Review of the use of remote sensing for monitoring wildfire risk conditions to support fire risk assessment in protected areas

Fire risk assessment is one of the most important components in the management of fire that offers the framework for monitoring fire risk conditions. Whilst monitoring fire risk conditions commonly revolved around field data, Remote Sensing (RS) plays key role in quantifying and monitoring fire risk indicators. This study presents a review of remote sensing data and techniques for fire risk monitoring and assessment with a particular emphasis on its implications for wildfire risk mapping in protected areas. Firstly, we concentrate on RS derived variables employed to monitor fire risk conditions for fire risk assessment. Thereafter, an evaluation of the prominent RS platforms such as Broadband, Hyperspectral and Active sensors that have been utilized for wildfire risk assessment. Furthermore, we demonstrate the effectiveness in obtaining information that has operational use or immediate potentials for operational application in protected areas (PAs). RS techniques that involve extraction of landscape information from imagery were summarised. The review concludes that in practice, fire risk assessment that consider all variables/indicators that influence fire risk is impossible to establish, however it is imperative to incorporate indicators or variables of very high heterogeneous and “multi-sensoral or multivariate fire risk index approach for fire risk assessment in PA.Keywords: Protected Areas, Fire Risk conditions; Remote Sensing, Wildfire risk assessmen

Forest Fire Risk Prediction

Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system.This was the motivation to publish this book, which is focused on quantifying and modelling the risk factors of forest fires. More specifically, the chapters in this book address four topics: (i) the use of fire danger metrics and other approaches to understand variation in wildfire activity; (ii) understanding changes in the flammability of live fuel; (iii) modeling dead fuel moisture content; and (iv) estimations of emission factors.The book will be of broad relevance to scientists and managers working with fire in different forest ecosystems globally

Estimation of herbaceous fuel moisture content using vegetation indices and land surface temperature from MODIS data

The monitoring of herbaceous fuel moisture content is a crucial activity in order to assess savanna fire risks. Faced with the difficulty of managing wide areas of vegetated surfaces, remote sensing appears an attractive alternative for terrestrial measurements because of its advantages related to temporal resolution and spatial coverage. Earth observation (EO)-based vegetation indices (VIs) and the ratio between Normalized Difference Vegetation Index (NDVI) and surface temperature (ST) were used for assessment of herbaceous fuel moisture content estimates and validated against herbaceous data collected in 2010 at three open savanna sites located in Senegal, West Africa. EO-based estimates of water content were more consistent with the use of VI as compared to the ratio NDVI/ST. Different VIs based on near-infrared (NIR) and shortwave infrared (SWIR) reflectance were tested and a consistent relationship was found between field measurements of leaf equivalent water thickness (EWT) from all test sites and Normalized Difference Infrared Index (NDII), Global Vegetation Moisture Index (GVMI) and Moisture Stress Index (MSI). Also, strong relationships were found between fuel moisture content (FMC) and VIs for the sites separately; however, they were weaker for the pooled data. The correlations between EWT/FMC and VIs were found to decrease progressively as the woody cover increased. Although these results suggest that NIR and SWIR reflectance can be used for the estimation of herbaceous water content, additional validation from an increased number of study sites is necessary to study the robustness of such indices for a larger variety of savanna vegetation types

Complex Vegetation Dynamics at the Fire-Grazing-Drought Nexus

The discipline of ecology long ago moved away from viewing systems as static entities where disturbance processes, environmental stochasticity, and spatiotemporal variability play minor roles in determining ecosystem structure and function. Ecological theory continue to develop frameworks and statistical techniques capable of describing the inherent complexity in natural systems. However, in dealing with the complexity in nature, many applied disciplines have yet to adopt such frameworks or statistical techniques. The objective of this study was bridge the gap between ecological theory and application by using complex systems theory to describe grassland vegetation dynamics at the fire-grazing-drought nexus. Chapters 2 and 3 take advantage of one of the most severe growing season droughts on modern record in the southern Great Plains and a long-term pyric herbivory experiment to investigate spatiotemporal patterns in vegetation at the fire-grazer interface. Through the application of metacommunity theory, Chapter 2 reveals scale switching in complex feedbacks between grassland productivity, fire behavior, forage quality, and grazer selection before and during extreme drought. Through the application of information-theoretic model comparison, Chapter 3 provides a method for applied fire modeling systems to quantitatively assess the impact of favoring central tendency in the characterization of grassland fuel properties that are the basis for predicting wildfire risk and behavior. Chapter 4 identifies thresholds in the flammability of J. virginiana (Eastern redcedar), a commonly planted horticultural tree rapidly invading across the Great Plains, across a gradient of fuel moisture contents to improve wildland fire risk assessments and monitoring programs. The results of these case studies will become even more important during the next century, when climate models forecast an increase in frequency and severity of growing season droughts across much of the Great Plains. Advisor: Dirac Twidwel

