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Remote Sensing And Image Interpretation

Series Editor's Introduction Preface Acknowledgments 1. The Idea of Agent-Based Modeling 1.1 Agent-Based Modeling 1.2 Some Examples 1.3 The Features of Agent-Based Modeling 1.4 Other Related Modeling Approaches 2. Agents, Environments, and Timescales 2.1 Agents 2.2 Environments 2.3 Randomness 2.4 Time 3. Using Agent-Based Models in Social Science Research 3.1 An Example of Developing an Agent-Based Model 3.2 Verification: Getting Rid of the Bugs 3.3 Validation 3.4 Techniques for Validation 3.5 Summary 4. Designing and Developing Agent-Based Models 4.1 Modeling Toolkits, Libraries, Languages, Frameworks, and Environments 4.2 Using NetLogo to Build Models 4.3 Building the Collectivities Model Step by Step 4.4 Planning an Agent-Based Model Project 4.5 Reporting Agent-Based Model Research 4.6 Summary 5. Advances in Agent-Based Modeling 5.1 Geographical Information Systems 5.2 Learning 5.3 Simulating Language Resources Glossary References Index About the Author

What are agent-based models?

Strategic adjustment of land use policy under the economic transformation

https://cyberleninka.org/article/n/1028779.pdf

Flash Flood Hazard Mapping Using Satellite Images and GIS Tools: A case study of Najran City, Kingdom of Saudi Arabia (KSA)

Floods are natural disasters with significant socio-economic consequences Urban areas with uncontrolled urban development, rapid population growth, an unregulated municipal system and an unplanned change of land use belong to the highly sensitive areas where floods cause devastating economic and social losses The aim of this paper is to present a reliable GIS multi-criteria methodology for hazard zones’ mapping of flood-prone areas in urban areas The proposed methodology is based on the combined application of geographical information systems (GIS) and multi-criteria decision analysis (MCDA) The methodology considers six factors that are relevant to the hazard of flooding in urban areas: the height, slope, distance to the sewage network, the distance from the water surface, the water table and land use The expert evaluation takes into account the nature and severity of observed criteria, and it is tested using three scenarios: the modalities of the analytic hierarchy process (AHP) The first of them uses a new approach to the exploitation of uncertainty in the application of the AHP technique, the interval rough numbers (IR’AHP) The second one uses the fuzzy technique for the exploitation of uncertainty with the AHP method (F’AHP), and the third scenario contemplates the use of the traditional (crisp) AHP method The proposed methodology is demonstrated in Palilula Municipality, Belgrade, Serbia In the last few decades, Palilula Municipality has been repeatedly devastated by extreme flood events These floods severely affected the transportation networks and other infrastructure Historical flood inundation data have been used in the validation process The final urban flood hazard map proves a satisfactory agreement between the flood hazard zones and the spatial distribution of historical floods that happened in the last 58 years The results indicate that the scenario in which the IR’AHP methodology is used provides the highest level of compatibility with historical data on floods The produced map showed that the areas of very high flood hazard are located on the left Danube River bank These areas are characterized by lowland morphology, gentle slope, sewage network, expansion of impermeable locations and intense urbanization The proposed GIS-IR’AHP methodology and the results of this study provide a good basis for developing a system of flood hazard management in urban areas and can be successfully used for spatial city development policy

Application of GIS-Interval Rough AHP Methodology for Flood Hazard Mapping in Urban Areas

Fusion of close range photogrammery and the relatively new technology of terrestrial laser scanning methods offer new opportunities for photorealistic 3D models presentation, classification of real world objects and virtual reality creation (fly through). Laser scanning technology could be seen as a complement to close-range photogrammetry. For instance, terrestrial laser scanners (TLS) have the ability to rapidly collect high-resolution 3D surface information of an object. The same type of data could be generated using close range photogrammetric (CRP) techniques, but image disparities common to close range scenes makes this an operator intensive task. The imaging systems of some TLSs do not have very high radiometric resolution whereas high-resolution digital cameras used in modern CRP do. Finally, TLSs are essentially Earth-bound whereas cameras can be moved at will around the object being imaged. This paper presents the result of an initial study into the fusion of terrestrial laser scanner generated 3D data and highresolution digital images. Three approaches for their fusion have been investigated data fusion which integrates data from the sensors to create synthetic perspective imagery; image fusion (synthetic perspective imagery and the intensity images); and modelbased image fusion (2D intensity image and the 3D geometric model). Image registration, which includes feature detection and feature correspondence matching, is performed prior to fusion, to determine the relative rotation and translation of the digital camera relative to the laser scanner. To overcome the differences in datasets, a feature and area based matching algorithm was successfully developed and implemented. Some results of measurements on interest points and correspondence matching are presented. The result of the initial study shows that most promise is offered by model-based approaches.

