Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

Hydrological consequences of land-cover change: Quantifying the influence of plants on soil moisture with time-lapse electrical resistivity

Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.

Spatial disaggregation of land systems mapping in the Burnett catchment (South-East Queensland)

This project examined the potential for historical mapping of land resources to be upgraded to meet current requirements for natural resource management. The methods of spatial disaggregation used to improve the scale of mapping were novel and provide a method to rapidly improve existing information. The thesis investigated the potential to use digital soil mapping techniques and the multi-scale identification of areas within historical land systems mapping to provide enhanced information to support modern natural resource management needs. This was undertaken in the Burnett Catchment of South-East Queensland.

Implications for sustainable land use in high-density cities: Evidence from Hong Kong

Sustainable land use policies are concerned with the kind of world we want to live in now, and in future, and therefore inevitably involve some form of community involvement or consultation process. Hong Kong's sustainable land use planning system is well developed, involving considerable community participation and therefore serves as a good model for similarly situated cities. However, although there are several recent studies involving aspects of its land use planning system, none has yet examined the system as a whole from the perspective of sustainability. To correct this, this paper describes the land use conditions of Hong Kong from both demand and supply perspectives, reviewing its statutory and administrative procedures of land development and allocation together with the sustainable urban renewal practices involved. Problems in current sustainable land use planning and management, such as difficulties in urban renewal, the inherent shortage of land and the lengthy time involved due to need for coordination and responsiveness to multiple stakeholders, and outdated and overcomplicated administrative processes were also analyzed.

Bat habitat requirements : implications for land use planning

Knowledge of the habitat requirements of bat species is needed in decision making in land use planning. Bats' hibernation requirements were studied both in Estonia and in southern Finland. In both countries, the northern bat and the brown long-eared bat hibernated in colder and drier locations, whereas Daubenton's bat and Brandt's/whiskered bats hibernated in warmer and more humid locations. In Estonia, the pond bat hibernated in the warmest and most humid conditions, whereas Natterer's bat hibernated in the coldest and driest conditions. Hibernacula were at their coldest in mid-season and became warmer towards the end of the season. The results suggest that bats made an active choice of colder hibernation temperatures at the seasons end. They minimised the negative effects of hibernation early in the hibernation season by hibernating in warmer locations and energy expenditure late in the hibernation season by hibernating in colder locations. The use of foraging habitats was studied in northern and southern Finland. The northern bat used foraging sites opportunistically. Daubenton's bat foraged mainly in water habitats, whereas Brandt's/whiskered bats and the brown long-eared bat foraged mainly in forest habitats. In northern Finland, Daubenton's bats foraged almost exclusively on rivers and typically together with the northern bat. Daubenton's bats and Brandt's/whiskered bats were found only where there were lower ambient light levels. One of the most important things in the management of foraging areas for them is to keep them shady. Hibernacula in Finland typically housed few bats, suggesting that hibernation sites used by even a small number of bats are important. Bats typically used natural stone for hibernation suggesting that natural underground sites in rocks or cliffs or man-made underground sites built using natural stone are important for them. The results suggest that appropriate timing of surveys may vary according to the species and latitude.

Cover for plans regarding the Rykovo tract of land

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Cover page of a binder for plans of tracts of land on Crimea

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Cover for plans regarding the Naǐbrot, Busul-Montanaǐ, Urchuk, Abuslar i Friling tracts of land in the Fraǐdorf region

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Cover for plans regarding theRaitendorf and Maĭfelʻd tracts of land in the Dzhankoĭ region

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Cover for plans regarding the tract of land N 106 in the Dzhankoĭ region

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Cover for plans regarding the Komzetovka - N48, Ikor and Naǐdorf tracts of land in the Evpatoria region

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Land use regression model (LUR) for ultrafine particles in Brisbane

Traffic-related air pollution has been associated with a wide range of adverse health effects. One component of traffic emissions that has been receiving increasing attention is ultrafine particles(UFP, < 100 nm), which are of concern to human health due to their small diameters. Vehicles are the dominant source of UFP in urban environments. Small-scale variation in ultrafine particle number concentration (PNC) can be attributed to local changes in land use and road abundance. UFPs are also formed as a result of particle formation events. Modelling the spatial patterns in PNC is integral to understanding human UFP exposure and also provides insight into particle formation mechanisms that contribute to air pollution in urban environments. Land-use regression (LUR) is a technique that can use to improve the prediction of air pollution.

Use of climate information for farm-level decision making: rainfed groundnut in southern India

The production of rainfed crops in semi-arid tropics exhibits large variation in response to the variation in seasonal rainfall. There are several farm-level decisions such as the choice of cropping pattern, whether to invest in fertilizers, pesticides etc., the choice of the period for planting, plant population density etc. for which the appropriate choice (associated with maximum production or minimum risk) depends upon the nature of the rainfall variability or the prediction for a specific year. In this paper, we have addressed the problem of identifying the appropriate strategies for cultivation of rainfed groundnut in the Anantapur region in a semi-arid part of the Indian peninsula. The approach developed involves participatory research with active collaboration with farmers, so that the problems with perceived need are addressed with the modern tools and data sets available. Given the large spatial variation of climate and soil, the appropriate strategies are necessarily location specific. With the approach adopted, it is possible to tap the detailed location specific knowledge of the complex rainfed ecosystem and gain an insight into the variety of options of land use and management practices available to each category of stakeholders. We believe such a participatory approach is essential for identifying strategies that have a favourable cost-benefit ratio over the region considered and hence are associated with a high chance of acceptance by the stakeholders. (C) 2002 Elsevier Science Ltd. All rights reserved.

Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.