. 2005. Applying geostatistics for investigations of forest ecosystems using remote sensing imagery. Silva Fennica 39(4): 599-617.Geostatistically based methods that utilize textural information are frequently used to analyze remote sensing (RS) images. The role of these methods in analyzing forested areas increased rapidly during the last several years following advancements in highresolution RS technology. The results of numerous applications of geostatistical methods for processing RS forest images are encouraging. This paper summarizes such results. Three closely related topics are reviewed: 1) specific properties of geostatistical measures of spatial variability calculated from digital images of forested areas, 2) determination of biophysical forest parameters using semivariograms and characterization of forest ecosystem structure at the stand level, and 3) forest classification methods based on spatial information.

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Forest resources have a high economic value in the State of Georgia (USA) and the landscape is frequently disturbed as a part of forest management activities, such as plantation forest management activities. Thus, tracking the stand-clearing disturbance history in a spatially referenced manner might be pivotal in discussions of forest resource sustainability within the State. The two major objectives of this research are (i) to develop and test a reliable methodology for statewide tracking of forest disturbances in Georgia, (ii) to consider and discuss the use and implications of the information derived from the forest disturbance map. Two primary disturbance detection methods, a threshold algorithm and a statistical boundary method, were combined to develop a robust estimation of recent forest disturbance history. The developed model was used to create a forest disturbance record for the years 1987–2016, through the use of all available Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+) data. The final product was a raster database, where each pixel was assigned a value corresponding to the last disturbance year. The overall accuracy of the forest disturbance map was 87%, and it indicated that 4,503,253 ha, equivalent to 29.2% of the total land area in Georgia, experienced disturbances between 1987 and 2016. The estimated disturbed area in each year was highly variable and ranged between 84,651 ha (±36,354 ha) to 211,780 ha (±49,504 ha). By combining the use of the disturbance map along with the 2016 database from the National Land Cover Database (NLCD), we also analyzed the regional variation in the disturbance history. This analysis indicated that disturbed forests in urban areas were more likely to be converted to other land-uses. The forest disturbance record created in this research provides the necessary spatial data and address forest resource sustainability in Georgia. Additionally, the methodology used has application in the analysis of other resources, such as the estimation of the aboveground forest biomass.

We used long-term simulation analysis in a spatially explicit forest management model called OPTIONS to investigate the impact of the rotation age, intensive management practices, and harvesting limits on wood production, harvesting opportunities, and long-term resource sustainability. The initial forest inventory is compiled from data sets of the US Forest Service Forest Inventory Analysis Unit, various GIS data, Landsat 5 Thematic Mapper imagery, and simplified assumptions about the spatial distribution of different forest cover types. We determined the parameters of the model from published and unpublished literature and from interviews with experts in the area of forest management in the southeastern United States. The sensitivity analyses reveal the impacts of the individual factors of the rotation age, intensive management practices, and harvesting limits and of the interaction of these factors on the sustainability of the forest resources. The results of the analyses suggest that the current timberland in Georgia can easily sustain the current level of harvesting with the current level of intensive management practices for different choices of the rotation ages. The volume available for harvesting would increase with an increasing rate of transition to intensively managed plantations (IMPs) regardless of the level of harvesting limits and rotation age. To ensure sustainability of forest resources under an increasing harvest scenario, part of new plantations would be required to convert to intensive management. The higher the harvesting limit, the more intensively managed plantations needed. The patterns of the changes in the volume available for harvesting by species groups were different for cases of keeping current harvesting limits and IMP levels versus applying increasing harvesting limits and an increasing transition rate to IMPs. Harvestable volumes are significantly different among each level of the three analyzed factors: transition rate to IMPs, rotation age, and harvesting limits. The study informs land use and policy decisionmakers about potential sensitivities of Georgia forest resource productivities to changes in forest practices-related rules and regulations.

We developed a case study for estimating carbon stock (stored and annually sequestered) in aboveground and belowground portions of all the live trees located on the main campus of the University of Georgia. We recorded species, diameter at breast height, and height of trees located between East Broad Street and Carlton Street (north–south direction) and East Campus Road and Lumpkin Street (east–west direction) covering an area of 94.1 hectares. We used i-Tree Eco V6 for estimating carbon stock. There are 6,915 trees in the study area, out of which 73.0 percent (5,049 trees), 32.3 percent (2,236 trees), and 0.7 percent (50 trees) are native, understory, and invasive, respectively. The total carbon stored in trees is 3,450.4 t (SD = 65), and the annual sequestration rate is about 65 t. The University of Georgia should adopt a multifaceted approach for offsetting or reducing the overall carbon emissions, as annual sequestered carbon in measured trees is only 0.11 percent of the total carbon emitted by the university in 2018. This study highlights the role of trees in meeting the carbon reduction challenges faced by colleges and universities across the United States and beyond, and contextualizes the role of green spaces in general, and trees, in particular toward the ongoing movement of sustainable universities and campuses worldwide. Study Implications: Across the United States and beyond, universities and colleges are actively exploring ways to reduce their overall environmental footprint for achieving sustainable development goals. Trees located on the campuses of universities and colleges provide various ecosystem services, including carbon storage and annual sequestration. We advise that universities and colleges should explore other options to reduce or offset their annual carbon emissions, as the quantity of carbon annually sequestered in trees located on the main campuses could be small relative to their overall annual carbon emissions.