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A high resolution depth attenuation product (Kdhires) was developed using MODIS 500 m and 250 m spectral bands. The Kdhires was compared with Wang’s operational Kd for the Chesapeake Bay. Minimal differences were observed between the two methods, with greatest deviation occurring in areas of high turbidity in the tributaries. After tuning the new Kdhires, the mean absolute error and bias between the two algorithms was 0.22 m?1 and 0.026 m?1, indicating good agreement. Higher spatial resolution provides for improved retrievals along the coast and into the narrow sections of the tributaries, coinciding with areas of concern to estuarine health and coastal management applications.  相似文献   
2.
We show that the vegetation canopy of the Amazon rainforest is highly sensitive to changes in precipitation patterns and that reduction in rainfall since 2000 has diminished vegetation greenness across large parts of Amazonia. Large-scale directional declines in vegetation greenness may indicate decreases in carbon uptake and substantial changes in the energy balance of the Amazon. We use improved estimates of surface reflectance from satellite data to show a close link between reductions in annual precipitation, El Niño southern oscillation events, and photosynthetic activity across tropical and subtropical Amazonia. We report that, since the year 2000, precipitation has declined across 69% of the tropical evergreen forest (5.4 million km2) and across 80% of the subtropical grasslands (3.3 million km2). These reductions, which coincided with a decline in terrestrial water storage, account for about 55% of a satellite-observed widespread decline in the normalized difference vegetation index (NDVI). During El Niño events, NDVI was reduced about 16.6% across an area of up to 1.6 million km2 compared with average conditions. Several global circulation models suggest that a rise in equatorial sea surface temperature and related displacement of the intertropical convergence zone could lead to considerable drying of tropical forests in the 21st century. Our results provide evidence that persistent drying could degrade Amazonian forest canopies, which would have cascading effects on global carbon and climate dynamics.Rise in equatorial sea surface temperature has led to concerns that intensified El Niño southern oscillation (ENSO) events and a displacement of the intertropical convergence zone (1) could alter precipitation patterns in Amazonia (2, 3), resulting in increased length of the dry season (4) and more frequent severe droughts (5, 6). The feedbacks of such drying on global climate change could be substantial; the Amazon rainforest stores an estimated 120 billion tons of carbon (7, 8). Loss of forest productivity across Amazonia would clearly exacerbate atmospheric CO2 levels (9, 10); however, the extent to which drying affects terrestrial vegetation is currently unknown (11). Satellite remote sensing is the only practical way to observe the potential impacts that these changes may have on vegetation at useful spatial and temporal scales (12), but in recent years, conflicting results have been reported of whether productivity of tropical forests is limited by sunlight or precipitation (7, 11, 1316). Several studies have indicated that gross primary productivity increases initially during drought as a result of an increase in photosynthetically active radiation (PAR) (17, 18), but sensitivity to prolonged drought events and thresholds of forest dieback remain unclear. For instance, as a result of the severe Amazon drought in 2005, Phillips et al. (8) estimated an accumulated carbon loss of 1.2–1.6 petagram (Pg) based on records from 55 long-term monitoring plots. In contrast, Saleska et al. (13) reported greening of the Amazon forest based on remotely sensed estimates of the enhanced vegetation index acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA). Saleska et al. (13) concluded that tropical forests were more drought resistant than previously thought and remained a strong carbon sink even during drought. However, these assertions were subsequently questioned (7, 11), and after a second drought in 2010, Xu et al. (19) documented widespread decline in tropical vegetation.Similar to interannual changes related to drought, there have also been contradictory findings related to seasonal changes between dry and wet seasons. A substantial body of literature (15, 17, 18, 2022) supports the view that photosynthetic activity increases during the dry season in response to an increase in incident PAR, whereas water supply is maintained through deep root systems of tropical forests (23). In contrast, Morton et al. (14) argued that MODIS-derived observations of seasonal greening of tropical vegetation are an artifact of the sun-sensor geometry, concluding that tropical forests maintain consistent greenness throughout the dry and wet seasons.Resolving the discussion about drought tolerance of tropical vegetation is critical to reduce uncertainties in carbon balance models (16, 24, 25) and establish possible thresholds beyond which forest dieback may occur (15). Recent work suggests a substantial uncertainty of MODIS surface reflectance across the Amazon basin as a likely cause of these discrepancies in interpretation (2628). Surface reflectance is routinely derived from top of atmosphere measurements using pixel-based atmospheric correction and cloud screening (29). Poor estimation of atmospheric aerosol loadings (11, 26) and deficiencies in cloud screening (30) can, therefore, introduce errors in vegetation indices (27). We take advantage of a new multiangle implementation of atmospheric correction algorithm (MAIAC) (31) to refine the analysis of the sensitivity of tropical and subtropical vegetation to variation in precipitation using daily observations of MODIS surface reflectance acquired between 2000 and 2012. MAIAC improves the accuracy of satellite-based surface reflectance over tropical vegetation by 3- to 10-fold compared with current MODIS products (30). This improvement is accomplished, in part, through a more accurate and less conservative cloud mask, which increases the number of clear-sky observations by a factor of 2–5 compared with standard procedures (30). A higher number of clear-sky observations is particularly important for analysis of tropical regions, where average cloud cover may be as high as 70% during the dry season and 95–99% during the wet season (30). This improvement along with the removal of calibration errors in the latest MODIS Terra Collection 6 (C6) data provide us with more confidence in interpreting the state and changes in the Amazon forests.  相似文献   
3.
Lake Erie, the world’s tenth largest freshwater lake by area, has had recurring blooms of toxic cyanobacteria for the past two decades. These blooms pose potential health risks for recreation, and impact the treatment of drinking water. Understanding the timing and distribution of the blooms may aid in planning by local communities and resources managers. Satellite data provides a means of examining spatial patterns of the blooms. Data sets from MERIS (2002–2012) and MODIS (2012–2014) were analyzed to evaluate bloom patterns and frequencies. The blooms were identified using previously published algorithms to detect cyanobacteria (~25,000 cells mL−1), as well as a variation of these algorithms to account for the saturation of the MODIS ocean color bands. Images were binned into 10-day composites to reduce cloud and mixing artifacts. The 13 years of composites were used to determine frequency of presence of both detectable cyanobacteria and high risk (>100,000 cells mL−1) blooms. The bloom season according to the satellite observations falls within June 1 and October 31. Maps show the pattern of development and areas most commonly impacted during all years (with minor and severe blooms). Frequencies during years with just severe blooms (minor bloom years were not included in the analysis) were examined in the same fashion. With the annual forecasts of bloom severity, these frequency maps can provide public water suppliers and health departments with guidance on the timing of potential risk.  相似文献   
4.
山丘地区植被指数与钉螺分布的关系   总被引:2,自引:1,他引:1  
目的研究云南省山丘地区钉螺分布和植被指数之间的关系。方法使用GPS定位螺点,收集螺情指标。在遥感软件中叠加螺点矢量图和中分辨率成像光谱仪植被指数图,提取归一化差异植被指数(NDVI)值,并与钉螺出现率和钉螺密度进行相关分析,建立回归方程。结果大理市45个流行村的114个螺点数据表明,95%钉螺分布在NDVI为0.414 4~0.760 7的地区,有螺框出现率、钉螺密度和NDVI值的关系季节性较强,以9月份相关系数最高,并可以初步建立回归方程。结论山丘地区植被和钉螺分布存在一定关系。  相似文献   
5.
Fires are a major contributor to atmospheric budgets of greenhouse gases and aerosols, affect soils and vegetation properties, and are a key driver of land use change. Since the 1990s, global burned area (BA) estimates based on satellite observations have provided critical insights into patterns and trends of fire occurrence. However, these global BA products are based on coarse spatial-resolution sensors, which are unsuitable for detecting small fires that burn only a fraction of a satellite pixel. We estimated the relevance of those small fires by comparing a BA product generated from Sentinel-2 MSI (Multispectral Instrument) images (20-m spatial resolution) with a widely used global BA product based on Moderate Resolution Imaging Spectroradiometer (MODIS) images (500 m) focusing on sub-Saharan Africa. For the year 2016, we detected 80% more BA with Sentinel-2 images than with the MODIS product. This difference was predominately related to small fires: we observed that 2.02 Mkm2 (out of a total of 4.89 Mkm2) was burned by fires smaller than 100 ha, whereas the MODIS product only detected 0.13 million km2 BA in that fire-size class. This increase in BA subsequently resulted in increased estimates of fire emissions; we computed 31 to 101% more fire carbon emissions than current estimates based on MODIS products. We conclude that small fires are a critical driver of BA in sub-Saharan Africa and that including those small fires in emission estimates raises the contribution of biomass burning to global burdens of (greenhouse) gases and aerosols.

