GIS in Regeneration of Forest Disturbances

Annotated Bibliography

Arianoutsou, M., Koukoulas, S., & Kazanis, D. (2011). Evaluating Post-Fire Forest Resilience Using GIS and Multi-Criteria Analysis: An Example from Cape Sounion National Park, Greece. Environmental Management, 47(3), 384–397.

An ecosystem’s historic fire regime is a major driver of its evolution, diversity, function, and distribution and is pivotal in establishing vegetation community responses. Mediterranean climate ecosystems are characterized by the occurrence of frequent wildfires that have shaped them. The potential changes in this regions fire regime due to climate change and the subsequent effect on plant communities and ecosystem resilience is of major concern. Here the authors integrate decision-support techniques in a GIS framework to develop a Multi Criteria Decision Analysis (MCDA) approach to evaluate the risk of loss of post-fire resilience in Pinus halepensis forest ecosystems. They synthesize bio-indicator data, such as vegetation type cover and relative species richness, with geo-indicator data, such as fire history, topography, and soil type, to rank the contribution of each factor. The final product of this study is a ranking map illustrating the variable risk of losing resilience across the landscape which can be used to identify high risk areas and inform post-fire management strategies.

Cherepanova, E., & Feoktistova, N. (2019). Multiscale Remote Sensing and Gis Approach for Monitoring of Post-Fire Burn Severity and Vegetation Recovery in High-Latitude Forest. International Multidisciplinary Scientific GeoConference : SGEM, 19(2.1), 965–972.

Considering the vast size and inaccessibility of the Arctic regions, on the ground field research is limited, for this reason remote sensing is particularly useful for environmental monitoring and assessing the state of high-latitude forests. Using contemporary remote sensing systems and data processing methods, it is possible for researchers to obtain a continuous chrono sequence of vegetation recovery stages. The authors of this study propose and test methods for using remote sensor data and GIS to monitor fires at extreme latitudes. This research used the larch Larix sibirica forests in the Zhigansky district of Yukatia, Russia as a test subject. Detection of burned areas at this high latitude was determined by the analysis of long-term series of space data obtained from both Terra/Aqua and Landsat satellites. Burn severity and vegetation recovery were based on vegetation indices calculated using MODIS daily data with a spatial resolution of 500 m large, burned areas (>50km²) and Landsat daily data with a resolution of 30 m for smaller burned areas. Comparing the results of burnt areas from multiple satellite products with varying spatial scales determined that using MODIS data 500 m resolution was sufficient for monitoring fires in the region. The proposed methods, of using low and medium resolution remote sensing data to quantify spatial and temporal dynamics of the restoration of high latitude burned areas, appear effective for obtaining high-quality, cost-effective information to support a management decision-making process.

Coop, J. D., DeLory, T. J., Downing, W. M., Haire, S. L., Krawchuk, M. A., Miller, C., Parisien, M.-A., & Walker, R. B. (2019). Contributions of fire refugia to resilient ponderosa pine and dry mixed-conifer forest landscapes. Ecosphere, 10(7), e02809.

A change in a regions historic fire regime may lead to shifts in forest composition or even loss of forest ecosystems. Dry mixed-conifer forest landscapes of the Western U.S. may be particularly vulnerable to changing fire regimes. Fire refugia, forest patches that survive fire events, can be an important seed source for forest recovery. In this study the researchers used imagery from the National Agriculture Imagery Program (NAIP) and fire perimeter polygons from Monitoring Trends in Burn Severity project to create high-resolution maps of tree cover to stratify field sampling locations and generate spatial predictor variables for statistical models. Statistical analysis and simulation modeling was done using R software. The assessment focused on the relationships between tree seedling abundances related to refugium distance and density. It was found that regeneration of ponderosa pine and obligate-seeding mixed-conifer tree species assemblages was positively predicted by proximity to and density of fire refugia.

Donato, D. C., Fontaine, J. B., Campbell, J. L., Robinson, W. D., Kauffman, J. B., & Law, B. E. (2009). Conifer regeneration in stand-replacement portions of a large mixed-severity wildfire in the Klamath—Siskiyou Mountains. Canadian Journal of Forest Research, 39(4), 823+.

