Download or read book Disturbances in the Siberian Boreal Forest mapping fire scars disturbances using a multi temporal multi sensor approach written by C. George 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 Understanding Forest Disturbance and Spatial Pattern written by Michael A. Wulder and published by CRC Press. This book was released on 2006-07-27 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing and GIS are increasingly used as tools for monitoring and managing forests. Remotely sensed and GIS data are now the data sources of choice for capturing, documenting, and understanding forest disturbance and landscape pattern. Sitting astride the fields of ecology, forestry, and remote sensing/GIS, Understanding Forest Disturbanc

Download or read book Mapping Forest Changes Using Multi temporal Remote Sensing Images written by Yanlei Chen and published by . This book was released on 2014 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: We developed a semi-automatic algorithm named Berkeley Indices Trajectory Extractor (BITE) to detect forest disturbances, especially slow-onset disturbances such as insect mortality, from time series of Landsat 5 Thematic Mapper (TM) images. BITE is a streamlined process that features trajectory extraction and interpretation of multiple spectral indices followed by an integration of all indices. The algorithm was tested over Grand County in Colorado, located in the Southern Rocky Mountains Ecoregion, where forests dominated by lodgepole pine have been under mountain pine beetle attack since 2000. We produced a disturbance map using BITE with an identification accuracy of 94.7% assessed from 602 validation sample pixels. The algorithm shows its robustness in deriving forest disturbance type and timing with the presence of different levels of atmospheric conditions, noises, pixel misregistration and residual cloud/snow cover in the imagery. Outputs of the BITE algorithm could be used in studies designed to increase understanding of the mechanisms of mountain pine beetle dispersal and tree mortality, as well as other types of forest disturbances. Large remote sensing datasets, that either cover large areas or have high spatial resolution, are often a burden for information mining for scientific studies. Here, we present an approach that conducts clustering after gray-level vector reduction. In this manner, the speed of clustering can be considerably improved. The approach features applying eigenspace transformation to the dataset followed by compressing the data in the eigenspace and storing them in coded matrices and vectors. The clustering process takes advantage of the reduced size of the compressed data and thus reduces computational complexity. We name this approach Clustering Based on Eigen Space Transformation (CBEST). In our experiment with a subscene of Landsat Thematic Mapper (TM) imagery, CBEST was found to be able to improve speed considerably over conventional K-means as the volume of data to be clustered increases. We assessed information loss and several other factors. In addition, we evaluated the effectiveness of CBEST in mapping land cover/use with the same image that was acquired over Guangzhou City, South China and an AVIRIS hyperspectral image over Cappocanoe County, Indiana. Using reference data we assessed the accuracies for both CBEST and conventional K-means and we found that the CBEST was not negatively affected by information loss during compression in practice. We then applied CBEST in mapping the forest change from 1986-2011 for the entire state of California, USA with over 400 Landsat TM images. We discussed potential applications of the fast clustering algorithm in dealing with large datasets in remote sensing studies. We present an efficient approach for a practice of large-area mapping of forest changes based on the Clustering Based on Eigen Space Transformation (CBEST) algorithm using remote sensing. By analyzing 450 Landsat Thematic Mapper (TM) satellite images from 1986 to 2011 with a five-year interval covering the entire state of California, USA, we derived a forest change type map, a forest loss map and a forest gain map. Although California has 99.6 million acres land area in total and the spatial resolution of Landsat TM is 30m, the computing time of the task took only 10 hours in a computer with an Intel 2.8 Ghz i5 CPU and 8 Gigabytes RAM. The overall accuracy of the forest cover in year 2011 was reported as 92.9% " 1.6%. We found that the estimated forest area changed from 28.20 " 1.98 million acres to 28.05 " 1.98 million acres from 1986-2011. In particular, our rough estimate indicates that each year California's forest experienced loss of 92 thousand acres and recovery of 85 thousand acres, resulting in seven thousand acres forest loss per year. In addition, during 1986-2011, around 12% of the forestland experienced changes, in which the change was 4% each for deforestation, afforestation and deforestation then recovered respectively. We concluded that the forestland in California had been managed in a sustainable manner over the 25 years, since no significantly directional changes were observed. Our approach made a tighter estimate of the true canopy coverage such that 29% of land in California is forestland, comparing with the statistics of 33% and 40% made by previous studies that had lower spatial resolution and shorter temporal coverage.