/pdf/automatic-fusion-of-photogrammetric-imagery-and-laser-1rfyjreeqn.pdf

Automatic fusion of photogrammetric imagery and laser scanner point clouds

Flood is one of the most devastating natural hazards which lead to the loss of lives, properties and resources. It has therefore become important to create easily read, rapidly accessible flood hazard map, which will prioritize the mitigation effects. This study addresses the need for an efficient and cost-effective methodology for preparing flood hazard maps in Ghana, particularly those regions where floods pose a recurrent danger. An additive model was utilized to create a composite flood hazard index of the study area. Taking Northern region as an example, and using available topographical, land cover and demographic data, the study created a district level map indicating flood hazard prone areas. A composite flood hazard index was developed incorporating variables of near distance to the White Volta River, population density, number of towns in each district, area of cultivated savanna (crops), and availability of high ground (Shelter). Also, maximum flood hazard zones were mapped in a GIS environment. The study demonstrated the potentials of GIS applications in flood hazard mapping.

Flood Hazard Mapping using Aster Image data with GIS

The main aim of this paper is to examine the effects of peri-urbanization on peri-urban land use change patterns, using a binary logistic regression model, in the Bosomtwe district of the Asante region, Ghana. The decision to convert from agricultural land uses to residential and commercial land uses are driven by a myriad of factors, ranging from social to economic in the Bosomtwe District. A triangulation of qualitative and quantitative design was used. Household questionnaires were proportionately administered to 270 respondents in 14 communities, on the basis of population. The data was subjected to the Pearson’s Chi-square, Nigelkerk R2 and Cramer’s V test of strength of association. Astep-wise binary logistic regression modeling was performed using the PASW v.17. Pearson chi-square value of ?2 = 73.546 at 26 degrees was significant at p< .000,athough the Cramer’s V test of the strength of the association was moderate at V = 0.37. The logistic regression model reported an overall significance of the model at p< .000 with ?2 = 24.453, at 4 degrees of freedom. The confidence intervals of (CIs) of (CI: 1.358—4.517) and (CI: 1.039—11.486) for the two main predictors of the outcome, and a B(Exp) values ranging between 2.477 and 3.455 were also reported. This means the odds of respondents being more likely to change their land uses is about 66%. Increasing rate of peri-urbanization is caused by increasing demand for residential, recreational (Hotels and Guest houses) and commercial land uses at the expense of agro-forest land uses. These have some negative implications on local climate and food security. The District assembly should strictly monitor physical development in line with planning schemes.

/pdf/determinants-of-peri-urbanization-and-land-use-change-3n09g7lawy.pdf

Determinants of Peri-Urbanization and Land Use Change Patterns in Peri-Urban Ghana

This paper reviews the effect of applying optimization methods on the collection process of solid waste, with particular interest in mathematical programming and geographic information system approaches in developing countries. Mathematical programming approaches maximize or minimize an objective function for improvement in procedure, to ensure operational efficiency and also serve as decision support tools. They however provide partial solutions when implemented in reality and cannot fully handle road network constraints. Geographic information system approaches allow processing of additional considerations, often ignored in other methods, such as the street network modeling. Incorporating environmental pollution consideration is very challenging in this approach, the vehicle routing problem solver encountering limits for large data. For enhanced efficiency of the vehicle routing systems, studies should further focus on incorporating all network constraints, environmental pollution considerations, and impact of land use changes on routing.

/pdf/optimal-routing-of-solid-waste-collection-trucks-a-review-of-2i98nkrk5n.pdf

Optimal Routing of Solid Waste Collection Trucks: A Review of Methods

Using Satellite Remote Sensing and Geographic Information System, this paper analyzes the land use and land cover change dynamics in the Bosomtwe District of Ghana, for 1986, 2010 thematic mapper and enhanced thematic Mapper+ (TM/ETM+) images, and 2014 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIS) image. The three images were geo-referenced and processed for classification, using the maximum likelihood classifier algorithm. A Jeffries-Matusita’s separability check was used in confirming the degree of spectral separation acceptability of the bands used for each of the land use and land cover classes. The best Kappa hat statistic of classification accuracy was 83%. Land Use and Land Cover (LULC) transition analysis in Environmental Systems Research Institute ESRI’s ArcMap was performed. The results of the classification over the three periods showed that built up, bare land and concrete surfaces increased from 1201 in 1986 to 5454 ha in 2010. Dense forest decreased by 2253 ha over the same period and increased by 873 ha by the 2014. Low forest also decreased by 1043 ha in 2010; however, it increased by 13% in 2014. Our findings showed some of the important changes in the land use and land cover patterns in the District. After the urbanization process, coupled with farmland abandonment, between 1986 and 2010, substantial increments in urban land and clear increments in farmland coverage between 1986 and 2014were found to be the reason for vegetation cover decreases. This suggests that major changes in the socio-ecological driving forces affecting landscape dynamics have occurred in the last few decades.

/pdf/application-of-geo-information-techniques-in-land-use-and-4xli3gbods.pdf

Eric Kwabena Forkuo

Papers

Automatic fusion of photogrammetric imagery and laser scanner point clouds

Flood Hazard Mapping using Aster Image data with GIS

Determinants of Peri-Urbanization and Land Use Change Patterns in Peri-Urban Ghana

Optimal Routing of Solid Waste Collection Trucks: A Review of Methods

Application of Geo-Information Techniques in Land Use and Land Cover Change Analysis in a Peri-Urban District of Ghana