Vector Database Research Articles

Wavelet-Contourlet Retrieval Using Energy and Kurtosis Features

To improve the retrieval rate of contourlet transform retrieval system and reduce the redundancy of contourlet which cost two much time in building feature vector database, a new wavelet-contourlet transform retrieval system was proposed. Six different features, including mean, standard deviation, absolute mean energy, L2 energy, skewness and kurotis contributions to retrieval rates were examined. Based on the single feature ability in retrieval system, a new contourlet retrieval system was proposed. The feature vectors were constructed by cascading the absolute mean energy and kurtosis of each sub-band contourlet coefficients and the similarity measure used here is Canberra distance. Experimental results on 109 brodatz texture images show that using the features cascaded by absolute mean and kurtosis can lead to a higher retrieval rate than several contourlet transform retrieval systems which utilize the combination feature of standard deviation and absolute mean energy most commonly used today under same dimension of feature vectors.

Synergistic use of Landsat Multispectral Scanner with GIRAS land-cover data to retrieve impervious surface area for the Potomac River Basin in 1975

For many studies of urbanization, particularly those covering broad spatial extents and thus requiring the perspective afforded by satellite remote sensing, the longest time series of impervious surface area (ISA) initiate with the availability of Landsat Thematic Mapper (TM) data in the mid 1980s. Earlier generation remote sensing data, such as Landsat Multispectral Scanner (MSS) do not generally lead to robust representations of impervious surface area due to poor spectral differentiation between impervious and non-impervious surfaces lacking vegetation. In the 1970s, however, the USGS completed a comprehensive mapping of land cover based on aerial photography called the Geographic Information Retrieval and Analysis System (GIRAS). In this paper we describe a methodology for retrieving ISA estimates through the fusion of GIRAS land cover with historic and contemporary remote sensing data, resulting in a data set that is temporally comparable to more modern data sets (e.g. the National Land Cover Database (NLCD) ISA product). We calculate correlation coefficients between our data set and digitized aerial photography at 4 spatial resolutions, exhibiting a maximum correlation of 0.65 at 120-m and 240-m pixel sizes. Our highest resolution product (30-m) exhibited 94% accuracy and a kappa coefficient of 36% in rural areas, and 90.7% accuracy and a kappa coefficient of 59.6% in suburban areas. Further, we show that trends in urban area through time derived from these data exhibit accelerating rates of development throughout the Potomac River basin 1975–2001, including increased development in riparian buffer zones and on steeper topography. These results are applicable wherever low-resolution vector-based data sets of urban area are available or could be generated for the pre-Landsat TM era.

Distribution of the main malaria vectors in Kenya

BackgroundA detailed knowledge of the distribution of the main Anopheles malaria vectors in Kenya should guide national vector control strategies. However, contemporary spatial distributions of the locally dominant Anopheles vectors including Anopheles gambiae, Anopheles arabiensis, Anopheles merus, Anopheles funestus, Anopheles pharoensis and Anopheles nili are lacking. The methods and approaches used to assemble contemporary available data on the present distribution of the dominant malaria vectors in Kenya are presented here.MethodPrimary empirical data from published and unpublished sources were identified for the period 1990 to 2009. Details recorded for each source included the first author, year of publication, report type, survey location name, month and year of survey, the main Anopheles species reported as present and the sampling and identification methods used. Survey locations were geo-positioned using national digital place name archives and on-line geo-referencing resources. The geo-located species-presence data were displayed and described administratively, using first-level administrative units (province), and biologically, based on the predicted spatial margins of Plasmodium falciparum transmission intensity in Kenya for the year 2009. Each geo-located survey site was assigned an urban or rural classification and attributed an altitude value.ResultsA total of 498 spatially unique descriptions of Anopheles vector species across Kenya sampled between 1990 and 2009 were identified, 53% were obtained from published sources and further communications with authors. More than half (54%) of the sites surveyed were investigated since 2005. A total of 174 sites reported the presence of An. gambiae complex without identification of sibling species. Anopheles arabiensis and An. funestus were the most widely reported at 244 and 265 spatially unique sites respectively with the former showing the most ubiquitous distribution nationally. Anopheles gambiae, An. arabiensis, An. funestus and An. pharoensis were reported at sites located in all the transmission intensity classes with more reports of An. gambiae in the highest transmission intensity areas than the very low transmission areas.ConclusionA contemporary, spatially defined database of the main malaria vectors in Kenya provides a baseline for future compilations of data and helps identify areas where information is currently lacking. The data collated here are published alongside this paper where it may help guide future sampling location decisions, help with the planning of vector control suites nationally and encourage broader research inquiry into vector species niche modeling.

