ALBERT

Beschreibung: This article presents a new method for burned area mapping using high-resolution satellite images in the Mediterranean ecosystem. In such a complex environment, high-resolution satellite images represent an appropriate data source for identifying fire-affected areas, and single postfire data are often the only available source of information. The method proposed here integrates several spectral indices into a fuzzy synthetic indicator of likelihood of burn. The indices are interpreted through fuzzy membership functions that have been derived with a partially data-driven approach exploiting training data and expert knowledge. The final map of fire-affected areas is produced by applying a region growing algorithm on the basis of seed pixels selected on a conservative threshold of the synthetic fuzzy score. The algorithm has been developed and tested on a set of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes acquired over Southern Italy. Validation showed that the accuracy of the burned area maps is comparable or even better [overall accuracy (OA) 〉 90%, K 〉 0.76] than that obtained with approaches based on single index thresholds adapted to each image. The method described here provides an automatic approach for mapping fire-affected areas with very few false alarms (low commission error), whereas omission errors are mainly related to undetected small burned areas and are located in heterogeneous sparse vegetation cover.

Beschreibung: Earth ecosystems are not static, and they respond to environmental changes, particularly climatic and anthropogenic. Precipitation varying in its extremeness, with shifts to greater or lesser intensity of individual storms and/or to change in the length and frequency of wet and dry periods, can adversely affect both urban and rural ecosystems. Here, the authors review long-term precipitation records of the central Mediterranean area and employ a Web geographical information system (GIS)-based analytical approach to compare current rainfall impact with historical data on different spatial and temporal scales. Autumn (September–November) was recognized as the most hazardous season that marks the evidence of a changing climate, with a shift toward more intense rainfalls in recent times. In the first decade of the third millennium, areas of peninsular and insular Italy have been especially affected by extreme rains. A focus was put on the island of Sicily, where extraordinary rain events occurred in September 2009, discussed in the context of upcoming trends and climate histories. An improved knowledge and understanding of the scale at which changes on extremes occur is essential for dealing with the forthcoming challenges regarding soil and water conservation practices. The characteristics of changes in natural rainfall, its role on terrestrial ecosystems, and its effect on surface water erosion dynamics are discussed. It is argued that understanding these issues are major priorities for future research to promote a better understanding of the Earth interaction with water resources and related hydrological issues.

Beschreibung: In the early 1900s, tree-ring scientists began analyzing the relative widths of annual growth rings preserved in the cross sections of trees to infer past climate variations. Now, many ring-width index (RWI) chronologies, each representing a specific site and species, are archived online within the International Tree-Ring Data Bank (ITRDB). Comparing annual tree-ring-width data from 1097 sites in the continental United States to climate data, the authors quantitatively evaluated how trees at each site have historically responded to interannual climate variations. For each site, they developed a climate-driven statistical growth equation that uses regional climate variables to model RWI values. The authors applied these growth models to predict how tree growth will respond to twenty-first-century climate change, considering four climate projections. Although caution should be taken when extrapolating past relationships with climate into the future, the authors observed several clear and interesting patterns in the growth projections that seem likely if warming continues. Most notably, the models project that productivity of dominant tree species in the southwestern United States will decrease substantially during this century, especially in warmer and drier areas. In the northwest, nonlinear growth relationships with temperature may lead to warming-induced declines in growth for many trees that historically responded positively to warmer temperatures. This work takes advantage of the unmatched temporal length and spatial breath of annual growth data available within the ITRDB and exemplifies the potential of this ever-growing archive of tree-ring data to serve in meta-analyses of large-scale forest ecology.

Beschreibung: The authors simulated the effects of Amazonian mesoscale deforestation in the boundary layer and in rainfall with the Brazilian Regional Atmospheric Modeling System (BRAMS) model. They found that both the area and shape (with respect to wind incidence) of deforestation and the soil moisture status contributed to the state of the atmosphere during the time scale of several weeks, with distinguishable patterns of temperature, humidity, and rainfall. Deforestation resulted in the development of a three-dimensional thermal cell, the so-called deforestation breeze, slightly shifted downwind to large-scale circulation. The boundary layer was warmer and drier above 1000-m height and was slightly wetter up to 2000-m height. Soil wetness affected the circulation energetics proportionally to the soil dryness (for soil wetness below ∼0.6). The shape of the deforestation controlled the impact on rainfall. The horizontal strips lined up with the prevailing wind showed a dominant increase in rainfall, significant up to about 60 000 km2. On the other hand, in the patches aligned in the opposite direction (north–south), there was both increase and decrease in precipitation in two distinct regions, as a result of clearly separated upward and downward branches, which caused the precipitation to increase for patches up to 15 000 km2. The authors’ estimates for the size of deforestation impacting the rainfall contributed to fill up the low spatial resolution in other previous studies.

