Flood Risk and Resilience

Flooding is widely recognized as a global threat, due to the extent and magnitude of damage it causes around the world each year. Reducing flood risk and improving flood resilience are two closely related aspects of flood management. This book presents the latest advances in flood risk and resilience management on the following themes: hazard and risk analysis, flood behaviour analysis, assessment frameworks and metrics and intervention strategies. It can help the reader to understand the current challenges in flood management and the development of sustainable flood management interventions to reduce the social, economic and environmental consequences from flooding

ICT and COMPRAM to assess road traffic congestion management in Kinshasa

Abstract: Traffic Congestion Management (TCM) in a megacity like Kinshasa, capital of the DR Congo, is a knowledge and real life problem of complex nature. Here, the authors describe the TCM problem through 9 phases of the layer 1 of the COMPRAM methodology. TCM is a worldwide complex societal problem and specifically in Kinshasa where it presents a set of characteristics such as ‘chaotic’ driver behaviour, road potholes and the road network physiognomy doesn’t respond to the supply- versus demand-side equation. The other complex problems include the absence of road planning with consideration to demographic parameters and car ownership increase, no suitable traffic operations infrastructure and limited funds for both maintaining existing roads and building additional ones. To solve this TCM problem, the authors propose a TTCMP (Triangular Traffic Congestion Management Process) framework as an output based layer 1 of COMPRAM by identifying types and sources of congestion, followed by a TCM problem description and a set of technical elements for ‘curbing’ traffic congestion with an overview on a Bluetooth based technology for traffic data collection as an adapted ICT4D solution for a low-income city like Kinshasa

Geospatial technology, a satellite -based change detection agent: imperative for analysis and management of vegetation resources in developing economy

The application of geospatial technology, apart from being used in diverse specialty of human endeavours, has made immense contribution towards monitoring and evaluating the vulnerability and changing pattern of diverse vegetation ecosystems. Thus, it is being rated among the most accurate means of detecting the trend of canopy cover conditions of a locality over a period of time. In the light of this, the present review focused on geospatial tool as a satellite-based change detection agent for the analysis of vegetation in sustainable resource management. Following the various conventional approaches to a critical review, the application of geospatial tool in the in-situ and ex-situ analytical phases has indicated its usefulness in evaluation of vegetation ecosystem. It has also proven useful in vegetation resource location and management, harvest planning, fire management, map development, strategic planning, modelling and statistical analysis. Its benefit for detecting changes gives more perspectives than the prehistoric ground measurement. It is faster, easier, energy and time-saving and accurately improving organisational integration. Though of great importance in change detection, geospatial tool is associated with four major issues which include institutional, social, economic and infrastructural challenges. However, researchers should be encouraged to explore this application in order to detect future trend (forecasting) and make researches more globally acceptable

Geospatial technology, a satellite -based change detection agent: imperative for analysis and management of vegetation resources in developing economy

The application of geospatial technology, apart from being used in diverse specialty of human endeavours, has made immense contribution towards monitoring and evaluating the vulnerability and changing pattern of diverse vegetation ecosystems. Thus, it is being rated among the most accurate means of detecting the trend of canopy cover conditions of a locality over a period of time. In the light of this, the present review focused on geospatial tool as a satellite-based change detection agent for the analysis of vegetation in sustainable resource management. Following the various conventional approaches to a critical review, the application of geospatial tool in the in-situ and ex-situ analytical phases has indicated its usefulness in evaluation of vegetation ecosystem. It has also proven useful in vegetation resource location and management, harvest planning, fire management, map development, strategic planning, modelling and statistical analysis. Its benefit for detecting changes gives more perspectives than the prehistoric ground measurement. It is faster, easier, energy and time-saving and accurately improving organisational integration. Though of great importance in change detection, geospatial tool is associated with four major issues which include institutional, social, economic and infrastructural challenges. However, researchers should be encouraged to explore this application in order to detect future trend (forecasting) and make researches more globally acceptable