Vector data model of the Müller’s map of Bohemia

The Muller’s map of Bohemia is one of the most important maps of Czech history. In the last couple of years this map has been scanned and analysed a few times. Spatial position of the map symbols is usually compared with current situation. Using this method we can explore changes of the landscape through the ages. The crucial problem of this approach is georeferencing raster image into some well defined coordinate system. The best way to handle that problem is using ground control points (GCPs) and appropriate type of spatial transformation. The problem of choosing the best set of GCPs is not solved correctly yet. Usually well identifiable points are used depending on the researcher’s meaning. Proposed method is based on creating full vector data model of the map. Having complete vector database of the map, we can test many combinations of GCPs and many types of spatial transformation. Another great advantage of vector database is the fact, that vector data are easier to be analysed (e.g. spatial overlays, proximity analyses, or spatial statistics) in GIS software. As we wanted to make a new thorough analysis of the Muuller’s map of Bohemia, we decided to create its full vector data model. Methods of creating the model are explained in this article. At the end the map was georeferenced and several spatial statistics were done.

Analysis of spatial pattern of settlements in the federal capital territory of Nigeria using vector-based GIS data

Human settlements are important, seemingly static but dynamic, features of the cultural landscape that have attracted several studies due to the important role they play in human life. This paper examined the spatial distribution of settlements in the Federal Capital Territory (FCT) of Nigeria. The analysis uses vector based GIS data derived from the 1989 political map of the FCT. Map composition was done with ArcView 3.2a software and the nearest neighbour statistics was computed using the pattern analysis function of Ilwis 3.0 software. The result of the quadrat count analysis yielded a variance mean ratio of 1.34 to show that the settlements of the FCT were clustered in space as opposed to the subjective findings of some authors, which suggested that the settlements were evenly spread. Analysis of the degree of clustering reveals that 51 per cent of all settlement pair has a separation of less than four kilometres, 63 per cent has a separation of less than five kilometres, 79 per cent has less than six kilometres while 97 per cent has a separation of less then nine kilometres. It was thus found out that, for 80 per cent of all settlements in the point map, one nearest neighbour can be found within a radius of 2 kilometres. Also, for 68 per cent of the settlements, three nearest neighbours can be found while for 60 per cent of the settlements, six nearest neighbours can be found within a radius of 2 kilometres. Analysis of the distance at which neighbours could be found revealed that the probability of finding six neighbours becomes 1 at a distance of one kilometre. This indicates that, we are 100 per cent sure of finding 6 nearest neighbours within a distance of one kilometre radius on the map.

Automated Image-to-Map Discrepancy Detection using Iterative Trimming

Keeping existing vector databases Lip to date is a real challenge for GIS data providers. This study directly compares a a map with a more recent image in order to detect the discrepancies between them. An automatic workflow was designed to process the image based on existing information extracted from the vector database. First, geographic object-based image anal is provided automatically labeled image segments after matching, the vector database to the image. Then, discrepancies were detected using a statistical iterative trimming, where outliers were excluded based on a likelihood threshold. Applied on forest map updating, the proposed workflow, was able to detect about 75 percent of the forest regeneration, and 100 percent of the clear cuts with less than 10 percent of commission errors. This discrepancy detection approach assumes that discrepancy corresponds to small proportion of the map area and is very promising in diverse applications thanks to its flexibility.