Download or read book Forest fire scar detection in the boreal forest with multi temporal SPOT VEGETATION data written by F F (France) Gerard 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 Fire in Ecosystems of Boreal Eurasia written by Johann Georg Goldammer and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the first priority areas among joint East/West research programs is the rational use of natural resources and sustainable development of regions. In the boreal zone of North America and Eurasia forests are economically very important and, at the same time highly vulnerable to disturbances. Because of its size and ecological functions the boreal forest zone and its most dynamic disturbance factor - fire - play an important role in ecosystem processes on global scale. Interest within the global change research community in Northern Eurasia (Fennoscandia, European Russia, Siberia, and the Far East of Russia) has grown dramatically in the last few years. It is a vast area about which very little is known. It is a region where temperature rise due to anthropogenic climate forcing is predicted to be the greatest, and where the consequent feedbacks to the atmosphere are potentially large. In addition, it is poised to undergo rapid economic development, which may lead to large and significant changes to its land cover. Much of this interest in Northern Eurasia, as in the high latitude regions in general, is centerd on its role in the global carbon cycle, which is likely to be significantly affected under global change. New research initiatives between Western and Eastern countries have been designed to address a series of phenomena, problems and management solutions.

Download or read book An Unsupervised Classification based Time Series Change Detection Approach for Mapping Forest Disturbance written by Ilia Parshakov and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Unsupervised Classification to Change (UC-Change) is a new remote sensing approach for mapping areas affected by logging and wildfires. It addresses the main limitations of existing image time-series change detection techniques, such as limited multi-sensor capabilities, use of purely spectral-based forest recovery metrics, and poor detection of salvage harvesting. UC Change detects disturbances and tracks forest recovery by analyzing changes in the spatial distribution of spectral classes over time. The algorithm detected approximately 85% and 70% of reference cutblock and fire scar pixels at a ±2-year temporal agreement, respectively, consistently outperforming existing algorithms across different biogeoclimatic zones of British Columbia, Canada. The results indicate an upper estimate of 7.5 million ha of forest cleared between 1984 and 2014, which is above estimates based on existing maps and databases (6.3 - 6.7 million ha). Also presented is a new framework for using open-access data for validation of change detection results.

Download or read book Multi temporal and Multi sensor Monitoring of Forest Disturbance written by Suming Jin and published by . This book was released on 2005 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Leveraging Multi Sensor Time Series Datasets to Map Short and Long Term Forest Disturbances and Drivers of Change in the Colombian Andes written by Paulo Jose Murillo Sandoval and published by . This book was released on 2017 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: The spatial distribution of forest disturbance is commonly calculated using a satellite imagery-driven bi- or tri-temporal change analysis. Working in Colombia’s Cordillera de los Picachos National Natural Park – a region of consistent cloud cover and dramatic topographic relief – a change assessment with such infrequent observations cannot capture long-term trends of vegetative decline (browning) or improvement (greening) nor the drivers associated with these changes. In recognition of the importance of spatio-temporally explicit information for assessing the effects of socio-environmental change and conservation strategy implementation, I developed a rigorous assessment of vegetation change using MODIS and Landsat time-series data and the Breaks For Additive Season and Trend (BFAST) algorithm to identify the timing, trends, and locations of change as well the associated drivers. First, I measured long-term vegetation trends from 2001-2015 using a Moderate Resolution Imaging Spectroradiometer (MODIS)-based 250m resolution Multi-Angle Implementation of Atmospheric Correction (MAIAC) time-series, and mapped short-term disturbances using all available Landsat images (149 dates from Landsat 5, 7, and 8). BFAST trends based on MAIAC data indicate a net greening in 6% of the park, with a net browning trend of 2.5% in the 10km-wide region surrounding the park. I also identified a 12,500 ha area within Picachos (4% of the park’s total area) that experienced a consecutive vegetative decline or browning during every year of study, a result corroborated with a BFAST Monitor assessment using finer 30m resolution Landsat data. With Landsat, I recorded 12,642 ha (±1440) of disturbed forest within the park at high spatial and temporal accuracy. Spatially, Landsat results had user’s and producer’s accuracies of 0.95±0.02 and 0.83±0.18, respectively. Temporally, a TimeSync-supported temporal validation assessment showed that 75% of Landsat-detected dates of disturbance events were accurate within ± 6 months. With disturbances identified, I characterized disturbances within Picachos’ southeastern foothills and associated drivers using a set of metrics related to the spectral, pattern and trend properties of disturbance patches derived from Landsat time-series data (1996-2015). A training dataset was initially developed to identify drivers of disturbances using Corine Land Cover maps and high-resolution imagery. A Random Forests classifier was used to attribute disturbances to specific drivers of forest cover change: conversion to pasture, conversion to subsistence agriculture, and non-stand replacing disturbance (i.e., thinning). Attribution of changes had high accuracy at patch and area levels with 1-5% commission and 2-14% omission errors, respectively, for regions that were converted to pasture or experienced thinning. Lower agreement was found for agricultural conversion with 43% omission and 9% commission errors. I found that conversion to pasture is the main cause of forest cover loss within Picachos at 9901 ha (±72) corresponding to 14.7% of Picachos’ foothills, and that subtle forest alteration contributed to 1327 ha (±92) of forest degradation. Recognizing the diversity of pressures facing conservation strategy implementation in the region, these results have direct relevance for anticipating future land use pressures within Colombia, as well as across similar regions in the Andes-Amazon transition area. Indeed, since these results reveal the possibility to uncover historical disturbances related to human-incursion in protected landscapes, the methods are well suited to enhancing landscape planning particularly where biodiversity richness is quickly diminishing due to anthropogenic presence.

