The repeatability of stand measurements derived from LiDAR data was tested in east-central Mississippi. Data collected from LiDAR missions and from ground plots were analyzed to estimate stand parameters. Two independent LiDAR missions were flown in approximate orthogonal directions. Field plots were generated where the missions overlapped, and tree data were taken in these plots. LiDAR data found 86-100% of mature pine trees, 64-81% of immature pine trees, and 63-72% of mature hardwood trees. Immature and mature pine tree heights measured from LiDAR were found to be significantly different (α= 0.05) than field measured heights. Individual tree volumes and plot volume for mature pines were precisely predicted in both flight directions. The results of this study showed that LiDAR repeatability in mature pines can be accurately achieved. But immature pine and hardwood plots were unable to match the repeatability of the mature pine plots.

Forest community characteristics on six forest stands in northeastern Mississippi were investigated. Study sites included two cottonwood stands, two managed hardwood stands, and two unmanaged hardwood stands. Relationships between forest stand components and habitat characteristics were estimated. Measured forest stand characteristics included regeneration, midstory and overstory to estimate species composition and forest structure. Basal area, crown density, standing dead trees and fallen dead tree measurements were also taken in the fall of 2010. A higher amount of tree species in the cottonwood and managed hardwood stands with the unmanaged hardwood stands having the lowest number of tree species. It was also detected that the unmanaged hardwood stands contained a higher DBH of 29.0 cm than the remaining stands. Cottonwood stands had a higher tree per hectare than the other stands. The unmanaged hardwood stands also contained the largest amount of standing and fallen dead trees.

Multiple linear and ordinal logistic regression methods were used to develop cubic foot volume (outside bark to a pulpwood diameter top) estimation models for the central Mississippi Institute for Forest Inventory (MIFI) inventory region of Mississippi, USA based on multi-scene Landsat derived variables. These models were used to stratify the region into volume classes to estimate the statistical gains made from a stratified random sample versus a complete random sample. Ordinal logistic regression produced higher accuracy statistics for all forest cover classes except the mixed forest cover class and the method is recommended to be used to estimate cubic foot volume (outside bark to a pulpwood diameter top) for the study area. Statistical gains from ordinal logistic regression averaged 30.34% and relative precision averaged 1.53 for the study area. For each forest cover type volume model that was produced, it was found that the interaction variable between Landsat TM band 5 and the GIS age variable was statistically significant.

The forest products industry is a major component of the economic base for many states in the southeastern United States. Forest inventories that are precise within a 50- to 80-mile mill working circle and the availability of decision support tools for locating mills are of primary importance in attracting and sustaining the industry. This research focuses on the current status of the State of Mississippi's efforts to provide forest inventory information to attract forest industry and balance potentially increased utilization due to new markets with resource sustainability. A pilot study is described that integrates a decision support system (DSS) in a 40-mile radius working circle with a geo-spatially based county-level forest inventory and a transportation network to determine the feasibility and optimal location of a case study Oriented Strand Board (OSB) mill. A linear programming (LP) model was constructed to minimize the cost of procuring and transporting wood to the case study OSB mill site. Net revenue (NR) was calculated to assess financial feasibility of placing the mill at the selected location.

QuickBird satellite data was used to examine stem density, basal area, and crown density, as potential forest strata to aid in volume estimations for a regional inventory program. The classes used for analysis were pine pole and sawtimber, and hardwood pole and sawtimber. Total height, height to live crown, diameter at breast height (dbh), and crown class were measured on 129 field plots used in image classification and accuracy assessments. Supervised classification produced overall accuracy of 85% with a Kappa of 0.8065. The classification was used for the extraction of mean band data and percent of forested pixels. Satellite derived variables were used with field measurements such as average basal area and stem density for regression analysis to predict forest characteristics such as stem density and crown closure that are indicators of volume variability. The R2 values ranged from 0.0005 to 0.2815 for hardwoods and 0.0001 to 0.6174 for pines.

