Sub-Saharan African urbanisation and global environmental change

Scientific evidence for global environmental change in Africa presents a prima facia case for increased human migration and displacement. Closer scrutiny of the evidence on demographic change, however, suggests that migration and displacement are less important variables in explaining the human dimensions of global environmental change on the continent than is commonly projected. Natural population growth in cities is a more important dynamic in the evolving system of human settlement in Africa and this significant shift in where people live, both now and in the future is overlooked by the emphasis on the potential impact of environmentally induced migration. Even without any movement from the countryside, cities represent the fastest growing sector of the sub-Saharan African population. The existing vulnerability of African cities, with their fast growing populations and weak management means any environmental change is likely to have significant consequences for cities. Taking the sub-Saharan African demographic evidence seriously means that the scholarly and policy emphasis currently directed to GEC migration and displacement might be more effectively redirected to questions of the interface between global environmental change and urban areas.     

Cyclone Frame Prediction by Gaussian Mixture Modeling of the Three Penultimate Time-Lapse Frames

A fast cyclone frame prediction is proposed in this paper that fits a Gaussian Mixture model on the spatio-temporal data extracted from the three penultimate time-lapse frames, prior to fuzzy regression. Unlike the previous work in Verma and Pal (In: Applied Imagery Pattern Recognition Workshop (AIPR), pp. 1–8, 2010) that models the entire history on a per pixel basis, a single Gaussian mixture is used for fitting the spatio-temporal data within the time-span of the last three frames, making the process faster and more accurate. The increase in accuracy is attributed to the fact that cyclones evolve over time and thus the recent frames give a more meaningful insight into the predictions for the next frame. The number of components in the Gaussian mixture is determined from the occurrence of equally likely modes that correspond to high entropy peaks. Our results on satellite videos of recent cyclones that hit the Indian seas show a high accuracy of frame prediction.     

Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR

Background

Accurate estimation of aboveground forest biomass (AGB) and its dynamics is of paramount importance in understanding the role of forest in the carbon cycle and the effective implementation of climate change mitigation policies. LiDAR is currently the most accurate technology for AGB estimation. LiDAR metrics can be derived from the 3D point cloud (echo-based) or from the canopy height model (CHM). Different sensors and survey configurations can affect the metrics derived from the LiDAR data. We evaluate the ability of the metrics derived from the echo-based and CHM data models to estimate AGB in three different biomes, as well as the impact of point density on the metrics derived from them.

Results

Our results show that differences among metrics derived at different point densities were significantly different from zero, with a larger impact on CHM-based than echo-based metrics, particularly when the point density was reduced to 1 point m^?2. Both data models-echo-based and CHM-performed similarly well in estimating AGB at the three study sites. For the temperate forest in the Sierra Nevada Mountains, California, USA, R² ranged from 0.79 to 0.8 and RMSE (relRMSE) from 69.69 (35.59%) to 70.71 (36.12%) Mg ha^?1 for the echo-based model and from 0.76 to 0.78 and 73.84 (37.72%) to 128.20 (65.49%) Mg ha^?1 for the CHM-based model. For the moist tropical forest on Barro Colorado Island, Panama, the models gave R² ranging between 0.70 and 0.71 and RMSE between 30.08 (12.36%) and 30.32 (12.46) Mg ha^?1 [between 0.69–0.70 and 30.42 (12.50%) and 61.30 (25.19%) Mg ha^?1] for the echo-based [CHM-based] models. Finally, for the Atlantic forest in the Sierra do Mar, Brazil, R² was between 0.58–0.69 and RMSE between 37.73 (8.67%) and 39.77 (9.14%) Mg ha^?1 for the echo-based model, whereas for the CHM R² was between 0.37–0.45 and RMSE between 45.43 (10.44%) and 67.23 (15.45%) Mg ha^?1.

Conclusions

Metrics derived from the CHM show a higher dependence on point density than metrics derived from the echo-based data model. Despite the median of the differences between metrics derived at different point densities differing significantly from zero, the mean change was close to zero and smaller than the standard deviation except for very low point densities (1 point m^?2). The application of calibrated models to estimate AGB on metrics derived from thinned datasets resulted in less than 5% error when metrics were derived from the echo-based model. For CHM-based metrics, the same level of error was obtained for point densities higher than 5 points m^?2. The fact that reducing point density does not introduce significant errors in AGB estimates is important for biomass monitoring and for an effective implementation of climate change mitigation policies such as REDD + due to its implications for the costs of data acquisition. Both data models showed similar capability to estimate AGB when point density was greater than or equal to 5 point m^?2.

     

Measured and perceived visual complexity: a comparative study among three online map providers

We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.     

GI Science, Disasters, and Emergency Management

Societal responses to disasters begin with the initial post‐event rescue and relief operations, followed by recovery, reconstruction, and then transcend into mitigation actions including the development of pre‐impact preparedness measures, collectively known as the emergency response cycle. This paper highlights some of the applications of GI Science to the emergency response cycle, citing examples from natural hazards and from the World Trade Center disaster on 11th September 2001. More importantly, the paper describes some of the constraints on the utilization of GI Science by the practitioner community: understandable user interfaces; data quantity, quality, and integration; real‐time data and information. Finally, the paper suggests some important GI Science research areas based on the needs of the disasters and emergency management research and practitioner communities.     