Download or read book Fire Regimes Spatial and Temporal Variability and Their Effects on Forests written by Yves Bergeron and published by MDPI. This book was released on 2018-04-13 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Fire Regimes: Spatial and Temporal Variability and Their Effects on Forests" that was published in Forests

Download or read book Advancing Wildfire Fuel Mapping and Burn Severity Assessment in Alaskan Boreal Forest Using Multi sensor Remote Sensing written by Christopher William Smith and published by . This book was released on 2021 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wildfires in Alaska have been increasing in frequency, size, and intensity putting a strain on communities across the state, especially remote communities lacking firefighting infrastructure to address large scale fire events. Advances in remote sensing techniques and data provide an opportunity to generate high quality map products that can better inform fire managers to allocate resources to areas of most risk and inform scientists how to predict and understand fire behavior. The overarching goal of this thesis is therefore to build insight into methods that can be applied to create highly detailed fire statistic map products in Alaska. To address this overarching goal we tested several methods for generating fire fuel, burn severity, and wildfire hazard maps that were validated using data collected in the field. Applying the Random Forest classifier on Airborne Visible/ Infrared Imaging Spectrometer Next-Generation (AVIRIS-NG) hyperspectral data we were able to produce a fire fuel map with an 81% accuracy. We then tested two supervised machine learning classifiers, post fire standard spectral indices, and differenced spectral indices for their performance in assessing burn severity. We found that supervised machine learning classifiers outperform other algorithms when there is an adequate amount of training data. Using the support vector machine and random forest classifiers we were able to generate burn severity maps with 83% accuracy at the 2019 Shovel Creek Fire. Lastly, we looked for a relationship between burn severity and environmental conditions prevalent during the Shovel Creek and Nugget Creek fires. Overall, these products can be used by fire managers and scientists to assess fire risk, limit the damages caused by wildfires through adequate resource allocation, and provide the guidelines for creating future high quality fire fuel maps.