Remote sensing in Michigan for land resource management

The Environmental Research Institute of Michigan is conducting a program whose goal is the large-scale adoption, by both public agencies and private interests in Michigan, of NASA earth-resource survey technology as an important aid in the solution of current problems in resource management and environmental protection. During the period from June 1975 to June 1976, remote sensing techniques to aid Michigan government agencies were used to achieve the following major results: (1) supply justification for public acquisition of land to establish the St. John's Marshland Recreation Area; (2) recommend economical and effective methods for performing a statewide wetlands survey; (3) assist in the enforcement of state laws relating to sand and gravel mining, soil erosion and sedimentation, and shorelands protection; (4) accomplish a variety of regional resource management actions in the East Central Michigan Planning and Development Region. Other tasks on which remote sensing technology was used include industrial and school site selection, ice detachment in the Soo Harbor, grave detection, and data presentation for wastewater management programs

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Land-use and land-cover analysis of Ilorin Emirate between 1986 and 2006 using landsat imageries

This paper examines changes in land-use and land-cover pattern in Ilorin Emirate in Nigeria between 1986 and 2006. Landsat images of Ilorin Emirates at  three epochs (1986, 2000 and 2006) were used. An administrative map of local governments in Kwara State and a land-use map of Ilorin were used as base maps. Global Mapper Software was used for the image enhancement; image classification was done with environment for visualizing images (ENVI) software   and was later exported to the ArcGIS for further  processing and analysis. The land consumption rate and land absorption coefficient was determined to aid  the  quantitative assessment of change. Subsequently, an attempt was made at projecting the observed land-use / land-cover for a period of 14 years  ending  at 2020. The result of the work shows a gradual growth in built-up land between 1986 and 2000 and this tends to grow more rapidly between 2000  and 2006. It was also observed that the change by 2020 may likely follow the trend observed in 2000 and 2006. It is recommended that the information from the results of this work should be use to optimally and effectively plan and manage the study area.Key words: Land-use, land-cover, land consumption rate, land absorption coefficient, change detection

Safety impact of connected and autonomous vehicles on motorways: a traffic microsimulation study

Connected and Autonomous Vehicles (CAVs) promise to improve road safety greatly. Despite the numerous CAV trials around the globe, their benefit has yet to be proven using real-world data. The lack of real-world CAV data has shifted the focus of the research community from traditional safety impact assessment methods to traffic microsimulation in order to evaluate their impacts. However, a plethora of operational, tactical and strategic challenges arising from the implementation of CAV technology remain unaddressed. This thesis presents an innovative and integrated CAV traffic microsimulation framework that aims to cover the aforementioned shortcomings.A new CAV control algorithm is developed in C++ programming language containing a longitudinal and lateral control algorithm that for the first time takes into consideration sensor error and vehicle platoon formulation of various sizes. A route-based decision-making algorithm for CAVs is also developed. The algorithm is applied to a simulated network of the M1 motorway in the United Kingdom which is calibrated and validated using instrumented vehicle data and inductive loop detector data. Multiple CAV market penetration rate, platoon size and sensor error rate scenarios are formulated and evaluated. Safety evaluation is conducted using traffic conflicts as a safety surrogate measure which is a function of time-to-collision and post encroachment time. The results reveal significant safety benefit (i.e. 10-94% reduction of traffic conflicts) as CAV market penetration increases from 0% to 100%; however, it is underlined that special focus should be given in the motorway merging and diverging areas where CAVs seem to face the most challenges. Additionally, it is proven that if the correct CAV platoon size is implemented at the appropriate point in time, greater safety benefits may be achieved. Otherwise, safety might deteriorate. However, sensor error does not affect traffic conflicts for the studied network. These results could provide valuable insights to policy makers regarding the reconfiguration of existing infrastructure to accommodate CAVs, the trustworthiness of existing CAV equipment and the optimal platoon size that should be enforced according to the market penetration rate.Finally, in order to forecast the conflict reduction for any given market penetration rate and understand the underlying factors behind traffic conflicts in a traffic microsimulation environment in-depth, a hierarchical spatial Bayesian negative binomial regression model is developed, based on the simulated CAV data. The results exhibit that besides CAV market penetration rate, speed variance across lanes significantly affects the production of simulated conflicts. As speed variance increases, the safety benefit decreases. These results emphasize the importance of speed homogeneity between lanes in a motorway as well as the increased risk in the motorway merging/diverging areas.</div

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem