Analysing trade-offs and synergies between SDGs for urban development, food security and poverty alleviation in rapidly changing peri-urban areas: a tool to support inclusive urban planning

Transitional peri-urban contexts are frontiers for sustainable development where land-use change involves negotiation and contestation between diverse interest groups. Multiple, complex trade-offs between outcomes emerge which have both negative and positive impacts on progress towards achieving Sustainable Development Goals (SDGs). These trade-offs are often overlooked in policy and planning processes which depend on top-down expert perspectives and rely on course grain aggregate data which does not reflect complex peri-urban dynamics or the rapid pace of change. Tools are required to address this gap, integrate data from diverse perspectives and inform more inclusive planning processes. In this paper, we draw on a reinterpretation of empirical data concerned with land-use change and multiple dimensions of food security from the city of Wuhan in China to illustrate some of the complex trade-offs between SDG goals that tend to be overlooked with current planning approaches. We then describe the development of an interactive web-based tool that implements deep learning methods for fine-grained land-use classification of high-resolution remote sensing imagery and integrates this with a flexible method for rapid trade-off analysis of land-use change scenarios. The development and potential use of the tool are illustrated using data from the Wuhan case study example. This tool has the potential to support participatory planning processes by providing a platform for multiple stakeholders to explore the implications of planning decisions and land-use policies. Used alongside other planning, engagement and ecosystem service mapping tools it can help to reveal invisible trade-offs and foreground the perspectives of diverse stakeholders. This is vital for building approaches which recognise how trade-offs between the achievement of SDGs can be influenced by development interventions

Web-Based Spatial Decision Support System and Watershed Management with a Case Study

In order to maintain a proper balance between development pressure and water resources protection, and also to improve public participation, efficient tools and techniques for soil and water conservation projects are needed. This paper describes the development and application of a web-based watershed management spatial decision support system, WebWMPI. The WebWMPI uses the Watershed Management Priority Indices (WMPI) approach which is a prioritizing method for watershed management planning and it integrates land use/cover, hydrological data, soils, slope, roads, and other spatial data. The land is divided into three categories: Conservation Priority Index (CPI) land, Restoration Priority Index (RPI) land, and Stormwater Management Priority Index (SMPI) land. Within each category, spatial factors are rated based on their influence on water resources and critical areas can be identified for soil conservation, water quality protection and improvement. The WebWMPI has user-friendly client side graphical interfaces which enable the public to interactively run the server side Geographic Information System to evaluate different scenarios for watershed planning and management. The system was applied for Dry Run Creek watershed (Cedar Falls, Iowa, US) as a demonstration and it can be easily used in other watersheds to prioritize crucial areas and to increase public participation for soil and water conservation projects

Normal background concentrations (NBCs) of contaminants in English soils : final project report

The British Geological Survey (BGS) has been commissioned by the Department for Environment, Food and Rural Affairs (Defra) to give guidance on what are normal levels of contaminants in English soils in support of the Part 2A Contaminated Land Statutory Guidance. This has initially been done by studying the distribution of four contaminants – arsenic, lead, benzo[a]pyrene (BaP) and asbestos – in topsoils from England. This work was extended to a further four contaminants (cadmium, copper, nickel and mercury) which enabled methodologies developed to be tested on a larger range of contaminants. The first phase of the Project gathered data sets that were: nationally extensive; systematically collected so a broad range of land uses were represented; and collected and analysed to demonstrably and acceptable levels of quality. Information on the soil contaminant concentrations in urban areas was of particular importance as the normal background is considered to be a combination of both natural and diffuse anthropogenic contributions to the soil. Issues of soil quality are most important in areas where these affect most people, namely, the urban environment. The two principal data sets used in this work are the BGS Geochemical Baseline Survey of the Environment (G-BASE) rural and urban topsoils (37,269 samples) and the English NSI (National Soil Inventory) topsoils (4,864 samples) reanalysed at the BGS laboratories by X-ray fluorescence spectrometry (XRFS) so both data sets were highly compatible. These two data sets provide results for most inorganic element contaminants, though results explored for mercury and BaP are drawn from a variety of different and much less extensive data sets

Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh

Landslides are a common hazard in the highly urbanized hilly areas in Chittagong Metropolitan Area (CMA), Bangladesh. The main cause of the landslides is torrential rain in short period of time. This area experiences several landslides each year, resulting in casualties, property damage, and economic loss. Therefore, the primary objective of this research is to produce the Landslide Susceptibility Maps for CMA so that appropriate landslide disaster risk reduction strategies can be developed. In this research, three different Geographic Information System-based Multi-Criteria Decision Analysis methods—the Artificial Hierarchy Process (AHP), Weighted Linear Combination (WLC), and Ordered Weighted Average (OWA)—were applied to scientifically assess the landslide susceptible areas in CMA. Nine different thematic layers or landslide causative factors were considered. Then, seven different landslide susceptible scenarios were generated based on the three weighted overlay techniques. Later, the performances of the methods were validated using the area under the relative operating characteristic curves. The accuracies of the landslide susceptibility maps produced by the AHP, WLC_1, WLC_2, WLC_3, OWA_1, OWA_2, and OWA_3 methods were found as 89.80, 83.90, 91.10, 88.50, 90.40, 95.10, and 87.10 %, respectively. The verification results showed satisfactory agreement between the susceptibility maps produced and the existing data on the 20 historical landslide locations

Panel discussion: U.S. EPA using modeling and ecosystem services to enhance coastal decision making