Download or read book Wildland Fire Danger Estimation And Mapping The Role Of Remote Sensing Data written by Emilio Chuvieco and published by World Scientific. This book was released on 2003-09-29 with total page 280 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 Monitoring and Ecological Modeling of Insect Outbreak Dynamics in the Southern Rocky Mountains Ecoregion written by Lu Liang and published by . This book was released on 2015 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mountain pine beetle (Dendroctonus ponderosae; MPB) population has existed at endemic levels in the pine forests of western North America for centuries, but in recent decades it grew to epidemic levels and outbroke over extensive areas from British Columba in Canada to New Mexico in the United States. The current MPB outbreaks have impacted large expanses of lodgepole and ponderosa pine forests, reduced their ability to act as carbon sinks, altered wildfire hazards, affected wildlife populations, changed regional climate, modified local surface energy balance and water quality. Those effects are predicted to increase as a consequence of the direct and indirect effects of climate changes. Despite severe impacts of MPB, substantial unknowns and uncertainties still exist about its historical and current spatial-temporal patterns, future potential distributions, disturbance regime characteristics, ways of interaction with other major disturbance events, and impacts on forest resilience mechanisms. In this dissertation, I first explored the potential of medium resolution satellite imagery in mapping the chronic insect disturbance in the Southern Rocky Mountains Ecoregion. A forest-growth trend analysis method that integrates temporal trajectories in Landsat images and decision tree techniques was introduced to derive annual forest disturbance maps over a period of one decade. This workflow is able to capture the disturbance events as represented by spectral-temporal segments after the removal of observational noises from temporal trajectories in Landsat images, and efficiently recognizes and attributes events based on the characteristics of the segments. Higher overall accuracy (OA) was achieved when compared with the traditional single-date classifications, and a smaller number of training sample units is required compared with maximum likelihood and random forest classifiers. To test the feasibility of the trajectory-based approach at broader scales, I advanced this method by replacing the decision tree based semi-automatic event labeling procedure with an automatic attribution step via random forest, which was run on a set of segment features containing information on spatial-temporal neighborhoods. Meanwhile, I developed a new sampling strategy that intensively selects sample units in overlapping areas among images acquired from adjacent rows, and automatically adds spectrally dissimilarity sample units from non-overlapping areas, to improve the efficiency of representative sample selection at the ecoregion scale. The mean OA for all scenes was 82%. The satellite derived multi-temporal landscape quantification results revealed that MPB accounted for 70% of the total area of disturbance. I found that whether fire and MPB are linked disturbances depended on their occurring sequences. Fire severity was largely unrelated to pre-fire MPB outbreak severity, whereas post-fire beetle severity was shown to decrease with fire severity. The recovery rate varied among different disturbance types. Half of the clearcut and fire areas were at various stages of recovery, but the regeneration rate was much slower at MPB disturbed sites. Beetle outbreaks and fire created a positive compound effect on the seedling reestablishment, which suggests that beetle-killed serotinous lodgepole pines might have a new forest resilience mechanism to subsequent wildfire. Following the depiction of the disturbance pattern in landscapes, I further assessed the effects of a variety of biotic and abiotic factors on the outbreak dynamics in Grand County, Colorado. Thirty-four variables were included to develop a number of general linear models (GLM). Case and control samples were extracted from maps derived from satellite image. I first removed non-significant predictors based on the Bayesian Information Criterion in a multiple backward stepwise selection, and then built the model using the retained variables. A correction factor was added into the traditional GLM to account for model bias introduced by different ratios of case and control observations in the sample and in the population. Finally, I evaluated the model performance with an independent validation dataset, and generated predictive maps of MPB mortality. The final model had an average area under the curve value of 0.72 in predicting the annual area of new mortality. The results showed that neighborhood mortality, winter mean temperature anomaly, and residential housing density were positively associated with MPB mortality, whereas summer precipitation was negatively related. The extent of MPB mortality will expand under both RCP 4.5 and 8.5 climate-change scenarios, which implies that the impacts of MPB outbreaks on vegetation composition and structure, and ecosystem functioning are likely to increase in the future. Disturbance is the main driver for the heterogeneous landscape mosaic, and the understanding about its pattern, regime characteristics, impacts on forest resilience system and future trend is of great importance to many fields of research, such as carbon cycling, biological conservation, and environmental protection. The overall working approach in this dissertation provides feasible algorithms that can be applied to other regions, and can aid in generating consistent and high temporal frequency data on insect mortality and other disturbances impacting a variety of ecosystem services.

Download or read book Fire Effects on Soil Properties written by Paulo Pereira and published by CSIRO PUBLISHING. This book was released on 2019-02-01 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wildland fires are occurring more frequently and affecting more of Earth's surface than ever before. These fires affect the properties of soils and the processes by which they form, but the nature of these impacts has not been well understood. Given that healthy soil is necessary to sustain biodiversity, ecosystems and agriculture, the impact of fire on soil is a vital field of research. Fire Effects on Soil Properties brings together current research on the effects of fire on the physical, biological and chemical properties of soil. Written by over 60 international experts in the field, it includes examples from fire-prone areas across the world, dealing with ash, meso and macrofauna, smouldering fires, recurrent fires and management of fire-affected soils. It also describes current best practice methodologies for research and monitoring of fire effects and new methodologies for future research. This is the first time information on this topic has been presented in a single volume and the book will be an important reference for students, practitioners, managers and academics interested in the effects of fire on ecosystems, including soil scientists, geologists, forestry researchers and environmentalists.

Download or read book Detecting and mapping forest disturbances in the boreal forests of Canada and Siberia written by F F (France) Gerard and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Characterizing the Spatial Patterns and Spatially Explicit Probabilities of Post Fire Vegetation Residual Patches in Boreal Wildfire Scars written by Yikalo Hayelom Araya and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Permafrost Ecosystems written by Akira Osawa and published by Springer Science & Business Media. This book was released on 2010-01-04 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing from a decade-long collaboration between Japan and Russia, this important volume presents the first major synthesis of current knowledge on the ecophysiology of the coniferous forests growing on permafrost at high latitudes. It presents ecological data for a region long inaccessible to most scientists, and raises important questions about the global carbon balance as these systems are affected by the changing climate. Making up around 20% of the entire boreal forests of the northern hemisphere, these ‘permafrost forest ecosystems’ are subject to particular constraints in terms of temperature, nutrient availability, and root space, creating exceptional ecosystem characteristics not known elsewhere. This authoritative text explores their diversity, structure, dynamics and physiology. It provides a comparison of these forests in relation to boreal forests elsewhere, and concludes with an assessment of the potential responses of this unique biome to climate change. The book will be invaluable to advanced students and researchers interested in boreal vegetation, forest ecology, silviculture and forest soils, as well as to researchers into climate change and the global carbon balance.

Download or read book First Order Fire Effects Model written by Elizabeth D. Reinhardt and published by . This book was released on 1997 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.