Beschreibung: Predicting the location and timing of mudslides with adequate lead time is a scientifically challenging problem that is critical for mitigating landslide impacts. Here, a new dynamic modeling system is described for monitoring and predicting storm-triggered landslides and their ecosystem implications. The model ingests both conventional and remotely sensed topographic and geologic data, whereas outputs include diagnostics required for the assessment of the physical and societal impacts of landslides. The system first was evaluated successfully in a series of experiments under idealized conditions. In the main study, under real conditions, the system was assessed over a mountainous region of China, the Yangjiashan Creeping (YC) slope. For this data-rich section of the Changjiang River, the model estimated creeping rates that had RMS errors of ∼0.5 mm yr−1 when compared with a dataset generated from borehole measurements. A prediction of the creeping curve for 2010 was made that suggested significant slope movement will occur in the next 5 years, without any change in the current precipitation morphology. However, sliding will become imminent if a storm occurs in that 5-yr period that produces over 150 mm of precipitation. A sensitivity experiment shows that the identified location fails first, triggering domino-effect slides that progress upslope. This system for predicting storm-triggered landslides is intended to improve upon present warning lead times to minimize the impacts of shallow, fast moving, and therefore hazardous landslides.

Beschreibung: Southern forests contribute significantly to the carbon sink for the atmospheric carbon dioxide (CO2) associated with the anthropogenic activities in the United States. Natural disasters like hurricanes are constantly threatening these forests. Hurricane winds can have a destructive impact on natural vegetation and can adversely impact net primary productivity (NPP). Hurricane Katrina (23–30 August 2005), one of the most destructive natural disasters in history, has affected the ecological balance of the Gulf Coast. This study analyzed the impacts of different categories of sustained winds of Hurricane Katrina on NPP in Mississippi. The study used the Carnegie–Ames–Stanford Approach (CASA) model to estimate NPP by using remote sensing data. The results indicated that NPP decreased by 14% in the areas hard hit by category 3 winds and by 1% in the areas hit by category 2 winds. However, there was an overall increase in NPP, from 2005 to 2006 by 0.60 Tg of carbon, in Mississippi. The authors found that Pearl River, Stone, Hancock, Jackson, and Harrison counties in Mississippi faced significant depletion of NPP because of Hurricane Katrina.

Beschreibung: Monthly climatologies (1971–2000 monthly averages) for stations in the western United States, obtained from the NOAA/National Climatic Data Center (NCDC), are used to illustrate the spatial variations in the annual cycle of climate. Animated map sequences of temperature and precipitation, their average, intermonthly changes, and the local timing of annual maxima or minima provide a comprehensive spatiotemporal baseline of regional climate. The animated maps illustrate three scales of variation: 1) broadscale patterns related to the annual cycle of insolation and hemispheric-scale atmospheric circulation features; 2) mesoscale patterns related to location on the continent and the influence of specific regional circulation features like those associated with the North American monsoon; and 3) smaller-scale spatial variations, related to the mediation by local physiography of the influence of large-scale circulation. Although most western U.S. stations have temperature maxima in July, a delay occurs at stations along the West Coast and interior Washington, northern Idaho, and Montana. A seesaw pattern of precipitation maxima is evident between coastal areas (winter dominated) and the interior (summer dominated). Cluster analyses of the ratio of monthly-to-annual precipitation values for each station identify regions with similar annual cycles of precipitation. Regions of high spatial heterogeneity in the timing of when precipitation occurs include the northern Rocky Mountains, Utah, Arizona, and northwestern Montana. The superimposition of these three scales of spatial variability leads to steep gradients and, in some regions, considerable spatial heterogeneity in annual precipitation. The regional patterns of precipitation heterogeneity highlight vulnerability to drought, especially in regions of the interior west that do not have a dominant precipitation month or season.