Practicable methodologies for delivering comprehensive spatial soils information

This thesis is concerned with practicable methodologies for delivering comprehensive spatial soil information to end-users. There is a need for relevant spatial soil information to complement objective decision-making for addressing current problems associated with soil degradation; for modelling, monitoring and measurement of particular soil services; and for the general management of soil resources. These are real-world situations, which operate at spatial scales ranging from field to global scales. As such, comprehensive spatial soil information is tailored to meet the spatial scale specifications of the end user, and is of a nature that fully characterises the whole-soil profile with associated prediction uncertainties, and where possible, both the predictions and uncertainties have been independently validated. ‘Practicable’ is an idealistic pursuit but nonetheless necessary because of a need to equip land-holders, private-sector and non-governmental stakeholders and, governmental departments including soil mapping agencies with the necessary tools to ensure wide application of the methodologies to match the demand for relevant spatial soil information. Practicable methodologies are general and computationally efficient; can be applied to a wide range of soil attributes; can handle variable qualities of data; and are effective when working with very large datasets. In this thesis, delivering comprehensive spatial soil information relies on coupling legacy soil information (principally site observations made in the field) with Digital Soil Mapping (DSM) which comprises quantitative, state-of-the-art technologies for soil mapping. After the General Introduction, a review of the literature is given in Chapter 1 which describes the research context of the thesis. The review describes soil mapping first from a historical perspective and rudimentary efforts of mapping soils and then tracks the succession of advances that have been made towards the realisation of populated, digital spatial soil information databases where measures of prediction certainties are also expressed. From the findings of the review, in order to deliver comprehensive spatial soil information to end-users, new research was required to investigate: 1) a general method for digital soil mapping the whole-profile (effectively pseudo-3D) distribution of soil properties; 2) a general method for quantifying the total prediction uncertainties of the digital soil maps that describe the whole-profile distribution of soil properties; 3) a method for validating the whole-profile predictions of soil properties and the quantifications of their uncertainties; 4) a systematic framework for scale manipulations or upscaling and downscaling techniques for digital soil mapping as a means of generating soil information products tailored to the needs of soil information users. Chapters 2 to 6 set about investigating how we might go about doing these with a succession of practicable methodologies. Chapter 2 addressed the need for whole-profile mapping of soil property distribution. Equal-area spline depth functions coupled with DSM facilitated continuous mapping the lateral and vertical distribution of soil properties. The spline function is a useful tool for deriving the continuous variation of soil properties from soil profile and core observations and is also suitable to use for a number of different soil properties. Generally, mapping the continuous depth function of soil properties reveals that the accuracy of the models is highest at the soil surface but progressively decreases with increasing soil depth. Chapter 3 complements the investigations made in Chapter 2 where an empirical method of quantifying prediction uncertainties from DSM was devised. This method was applied for quantifying the uncertainties of whole-profile digital soil maps. Prediction uncertainty with the devised empirical method is expressed as a prediction interval of the underlying model errors. The method is practicable in the sense that it accounts for all sources of uncertainty and is computationally efficient. Furthermore the method is amenable in situations where complex spatial soil prediction functions such as regression kriging approaches are used. Proper evaluation of digital soil maps requires testing the predictions and the quantification of the prediction uncertainties. Chapter 4 devised two new criteria in which to properly evaluate digital soil maps when additional soil samples collected by probability sampling are used for validation. The first criterion addresses the accuracy of the predictions in the presence of uncertainties and is the spatial average of the statistical expectation of the Mean Square Error of a simulated random value (MSES). The second criterion addresses the quality of the uncertainties which is estimated as the total proportion of the study area where the (1-α)-prediction interval (PI) covers the true value (APCP). Ideally these criteria will be coupled with conventional measures of map quality so that objective decisions can be made about the reliability and subsequent suitability of a map for a given purpose. It was revealed in Chapter 4, that the quantifications of uncertainty are susceptible to bias as a result of using legacy soil data to construct spatial soil prediction functions. As a consequence, in addition to an increasing uncertainty with soil depth, there is increasing misspecification of the prediction uncertainties. Chapter 2, 3, and 4 thus represent a framework for delivering whole-soil profile predictions of soil properties and their uncertainties, where both have been assessed or validated across mapping domains at a range of spatial scales for addressing field, farm, regional, catchment, national, continental or global soil-related problems. The direction of Chapters 5 and 6 however addresses issues specifically related to tailoring spatial soil information to the scale specifications of the end-user through the use of scale manipulations on existing digital soil maps. What is proposed in Chapter 5 is a scaling framework that takes into account the scaling triplet of digital soil maps—extent, resolution, and support—and recommends pedometric methodologies for scale manipulation based on the scale entities of the source and destination maps. Upscaling and downscaling are descriptors for moving up to coarser or down to finer scales respectively but may be too general for DSM. Subsequently Fine-gridding and coarse-gridding are operations where the grid spacing changes but support remains unchanged. Deconvolution and convolution are operations where the support always changes, which may or may not involve changing the grid spacing. While disseveration and conflation operations occur when the support and grid size are equal and both are then changed equally and simultaneously. There is an increasing richness of data sources describing the physical distribution of the Earth’s resources with improved qualities and resolutions. To take advantage of this, Chapter 6 devises a novel procedure for downscaling, involving disseveration. The method attempts to maintain the mass balance of the fine scaled predictions with the available coarse scaled information, through an iterative algorithm which attempts to reconstruct the variation of a property at a prescribed fine scale through an empirical function using environmental or covariate information. One of the advantages associated with the devised method is that soil property uncertainties at the coarse scale can be incorporated into the downscaling algorithm. Finally Chapter 7 presents a synthesis of the investigations made in Chapters 2 to 6 and summarises the pertinent findings. Directly from the investigations carried out during this project there are opportunities for further work; both in terms of addressing shortcomings that were highlighted but not investigated in the thesis, and more generally for advancing digital soil mapping to an operational status and beyond

