Stijn Hantson

Evaluation of different topographic correction methods for Landsat imagery

Abstract The recent free availability of Landsat historical data provides new potentials for land-cover change studies. Multi-temporal studies require a previous radiometric and geometric homogenization of input images, to better identify true changes. Topographic normalization is one of the key steps to create consistent and radiometricly stable multi-temporal time series, since terrain shadows change throughout time. This paper aims to evaluate different methods for topographic correction of Landsat TM-ETM+ data. They were assessed for 15 ETM+ images taken under different illumination conditions, using two criteria: (a) reduction of the standard deviation (SD) for different land-covers and (b) increase in temporal stability of a time series for individual pixels. We observed that results improve when land-cover classes where processed independently when applying the more advanced correction algorithms such as the C-correction and the Minnaert correction. Best results were obtaining for the C-correction and the empiric–statistic correction. Decreases of the SD for bare soil pixels were larger than 100% for the C-correction and the empiric–statistic correction method compared to the other correction methods in the visible spectrum and larger than 50% in the IR region. In almost all tests the empiric–statistic method provided better results than the C-correction. When analyzing the multi-temporal stability, pixels under bad illumination conditions (northern orientation) improved after correction, while a deterioration was observed for pixels under good illumination conditions (southern orientation). Taken this observation into account, a simple but robust method for topographic correction of Landsat imagery is proposed.

Integrating geospatial information into fire risk assessment

Fire risk assessment should take into account the most relevant components associated to fire occurrence. To estimate when and where the fire will produce undesired effects, we need to model both (a) fire ignition and propagation potential and (b) fire vulnerability. Following these ideas, a comprehensive fire risk assessment system is proposed in this paper,whichmakesextensiveuseofgeographicinformationtechnologiestoofferaspatiallyexplicitevaluationoffirerisk conditions. The paper first describes the conceptual model, then the methods to generate the different input variables, the approachestomergethosevariablesintosyntheticriskindicesandfinallythevalidationoftheoutputs.Themodelhasbeen applied at a national level for the whole Spanish Iberian territory at 1-km 2 spatial resolution. Fire danger included human factors, lightning probability, fuel moisture content of both dead and live fuels and propagation potential. Fire vulnerability was assessed by analysing values-at-risk and landscape resilience. Each input variable included a particular accuracy assessment, whereas the synthetic indices were validated using the most recent fire statistics available. Significant relations (P,0.001) with fire occurrence were found for the main synthetic danger indices, particularly for those associated to fuel moisture content conditions.

A human-driven decline in global burned area

Burn less, baby, burn less Humans have, and always have had, a major impact on wildfire activity, which is expected to increase in our warming world. Andela et al. use satellite data to show that, unexpectedly, global burned area declined by ∼25% over the past 18 years, despite the influence of climate. The decrease has been largest in savannas and grasslands because of agricultural expansion and intensification. The decline of burned area has consequences for predictions of future changes to the atmosphere, vegetation, and the terrestrial carbon sink. Science, this issue p. 1356 Global burned area has declined by ~25% over the past 18 years. Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.

Anthropogenic effects on global mean fire size

Wildland fires are an important agent in the earth’s system. Multiple efforts are currently in progress to better represent wildland fires in earth system models. Although wildland fires are a natural disturbance factor, humans have an important effect on fire occurrence by directly igniting and suppressing fires and indirectly influencing fire behaviour by changing land cover and landscape structure. Although these factors are recognised, their quantitative effect on fire growth and burned area are not well understood and therefore only partly taken into account in current process-based fire models. Here we analyse the influence of humans on mean fire size globally. The mean fire size was extracted from the global Moderate Resolution Imaging Spectroradiometer (MODIS) burned area product MCD45. We found a linear decreasing trend between population density and observed mean fire size over the globe, as well as a negative effect of cropland cover and net income. We implemented the effect of population density on fire growth in a global vegetation model including a process-based fire model (SPITFIRE–JSBACH). When including this demographic control, spatial trends in modelled fraction of burned area generally improved when compared with satellite-derived burned area data. More process-based solutions to limit fire spread are needed in the future, but the empirical relations described here serve as an intermediate step to improve current fire models.

Why trees and shrubs but rarely trubs

An analysis of the maximum height of woody plant species across the globe reveals that an intermediate size is remarkably rare. We speculate that this may be due to intrinsic suboptimality or to ecosystem bistability with open landscapes favouring shrubs, and closed canopies propelling trees to excessive tallness.

Influence of wind speed on the global variability of burned fraction: A global fire model's perspective

Understanding of fire behaviour, especially fire spread, is mostly based on local-scale observations but the same equations are applied in global models on a much coarser scale. Most model formulations include the effect of wind speed with a positive influence on fire spread. Availability of global datasets offers new possibilities to evaluate these approaches based on local-scale observations at the global scale. Here, we analyse the relation between wind speed derived from three datasets and remotely sensed burned fraction (burned area divided by grid cell area) on a climate model grid scale. The bivariate relationship between burned fraction and wind speed is characterised by an initial increase in burned fraction and a decrease in burned fraction for wind speeds higher than 2–3 ms–1. In a multivariate analysis we additionally included the effect of tree cover, precipitation or atmospheric moisture, temperature, vegetation net primary productivity and population density on burned fraction. This analysis confirmed the lack of an increase in burned fraction for high wind speeds on annual and daily time scale. From the observation-based analysis we conclude that a positive response of burned fraction for high wind speed should not be applied in coarse-scale global fire models.

