A comparison between analytical aerial photogrammetry,laser scanning,total station and global positioning system surveys for generation of digital terrain model

The present paper compares between four data sources for creating digital terrain models (DTMs), based on analytical aerial photogrammetry, laser scanning, total station (TS) and global positioning system surveys. The case study presents the comparative results obtained using the methods listed above. After obtaining the ground coordinates of points using each method, DTMs were created using Surfer Software to establish comparison consistency. To check accuracy of each method used, a series of 100 independent points were collected at random positions over the case study area using the TS for horizontal position and a digital level for elevation. The comparison of the results of the methods was performed based on accuracy and efficiency aspects. The results have shown that TS and terrestrial laser scanners (TLSs) could represent precise, effective and rapid solutions to produce economical and accurate DTMs. Also, using TLSs allow more various possibilities of data representation.     

Semi-automatic Process for Hybrid DTM Generalization based on Structural Elements Multi-analysis

Abstract

The generalization of digital terrain models (DTMs) is a tool of great potential for simultaneous cartographic and photogrammetry generation processes at different scales, the main object of which is to feed different geographic information systems (GIS). These GIS enable multi-scale analysis and visualization through different data bases. This research proposes a semi-automatic DTM generalization process conditioned by a series of predefined parameters resulting in the generation of hybrid DTMs at different scales starting from a single cloud of points obtained through large-scale massive data acquisition processes. The generalization results obtained, applied on different areas of different relief, offer specific application ranks for each parameter with great precision, in contrast with DTMs obtained directly in each scale.     

Landscape Dynamics in North East Region of India (Meghalaya State) Using Spatial Decision Tree Model

Abstract

India has figured with two hotspots ‐ the Western Ghats and the Eastern Himalayas ‐ in an identification of 8 ‘hottest’ biodiversity hotspots (Myers et. al. 2000). The Meghalaya state (study area) in North Eastern India lies within the “Indo‐Burma” area, which is one of the 8 ‘hottest’ biodiversity hotspots. Timber extraction, the age‐old practice of shifting cultivation and mining has been a major cause of extensive changes in this landscape. Human induced disturbance differs from natural disturbance especially in extension, severity and frequency. Spatial presentation of landscape dynamics can be used to infer disturbance regimes horizontally. Disturbance regimes are mostly dominated by landuse practices in Meghalaya and these landuse practices are important contributors for overall interpretation of ecological processes operating within the landscape. In this scenario, the development of models to study landscape dynamics using remote sensing and GIS would be of great importance to ecologists. In this paper, we make an attempt to characterize landscape dynamics using a decision tree based approach. The varying impacts of human interventions reflected in three zones at landscape level have been brought out in the present study. The physiographic zones of Meghalaya (viz. Garo hills, