Download or read book The Use of Remote Sensing Indices to Determine Wildland Burn Severity in Semiarid Sagebrush Steppe Rangelands Using Landsat ETM and SPOT 5 written by Jill M. Norton and published by . This book was released on 2006 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study evaluates ten remote sensing indices to detect burned areas and burn severity in a southeastern Idaho study area. While fire-related studies have been performed in forested ecosystems, few have been conducted in sagebrush steppe rangelands. Burn severity, defined as the completeness of aboveground vegetation removal during the burn, is useful in determining the type and location of treatment(s) that land managers can implement to speed recovery and thus in assessing effectiveness and speed of landscape recovery. This study utilizes pre- and post-fire field-based sampling as ground control for image processing of Landsat ETM+ and SPOT 5 multispectral imagery. Single and multi-date indices were validated through accuracy-assessment techniques. Remote sensing indices comparing burned with unburned areas had better overall, user's, and producer's accuracies than indices comparing levels of burn severity. The best burn versus unburned index was the Soil Adjusted Vegetation Index (SAVI; 100% overall accuracy) derived from SPOT imagery, and the best burn severity index was the relative differenced Normalized Burn Ratio (RdNBR; 73% overall accuracy) derived from Landsat imagery. These two indices provided the highest user's and producer's accuracies.
Download or read book GIScience Remote Sensing written by and published by . This book was released on 2008 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Wildland Fire Danger Estimation and Mapping written by Emilio Chuvieco and published by World Scientific. This book was released on 2003 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a wide range of techniques for extracting information from satellite remote sensing images in forest fire danger assessment. It covers the main concepts involved in fire danger rating, and analyses the inputs derived from remotely sensed data for mapping fire danger at both the local and global scale. The questions addressed concern the estimation of fuel moisture content, the description of fuel structural properties, the estimation of meteorological danger indices, the analysis of human factors associated with fire ignition, and the integration of different risk factors in a geographic information system for fire danger management.
Download or read book Remote Sensing Modeling and Applications to Wildland Fires written by John J. Qu and published by Springer. This book was released on 2014-12-12 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientists and managers alike need timely, cost-effective, and technically appropriate fire-related information to develop functional strategies for the diverse fire communities. "Remote Sensing Modeling and Applications to Wildland Fires" addresses wildland fire management needs by presenting discussions that link ecology and the physical sciences from local to regional levels, views on integrated decision support data for policy and decision makers, new technologies and techniques, and future challenges and how remote sensing might help to address them. While creating awareness of wildland fire management and rehabilitation issues, hands-on experience in applying remote sensing and simulation modeling is also shared. This book will be a useful reference work for researchers, practitioners and graduate students in the fields of fire science, remote sensing and modeling applications. Professor John J. Qu works at the Department of Geography and GeoInformation Science at George Mason University (GMU), USA. He is the Founder and Director of the Environmental Science and Technology Center (ESTC) and EastFIRE Lab at GMU.
Download or read book Remote Sensing of Large Wildfires written by Emilio Chuvieco and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a systematic review of the different applications for remote sensing and geographical information system techniques in research and management of forest fires. The authors have been involved in this field of research for several years. The book also benefits from data generated within the Megafires project, founded under the DG-XII of the European Union. A clear integration of research and experience is provided. New data gathered from fires affecting European countries between 1991 and 1997 are included as well as satellite images and auxiliary cartographic information. Geographic Information System files have been included in the attached CD-ROM depicting land cover, elevation, Koeppen classification climates and NOAA-AVHRR data of all European Mediterranean Europe at 1 sq km resolution. All these files are in Idrisi format and can be easily accessed from any GIS program. An Idrisi viewer has also been included in the CD-ROM.
Download or read book Remote Sensing of Burn Severity and the Interactions Between Burn Severity Topography and Vegetation in Interior Alaska written by Justin Frederick Epting and published by . This book was released on 2004 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A variety of single-band, band ratio, vegetation index, and multivariate algorithms were evaluated for mapping burn severity using Landsat TM and ETM+ imagery across four burns in interior Alaska. The Normalized Burn Ratio (NBR) outperformed all algorithms, both when tested as a single post-fire value and when tested as a differenced (prefire-postfire) value. The NBR was then used to map burn severity at a historical burn near Yukon-Charley Rivers National Preserve and a time-series of images from 1986 to 2002 was analyzed to investigate interactions between vegetation, burn severity, and topography. Strong interactions existed between vegetation and burn severity, but the only topographic variable that had a significant relationship with burn severity was elevation, presumably due to the strong control of elevation on vegetation type. The highest burn severity occurred in spruce forest, while the lowest occurred in broadleaf forest. Areas with high burn severity experienced disproportionately more shifts toward spruce woodland and shrub classes, while areas with low to moderate severity were less likely to change vegetation type. Finally, vegetation recovery, estimated using a remotely-sensed vegetation index, peaked between 8-14 years post-fire, and recovery was highest for areas with the highest burn severity"--Leaf iii.