Long-term Wood Production in Water-Limited Forests: Evaluating Potential CO2 Fertilization Along with Historical Confounding Factors

Increased aridity may have severe effects on productivity of dry forests. However, it remains unclear to what degree the positive effects of elevated CO2 (both increased carboxylation rates and enhanced water-use efficiency) may offset the negative effects of drought and climate warming. In forest ecosystems, it is particularly challenging to evaluate CO2 effects on productivity because the impacts of climate variability, competition, and management, combine to have longlasting effects on stand-level productivity. Here we address this problem using a unique long-term database containing repeated inventories of wood biomass for every decade from 1912 to 2002 in a pine forest (Pinus pinaster Ait.) in central Spain (≈7,500 ha.). The approach is based upon a combination of statistical analyses of long-term historical management data and mechanistic modeling which allows us to evaluate the effects of potential CO2 fertilization, climate, and stand structure on woody net primary production (W-NPP). We found a significant negative effect of drought on W-NPP during the first half of the twentieth century that diminishes at the turn of the century. Simulations with a process-based ecosystem model, ORCHIDEE, suggest that wood production under conditions that included CO2 fertilization produced a more highly correlated long-term W-NPP than simulations keeping CO2 values in preindustrial levels. Interestingly, however, the CO2 effect was only apparent when accounting for confounding factors such as competition and management legacies. Identifying CO2 fertilization on forest growth is a critical issue, and requires partitioning CO2 effects from confounding factors that have jointly shaped stand dynamics and carbon balance during the twentieth century.

Fire in the Earth System: Bridging Data and Modeling Research

This is a preliminary PDF of the author-produced manuscript that has been peer-reviewed and accepted for publication. Since it is being posted so soon after acceptance, it has not yet been copyedited, formatted, or processed by AMS Publications. This preliminary version of the manuscript may be downloaded, distributed, and cited, but please be aware that there will be visual differences and possibly some content differences between this version and the final published version.

Global fire size distribution: from power law to log-normal

Wildland fires are one of the main alleged examples of Self-Organised Criticality (SOC), with simple SOC models resulting in the expectation of a power-law fire size frequency distribution. Here, we test whether fire size distributions systematically follow a power law and analyse their spatial variation for eight distinct areas over the globe. For each of the areas, we examine the fire size frequency distribution using two types of plots, maximum likelihood estimation and chi-square tests. Log-normal emerges as a suitable option to fit the fire size distribution in this variety of environments. In only two of eight areas was the power law (which is a particular case of the log-normal) not rejected. Notably, the two parameters of log-normal are related to each other, displaying a general linear relation, which extends to the sites that can be described with a power law. These results do not necessarily refute the SOC hypothesis, but reveal the presence of other processes that are, at least, modulating the outcome of SOC in some areas.

Temperate forest and open landscapes are distinct alternative states as reflected in canopy height and tree cover

The suggestion that woody plants of intermediate height between trees and shrubs (‘trubs’) are conspicuously rare [1] invoked much interest. Two comments showed regional species lists that did not have this paucity of medium-sized woody plants 2 and 3. In response, we hypothesized that the bimodality of height in the global database [4] might reflect a field bimodality of dominant growth forms that can be less apparent if one looks merely at species lists, which typically feature a significant proportion of rare species that contribute little to the vegetation structure. Here, we use high-precision laser altimetry data to show that, across continents, temperate vegetation does indeed have two dominant modes in maximum canopy height. We also respond to a follow-up comment [5] and show that the detected canopy height bimodality corresponds closely to a bimodality in tree cover, suggesting that, much as in the tropics, forest and open landscapes are distinct stable states in temperate climate zones. We analyzed the frequency distribution of two continuous variables, tree cover and maximum canopy height (90th percentile), in 0.5 × 0.5 degree grid cells (Figure 1A) across temperate regions globally. While tree cover estimates are based on a rather intricate algorithm [6], canopy height estimates can now be obtained in a relatively straightforward way using data from high-precision laser altimetry instrument in satellites [7]. Our results reveal that the distribution of canopy height has marked modes around 6 m and 20 m. Combining the canopy height information with remotely sensed tree cover (Figure 1B) reveals that the 20-m mode is dominated by closed forest, whereas the 6-m mode mostly has very low woody cover. Although transition zones between forest and open landscapes exist, and all feasible canopy heights are observed in the field, there is a clear tendency to find either forest or open landscape in any given 0.5 × 0.5 degree grid cell, with corresponding canopy heights of around 20 and 6 m, respectively.