Geographic information technology usage in developing countries – A case study in Mozambique

ABSTRACT

Geographic information technologies (GIT) have matured, have become pervasive throughout many types of organizations over recent decades and gained a wide range of attention in diverse sectors of society. The goal of this paper is to identify the main drivers and uses of GIT in organizations and to give an overview of GIT uses in developing countries with a focus on a case study developed for Mozambique by analyzing the results of a survey of 123 Mozambican organizations that are current GIT users. The results show that the main drivers behind are compatibility, complexity, competitive pressure, donor pressure, government policy, intention to adopt, innovation, relative advantage, security, and technology competence. Organizations of the public and private sectors use GIT for customer/resource/risk management, decision support, education, research, monitoring, prediction, simulation, suitability analysis, sustainability, use and access.     

Image matching as a data source for forest inventory – Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method.Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.     

The end of a paradigm: is Zipf’s law universal?

It is largely accepted among geographers and economists that the City Size Distribution (CSD) is well described by a power law, i.e., Zipf’s law. This opinion is shared by this community in a manner it could be treated as a paradigm. In reality, however, Zipf’s law is not always observed (even as an approximation), and we prefer to adopt a classification of the CSD into three classes. In this work, we present the characteristics of these classes and give some examples for them. We use the Israeli system of cities as an interesting case study in which the same ensemble of cities passes from one class to another. We relate this change to the urbanization process that occurred in Israel from the 1960s onwards.     

Virtual representations of antique globes – new ways of touching the untouchable

Abstract

The starting point of this paper is the idea that a comprehensive understanding of the earth and its systems calls for consideration of bygone views of the world. Creating facsimiles of antique globes in the form of digital globes provides a new opportunity to make such bygone world views accessible to a wide scientific audience. However, up to now, little practical experience in applying digital technology on globes has been made. Considering these attempts by thorough synopsis, this article deduces a comprehensive approach on virtual representations of antique globes that can be described by the superordinate concept of virtual representation. This concept comprises facilities of data acquisition of the original globe, ways of visualising the digitised globe and its final cartographic preparation. Applications that arise from this procedure are exemplified through both virtual hyperglobes and tactile hyperglobes. New findings on a 16th century earth globe are encouraging results of the presented virtual representation approach, which may offer a sustainable visualisation platform of interdisciplinary research.     

Geographic information system for semi‐detailed mapping of soils in a semi‐arid region

Abstract

The paper presents a GIS model for mapping soils in the semi arid region of Israel. The model is based on a priori knowledge of the soil generating factors in the study area, namely (1) the parent‐material (lithology) which determines the origin of the soil; and (2) the relief (including the drainage patents) which is responsible for erosion, deposition, and leaching processes along the catena. A special attempt was made to represent soil belts in small subwatersheds with different parent‐material. The width of these belts can be varied as a function of the local relief.

We believe that GIS techniques, in contrast to conventional survey and mapping methods, have the potential to overcome the manpower and fiscal restrictions which limit monitoring of large areas and areas which are for different reasons difficult to access. However, systematically generalizing a spatial model for a large area may introduce some errors, either due to local variations which were not taken into account, or regional variations.     

Analysis of Object Depth Effects on Accuracy of Dimensional Shape in X and Y Directions Using Single Non-metric Image

In general, to reconstruct the accurate shape of buildings, we need at least one stereomodel (two photographs) for each building. In most cases, however, only a single non-metric photograph is availabl...     

Quality aspects of a GPS reference network in Antarctica – a simulation study

GPS has become an essential tool for the precise determination of point positions. Since GPS campaigns for geodynamic purposes – such as the monitoring of recent crustal movements – require major financial efforts, it is essential to ensure already in the planning phase a good network quality and the attainment of the scientific goals in a reasonable time. The paper outlines an operationally oriented procedure for these purposes based on the simulation and processing of GPS carrier-phase observations. Sensitivity analysis techniques are applied to describe both the network strain as it may be induced by gross errors and the detectability of point movements between two sessions or two campaigns. In addition, the eigenvalue decomposition of the variance-covariance matrix of the GPS coordinates will be used to identify weakly determined network components. The design of the SCAR Epoch 95 Campaign GPS network is discussed throughout the paper. It was realized in the Antarctic summer 1994/1995 on the Antarctic peninsula. Received: 30 November 1995 / Accepted: 1 July 1997     