Download or read book Using NDVI to Assess Departure from Average Greenness and Its Relation to Fire Business written by Robert E. Burgan and published by . This book was released on 1996 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Validating Burn Severity Classifications Using Landsat Imagery Across Western Canadian National Parks written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: National parks in western Canada experience wildland fire events at differing frequencies, intensities, and burn severities. These episodic disturbances have varying implications for various biotic and abiotic processes and patterns. To predict burn severity, the differenced Normalized Burn Ratio (dNBR) algorithm, derived from Landsat imagery, has been used extensively throughout the wildland fire community. Researchers have often employed this approach to study the effects of fire across multiple contrasting landscapes. Many remote sensing scientists have concluded that incorporating pre-fire information into the current remote sensing dNBR methodology may make such models more transferable. In the first study the main purpose was to investigate the accuracies of the absolute dNBR versus its relative form (RdNBR) to estimate burn severity, in which was hypothesized that RdNBR would outperform dNBR based on former research by Miller and Thode (2007). The secondary purpose was to examine and compare the accuracies of RdNBR and dNBR algorithms in pre-fire landscapes with low canopy closure and high heterogeneity. Results indicate that the RdNBR-derived model did not estimate burn severity more accurately than dNBR (65.2% versus 70.2% classification accuracy, respectively) nor indicate improved estimates in the more heterogeneous and low canopy cover landscapes. In addition, we concluded that RdNBR is no more effective than dNBR at the regional, individual, and fine-scale vegetation levels. The results herein support the continued use of both the dNBR and RdNBR methods and the pursuit of developing regional models. In the second study, we compare the transferability of an overall model and those stratified by land cover and ecozone. Our second objective was to test the statistical benefit of incorporating pre- and post-fire information into standard dNBR approaches. We determined that an overall dNBR derived model successfully estimated burn severity for the majority o.
Download or read book Wildland Fire Danger written by Emilio Chuvieco and published by . This book was released on 2003 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evaluating the Effects of Spatial Scale on Remotely Sensed Mapping of Burn Severity written by Kurtis Nelson and published by . This book was released on 2005 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evaluation of Wildfire Burn Severity Classification Utilising Ground and Remote Sensing Methodologies South Colorado USA written by Victoria Williams and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Remote Sensing of Postfire Environmental Damage and Recovery Dynamics written by Alfonso Fernández-Manso and published by Mdpi AG. This book was released on 2022-10-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding forest fire regimes involves characterizing spatial distribution, recurrence, intensity, seasonality, size, and severity. In recent years, knowledge of damage levels can be directly related to the environmental impact of fire and, at the same time, it is a valuable estimator of fire intensity, when the data about it are not available. Remote sensing may be seen as a tool to accurately assess burn severity and to predict the potential effects of forest fires on ecosystems, thus making the prediction of the regeneration of the plant community and the effects on ecosystems easier. This information is basic to facilitate decision-making in the post-fire management of fire-prone ecosystems. Nowadays, there has been intense research activity in relation to burned areas, burn severity, and vegetation regeneration because fires in many areas of the planet are becoming more severe and extensive, and their correct evaluation and follow-up is posing great challenges to current scientists. The current advances in remote sensing and related sciences will allow us to evaluate the damage with greater precision and to know with greater reliability the dynamics of recovery. This reprint contains studies on new remote sensing technologies, new sensors, data collections, and processing methodologies that can be successfully applied in burn severity mapping, vegetation recovery monitoring, and post-fire management of fire-prone ecosystems affected by large fires. We hope this book can help readers become more familiar with this knowledge and foster an increased interest in this field.
Download or read book Remote Sensing Procedures to Update Forested Geospatial Datasets After a Landscape Altering Event written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The creation of accurate geospatial datasets like vegetation and fire fuel loads is a time consuming effort and these datasets are routinely used by resource managers. Therefore the accuracy of these datasets is vital. Vegetation and fire fuel load datasets often represent a dynamic landscape and landscape altering events such as a wildland fire or a hurricane can drastically change that landscape. The goal of this research is to investigate the use of automated change detection techniques that can not only indicate areas of change but also quantify the magnitude of change that occurred as well. Hurricane Isabel did extensive damage to the forest landscapes of central Virginia in September of 2003, specifically Petersburg National Battlefield. The Rocky Top Fire occurred in July of 2002 in Shenandoah National Park, resulting in a mosaic pattern of burns, covering roughly 1500 acres. The objective of this research was to test the use of remote sensing procedures to update vegetation and fire fuel load spatial datasets. First, using digital orthorectified photomosaics, the automated feature extraction technique Visual Learning System's Feature Analyst, was employed to delineate forest damage following Hurricane Isabel. Second, the satellite based remote sensing technique Normalized Burn Ratio, was utilized to delineate and quantify burn severity on vegetation after the Rocky Top Fire. A third objective was to estimate fire behavior differences between the existing pre-event and the remotely sensed post-event fuel load datasets using the FARSITE model, thereby cataloging the potential need for vegetation and fuel load updates. The results of this research show that, 1) VLS Feature Analyst is an excellent indicator of downed woody debris, 2) the Normalized Burn Ratio is the best technique available for indicating and quantifying the effects of a wildland fire on the landscape, 3) changes in assigned Fuel Models, especially in the Logging Slash group, affect FARSITE outc.
Download or read book Twenty Year 1984 2004 Temporal and Spatial Burn Severity Patterns Inferred from Satellite Imagery in the Gila National Forest New Mexico written by Zachary Alan Holden and published by . This book was released on 2008 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent increasing trends in fire extent have been documented, yet little is known about how climate, vegetation and topography influence the patterns of burn severity (defined here as the magnitude of vegetation change one year post-fire relative to pre-fire conditions) of those fires. Here, I use satellite-derived burn severity data to infer 20-year patterns of burn severity relative to topography and climate. A time series of Landsat Thematic Mapper (TM) satellite images were used to map 114 fires (195,600 hectares burned) on the Gila National Forest from 1984-2004. Burn severity of each fire was inferred from the Relative Differenced Normalized Burn Ratio (RdNBR), a derivative of the differenced Normalized Burn Ratio. Data from nearby weather and Snowpack Telemetry (SNOTEL) stations were used to evaluate the influence of Snow Water Equivalent (SWE) and precipitation patterns on severe fire occurrence. Vegetation and Digital Elevation Model-derived Geographic Information System (GIS) layers were used to analyze the spatial patterns of severe fire occurrence on the 1.4 million-hectare Gila National Forest. Severe fire occurred more frequently at high elevations, in mesic spruce-fir and mixed-conifer vegetation types, on north-facing slopes and where solar radiation and heat load index values were low. Within drier Potential Vegetation Types, severe fire occurred more frequently where moisture was more available. However, this pattern shifts at higher elevations, where areas with high heat load indexes and exposed south-facing slopes increased the probability of severe fire occurrence during this twenty-year period. Random Forest predictions of severe fire occurrence using topographic variables as predictors yielded classification accuracies of 82% and 63% for two (high severity vs. other) and three (low, moderate, high severity) class burn severity grids. Spring precipitation, SWE and precipitation-free periods during the fire season (April-July) were significantly related to area burned and area burned severely, with the length of dry periods explaining most of the variation in fire extent and severity. These precipitation metrics were strongly correlated with 17-year patterns of spring and early summer vegetation green-up inferred from the Advanced Very High Resolution Radiometer (AVHRR). Spectral indices used in this study were derived from the Landsat TM sensor. However the life of this sensor may be limited and other remotely sensed data on burn severity patterns will likely be sought in the future. Using pre and post-fire images from 4 different satellite sensors with varying spatial and spectral resolutions (Quickbird, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)), Landsat TM and the Moderate Resolution Imaging Spectroradiometer (MODIS) correlations between ground-based Composite Burn Index (CBI) plots and satellite-derived indices were compared. ASTER and Quickbird-derived indices performed as well or better than the Landsat-derived dNBR.
Download or read book Remote Sensing and Modeling Applications to Wildland Fires written by John J. Qu and published by . This book was released on 2013 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Using Remotely Sensed Indices of Fire Severity and Vegetation Structure to Identify Patterns of Avian Occurrence Following Changes in Fire Management Policy Within Great Smoky Mountains National Park written by Eli Theofen Rose and published by . This book was released on 2015 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Remote Sensing and Hydrological Modeling of Burn Scars written by Mary Ellen Miller and published by . This book was released on 2007 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributions stemming from these studies include improved burn scar maps for studying historical fire extent and demonstration of the feasibility of using thermal satellite data to predict burn scar extent when clouds and smoke obscure visible bands. The incorporation of Landsat derived burn severity maps was shown to improve post-fire erosion modeling results. Finally the potential post-fire burn severity and erosion risk maps generated for western US forests will be used for planning pre-fire fuel reduction treatments.
