The spontaneous vegetation in urban residential gardens of Galveston, Texas

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Bibliography: leaves 94-106.Not availabl

Automation of data input in the A & M watershed model using GIS

Vita.Integration of hydrologic modeling into a GIS environment can help optimize the use of available digital data while improving the simulation of basin-wide effects of management decisions. This research demonstrates the feasibility of linking predictive hydrologic models in a GIS environment to facilitate urban stormwater management. The A&M Watershed Model was linked to an ARC/INFO database, and the Wolf Pen Creek watershed case study was used to demonstrate the advantages of the method for land use planning. The tool allows planners to simulate basin-wide effects of the consequences of their decisions. The consistency of hydrologic parameter computations allows for reliable analysis of the effects different scenarios would have on the hydrology. The cost effectiveness of different methods to generate the required input for the A&M Watershed Model was compared: the traditional data entry method using paper maps, the use of GIS without automation of data input computations, and the use of GIS with automated data input. The use of GIS databases without automation of model parameter computations provides more consistent hydrologic parameter computations than the traditional data gathering techniques, yet remains labor intensive. With an integrated model, substantial time savings were obtained, mainly by replacing labor time by computer time for routine tasks

Automation of data input in the A & M watershed model using GIS

Vita.Integration of hydrologic modeling into a GIS environment can help optimize the use of available digital data while improving the simulation of basin-wide effects of management decisions. This research demonstrates the feasibility of linking predictive hydrologic models in a GIS environment to facilitate urban stormwater management. The A&M Watershed Model was linked to an ARC/INFO database, and the Wolf Pen Creek watershed case study was used to demonstrate the advantages of the method for land use planning. The tool allows planners to simulate basin-wide effects of the consequences of their decisions. The consistency of hydrologic parameter computations allows for reliable analysis of the effects different scenarios would have on the hydrology. The cost effectiveness of different methods to generate the required input for the A&M Watershed Model was compared: the traditional data entry method using paper maps, the use of GIS without automation of data input computations, and the use of GIS with automated data input. The use of GIS databases without automation of model parameter computations provides more consistent hydrologic parameter computations than the traditional data gathering techniques, yet remains labor intensive. With an integrated model, substantial time savings were obtained, mainly by replacing labor time by computer time for routine tasks

Space and time related determinants of public transport use in trip chains

This research aims at gaining a better understanding about time and space related determinants, which are generally acknowledged to be important factors in the choice of transport mode. The effect of trip chaining is taken into account to improve the insight in the relation between the choice of transport mode and time factors. The data source is the first large scale Belgian mobility survey, carried out in 1998–1999, complemented with a newly created database, containing for each trip a calculated public transport trip. This allows comparing for each trip the actual travel time with the calculated travel time by public transport. Using elasticities and regression techniques the relation between travel time components and public transport use is quantified. On trip level, a clear relation is found between waiting and walking time and public transport use. On trip chain level, travel time variables for the whole trip chain such as the maximum and the range in the travel time ratio provide a significant improvement to the explanatory power of the regression model. The results contain parameters for model input and recommendations to public transport companies on information provision, intermodality and supply

Meer data meer inzicht?

Big Data is hot. Maar leidt meer data tot meer inzicht? En kunnen we dergelijke data inzetten voor beleidsvraagstukken in de ruimtelijke ordening? Op dit moment groeit de interesse van beleidsmakers voor bronnen zoals Facebook, Google, Twitter, Instagram of blogs die waardevolle informatie bevatten die normaal moeilijk te verzamelen zijn op korte termijn. Big Data kan een meer regelmatige, kosteneffectieve en geharmoniseerde gegevensverzameling bieden en een gelegenheid zijn om gemakkelijker nieuwe belangrijke problemen aan te pakken zoals bijvoorbeeld klimaat, gezondheid of huisvesting. De grote doorbraak betreffende praktische toepassingen van Big Data-bronnen in plannings- en ontwikkelingsprocessen moet echter nog komen.. De beschikbaarheid van tijdige, nauwkeurige statistische informatie stelt beleidsmakers, praktijk-mensen, onderzoekers en andere belanghebbenden in staat om een breed scala aan kwesties aan te pakken in het zich snel ontwikkelende economische en sociale landschap van vandaag. In toenemende mate kan informatie van het analyseren van internetactiviteiten of sociale media worden gebruikt voor het observeren van trends in ruimtelijke ordening en interessante mogelijkheden bieden om beleid te ondersteunen met actuele informatie. Spanningen op de woningmarkt hebben gevolgen voor het verhuisgedrag van mensen, wat opnieuw gevolgen heeft voor de arbeidsmobiliteit. Dit onderzoek illustreert in hoeverre 'big data' kan worden gebruikt om bestaand ruimtelijk beleid te verrijken en meer up-to-date bewijsmateriaal te leveren bij het inschatten van nieuwe trends voordat hun effecten zichtbaar worden in traditionele gegevensverzamelingen (nationale statistieken). Het onderzoek gaat dieper in op bestaande praktijkervaringen in België en Nederland, werkt een case uit m.b.t. huisvestingsdynamieken en doet voorstellen naar de toekomst om na te gaan hoe big data in beleidsvraagstukken omtrent ruimtelijke ordening een rol kan spelen. Van belang daarbij is het slim combineren van data.status: publishe