Geoprocessing in Cloud Computing platforms – a comparative analysis

Abstract

The emergence of Cloud Computing technologies brings a new information infrastructure to users. Providing geoprocessing functions in Cloud Computing platforms can bring scalable, on-demand, and cost–effective geoprocessing services to geospatial users. This paper provides a comparative analysis of geoprocessing in Cloud Computing platforms – Microsoft Windows Azure and Google App Engine. The analysis compares differences in the data storage, architecture model, and development environment based on the experience to develop geoprocessing services in the two Cloud Computing platforms; emphasizes the importance of virtualization; recommends applications of hybrid geoprocessing Clouds, and suggests an interoperable solution on geoprocessing Cloud services. The comparison allows one to selectively utilize Cloud Computing platforms or hybrid Cloud pattern, once it is understood that the current development of geoprocessing Cloud services is restricted to specific Cloud Computing platforms with certain kinds of technologies. The performance evaluation is also performed over geoprocessing services deployed in public Cloud platforms. The tested services are developed using geoprocessing algorithms from different vendors, GeoSurf and Java Topology Suite. The evaluation results provide a valuable reference on providing elastic and cost-effective geoprocessing Cloud services.     

Water resource applications with RADARSAT-2 – a preview

Abstract

Fresh water is arguably the most vital resource for many aspects of a healthy and stable environment. Monitoring the extent of surface water enables resource managers to detect perturbations and long term trends in water availability, and set consumption guidelines accordingly. Potential end-users of water-related observations are numerous and reflect society as a whole. They encompass scientists and managers at all levels of government, aboriginal groups, water/power utility managers, farmers, planners, engineers, hydrologists, medical researchers, climate scientists, recreation enthusiasts, public school to post-graduate students, many special interest groups and the general public. Water data and analyses generate information products that benefit water resources planning and management, engineering design, plant operations, navigation activities, health research, water quality assessments and ecosystem management. As well, they serve as inputs for flood and drought warnings and weather and climate prediction models. Radar data in general, and RADARSAT in particular, are very good for detecting open surface water and have been used operationally for flood monitoring in many countries. Significant radar data archives now exist to analyse seasonal, annual and decadal trends, in order to attain a better understanding of the freshwater cycle. Radar data are also useful for wetland classification and soil moisture estimation. With the increasing pressure on water resources, both from a quality as well as a quantity perspective, the need will continue to increase for reliable information.

RADARSAT-2 has several innovations that will enhance the ability to provide useful information about water resources. This paper provides an overview of the use of radar in general, and RADARSAT-2 in particular, for the generation of information products useful to water resource managers.     

Evaluating the performance of a new classifier – the GP-OAD: A comparison with existing methods for classifying rock type and mineralogy from hyperspectral imagery

In this study, we compare three commonly used methods for hyperspectral image classification, namely Support Vector Machines (SVMs), Gaussian Processes (GPs) and the Spectral Angle Mapper (SAM). We assess their performance in combination with different kernels (i.e. which use distance-based and angle-based metrics). The assessment is done in two experiments, under ideal conditions in the laboratory and, separately, in the field (an operational open pit mine) using natural light. For both experiments independent training and test sets are used. Results show that GPs generally outperform the SVMs, irrespective of the kernel used. Furthermore, angle-based methods, including the Spectral Angle Mapper, outperform GPs and SVMs when using distance-based (i.e. stationary) kernels in the field experiment. A new GP method using an angle-based (i.e. a non-stationary) kernel – the Observation Angle Dependent (OAD) covariance function – outperforms SAM and SVMs in both experiments using only a small number of training spectra. These findings show that distance-based kernels are more affected by changes in illumination between the training and test set than are angular-based methods/kernels. Taken together, this study shows that independent training data can be used for classification of hyperspectral data in the field such as in open pit mines, by using Bayesian machine-learning methods and non-stationary kernels such as GPs and the OAD kernel. This provides a necessary component for automated classifications, such as autonomous mining where many images have to be classified without user interaction.     