This panel will discuss the research being conducted, and the models being used in three current coastal EPA studies being conducted on ecosystem services in Tampa Bay, the Chesapeake Bay and the Coastal Carolinas. These studies are intended to provide a broader and more comprehensive approach to policy and decision-making affecting coastal ecosystems as well as provide an account of valued services that have heretofore been largely unrecognized. Interim research products, including updated and integrated spatial data, models and model frameworks, and interactive decision support systems will be demonstrated to engage potential users and to elicit feedback. It is anticipated that the near-term impact of the projects will be to increase the awareness by coastal communities and coastal managers of the implications of their actions and to foster partnerships for ecosystem services research and applications. (PDF contains 4 pages

Assessment of coastal watershed erosion potential using geographic information systems and expert input for decision support

Sediment is a major impairment in many streams and rivers in the drainage basins along the northern Gulf of Mexico. The use of geospatial technologies improves assessment and decision making for the management of environmental resources and conditions for coastal watersheds. This research focuses on the development of a conceptual qualitative model enhanced with expert input for the assessment of soil erosion potential in coastal watersheds. The conceptual model is built upon five layers (slope, precipitation, soil brightness or exposure, Kactor, and stream density) like those in a standard numerical soil loss model such as the Revised Universal Soil Loss Equation (RUSLE). The conceptual model produced a continuous surface to index erosion potential. Pearson’s correlation coefficient was used to identify variable sensitivity. The model was most sensitive to Kactor variable, followed by soil brightness, stream density, and slope. The model was not sensitive to the precipitation variable due to the lack of variability across the watershed. Expert input was added to the conceptual model for erosion potential with the Analytical Hierarchy Process (AHP). The AHP is used to value the importance of criteria, providing a quantitative weight for the qualitative data. The expert input increased the overall importance of topographic features and this increased cell counts in the upper erosion potential classes. The AHP weights were altered in 1% increments ranging from plus to minus 20% producing 201 unique runs. A quartile analysis of the runs was used to define areas of model agreement. The quartile analysis allowed for the application of an analysis mask to identify areas of increased erosion potential for improved management related decisions. The conceptual and AHP erosion potential output data, including watershed management priority rankings, were published as web mapping services for story map development as a transition to a decision support system. The limits of the story map to allow user interactions with model output rendered an unacceptable platform for decision support. The story map does offer an alternative to static reports and could serve to improve dissemination of spatial data as well as technical reports and plans like a watershed management plan

Geospatial Information as a Tool for Soil Resource Information, Management and Decision Support in Nigeria

Understanding and addressing the complexity of soil resources management and factors involved requires collection and interpretation of relevant data that will serve as decision support tools. Geospatial information is a veritable tool for soil resource information and decision support for soil management, which is yet to be well embraced in Nigeria. This paper emphasized the importance of geospatial information as a decision support tool to make better and informed decision in the management of soil resources. It also reviewed and discussed status of soil information systems and need to promote strategies for sustainable soil resource development in the country.Keywords: Soil information system, Decision support system, remote sensing, digital soil mappin

A multi-scale method to assess pesticide contamination risks in agricultural watersheds

The protection of water is now a major priority for environmental managers, especially around drinkingpumping stations. In view of the new challenges facing water agencies, we developed a method designedto support their public policy decision-making, at a variety of different spatial scales. In this paper, wepresent this new spatial method, using remote sensing and a GIS, designed to determine the contami-nation risk due to agricultural inputs, such as pesticides. The originality of this method lies in the useof a very detailed spatial object, the RSO (Reference Spatial Object), which can be aggregated to manyworking and managing scales. This has been achieved thanks to the pixel size of the remote sensing, witha grid resolution of 30 m × 30 m in our application.The method – called PHYTOPIXAL – is based on a combination of indicators relating to the environmen-tal vulnerability of the surface water environment (slope, soil type and distance to the stream) and theagricultural pressure (land use and practices of the farmers). The combination of these indicators for eachpixel provides the contamination risk. The scoring of variables was implemented according knowledgein literature and of experts.This method is used to target specific agricultural input transfer risks. The risk values are first calculatedfor each pixel. After this initial calculation, the data are then aggregated for decision makers, accordingto the most suitable levels of organisation. These data are based on an average value for the watershedareas.In this paper we detail an application of the method to an area in the hills of Southwest France. Weshow the pesticide contamination risk by in areas with different sized watersheds, ranging from 2 km2to 7000 km2, in which stream water is collected for consumption by humans and animals. The resultswere recently used by the regional water agency to determine the protection zoning for a large pumpingstation. Measures were then proposed to farmers with a view to improving their practices.The method can be extrapolated to different other areas to preserve or restore the surface water

Physical, Economical, Infrastructural and Social Flood Risk -- Vulnerability Analyses in GIS

An exhaustive knowledge of flood risk, vulnerability and exposure in different spatial locations is essential for developing an effective flood mitigation strategy for a watershed. In the present study, a flood risk-vulnerability analysis is performed. All four components of flood vulnerability: (a) physical; (b) economic; (c) infrastructure and (d) social, are evaluated individually using a Geographic Information System (GIS) environment. The proposed methodology estimates the impact on infrastructure vulnerability due to inundation of critical facilities, emergency service stations, and road bridges. The components of vulnerability are combined to determine the overall vulnerability. The patterns of land use and soil type are considered as two major components of flood exposure. Flood hazard maps, overall vulnerability and exposure are used to finally compute the flood risk at different locations in the watershed. The proposed methodology is implemented to six major damage centers in the Upper Thames River watershed, located in south-western Ontario of Canada to assess the flood risk. A web-based information system is developed for systematic presentation of the flood risk, vulnerability and exposures by postal code regions or Forward Sortation Areas (FSAs). The system is designed to provide support for different users, i.e., general public, decision-makers and water management professionals. An interactive analysis tool is developed within the web-based information system to assist in evaluation of the flood risk in response to a change in land use pattern.https://ir.lib.uwo.ca/wrrr/1019/thumbnail.jp