow extra-domain sample data to increase precision of domain estimates, offer a possible alternative. This research evaluates domain sample sizes and direct estimates in domains spanning large geographic extents and ranging from 1 to 10 years in temporal scope. In aggregate, domain sample sizes prove too small and standard errors of direct estimates too high. We subsequently compare two indirect estimators—one generated by averaging over observations that are proximate in space, the other by averaging over observations that are proximate in time—on the basis of estimated standard error. We also present a new estimator of the mean squared error (MSE) of indirect domain estimators which accounts for covariance between direct and indirect domain estimates. Borrowing sample data from within the geographic extents of our domains, but from an expanded set of measurement years, proves to be the superior strategy for augmenting domain sample sizes to reduce domain standard errors in this application. However, MSE estimates prove too frequently negative and highly variable for operational utility in this context, even when averaged over multiple proximate domains.

scholarly journals GESTÃO FLORESTAL NO MARANHÃO: ESTRUTURA ESTADUAL PÓS-DESCENTRALIZAÇÃO

FLORESTA ◽  
2014 ◽  
Vol 45 (2) ◽  
pp. 433
Author(s):  
José Das Dores De Sá Rocha ◽  
José Arimatéa Silva ◽  
Vitor Afonso Hoeflich ◽  
Francisco Carneiro Barreto Campello
Keyword(s):  
Forest Management ◽  
Public Management ◽  
Current Model ◽  
The State ◽  
Management Policy ◽  
Management Model ◽  
Regional Study ◽  
Management Planning ◽  
Forest Management Planning ◽  
Secondary Sources

As instituições dos estados do Nordeste que assumiram a gestão florestal foram diagnosticadas pelo Ministério do Meio Ambiente em 2009. Decorrente deste estudo regional, o presente trabalho tem como objetivos: i) Caracterizar os instrumentos de política e de gestão florestal no estado do Maranhão; ii) Analisar o atual modelo de gestão florestal estadual. Os dados foram obtidos de fontes secundárias na rede mundial de computadores e através da aplicação de questionários em dois Seminários realizados no próprio estado. Os instrumentos de política e gestão florestal foram classificados segundo suas características legais, econômicas e administrativas afetas ao tema. O modelo de gestão florestal foi analisado com base no modelo de excelência em gestão pública, adaptado para o estudo. As principais conclusões foram: há conflitos legais de competências da gestão florestal no estado, entre a SEMA e a SEAGRO; a SEMA é responsável pela política e pela gestão florestal maranhense; uma Superintendência de Gestão Florestal, ainda não institucionalizada, estava, na prática operando a gestão florestal; planejamento, execução e controle da gestão florestal foram avaliados, de modo geral, em situação insatisfatória, tanto pelo público interno da SEMA quanto pelos seus usuários.Palavras-chave: Modelo de gestão florestal; descentralização; Nordeste do Brasil. AbstractForest management in the State of Maranhão, beyond decentralization. The institutions in the Northeastern states that assumed forest management were diagnosed by the Ministry of Environment in 2009. Due to this regional study, this paper aims to: i) characterize the fundamentals of policy and forest management in the state of Maranhão, ii) analyze the current model of state forest management. Data were obtained from secondary sources on the World Wide Web and through questionnaires in two seminars held within the state. The fundamentals of policy and forest management were characterized on the basis of legal instruments, administrative and economic sympathetic to the issue. The forest management model was analyzed based on the model of excellence in public management, adapted for the study. The main conclusions were: conflicts of legal jurisdiction in the state of forest management, and between SEAGRO and SEMA.SEMA is responsible for forest management policy and Maranhão, a Superintendent of Forest Management, not yet institutionalized, was in practice the operating forest management, planning, execution and control of forest management were evaluated, in general, an unsatisfactory situation, both the public and internal SEMA by its users.Keywords: Forest Management model; decentralization; Northeast of Brazil.

Combining ALS and NFI training data for forest management planning: a case study in Kuortane, Western Finland

2009 ◽  
Vol 128 (3) ◽  
pp. 305-317 ◽  
Author(s):  
M. Maltamo ◽  
P. Packalén ◽  
A. Suvanto ◽  
K. T. Korhonen ◽  
L. Mehtätalo ◽  
...  
Keyword(s):  
Forest Management ◽  
Training Data ◽  
Management Planning ◽  
Forest Management Planning
Sign in / Sign up

Export Citation Format

Share Document