Fire plays an important role in the Earth system, impacting climate and air quality and affecting vegetation, soils, and human assets (13). Global annual BA is currently estimated to be between 4.2 and 4.7 million km2 (46). Fires burn naturally in many ecosystems, but currently, the majority of fires have an anthropogenic origin and are often used as a land management tool [e.g., in the deforestation process (4, 5)]. Fires impact climate by releasing greenhouse gases and aerosols and by modifying surface albedo (68).Satellite sensors are the preferred way to estimate BA, as they provide frequent and comprehensive observations of surface reflectance and thermal properties (9). However, most existing products are based on coarse spatial-resolution images (≥500 m), which provide a global view of fire occurrence almost daily but may have important omission and commission errors, particularly where fires are small in size (10). In fact, several regional assessments of those global BA products have identified substantial omission errors when compared to fire perimeters (1115). Omission of small fires may be the cause of observing higher omission than commission errors in existing validation efforts of global BA products (1517).A first approach to estimate the contribution of these small fires was proposed by Randerson et al. (18) based on a statistical method overlaying BA and active fire detections. They estimated that small fires led to an additional 24 to 54% BA compared to previous estimates. Thanks to recent developments in satellite instruments and computing power, we can now map BA with substantially higher spatial resolution (≤30 m) and for large geographic regions (1921), reducing the dependency on statistical methods and active fire detections.Our main goal was to compare a new BA dataset generated from medium-resolution images and its resulting fire carbon emissions with existing information based on global BA datasets derived from coarse-resolution data. We focused our analysis on Africa, as it accounts for about 70% of global BA (22) and about half of global fire carbon emissions (23). The medium-resolution BA product was developed from Sentinel-2 MultiSpectral Instrument (MSI) data under the Fire Disturbance project of the European Space Agency’s Climate Change Initiative (CCI) program. The product, named FireCCISFD11, covers the whole of sub-Saharan Africa at 20-m resolution for the year 2016 (21) (see Materials and Methods). We have compared this product with three global BA datasets derived from MODIS data: MCD64A1C6 (22), the Global Fire Emission Database version 4s (GFED4s) (23), and the Global Fire Atlas (GFA) (24). MCD64A1C6 is the most recent version of a widely used BA product for global analysis of biomass burning impacts (9, 25). GFED4s is based on an older version of the MCD64A1 dataset (C5.1) but includes BA estimates from small fires based on a statistical approach. This product is only available at 0.25° spatial resolution (23). The GFA was derived from the MCD64A1C6 product. It generates burned patches from detected burned pixels using contextual analysis (24). Our comparative analysis between FireCCISFD11 and global products included total BA (with MCD64A1 and GFED4s), fire size distribution (with MCD64A1 and GFA), BA stratified by land cover (MCD64A1), and fire emissions (derived from MCD64A1 and GFED4s).  相似文献   
6.