Building a Dynamic, Large-Scale Spatio-temporal Vector Database to Support a National Spatial Data Infrastructure in China

This paper introduces a comprehensive approach to support dynamic, large-scale spatio-temporal vector database development. The approach is based on a version-difference spatio-temporal data model that targets common problems in developing large-scale spatio-temporal vector databases. The scenario is to establish a National Fundamental Geospatial Information Dynamic Database (NFGIDD) in China. The proposed methodology was demonstrated by an experimental spatiotemporal database system that consists of a database management platform and a data processing system. The experimental results show that our methods have significant advantages over traditional spatio-temporal data models.

Integrating building footprints and LiDAR elevation data to classify roof structures and visualise buildings

Three-dimensional urban models are increasingly needed for applications as varied as urban planning and design, microclimate investigation and tourism. Light Detection And Ranging (LiDAR) data are considered to be highly suitable for the three-dimensional reconstruction of urban features such as buildings. Ongoing research is determining how best to integrate LiDAR elevation data with already available vector-based data. This paper reports research on combining building footprints and LiDAR to visualise an urban area (Portbury near Bristol, England) with an emphasis on representing buildings in a GIS environment. The main emphasis here is on retaining a vector model that is suitable for representing regular man-made structures. A major difference between this and earlier work is that before visualisation, this work classifies roof types of buildings as either flat or pitched. We compared LiDAR data at three point densities in terms of successful building type detection and visualisation: 1 (low), 16 (medium) and 40 (high) points per m 2. There are important data acquisition cost issues at each of these resolutions. High density LiDAR yielded the highest overall accuracy of building type detection and proved useful for identifying roof features, yet lower densities proved more useful for revealing overall roof morphology.

Bayesian Tensor Approach for 3-D Face Modeling

Effectively modeling a collection of three-dimensional (3-D) faces is an important task in various applications, especially facial expression-driven ones, e.g., expression generation, retargeting, and synthesis. These 3-D faces naturally form a set of second-order tensors-one modality for identity and the other for expression. The number of these second-order tensors is three times of that of the vertices for 3-D face modeling. As for algorithms, Bayesian data modeling, which is a natural data analysis tool, has been widely applied with great success; however, it works only for vector data. Therefore, there is a gap between tensor-based representation and vector-based data analysis tools. Aiming at bridging this gap and generalizing conventional statistical tools over tensors, this paper proposes a decoupled probabilistic algorithm, which is named Bayesian tensor analysis (BTA). Theoretically, BTA can automatically and suitably determine dimensionality for different modalities of tensor data. With BTA, a collection of 3-D faces can be well modeled. Empirical studies on expression retargeting also justify the advantages of BTA.

Computing continuous sky view factors using 3D urban raster and vector databases: comparison and application to urban climate

The use of high resolution 3D urban raster and vector databases in urban climatology is presented. It applies two different methods to the calculation of continuous sky view factors (SVF), compares their values and considers their usefulness and limitations in urban climate studies. It shows and evaluates the relationship between urban geometry, quantified by SVF, and intra-urban nocturnal temperature variations using areal means in the whole urban area of Szeged, a city located in southeast Hungary. Results from the vector and raster models shows similar SVF values (r 2 = 0.9827). The usefulness of using areal means in SVF-temperature relations is confirmed. The vector and the raster approaches to the derivation of areal means of SVF are both shown to be powerful tools to obtain a general picture of the geometrical conditions of an urban environment.

Who Needs Cartographers?