For operational forest management, a forest inventory is commonly conducted to determine the timber stocking and the value of standing trees in a stand. With time and costs constraints, appropriate sampling designs and models are required to perform the inventory efficiently, as well as to obtain reliable estimates for the variables needed to make projections. In this dissertation research, a simulation study was conducted to extensively explore four important topics in forest inventories: selection of measurement trees in point samples, projection from plot- and stand-level aggregations, subsampling height for volume estimation, and updating stand projections using periodic inventories. A series of simulated loblolly pine plantations with varying degrees of spatial heterogeneity were generated at different stages in stand development. Repeated sampling was used to examine various sampling schemes and growth projection methods. Highlights for the four topics follow: 1. Stand total volume can be reliably estimated using measurement trees tallied by Big BAF, point-double sampling, or random selection of a specified number of trees. However, number of trees per unit area in small-size classes were overestimated across the three tree-selection methods when sample data were aggregated into diameter classes. 2. Plot-level and stand-level projections produced similar estimates for dominant height, basal area, and stems per unit area. As spatial heterogeneity increased, stand-level projections indicated a significant bias of predicted total volume compared with the plot-level projections. 3. Sampling intensity, stand age and spatial heterogeneity have greater influence on the reliability for total volume estimation compared to subsampling intensity and measurement error for height measurements. 4.The variability of total volume estimates increases with increasing projection length (i.e., longer time intervals between inventory entry points). However, the estimates of stand total volume can be greatly improved by updating the models with information obtained in periodic forest inventories, especially when the original models are not well calibrated. The results of this study provide useful guidance and insights for forest practitioners to design forest inventories and improve growth projection systems in operational forest management. / Doctor of Philosophy / For operational forest management, a forest inventory is commonly conducted to determine the timber stocking and the value of standing trees in a stand for management decisions, financial planning and fiduciary reporting requirements. With time and costs constraints, appropriate sampling designs and models are required to perform the inventory efficiently, as well as to obtain reliable estimates for the variables needed to make stand projections. Loblolly pine (Pinus taeda L.) is the primary commercial species in the southeastern United States. In this dissertation research, a simulation study was conducted to extensively explore several important topics in forest inventories, including selection of measurement trees in point samples, projection from plot- and stand-level aggregations, subsampling height for volume estimation, and updating stand projections using periodic inventories. A series of simulated loblolly pine plantations with varying degrees of spatial heterogeneity were generated at different stages in stand development. Repeated sampling was used to examine various sampling schemes and growth projection methods. The results of this study provide useful guidance and insights for forest practitioners to design forest inventories and improve growth projection systems in operational forest management.

To ensure that thinning is done properly and correct due to instruction, regularly manual monitoring of the stand is done by the harvester operator after thinning. The aim of this study is to investigate the reliability of a newly developed program, that is using harvester data to automaticly calculate stand variables after thinning. A manual forest inventory was carried out in ten differens stands i south west of Sweden, where basal area, stem density, volume and species mix were estimated and compared to the automatically calculated data. The results shows that volume and stem density were estimated with high precision while the systematic deviation for basal area was 10 %, which is a significant differens.

No description available.