Interactions between climate and land-use change may drive widespread degradation of Amazonian forests. High-intensity fires associated with extreme weather events could accelerate this degradation by abruptly increasing tree mortality, but this process remains poorly understood. Here we present, to our knowledge, the first field-based evidence of a tipping point in Amazon forests due to altered fire regimes. Based on results of a large-scale, long-term experiment with annual and triennial burn regimes (B1yr and B3yr, respectively) in the Amazon, we found abrupt increases in fire-induced tree mortality (226 and 462%) during a severe drought event, when fuel loads and air temperatures were substantially higher and relative humidity was lower than long-term averages. This threshold mortality response had a cascading effect, causing sharp declines in canopy cover (23 and 31%) and aboveground live biomass (12 and 30%) and favoring widespread invasion by flammable grasses across the forest edge area (80 and 63%), where fires were most intense (e.g., 220 and 820 kW⋅m−1). During the droughts of 2007 and 2010, regional forest fires burned 12 and 5% of southeastern Amazon forests, respectively, compared with <1% in nondrought years. These results show that a few extreme drought events, coupled with forest fragmentation and anthropogenic ignition sources, are already causing widespread fire-induced tree mortality and forest degradation across southeastern Amazon forests. Future projections of vegetation responses to climate change across drier portions of the Amazon require more than simulation of global climate forcing alone and must also include interactions of extreme weather events, fire, and land-use change.Large areas of moist tropical forests are being altered by land-use practices and severe weather. People are clearing, thinning, and changing the composition of tropical forests (1, 2). Severe drought events superimposed upon these land-use activities increase forest susceptibility to fires (15). In the 2000s, for example, 15,000–26,000 km2 of Amazonian forests burned during years of severe drought (6). Widespread forest fires may become even more common in the Amazon Basin if the frequency of extreme weather events increases, particularly in the southeastern Amazon (1, 7). However, most model simulations of future trajectories of Amazonian forests have relied on global and regional climate forcing that do not consider the effects of fire on vegetation dynamics and structure (810).Our ability to predict future fire regimes in moist tropical forests is constrained by a lack of understanding of what triggers and controls high-intensity fires (7, 11). In nondrought years, primary forests typically do not catch fire during the dry season because the fine fuel layer is too humid to carry a fire (12). This characteristic of primary forests helps explain why forest fires were less frequent in pre-Colombian times than today (13), although indigenous peoples of the Amazon have used fire as a management tool for hundreds or thousands of years (14). Current anthropogenic disturbances in moist tropical forests (e.g., logging, forest conversion for crops and livestock, and the resulting fragmentation of forests) tend to thin forest canopies (5, 11) and expose forest interiors to warm air flowing horizontally from neighboring clearings, allowing the forest floor to dry more rapidly during rainless periods. When forest fires do occur under average weather conditions, they typically move through the understories slowly (15–25 m⋅hour−1), release little energy (50 kW⋅m−1), and are of short duration (4, 5, 15), extinguishing at night when relative humidity increases. Despite their low intensity, understory fires still exert strong influences on forest dynamics and structure because many tropical tree species are thin-barked and vulnerable to fire damage (12, 16, 17).During years of severe drought, Amazon forest fires are atypically intense, killing up to 64% of the trees (18, 19). This happens because fuel (e.g., twigs, leaves, branches, etc.) not only becomes drier, but also tends to become more abundant due to drought-related leaf and branch fall (20). Thus, compared with low-intensity fires that occur in nondrought years, severe droughts can trigger high-intensity fires that kill more trees. Unfortunately, the role of extreme weather events in the fire dynamics of moist tropical forests is difficult to study because they are hard to predict. As a result, the relationships between fire-induced tree mortality and extreme weather remain poorly understood, restricted mostly to postfire observations of tree mortality.To fill this gap, in 2004 we established a large-scale, long-term prescribed forest fire experiment in a transitional forest (between Amazon forests and savannas) in the southeastern Amazon (Figs. 1 and and2)—a2)—a region that is highly vulnerable to changes in fire regime, climate change, and their interactions (2). The experimental area consists of three adjacent 50-ha (1.0 × 0.5 km; Fig. 1) plots burned annually (B1yr), every 3 y (B3yr), or not at all (control) to represent a range of possible future forest fire frequencies (details in ref. 21). We used within-plot variability between the forest edge (0–100 m into the forest from the adjacent agricultural area) (Fig. 1) and forest interior (100–1,000 m) and the temporal variability in weather between 2004 and 2010 to address two questions: (i) Are there weather- and fuel-related thresholds in fire behavior that are associated with high levels of fire-induced tree mortality across two different fire regimes? (ii) What are the effects of an intense fire event on forest structure, flammability, and aboveground live carbon stocks? We also conducted a regional analysis of weather and fire scars to assess the spatial-temporal dynamics of forest fires in the 87,000 km2 of remaining forests in the Upper Xingu River Basin (Fig. 1).Open in a separate windowFig. 