Complex Vegetation Dynamics at the Fire-Grazing-Drought Nexus

The discipline of ecology long ago moved away from viewing systems as static entities where disturbance processes, environmental stochasticity, and spatiotemporal variability play minor roles in determining ecosystem structure and function. Ecological theory continue to develop frameworks and statistical techniques capable of describing the inherent complexity in natural systems. However, in dealing with the complexity in nature, many applied disciplines have yet to adopt such frameworks or statistical techniques. The objective of this study was bridge the gap between ecological theory and application by using complex systems theory to describe grassland vegetation dynamics at the fire-grazing-drought nexus. Chapters 2 and 3 take advantage of one of the most severe growing season droughts on modern record in the southern Great Plains and a long-term pyric herbivory experiment to investigate spatiotemporal patterns in vegetation at the fire-grazer interface. Through the application of metacommunity theory, Chapter 2 reveals scale switching in complex feedbacks between grassland productivity, fire behavior, forage quality, and grazer selection before and during extreme drought. Through the application of information-theoretic model comparison, Chapter 3 provides a method for applied fire modeling systems to quantitatively assess the impact of favoring central tendency in the characterization of grassland fuel properties that are the basis for predicting wildfire risk and behavior. Chapter 4 identifies thresholds in the flammability of J. virginiana (Eastern redcedar), a commonly planted horticultural tree rapidly invading across the Great Plains, across a gradient of fuel moisture contents to improve wildland fire risk assessments and monitoring programs. The results of these case studies will become even more important during the next century, when climate models forecast an increase in frequency and severity of growing season droughts across much of the Great Plains. Advisor: Dirac Twidwel

Agroforestry Opportunities for Enhancing Resilience to Climate Change in Rainfed Areas,

Not AvailableAgroforestry provides a unique opportunity to achieve the objectives of enhancing the productivity and improving the soil quality. Tree systems can also play an important role towards adapting to the climate variability and important carbon sinks which helps to decrease the pressure on natural forests. Realizing the importance of the agroforestry in meeting the twin objectives of mitigation and adaptation to climate change as well as making rainfed agriculture more climate resilient, the ICAR-CRIDA has taken up the challenge in pursuance of National Agroforestry Policy 2014, in preparing a book on Agroforestry Opportunities for Enhancing Resilience to Climate Change in Rainfed Areas at ICAR-CRIDA to sharpen the skills of all stakeholders at national, state and district level in rainfed areas to increase agricultural productivity in response to climate changeNot Availabl

Effects of Ponderosa Pine Ecological Restoration on Forest Soils and Understory Vegetation in Northern Arizona

The human exclusion of wildfire and overgrazing by livestock since settlement have caused dramatic changes in ponderosa pine (Pinus ponderosa Dougl ex Laws) forest ecosystems. These changes include increased numbers of tree stems, reduced understory cover and diversity, and the introduction of invasive, non-native understory species. This study evaluated the coverage and species composition of understory vegetation present in the “cool-season” (late spring and early summer) in a ponderosa pine forest on grazed and ungrazed plots that had undergone restoration treatments on three different soil/geologic parent material types near Flagstaff, Arizona, twelve years after tree thinning and grazing exclosure treatments were applied. Several measured soil properties, such as soil respiration and temperature, were also evaluated in this study. Species richness of “cool-season” vegetation was influenced more by grazing practices than restoration treatments. Differences could be less or greater when vegetation that is active later in the season is measured. Vegetative cover was significantly influenced by restoration treatments (9.3% cover under open canopies and 6.5% under dense canopies), probably due to differences in competition for light and other resources (i.e. soil moisture and nutrients). Unlike finding by Abella et al. (2015), who studied “warm-season” vegetation, “cool-season” understory cover was not influenced by soil parent material type in this study, which might suggest that differences in understory cover due to soil properties are only seen shortly after restoration treatments are applied, or the time of year vegetation is evaluated may play a role in the differences seen. Soil respiration was highest on limestone soil parent material type (3.3 g C-CO2 m-2 day-1), and soil temperature was lowest under closed canopy treatments (15°C)