In 1791, the British Government instructed the military to map the south of England at a scale of one inch to the mile (1:63 360) in preparation for an expected invasion attempt from French forces. Kent, in the extreme south-east of the country, was considered the most vulnerable area for attack and that was the subject area for the first map, completed in 1801. Thus was born Ordnance Survey and, within a few years, the practical value of appropriate maps had become more widely appreciated for the transfer and management of land, civil engineering projects and scientific applications such as the mapping of geological and archaeological information. By the mid-nineteenth century Ordnance Survey had assumed its modern role of providing the national mapping needs for the whole of Great Britain (that is England, Scotland and Wales) (Harley, 1975). Today, we are a wholly civilian, independent Government department that became a public-sector Trading Fund in 1999, giving us more commercial flexibility than we previously enjoyed but also greater responsibility for our finances and a commitment to making a profit. Ultimately, all our products and services rely on a network of around 300 surveyors employing ground and air survey techniques to maintain the ‘master map’ of the country at nominal capture scales of 1:1250 for urban areas, 1:2500 for rural areas and 1:10 000 for mountain and moorland areas, comprising in total some 230 000 maps. We began digitising these maps in the early 1970s in a fairly small way, the initial objective being to improve map production efficiencies and to produce electronic versions of the existing paper maps. No-one could foresee then the enormous explosion in the demand for, and use of, geographic information (GI) that we see around us today. The programme accelerated through the 1980s and was completed in 1995, to make Britain the first country in the world to compile such a detailed national vector database. The tiled and relatively unstructured (point and line) geometry of the original database was not only too coarse for effective data manipulation – now possible through today’s technological advances – but also did not meet increasing customer needs. Consequently, we have since completed a major re-engineering programme to develop the detailed topographic information, creating polygons to represent actual features with inferred links, resulting in some 440 million real-world objects. Every day surveyors, wherever they may be working in the country, download around 5 000 changes directly to the database using the latest technologies; these changes are then made available to our customers on the following day. This database update regime is maintained by change intelligence directing the data capture or by cyclic revision and ensures that any major changes to roads, building development and so on are recorded within six months of their ground completion.

Robust and Efficient Image Alignment Based on Relative Gradient Matching

In this paper, we present a robust image alignment algorithm based on matching of relative gradient maps. This algorithm consists of two stages; namely, a learning-based approximate pattern search and an iterative energy-minimization procedure for matching relative image gradient. The first stage finds some candidate poses of the pattern from the image through a fast nearest-neighbor search of the best match of the relative gradient features computed from training database of feature vectors, which are obtained from the synthesis of the geometrically transformed template image with the transformation parameters uniformly sampled from a given transformation parameter space. Subsequently, the candidate poses are further verified and refined by matching the relative gradient images through an iterative energy- minimization procedure. This approach based on the matching of relative gradients is robust against nonuniform illumination variations. Experimental results on both simulated and real images are shown to demonstrate superior efficiency and robustness of the proposed algorithm over the conventional normalized correlation method.

Use of vector polygons for the accuracy assessment of pixel-based land cover maps

Identifying appropriate validation sources for large-area land cover products is a challenge, with logistical constraints frequently necessitating the use of preexisting data sources. Several issues exist when comparing polygon (vector-based) datasets to raster imagery: geolocational mismatches, differences in features or classes mapped, disparity between the scale of polygon delineation and the spatial resolution of the image, and temporal discrepancies. To evaluate the potential impact of using vector coverages to assess the accuracy of pixel-based land cover maps, five evaluation protocols are applied to test sites located in British Columbia and Newfoundland and Labrador, Canada. One protocol directly compared the land cover of the sample unit to the land cover of the forest inventory polygon within which the sample unit fell, two protocols used different regions around the sample unit to define the land cover class, and two protocols were based on homogeneity criteria that restricted the selection of sample units. For the protocols tested, the overall accuracy values ranged from 34% to 58%. Given the broad range of accuracies achieved, the results suggest that caution is needed when making spatially explicit comparisons between raster and vector datasets. When possible, the use of purpose-collected validation data is recommended for the accuracy assessment of maps derived from remotely sensed data; if preexisting vector-based data are the only option for the validation, approaches accounting for the heterogeneity of classes within a given polygon are recommended.