O objetivo deste trabalho foi estimar o volume de madeira de um povoamento jovem de Pinus elliottii, localizado no litoral sudeste do Rio Grande do Sul, com imagens dos sensores LISS-III/ResourceSat-1 e TM/Landsat 5, comparando o desempenho destes para tal. Obtiveram-se imagens de setembro de 2010, mês coincidente com o inventário florestal feito na área de estudo. Os valores de reflectância espectral de superfície foram recuperados das imagens originais. Após o georreferenciamento, dos pixels coincidentes com a localização das unidades amostrais do inventário florestal foram extraídos os valores das reflectâncias nas quatro bandas espectrais equivalentes aos dois sensores, cujas respostas foram comparadas. Além das bandas espectrais foram utilizados os índices de vegetação (IV’s) SR, NDVI, SAVI, MVI e GNDVI. Também, foi proposto o ajuste destes IV’s originais pela idade do povoamento, os quais foram identificados por SR_i, NDVI_i, MVI_i e GNDVI_i. A aplicação do logaritmo nas bandas espectrais melhorou os valores dos coeficientes de correlação linear (r), à exceção do IVP, retornando valores entre 0,69 (IVP) a 0,83 (Verde) para o LISS-III e entre 0,68 (Vermelho) a 0,79 (IVM) para o TM; Com os IV’s o logaritmo melhorou os valores de r somente para os IV’s originais, retornando valores de r entre 0,77 (NDVI) a 0,84 (GNDVI) com o LISS-III e entre 0,73 (NDVI) a 0,82 (MVI) para o TM. Com os IV’s ajustados pela idade do povoamento a logaritimização não se mostrou necessária para melhorar a associação linear, retornando valores de r entre 0,79 (NDVI_i) a 0,82 (MVI_i) com o LISS-III e entre 0,74 (SR_i) a 0,80 (MVI_i) com o TM. Além disso, o ajuste pela idade aumentou o intervalo dinâmico dos IV’s ajustados, e, aparentemente, aumentou a sensibilidade nos povoamentos de maior volume. Diferenças significativas na associação linear entre os dados espectrais do TM e LISS-III com o volume só foram encontradas na banda equivalente do verde. Com dados TM, a equação melhor ajustada explicou 68% da variabilidade do volume; com dados LISS-III a equação explicou 72% da variabilidade. Estas equações geraram dois mapas de volume de madeira, onde as médias das estimativas obtidas com LISS-III estiveram dentro do intervalo de confiança da média do inventário florestal em 70% dos talhões considerados; para o TM a coincidência foi de 65% dos talhões. Conclui-se que os sensores LISS-III e TM apresentam alta similaridade e que a metodologia empregada pode ser utilizada para auxiliar no inventário florestal dos povoamentos jovens de P. elliottii na área de estudo principalmente pelo fato das estimativas obtidas pelas imagens cobrirem todo o talhão, ao passo que a amostragem do inventário florestal contempla menos de 2% da área. / The aim of this work was to estimate the wood volume of a young stand of Pinus elliottii, located on the southeastern coast of the state of Rio Grande do Sul, by imagery from LISS-III/ResourceSat-1 and TM/Landsat 5 sensors, comparing their performance for such. Images were obtained on September 2010, the month coincident with the forest inventory made in the study area. The surface spectral reflectance values were retrieved from the original images. After the georeferencing, the sampling units location from the forest inventory were used to select the pixels to extract the reflectance values on the four spectral bands equivalents for the two sensors, which answers were compared. In addition to the bands were used the Vegetation Indices (VI’s) SR, NDVI, SAVI, MVI and GNDVI. Also proposed was the adjusting of these original VI’s by the stand age, which ones were identified by SR_i, NDVI_i, MVI_i and GNDVI_i. The application of logarithm in the spectral bands improved the r values, with exception to NIR, achieving values between 0.69 (NIR) and 0.83 (Green) for LISS-III and between 0.68 (Red) and 0.79 (SWIR) for TM; With the VI’s, the logarithm improved the r values only for the original VI’s, returning r values from 0.77 (NDVI) to 0.84 (GNDVI) with LISS-III and r values from 0.73 (NDVI) to 0.82 (MVI) for TM. With the VI’s adjusted by stand age the logarithm was not necessary to improve the linear association, returning r values from 0.79 (NDVI_i) to 0.82 (MVI_i) with LISS-III and r values from 0.74 (SR_i) to 0.80 (MVI_i) with TM. Moreover, adjusting by age increased the dynamic range of the VI’s adjusted, and apparently increased the sensitivity in stands with larger volume. Significant differences in the linear association between TM and LISS-III spectral data with volume were just found on the green equivalent band. With TM data, the best fitted model explained 68% of the volume variability; with LISS-III data the model explained 72% of the variability. These models generated two wood volume maps, where the average of the estimates achieved with LISS-III were within the confidence level of the average from the forest inventory on 70% of the compartments considered; for TM the coincidence was on 65% of the compartments. It is conclude that the sensors LISS-III and TM presented high similarity and the methodology applied can be used to aid in forest inventory of young stands of P. elliottii in the study area mainly because the estimates obtained by the images cover the entire compartment, while the forest inventory sampling contemplates less than 2% of the area.