A methodology to produce geographical information for land planning using very-high resolution images

Actualmente, os municípios são obrigados a produzir, no âmbito da elaboração dos instrumentos de gestão territorial, cartografia homologada pela autoridade nacional. O Plano Director Municipal (PDM) tem um período de vigência de 10 anos. Porém, no que diz respeito à cartografia para estes planos, principalmente em municípios onde a pressão urbanística é elevada, esta periodicidade não é compatível com a dinâmica de alteração de uso do solo. Emerge assim, a necessidade de um processo de produção mais eficaz, que permita a obtenção de uma nova cartografia de base e temática mais frequentemente. Em Portugal recorre-se à fotografia aérea como informação de base para a produção de cartografia de grande escala. Por um lado, embora este suporte de informação resulte em mapas bastante rigorosos e detalhados, a sua produção têm custos muito elevados e consomem muito tempo. As imagens de satélite de muito alta-resolução espacial podem constituir uma alternativa, mas sem substituir as fotografias aéreas na produção de cartografia temática, a grande escala. O tema da tese trata assim da satisfação das necessidades municipais em informação geográfica actualizada. Para melhor conhecer o valor e utilidade desta informação, realizou-se um inquérito aos municípios Portugueses. Este passo foi essencial para avaliar a pertinência e a utilidade da introdução de imagens de satélite de muito alta-resolução espacial na cadeia de procedimentos de actualização de alguns temas, quer na cartografia de base quer na cartografia temática. A abordagem proposta para solução do problema identificado baseia-se no uso de imagens de satélite e outros dados digitais em ambiente de Sistemas de Informação Geográfica. A experimentação teve como objectivo a extracção automática de elementos de interesse municipal a partir de imagens de muito alta-resolução espacial (fotografias aéreas ortorectificadas, imagem QuickBird, e imagem IKONOS), bem como de dados altimétricos (dados LiDAR). Avaliaram-se as potencialidades da informação geográfica extraídas das imagens para fins cartográficos e analíticos. Desenvolveram-se quatro casos de estudo que reflectem diferentes usos para os dados geográficos a nível municipal, e que traduzem aplicações com exigências diferentes. No primeiro caso de estudo, propõe-se uma metodologia para actualização periódica de cartografia a grande escala, que faz uso de fotografias aéreas vi ortorectificadas na área da Alta de Lisboa. Esta é uma aplicação quantitativa onde as qualidades posicionais e geométricas dos elementos extraídos são mais exigentes. No segundo caso de estudo, criou-se um sistema de alarme para áreas potencialmente alteradas, com recurso a uma imagem QuickBird e dados LiDAR, no Bairro da Madre de Deus, com objectivo de auxiliar a actualização de cartografia de grande escala. No terceiro caso de estudo avaliou-se o potencial solar de topos de edifícios nas Avenidas Novas, com recurso a dados LiDAR. No quarto caso de estudo, propõe-se uma série de indicadores municipais de monitorização territorial, obtidos pelo processamento de uma imagem IKONOS que cobre toda a área do concelho de Lisboa. Esta é uma aplicação com fins analíticos onde a qualidade temática da extracção é mais relevante.Currently, the Portuguese municipalities are required to produce homologated cartography, under the Territorial Management Instruments framework. The Municipal Master Plan (PDM) has to be revised every 10 years, as well as the topographic and thematic