Geodetic grids in authoritative maps – new findings about the origin of the UTM Grid

ABSTRACT

Recent discoveries of Wehrmacht Maps in the Military Archive of the Federal Archive of Germany in Freiburg im Breisgau raised the motivation for further investigations into the history of the internationally employed Universal Transverse Mercator (UTM) projection which actually represents a prerequisite for the global use of Global Positioning System (GPS) – and thus of any type of navigation – instruments. In contrast to the frequently stated opinion that this map projection was first operationally used by U.S. Americans it turned out that presumably the first operational maps with indication of the orthogonal UTM grid were produced by German Wehrmacht officers prior to the post World War (WW) II triumph of this projection. Based on the authors´ recent discoveries this article reveals some hitherto hardly known facts concerning the history of cartography of the 1940s.     

iGeoTrans – a novel iOS application for GPS positioning in geosciences

The iGeoTrans is an iOS application designed for navigation purposes for iPhone, iPad and iPod Touch. This application uses Global Positioning System (GPS), Assisted GPS system, GLONASS, Wi-Fi and Cellular Network for positioning. The iGeoTrans has included datum transformations and map projections that enable users to convert the collected data between different coordinate systems for almost all areas in the world. In addition, other features are also included such as distance, area measurements, and GPS results could be exported to the AutoCad dxf format for GIS softwares. The average horizontal and vertical root mean square errors (RMSEs) for the static test are around 4.11 and 3.51?m, respectively. The horizontal RMSE for the dynamic outdoor test is around 2.72?m. The iGeoTrans application can be used to support surveying, mapping and geosciences fieldworks for any area in the world.     

Remote sensing of human beings – a perspective from nighttime light

City lights, fishing boats, and oil fields are the major sources of nighttime lights, therefore the nighttime light images provide a unique source to map human beings and their activities from outer space. While most of the scholars focused on application of nighttime light remote sensing in urbanization and regional development, the actual fields are much wider. This paper summarized the applications of nighttime light remote sensing into fields such as the estimation of socioeconomic parameters, monitoring urbanization, evaluation of important events, analyzing light pollution, fishery, etc. For estimation of socioeconomic parameters, the most promising progress is that Gross Domestic Product and its growth rate have been estimated with statistical data and nighttime light data using econometric models. For monitoring urbanization, urban area and its dynamics can be extracted using different classification methods, and spatial analysis has been employed to map urban agglomeration. As sharp changes of nighttime light are associated with important socioeconomic events, the images have been used to evaluate humanitarian disasters, especially in the current Syrian and Iraqi wars. Light pollution is another hotspot of nighttime light application, as the night light is related to some diseases and abnormal behavior of animals, and the nighttime light images can provide light pollution information on large scales so that it is much easier to analyze the effects of light pollutions. In each field, we listed typical cases of the applications. At last, future studies of nighttime light remote sensing have been predicted.     

Pervasive geo-security – a lightweight triple-A approach to securing distributed geo-service infrastructures

Security has recently become a major concern in distributed geo-infrastructures for spatial data provision. Thus, a lightweight approach for securing distributed low-power environments such as geo-sensor networks is needed. The first part of this article presents a survey of current security mechanisms for authentication and authorisation. Based on this survey, a lightweight and scalable token-based security infrastructure was developed, which is tailored for use in distributed geo-web service infrastructures. The developed security framework comprises dedicated components for authentication, rule-based authorisation and optimised storage and administration of access rules. For validation purposes, a prototypical implementation of the approach has been created.     

How fast is a cow? Cross‐Scale Analysis of Movement Data

Data representing the trajectories of moving point objects are becoming increasingly ubiquitous in GIScience, and are the focus of much methodological research aimed at extracting patterns and meaning describing the underlying phenomena. However, current research within GIScience in this area has largely ignored issues related to scale and granularity – in other words how much are the patterns that we see a function of the size of the looking glass that we apply? In this article we investigate the implications of varying the temporal scale at which three movement parameters, speed, sinuosity and turning angle are derived, and explore the relationship between this temporal scale and uncertainty in the individual data points making up a trajectory. A very rich dataset, representing the movement of 10 cows over some two days every 0.25 s is investigated. Our cross‐scale analysis shows firstly, that movement parameters for all 10 cows are broadly similar over a range of scales when the data are segmented to remove quasi‐static subtrajectories. However, by exploring realistic values of GPS uncertainty using Monte Carlo Simulation, it becomes apparent that fine scale measurement of all movement parameters is masked by uncertainties, and that we can only make meaningful statements about movement when we take these uncertainties into account.