O objetivo deste trabalho foi estimar o volume de madeira de um povoamento jovem de Pinus elliottii, localizado no litoral sudeste do Rio Grande do Sul, com imagens dos sensores LISS-III/ResourceSat-1 e TM/Landsat 5, comparando o desempenho destes para tal. Obtiveram-se imagens de setembro de 2010, mês coincidente com o inventário florestal feito na área de estudo. Os valores de reflectância espectral de superfície foram recuperados das imagens originais. Após o georreferenciamento, dos pixels coincidentes com a localização das unidades amostrais do inventário florestal foram extraídos os valores das reflectâncias nas quatro bandas espectrais equivalentes aos dois sensores, cujas respostas foram comparadas. Além das bandas espectrais foram utilizados os índices de vegetação (IV’s) SR, NDVI, SAVI, MVI e GNDVI. Também, foi proposto o ajuste destes IV’s originais pela idade do povoamento, os quais foram identificados por SR_i, NDVI_i, MVI_i e GNDVI_i. A aplicação do logaritmo nas bandas espectrais melhorou os valores dos coeficientes de correlação linear (r), à exceção do IVP, retornando valores entre 0,69 (IVP) a 0,83 (Verde) para o LISS-III e entre 0,68 (Vermelho) a 0,79 (IVM) para o TM; Com os IV’s o logaritmo melhorou os valores de r somente para os IV’s originais, retornando valores de r entre 0,77 (NDVI) a 0,84 (GNDVI) com o LISS-III e entre 0,73 (NDVI) a 0,82 (MVI) para o TM. Com os IV’s ajustados pela idade do povoamento a logaritimização não se mostrou necessária para melhorar a associação linear, retornando valores de r entre 0,79 (NDVI_i) a 0,82 (MVI_i) com o LISS-III e entre 0,74 (SR_i) a 0,80 (MVI_i) com o TM. Além disso, o ajuste pela idade aumentou o intervalo dinâmico dos IV’s ajustados, e, aparentemente, aumentou a sensibilidade nos povoamentos de maior volume. Diferenças significativas na associação linear entre os dados espectrais do TM e LISS-III com o volume só foram encontradas na banda equivalente do verde. Com dados TM, a equação melhor ajustada explicou 68% da variabilidade do volume; com dados LISS-III a equação explicou 72% da variabilidade. Estas equações geraram dois mapas de volume de madeira, onde as médias das estimativas obtidas com LISS-III estiveram dentro do intervalo de confiança da média do inventário florestal em 70% dos talhões considerados; para o TM a coincidência foi de 65% dos talhões. Conclui-se que os sensores LISS-III e TM apresentam alta similaridade e que a metodologia empregada pode ser utilizada para auxiliar no inventário florestal dos povoamentos jovens de P. elliottii na área de estudo principalmente pelo fato das estimativas obtidas pelas imagens cobrirem todo o talhão, ao passo que a amostragem do inventário florestal contempla menos de 2% da área. / The aim of this work was to estimate the wood volume of a young stand of Pinus elliottii, located on the southeastern coast of the state of Rio Grande do Sul, by imagery from LISS-III/ResourceSat-1 and TM/Landsat 5 sensors, comparing their performance for such. Images were obtained on September 2010, the month coincident with the forest inventory made in the study area. The surface spectral reflectance values were retrieved from the original images. After the georeferencing, the sampling units location from the forest inventory were used to select the pixels to extract the reflectance values on the four spectral bands equivalents for the two sensors, which answers were compared. In addition to the bands were used the Vegetation Indices (VI’s) SR, NDVI, SAVI, MVI and GNDVI. Also proposed was the adjusting of these original VI’s by the stand age, which ones were identified by SR_i, NDVI_i, MVI_i and GNDVI_i. The application of logarithm in the spectral bands improved the r values, with exception to NIR, achieving values between 0.69 (NIR) and 0.83 (Green) for LISS-III and between 0.68 (Red) and 0.79 (SWIR) for TM; With the VI’s, the logarithm improved the r values only for the original VI’s, returning r values from 0.77 (NDVI) to 0.84 (GNDVI) with LISS-III and r values from 0.73 (NDVI) to 0.82 (MVI) for TM. With the VI’s adjusted by stand age the logarithm was not necessary to improve the linear association, returning r values from 0.79 (NDVI_i) to 0.82 (MVI_i) with LISS-III and r values from 0.74 (SR_i) to 0.80 (MVI_i) with TM. Moreover, adjusting by age increased the dynamic range of the VI’s adjusted, and apparently increased the sensitivity in stands with larger volume. Significant differences in the linear association between TM and LISS-III spectral data with volume were just found on the green equivalent band. With TM data, the best fitted model explained 68% of the volume variability; with LISS-III data the model explained 72% of the variability. These models generated two wood volume maps, where the average of the estimates achieved with LISS-III were within the confidence level of the average from the forest inventory on 70% of the compartments considered; for TM the coincidence was on 65% of the compartments. It is conclude that the sensors LISS-III and TM presented high similarity and the methodology applied can be used to aid in forest inventory of young stands of P. elliottii in the study area mainly because the estimates obtained by the images cover the entire compartment, while the forest inventory sampling contemplates less than 2% of the area.