maps that describe the municipal territory. However, this period is inadequate for representing counties where urban pressure is high, and where the changes in the land use are very dynamic. Consequently, emerges the need for a more efficient mapping process, allowing obtaining recent geographic information more often. Several countries, including Portugal, continue to use aerial photography for large-scale mapping. Although this data enables highly accurate maps, its acquisition and visual interpretation are very costly and time consuming. Very-High Resolution (VHR) satellite imagery can be an alternative data source, without replacing the aerial images, for producing large-scale thematic cartography. The focus of the thesis is the demand for updated geographic information in the land planning process. To better understand the value and usefulness of this information, a survey of all Portuguese municipalities was carried out. This step was essential for assessing the relevance and usefulness of the introduction of VHR satellite imagery in the chain of procedures for updating land information. The proposed methodology is based on the use of VHR satellite imagery, and other digital data, in a Geographic Information Systems (GIS) environment. Different algorithms for feature extraction that take into account the variation in texture, color and shape of objects in the image, were tested. The trials aimed for automatic extraction of features of municipal interest, based on aerial and satellite high-resolution (orthophotos, QuickBird and IKONOS imagery) as well as elevation data (altimetric information and LiDAR data). To evaluate the potential of geographic information extracted from VHR images, two areas of application were identified: mapping and analytical purposes. Four case studies that reflect different uses of geographic data at the municipal level, with different accuracy requirements, were considered. The first case study presents a methodology for periodic updating of large-scale maps based on orthophotos, in the area of Alta de Lisboa. This is a situation where the positional and geometric accuracy of the extracted information are more demanding, since technical mapping standards must be complied. In the second case study, an alarm system that indicates the location of potential changes in building areas, using a QuickBird image and LiDAR data, was developed for the area of Bairro da Madre de Deus. The goal of the system is to assist the updating of large scale mapping, providing a layer that can be used by the municipal technicians as the basis for manual editing. In the third case study, the analysis of the most suitable roof-tops for installing solar systems, using LiDAR data, was performed in the area of Avenidas Novas. A set of urban environment indicators obtained from VHR imagery is presented. The concept is demonstrated for the entire city of Lisbon, through IKONOS imagery processing. In this analytical application, the positional quality issue of extraction is less relevant.GEOSAT – Methodologies to extract large scale GEOgraphical information from very high resolution SATellite images (PTDC/GEO/64826/2006), e-GEO – Centro de Estudos de Geografia e Planeamento Regional, da Faculdade de Ciências Sociais e Humanas, no quadro do Grupo de Investigação Modelação Geográfica, Cidades e Ordenamento do Territóri

Evaluating the Potential of a Geospatial/Geostatistical Methodology for Locating Rain-Derived Infiltration and Inflow into Wastewater Treatment Systems in the Minneapolis/St. Paul Metropolitan Area, Minnesota, USA