Virtual Hydrocarbon and Combinatorial Databases for Use with CAVEAT

Three new virtual databases have been developed for use with the bond-orientation-based database searching program CAVEAT. These consist of a database of trisubstituted monocyclic hydrocarbons having ethyl, vinyl, and phenyl substituents; a database of unsubstituted bicyclic hydrocarbons; and a database of core structures from established combinatorial synthetic methods having hydrogen, ethyl, vinyl, and phenyl substituents at the readily varied positions. Each collection of molecules was subjected to a batch conformational search, minimization, and conversion to a vector database for use with CAVEAT.

Vector analysis theory on landscape pattern ( VATLP)

Landscape indices are popular for the quantification of landscape pattern. However, all landscape indices being used so far are scalar quantities, and measure patterns without considering sufficiently the pattern shape and the directionality together. Based on planar characteristics defined in mechanics such as centroid, moment of inertia, product of inertia and principal axes, vector analysis theory on landscape pattern ( VATLP) is explored here. Firstly, we establish a coordinate system of centroidal principal axes ( CSCPA). Three related new indices including those describing the direction of pattern distribution (patch orientation (PO), vectorial patch orientation (VPO)), and that indicating the shape of patch's equivalent ellipse (eccentric rate (ER)) are deduced. These landscape metrics are then applied to the pattern analysis of the lakes in Qian-an county (the study area), Jilin province, China. The vector-based data sets of the study area come from the National Land Use/Cover Database (NLUCD). The application of the theory help us better understand the pattern formation of the lakes and the related ecological processes that occur on both ends of the major principal axis, e.g., the transportation of energy and materials flow, and the ecological gradients.

Runoff mapping using WEPP erosion model and GIS tools

Soil erosion, associated with environmental impacts and crop productivity loss, is usually considered the most impacting of surface hydrology processes. Runoff plays a major role in the erosion process, but it is also important by itself as it directly influences several surface hydrologic processes. In this paper, a computer interface (Erosion Database Interface, EDI) is described that allows processing the surface hydrology output database of the Water Erosion Prediction Project (WEPP) erosion prediction model, resulting in a georeferenced estimation of runoff. WEPP output contains non-georeferenced daily information about estimated runoff at the lower end of each Overland Flow Element. EDI, when running with WEPP, allows extracting WEPP-calculated runoff values, transforming them into annual means and relocating them in a georeferenced database readable by Geographic Information Systems (GIS). EDI was applied to a 1990 ha watershed in southeast Brazil, with vegetation of mainly sugarcane, forest, and pasture. A 100-year climate simulation was used as input to WEPP, and erosion values were calculated at about six points per hectare and interpolated to a raster format. EDI was successful in preparing the database for automatic calculation of erosion and hydrologic parameters with WEPP and to restore georeferences to mean annual accumulated runoff data that were imported in the GIS as a vector database. Of all the resulting maps, the runoff map is the one that integrates all of the input parameters required for WEPP simulation, thus reflecting not only the physical environment but also crop growth and management and tillage operations. A very small correlation between runoff and erosion shows them to behave independently. Moreover, it is concluded that on analyzing runoff related to agricultural management, georeferenced runoff studies are especially important. In this context, EDI may be a useful tool to assess the effect of tillage and crop management on runoff production.

Evaluation of Wildfire Mapping with NOAA/AVHRR Data by Land Cover Types and Eco-Regions in California

In order to determine the efficacy of archived remotely sensed data to create historic fire maps, this study compares a remote sensing based wildland fire map with an historical fire database for California, USA. Fires occurring in two years (1996 and 1999) were mapped using data obtained from the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. A vector database of fire perimeters, compiled and maintained by the State of California was obtained as a source of comparison for the AVHRR based fire map. The two datasets were overlaid and spatially compared in seven land cover types and ten ecoregions. The sources of disagreement and overlap between the datasets were quantified in order to elucidate trends in fire detection algorithm performance over the land cover types and ecoregions. Various methods of vector based comparison were examined in order to more effectively describe the spatial relationships between the two fire maps. The results show that algorithm performance varies over both ecosystem type and geographic region of California. The remote sensing method was able to map between 62% and 74% (1999 and 1996, respectively) of fire area mapped in the State maintained database. There was between 40% and 45% (1999 and 1996, respectively) of geographic overlap in the datasets. The results illustrate the need to calibrate remotely sensed algorithms by ecosystem type and geographic location in order to more effectively produce historic fire map products for research and other purposes.