1.High-resolution image (i.e., 1.85 m) of the experimental area in 2011 captured with the sensor Worldview-2. The dashed line represents the border between the North–South forest edge (0–100 m) and the forest interior (100–1,000 m). The North–South edge of the plots is bordered by a road and open agricultural fields, and the other plot boundaries are in contiguous forest. The control represents an unburned area, and B1yr and B3yr areas that were burned annually and every 3 y, respectively, from 2004 to 2010 (with the exception of 2008).Open in a separate windowFig. 2.(Left) Annual MCWD between 2000 and 2010 for the Upper Xingu Basin (solid circles) and the experimental field site (Fazenda Tanguro, solid triangles). The shaded area represents the SD of the mean and accounts for the spatial variability in MCWD across the Upper Xingu Basin. (Right) Average dry-season length (i.e., number of months with precipitation ≤100 mm) and the locations of both the Upper Xingu Basin (in gray) and the fire experiment (triangle). MCWD and monthly precipitation were derived from the TRMM.  相似文献   
7.
Schistosomiasis remains one of the most prevalent parasitic diseases in the tropics and subtropics, but current statistics are outdated due to demographic and ecological transformations and ongoing control efforts. Reliable risk estimates are important to plan and evaluate interventions in a spatially explicit and cost-effective manner. We analysed a large ensemble of georeferenced survey data derived from an open-access neglected tropical diseases database to create smooth empirical prevalence maps for Schistosoma mansoni and Schistosoma haematobium for a total of 13 countries of eastern Africa. Bayesian geostatistical models based on climatic and other environmental data were used to account for potential spatial clustering in spatially structured exposures. Geostatistical variable selection was employed to reduce the set of covariates. Alignment factors were implemented to combine surveys on different age-groups and to acquire separate estimates for individuals aged ≤20 years and entire communities. Prevalence estimates were combined with population statistics to obtain country-specific numbers of Schistosoma infections. We estimate that 122 million individuals in eastern Africa are currently infected with either S. mansoni, or S. haematobium, or both species concurrently. Country-specific population-adjusted prevalence estimates range between 12.9% (Uganda) and 34.5% (Mozambique) for S. mansoni and between 11.9% (Djibouti) and 40.9% (Mozambique) for S. haematobium. Our models revealed that infection risk in Burundi, Eritrea, Ethiopia, Kenya, Rwanda, Somalia and Sudan might be considerably higher than previously reported, while in Mozambique and Tanzania, the risk might be lower than current estimates suggest. Our empirical, large-scale, high-resolution infection risk estimates for S. mansoni and S. haematobium in eastern Africa can guide future control interventions and provide a benchmark for subsequent monitoring and evaluation activities.  相似文献   
8.
The south-west of Western Australia has experienced severe and prolonged drought over the last three decades. This has coincided with forest declines and more recently (following the summer of 2010–2011) sudden stand mortality in the Northern jarrah forest. Over the same period the Southern jarrah and Southern karri forests remained unaffected. The bioclimatic linkage between these localised climatic events and forest responses is key to developing a predictive capability that permits timely interventionist management strategies. We looked at the temporal dynamics of three accessible bioclimatic parameters (monthly mean diurnal temperature range, monthly mean precipitation and an aridity index derived from evaporation data) that were spatially registered with forested areas known to have been affected by this shift towards dryer and hotter conditions. Changes in forest condition were determined by accessing the vegetation fractional-cover data set, freely available from the high temporal resolution satellite MODIS. This data set provided estimates of three vegetation-related indices, namely photosynthetic vegetation, non-photosynthetic vegetation and bare soil cover. Both the climatic variables and the vegetative response variables were spatially co-registered over each of the three selected forest areas and a time series analysis undertaken for each variable. From the observed trends, we identify a set of threshold values for each bioclimatic metric and the approximate time lag associated with observed notable deterioration in the vegetation cover metrics.  相似文献   
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