Large stand replacing wildfires in temperate forests have the potential to eliminate seed sources over broad areas and may lead to significantly different regeneration dynamics compared to smaller scale burns. This study looks at natural regeneration following a 200,000-hectare mixed-severity wildfire in Oregon, USA. It quantifies the conifer and broadleaf regeneration in stand-replacement areas 2 and 4 years postfire and assesses the relative importance of distance from seed source (surviving mature trees) and local site conditions in determining regeneration densities. The two factors that exerted the strongest influence on regeneration were distance to seed source and soil parent material. Other factors such as topography and competing vegetation had little effect on conifer regeneration. They used Forest Service GIS data to perform landscape analysis and construct multi-layer maps identifying burn perimeters, burn severity, post fire tree survival (potential seed source), distances to potential seed sources, and soil parent material. The authors recognized that there are typically inaccuracies in fine-scale objects such as small, isolated patches of surviving trees, when using spatial data over large heterogeneous domains such as the study area. To validate the accuracy of the burn severity and seed source layers they cross-referenced using aerial photographs and opportunistic site visits and adjusted the estimates accordingly.

Nasery, S., & Kalkan, K. (2020). Burn area detection and burn severity assessment using Sentinel 2 MSI data: The case of Karabağlar district, İzmir/Turkey. Turkish Journal of Geosciences, 1(2), Article 2.

Wildfires destroy huge amounts of forest around the world every year. When considering vegetation regeneration, it is important to both detect the burned area and classify the burn severity. High burn severities can impact the nature of soils by destroying the organic matter content which negatively impacts the success of the regeneration of vegetation. Using remote sensing data is an efficient method to accurately map burned areas and assess levels of burn severity. This study was located in an area burned by a forest fire in 2019, in Karabağlar Menderes and Seferihisar districts of İzmir province, Turkey. The study focuses on using NBR and SAVI indices to accurately map the burn area and dNBR and dSAVI to classify the burn severity. SNAP software was used for data analysis and ArcGIS Pro was used for area calculation and plotting. The results of the study revealed that the burn was 6,910 hectares which dramatically contradicts the assertion by the media that the burn was only 500 hectares. 1,677 hectares were classified as high severity which is three to four times greater than what was reported in the media.

Petropoulos, G. P., Griffiths, H. M., & Kalivas, D. P. (2014). Quantifying spatial and temporal vegetation recovery dynamics following a wildfire event in a Mediterranean landscape using EO data and GIS. Applied Geography, 50, 120–131.

Wildfires are one of the most widespread and dramatic ecological disturbances of natural ecosystems. They can significantly impact the dynamics of land cover over variable spatial and temporal scales by the near complete removal of vegetation which in turn has cascading effect on all the organisms that live within the ecosystem. Information and study of the spatial-temporal distribution of vegetation recovery dynamics is important for deepening our general ecological understanding as well as informing policy and decision making around wildfire and landscape management. The rate of vegetation recovery can vary significantly from full recovery after only a few years to persistent impact for decades post fire. This study used a combination of EO and GIS to evaluate the vegetation recovery dynamics of a Mediterranean ecosystem that was impacted by a 2007 wildfire. The relationship between re-growth patterns and the topographical features of the burn scar was also investigated. Chronosequence analysis of the Normalized Difference Vegetation Index (NDVI) derived from Landsat TM images was the basis of the investigation. The post-fire NDVI was compared to the pre-fire pattern to determine the resilience and recovery rate of the ecosystem. Their results show a gradual but systematic recovery pattern where re-growth rates were somewhat higher on north aspects compared to south aspects.

Shin, S. S., Park, S. D., & Kim, G. (2022). Risk Assessment of Soil Erosion Using a GIS-Based SEMMA in Post-Fire and Managed Watershed. Sustainability, 14(12), Article 12.

Climate change may be contributing to an increase in wildfire frequency and severity in many places in the world including South Korea. Wildfires denude vegetation and burn litter layers and when combined with increased rainfall enhanced by climate variability can accelerate floods and erosion. One such instance occurred in 2019 in a mountainous region of South Korea where the impacts of a wildfire were further exasperated by flooding caused by the occurrence Typhoon Mitag in the same year. This study uses the Soil Erosion Model for Mountain Areas (SEMMA) in ArcGIS to quantitatively evaluate the risk of soil erosion in wildfire areas. The SEMMA model is an empirical model developed specifically for mountainous regions of South Korea to account for the local heterogeneity of parameters such as rainfall, soil, morphology, and vegetation. Soil erosion was simulated through multi-layer spatial analysis with the main parameters of SEMMA-Ic being the rainfall factor layer, the vegetation index layer, the soil factor layer, and the topographic factor layer. Results showed high erosion rates in areas damaged by wildfires although less than that of developed areas. Evaluation of the risk of erosion following wildfire is an important aspect of post-fire management planning.

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