Fuzzy vector median-based surface smoothing

This paper proposes a novel approach for smoothing surfaces represented by triangular meshes. The proposed method is a two-step procedure: surface normal smoothing through fuzzy vector median (FVM) filtering followed by integration of surface normals for vertex position update based on the least square error (LSE) criteria. Median and Order Statistic-based filters are extensively used in signal processing, especially image processing, due to their ability to reject outliers and preserve features such as edges and monotonic regions. More recently, fuzzy ordering theory has been introduced to allow averaging among similarly valued samples. Fuzzy ordering theory leads naturally to the fuzzy median, which yields improved noise smoothing over traditional crisp median filters. This paper extends the fuzzy ordering concept to vector-based data and introduces the fuzzy vector median filter. The application of FVM filters to surface normal smoothing yields improved results over previously introduced normal smoothing algorithms. The improved filtering results, coupled with LSE vertex position update, produces surface smoothing that minimizes the effects of noise while simultaneously preserving detail features. The proposed method is simple to implement and relatively fast. Simulation results are presented showing the performance of the proposed method and its advantages over commonly used surface smoothing algorithms. Additionally, optimization procedures for FVM filters are derived and evaluated.

Edge detection in multispectral images using the self-organizing map

In this paper, two new methods for edge detection in multispectral images are presented. They are based on the use of the self-organizing map (SOM) and a grayscale edge detector. With the 2-dimensional SOM the ordering of pixel vectors is obtained by applying the Peano scan, whereas this can be omitted using the 1-dimensional SOM. It is shown that using the R-ordering based methods some parts of the edges may be missed. However, they can be found using the proposed methods. Using them it is also possible to find edges in images which consist of metameric colors. Finally, it is shown that the proposed methods find the edges properly from real multispectral airplane images The size of the SOM determines the amount of found edges. If the SOM is taught using a large color vector database, the same SOM can be utilized for numerous images.

A GIS for the assessment of the spatio-temporal changes of the Kotychi lagoon, western Peloponnese, Greece

Kotychi lagoon, located at the northwestern coast of Peloponnese, Greece, is a biotope of great ecological and financial importance,protected by the Ramsar International Convention. Kotychi lagoon hasbeen severely degraded and transformed during the past 50 years, due to agricultural activities in the surrounding areas and watercourse alterations after the construction of Pinios river dam in the late 60's. Restoration works (dredging of a hibernation basin and five radial submerged channels) in the period 1989–1992, resulted in the improvement of the lagoon conditions and provided better conditions for the protection of the ecosystem. In this article, a Geographical Information System has been developed to quantify and spatially characterize the temporal changes on lagoon morphology and surface area for the period from 1945 to 1993. The vector database model of the ARC/INFO has enhanced for the handling the temporal changes of the spatial data. Spatial and thematic information concerning the surface area, topography, and the major cover types of the lagoon for years 1945, 1960, 1987 and 1993 was obtained from aerial photographs and land surveys of the area, and was stored in the GIS database. From the spatio-temporal analysis of the stored data, using as a reference surface the lagoon surface at the year 1945, the following conclusions can be drawn. A permanent decrease of the water surface of the lagoon has been observed between the years 1945 and 1987 (from 97.8 to 40.3% of the lagoon reference surface). In 1987 the surface of the lagoon covered by land or swampy areas reached its maximum (59.7% of the reference surface), while in 1993, after the restoration works, the water surface reached the 48.4% while the land and swampy areas decreased to 51.6% of the reference surface.