Fire in Australian savannas: From leaf to landscape

© 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. Savanna ecosystems comprise 22% of the global terrestrial surface and 25% of Australia (almost 1.9 million km2) and provide significant ecosystem services through carbon and water cycles and the maintenance of biodiversity. The current structure, composition and distribution of Australian savannas have coevolved with fire, yet remain driven by the dynamic constraints of their bioclimatic niche. Fire in Australian savannas influences both the biophysical and biogeochemical processes at multiple scales from leaf to landscape. Here, we present the latest emission estimates from Australian savanna biomass burning and their contribution to global greenhouse gas budgets. We then review our understanding of the impacts of fire on ecosystem function and local surface water and heat balances, which in turn influence regional climate. We show how savanna fires are coupled to the global climate through the carbon cycle and fire regimes. We present new research that climate change is likely to alter the structure and function of savannas through shifts in moisture availability and increases in atmospheric carbon dioxide, in turn altering fire regimes with further feedbacks to climate. We explore opportunities to reduce net greenhouse gas emissions from savanna ecosystems through changes in savanna fire management

Doctor of Philosophy

dissertationWildfire is a multifaceted, global phenomenon with ecological, environmental, climatic and socioeconomic impacts. Live fuel moisture content (LFMC) is a critical fuel property for determining fire danger. Previous research has used meteorological data and remote sensing to estimate LFMC with the goal of extending direct ground measurement. A fundemental understanding of plant physiology and spectral response toLFMC variation is needed to advance use of LFMC for fire risk management and remote sensing applications. This study integrates field samples of three species, lab measurements, remote sensing dataand statistical analysis to construct a more complete knowledge of the physical foundations of LFMC seasonalityfrom three perspectives: 1)relationships between soil moisture and LFMC; 2) spectroscopic analysis of seasonal changes in LFMC and leaf dry mass; 3) relationships between LFMC and leaf net heat content, and between leaf net heat content and remotely sensed indices. This study is the first to demonstrate a relationship between in situ soil moisture and LFMC. It also challengesthe current asumption of changing water content and stable dry matter content over time in remote sensing esimation of LFMC, showing the dominant contribution of dry matter in LFMC variation in some conifer species. The resultsdemonstrate the combination of spectroscopic data and partial least squares regression can improve modeling accuray for LFMC temporal variation, but the spectral response to changing LFMC and dry mass is difficult to seperate from broader spectral trends due to temporal change in chlorophyll, leaf structure, water and covaried biochemical components. Lastly it introducesa new vegetation variable, leaf net heat content, and demostrates its relationship with LFMC and potential for remote sensing estimation.This study will improve present capabilities of remote sensing for monitoring vegetation water stress and physiological properties. It will also advance understanding of seasonal changes in LFMC to better estimate fire danger and potential impacts of fire on ecosystems and the carbon cycle

ESA - RESGROW: Epansion of the Market for EO Based Information Services in Renewable Energy - Biomass Energy sector

Biomass energy is of growing importance as it is widely recognised, both scientifically and politically, that the increase of atmospheric CO2 has led to an enhanced efficiency of the greenhouse effect and, as such, warrants concern for climate change. It is accepted (IPCC 2011 and just recently in the draft version of the IPCC 2013 report) that climate change is partly induced by humans notably by using fossil fuels. For reducing the use of oil or coal, biomass energy is receiving more and more attention as an additional energy source available regionally in large parts of the world. Effective management of renewable energy resources is critical for the European and the global energy supply system. The future contribution of bioenergy to the energy supply strongly depends on its availability, in other words the biomass potential. Biomass potentials are currently mainly assessed on a national to regional or on a global level, with the bulk biomass potential allocated to the whole country. With certain biomass fractions being of low energy density, transport distances and thus their spatial distribution are crucial economic and ecological factors. For other biomass fractions a super-regional or global market is envisaged. Thus spatial information on biomass potentials is vital for the further expansion of bioenergy use. This study, which is an updated version of a study carried out in 2007 in frame of the ENVISOLAR project, analyses the potential use of Earth Observation data as input for biomass models in order to assessment and manage of the biomass energy resources especially biomass potentials of agricultural and forest areas with high spatial resolution (typical 1km x 1km). In addition to a sorrow review of recent developments in data availability and approaches in comparison to its 2007’ version, this study also includes a review on approaches to directly correlate remote sensing data with biomass estimations. An overview of existing biomass models is given covering models using remote sensing data as input as well as models using only meteorological and/or management data as input. It covers the full life cycle from the planning stage to plant management and operations (Figure 1). Several groups of stakeholders were identified