BIFoR FACE: Water–soil–vegetation–atmosphere data from a temperate deciduous forest catchment,including under elevated CO2

The ecosystem services provided by forests modulate runoff generation processes, nutrient cycling and water and energy exchange between soils, vegetation and atmosphere. Increasing atmospheric CO₂ affects many linked aspects of forest and catchment function in ways we do not adequately understand. Global levels of atmospheric CO₂ will be around 40% higher in 2050 than current levels, yet estimates of how water and solute fluxes in forested catchments will respond to increased CO₂ are highly uncertain. The Free Air CO₂ Enrichment (FACE) facility of the University of Birmingham's Institute of Forest Research (BIFoR) is the only FACE in mature deciduous forest. The site specializes in fundamental studies of the response of whole ecosystem patches of mature, deciduous, temperate woodland to elevated CO₂ (eCO₂). Here, we describe a dataset of hydrological parameters – seven weather parameters at each of three heights and four locations, shallow soil moisture and temperature, stream hydrology and CO₂ enrichment – retrieved at high frequency from the BIFoR FACE catchment.     

Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities

When formulating a hydrologic model, scientists rely on parameterizations of multiple processes based on field data, but literature review suggests that more frequently people select parameterizations that were included in pre-existing models rather than re-evaluating the underlying field experiments. Problems arise when limited field data exist, when “trusted” approaches do not get reevaluated, and when sensitivities fundamentally change in different environments. The physics and dynamics of snow interception by conifers is just such a case, and it is critical to simulation of the water budget and surface albedo. The most commonly used interception parameterization is based on data from four trees from one site, but results from this field study are not directly transferable to locations with relatively warmer winters, where the dominant processes differ dramatically. Here, we combine a literature review with model experiments to demonstrate needed improvements. Our results show that the choice of model form and parameters can vary the fraction of snow lost through interception by as much as 30%. In most simulations, the warming of mean winter temperatures from −7 to 0°C reduces the modelled fraction of snow under the canopy compared to the open, but the magnitude of simulated decrease varies from about 10% to 40%. The range of results is even larger when considering models that neglect the melting of in-canopy snow in higher-humidity environments where canopy sublimation plays less of a role. Thus, we recommend that all models represent canopy snowmelt and include representation of increased loading due to increased adhesion and cohesion when temperatures rise from −3 to 0°C. In addition to model improvements, field experiments across climates and forest types are needed to investigate how to best model the combination of dynamically changing forest cover and snow cover to better understand and predict changes to albedo and water supplies.     

Are peatlands in different states with respect to their thermodynamic behaviour? A simple test of peatland energy and entropy budgets

Whilst all ecosystems must obey the second law of thermodynamics, these physical bounds and controls on ecosystem evolution and development are largely ignored across the ecohydrological literature. To unravel the importance of these underlying restraints on ecosystem form and function, and their power to inform our scientific understanding, we have calculated the entropy budget of a range of peat ecosystems. We hypothesize that less disturbed peatlands are ‘near equilibrium’ with respect to the second law of thermodynamics and thus respond to change by minimizing entropy production. This ‘near equilibrium’ state is best achieved by limiting evaporative losses. Alternatively, peatlands ‘far-from-equilibrium’ respond to a change in energy inputs by maximizing entropy production which is best achieved by increasing evapotranspiration. To test these alternatives this study examined the energy balance time series from seven peatlands across a disturbance gradient. We estimate the entropy budgets for each and determine how a change in net radiation (ΔR_n) was transferred to a change in latent heat flux (ΔλE). The study showed that: (i) The transfer of net radiation to latent heat differed significantly between peatlands. One group transferred up to 64% of the change in net radiation to a change in latent heat flux, while the second transferred as little as 27%. (ii) Sites that transferred the most energy to latent heat flux were those that produced the greatest entropy. The study shows that an ecosystem could be ‘near equilibrium’ rather than ‘far from equilibrium’.     

Natural Attenuation of Perchlorate in Denitrified Groundwater

Monitoring of a well‐defined septic system groundwater plume and groundwater discharging to two urban streams located in southern Ontario, Canada, provided evidence of natural attenuation of background low level (ng/L) perchlorate (ClO₄^?) under denitrifying conditions in the field. The septic system site at Long Point contains ClO₄^? from a mix of waste water, atmospheric deposition, and periodic use of fireworks, while the nitrate plume indicates active denitrification. Plume nitrate (NO₃^?‐N) concentrations of up to 103 mg/L declined with depth and downgradient of the tile bed due to denitrification and anammox activity, and the plume was almost completely denitrified beyond 35 m from the tile bed. The ClO₄^? natural attenuation occurs at the site only when NO₃^?‐N concentrations are <0.3 mg/L, after which ClO₄^? concentrations decline abruptly from 187 ± 202 to 11 ± 15 ng/L. A similar pattern between NO₃^?‐N and ClO₄^? was found in groundwater discharging to the two urban streams. These findings suggest that natural attenuation (i.e., biodegradation) of ClO₄^? may be commonplace in denitrified aquifers with appropriate electron donors present, and thus, should be considered as a remediation option for ClO₄^? contaminated groundwater.     

Responses of benthic macroinvertebrates to thin-layer disposal of dredged material in Mississippi Sound, USA

Benthic community responses to thin-layer disposal of dredged material were assessed at three sites in Mississippi Sound, USA. Community composition differed between disposal and reference sites (ANOSIM) for each disposal event. Oweniid sand worms, Amphinomid fire worms, and brittle stars (Ophiuriodea) contributed the most to community distinctions between disposal and reference sites (SIMPER), with higher abundances at the disposal sites. Total infaunal abundance was similar to pre-disposal and reference conditions within 3-10 months of thin-layer disposal. Distinctions in community composition between disposal and reference sites (nMDS) persisted throughout the 16-month study period, but were less pronounced at the site where sediment composition was unchanged by disposal. Size distributions of some taxa (e.g., gastropod and hemichordate) suggest adults recolonized the newly deposited sediments either through vertical migration or lateral immigration from adjacent areas. Thin-layer disposal offers a viable alternative to conventional open-water disposal practices and warrants further exploration for other areas with deeper bathymetries and different hydrodynamic regimes.