Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

Modelling the impact of high rise buildings in urban areas on precipitation initiation

The impact of urban areas upon precipitation distribution has been studied for many years. However, the relative importance of the distribution and type of surface morphology and urban heating remains unclear. A simple model of the surface sensible heat flux is used to explore the impact of urban heterogeneity. Sensitivity experiments are carried out to test the validity of the model, and experiments with a schematic urban morphology are used to investigate the impact of different types of building arrays. It is found that high-rise buildings over relatively small areas may have just as much impact as somewhat lower buildings covering a much larger area. The urban area produces considerable spatial variation in surface sensible heat flux. Data from a C-band radar located to the north of Greater Manchester provides evidence that convective cells may be initiated by the sensible heat flux input generated by the high-rise buildings in the city centre when the atmospheric boundary layer is unstable. Copyright © 2007 Royal Meteorological Societ

Breaking new ground in mapping human settlements from space -The Global Urban Footprint-

Today 7.2 billion people inhabit the Earth and by 2050 this number will have risen to around nine billion, of which about 70 percent will be living in cities. Hence, it is essential to understand drivers, dynamics, and impacts of the human settlements development. A key component in this context is the availability of an up-to-date and spatially consistent map of the location and distribution of human settlements. It is here that the Global Urban Footprint (GUF) raster map can make a valuable contribution. The new global GUF binary settlement mask shows a so far unprecedented spatial resolution of 0.4 arcsec ($\sim12 m$) that provides - for the first time - a complete picture of the entirety of urban and rural settlements. The GUF has been derived by means of a fully automated processing framework - the Urban Footprint Processor (UFP) - that was used to analyze a global coverage of more than 180,000 TanDEM-X and TerraSAR-X radar images with 3m ground resolution collected in 2011-2012. Various quality assessment studies to determine the absolute GUF accuracy based on ground truth data on the one hand and the relative accuracies compared to established settlements maps on the other hand, clearly indicate the added value of the new global GUF layer, in particular with respect to the representation of rural settlement patterns. Generally, the GUF layer achieves an overall absolute accuracy of about 85\%, with observed minima around 65\% and maxima around 98 \%. The GUF will be provided open and free for any scientific use in the full resolution and for any non-profit (but also non-scientific) use in a generalized version of 2.8 arcsec ($\sim84m$). Therewith, the new GUF layer can be expected to break new ground with respect to the analysis of global urbanization and peri-urbanization patterns, population estimation or vulnerability assessment

Mapping standard for sprint orienteering: standardized competition maps for urban, park and forest areas

Orienteering maps are one of the map products where the symbol set is standardized, no national deviations are allowed. Orienteering has developed a new form of competition which was originally held in parks or urban areas. This competition form is a very short and fast event where good media coverage is possible. The use of parks and urban areas has a significant advantage: it brings the sport into the midst of people and offers opportunities for increasing public and media awareness of orienteering. The international specification for traditional orienteering maps contains symbols for man-made features. However, the symbol set needed revision and extension in order to provide a clear and unambiguous interpretation of urban terrain required for fair competition in sprint orienteering. There are a number of reasons why the mapping of urban areas needs a modified approach compared to that used for the depiction of the 'classic' forested terrain

Geographically Referenced Data for Social Science

An estimated 80% of all information has a spatial reference. Information about households as well as environmental data can be linked to precise locations in the real world. This offers benefits for combining different datasets via the spatial location and, furthermore, spatial indicators such as distance and accessibility can be included in analyses and models. HSpatial patterns of real-world social phenomena can be identified and described and possible interrelationships between datasets can be studied. Michael F. GOODCHILD, a Professor of Geography at the University of California, Santa Barbara and principal investigator at the Center for Spatially Integrated Social Science (CSISS), summarizes the growing significance of space, spatiality, location, and place in social science research as follows: "(...) for many social scientists, location is just another attribute in a table and not a very important one at that. After all, the processes that lead to social deprivation, crime, or family dysfunction are more or less the same everywhere, and, in the minds of social scientists, many other variables, such as education, unemployment, or age, are far more interesting as explanatory factors of social phenomena than geographic location. Geographers have been almost alone among social scientists in their concern for space; to economists, sociologists, political scientists, demographers, and anthropologists, space has been a minor issue and one that these disciplines have often been happy to leave to geographers. But that situation is changing, and many social scientists have begun to talk about a "spatial turn," a new interest in location, and a new "spatial social science" that crosses the traditional boundaries between disciplines. Interest is rising in GIS (Geographic Information Systems) and in what GIS makes possible: mapping, spatial analysis, and spatial modelling. At the same time, new tools are becoming available that give GIS users access to some of the big ideas of social science."

Constrained tGAP for generalisation between scales: the case of Dutch topographic data

This article presents the results of integrating large- and medium-scale data into a unified data structure. This structure can be used as a single non-redundant representation for the input data, which can be queried at any arbitrary scale between the source scales. The solution is based on the constrained topological Generalized Area Partition (tGAP), which stores the results of a generalization process applied to the large-scale dataset, and is controlled by the objects of the medium-scale dataset, which act as constraints on the large-scale objects. The result contains the accurate geometry of the large-scale objects enriched with the generalization knowledge of the medium-scale data, stored as references in the constraint tGAP structure. The advantage of this constrained approach over the original tGAP is the higher quality of the aggregated maps. The idea was implemented with real topographic datasets from The Netherlands for the large- (1:1000) and medium-scale (1:10,000) data. The approach is expected to be equally valid for any categorical map and for other scales as well

Geomorphological classification of urban landscapes. The case study of Rome (Italy)

The results of a long-lasting geomorphological survey carried out in Rome are summarized. A method aimed at integrating survey data, historical maps, aerial photographs and archaeological and geomorphological literature produced a geomorphological map of the present-day historical centre. The geomorphology of Rome is related to the paleogeographical conditions prior to the founding of the City; they allow us to recognize the stages of landscape evolution of the ancient Caput Mundi (Capital of the World). The study area has been affected by continuous man-made changes to the drainage network and to the topographic surface over the last 3000 years. It has forced the authors to develop innovative solutions to undertake effective analysis of the urban environment and the legend of the geomorphological map in this peculiar context. The resulting map is useful for urban planning and archaeological research

Constructing Melchior Lorichs's 'Panorama of Constantinople'

In Constructing Melchior Lorichs's Panorama of Constantinople, Nigel Westbrook, Kenneth Rainsbury Dark, and Rene Van Meeuwen propose that Melchior Lorichs's 1559 Panorama of Constantinople was created by using a viewing grid. The panorama is thus a reliable graphic source for the lost or since-altered Ottoman and Byzantine buildings of the city. The panorama appears to lie outside the conventional symbolic mode of topographical depiction common for its period and constitutes a rare "scientific" record of an encounter of a perspicacious observer with a vast subject. The drawing combines elements of allegory with extensive empirical observation. Several unknown structures, shown on the drawing, have been located in relation to the present-day topography of Istanbul, as a test-case for further research