Innovative spatial analysis techniques for traffic safety

The project “Innovative spatial analysis techniques for traffic safety” consists of three interrelated subprojects, linked into a multidisciplinary thematic network. The objective of this research was to improve the explanatory model for traffic safety, in order to clarify the interactions between safety factors, and progress in an explanatory model for traffic safety. In order to reach the objective, this project explored the potential of new data sources and analysis techniques. The following approaches were used by the research partners: Three innovative approaches were explored: • Remote sensing analysis of very high resolution satellite images (KUL): The potential of very high resolution satellite imagery for identification of land use, infrastructure and traffic characteristics was explored. • Spatial statistics (KUL) This part of the research included the analysis of statistically significant risk zones, and spatial regression of socio-economic characteristics of neighbourhoods, which might be related to accident concentrations • Model-based clustering of accidents (LUC) The accident data consisted of a database of all the accidents with casualties occurred in Belgium in the period 1991-1999. Per accident, about 100 attributes are recorded. Clustering techniques were used to structure, and to find patterns and relations in this large dataset. • Association rules (LUC) Association rules were used to identify the relevance of data, and to identify typical characteristics and circumstances of accidents in black zones. • Analysis of time-space variations in the spatial distribution of accidents (UCL) The stability and the spatio-temporal variations of black zones in a peri-urban environment were examined. • Multi-level analysis (UCL) Explanatory factors of traffic (un)safety appear to be very scale-dependent. Rather than developing an explanatory model for different scales, recent developments through multilevel frameworks provide the opportunity of examining interactions at different levels and of integrating interactions between scale levels.Scientific report.nrpages: 141status: publishe

A view on GIS- supported preventive conservation of world heritage

Monitoring and planning processes related to land use management in a spatial context, considering spatial interaction over time, always necessitate complex human decisions. Spatio-temporal decisions are about evaluating alternative answers to a variety of questions that can be categorized as “how?”, “when?”, “how long?”, “what?” and “what if?” questions. A decision in whatever planning process is a commitment to action, is goal specific and has to do with prediction of the future effects of the choices made. Some of the questions that guide spatial intervention planning can be answered using the analytical functionalities of standard GIS-software. However, when optimisation in the presence of multiple goals and criteria are at stake, spatial analysis needs to be complemented with adapted ranking and multicriteria evaluation techniques. In the last decades, worldwide efforts have contributed to a common language in spatiotemporal decision support. From the development of spatiotemporal decision support systems for forestry planning in South American and European context, a theoretical framework and a generic spatiotemporal Decision Support System (stDSS) generator tool were proposed. From this shared experience, the present short paper offers a view on the monitoring and planning needs as raised by the World Heritage City Preservation Management project vlirCPM, for human settlements in the Southern Andes of Ecuador. The main conclusion is that in order to define the requirements of decision support, practical goals and temporal scope must be very clear. Decision support system design, data management and complexity depend on proper formulation and stakeholder consensus on the questions, values and criteria to be handled by planning support tools. No computerized decision support tool will replace multi-actor decision making and has to be complemented and integrated with expert knowledge, multidirectional communication flows and documentation in order to offer a flexible “toolkit” to those involved with planning goals and action.Cuenc