A significant issue facing municipal wastewater treatment infrastructure (WWTI) is how to manage infiltration and inflow (I/I). I/I of rain and ground water permeate into WWTI after precipitation events, periods of groundwater table rise, and percolation from surrounding surface waters. This can create discharges above the infrastructure\u27s flow capacity, increase costs for processing the wastewater and add undesired stress to aging wastewater networks. In an attempt to assess this problem cost and time inefficient approaches have commonly been applied. This study utilizes a new and more radical methodology to try and make WWTI management more efficient. This study applies ArcGIS and Geostatistical Analysis to seven counties within the Metropolitan Council Environmental Services (MCES) network in the Minneapolis/St. Paul metro area. Data is collected from rain gauges and flow meters an average ten-year flow record is created from this data. The data is then analyzed in ArcGIS through Kriging to interpolate and predict where significant rates of I/I, due to high magnitude precipitation events, are located throughout the study area. I/I rates for high magnitude precipitation events are estimated through the comparison of the max flow rate data and the ten-year average flow rate. A percentage of increase flow is then calculated. Results reveal spatial patterns indicating variable I/I susceptibility across the MCES WWTI. By collaborating with MCES it is possible to determine how accurately this methodology can locate areas of high-risk I/I potential within the existing WWTI

Multiscale Landform Characterization for Land Use Evaluation using Fuzzy Sets

A multi-scale geomorphometric landform model was created through the use of fuzzy semantic import models and fuzzy overlay to measure distribution of landforms within parcels of the Conservation Reserve Program in a portion of the Delaware River Sub-basin in Northeast Kansas. Different fuzzy logic operators (intersect, algebraic mean, and fuzzy gamma) were used to test the impact of different model mechanisms on the resulting distributions of crisp and fuzzy membership values, and classification uncertainty measured by entropy values. Across scales (900 m2 to 16,900 m2 window sizes), only one crisp class (drainages) showed an optimal scale for detection area. The statistical distribution of fuzzy membership values were significantly different between the same classes derived from different overlay operators, but this had limited impact on the agreement between crisp landforms derived from the three operators at a single scale. Within each pairing of overlay operator and scale, the landform classes backslopes and flats had the highest proportional representation of classes at most entropy levels (0.95, 0.90, 0.85, and 0.75) except for locations within the single-highest entropy level (0.99), where the class proportions were more variable. This is significant, as both of these classes were dominant at different scales (backslopes at finer scales, and flats at coarser scales) within CRP Parcels. The fuzzy and multi-scale approach provides flexibility in assessing class-level uncertainty that had been previously unaddressed in the use of geomorphometric systems for mapping, modeling, and applied management applications

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

Unplanned dilution and ore-loss optimisation in underground mines via cooperative neuro-fuzzy network

The aim of study is to establish a proper unplanned dilution and ore-loss (UB: uneven break) management system. To achieve the goal, UB prediction and consultation systems were established using artificial neural network (ANN) and fuzzy expert system (FES). Attempts have been made to illuminate the UB mechanism by scrutinising the contributions of potential UB influence factors. Ultimately, the proposed UB prediction and consultation systems were unified as a cooperative neuro fuzzy system

Interdisciplinarity and research on local issues: evidence from a developing country

This paper examines the role of interdisciplinarity on research pertaining to local issues. Using Colombian publications from 1991 until 2011 in the Web of Science, we investigate the relationship between the degree of interdisciplinarity and the local orientation of the articles. We find that a higher degree of interdisciplinarity in a publication is associated with a greater emphasis on local issues. In particular, our results support the view that research that combines cognitively disparate disciplines, what we refer to as distal interdisciplinarity, is associated with more local focus of research. We discuss the policy implications of these results in the context of national research assessments targeting excellence and socio-economic impact

Quantitative Techniques in Participatory Forest Management

Forest management has evolved from a mercantilist view to a multi-functional one that integrates economic, social, and ecological aspects. However, the issue of sustainability is not yet resolved. Quantitative Techniques in Participatory Forest Management brings together global research in three areas of application: inventory of the forest variables that determine the main environmental indices, description and design of new environmental indices, and the application of sustainability indices for regional implementations. All these quantitative techniques create the basis for the development of scientific methodologies of participatory sustainable forest management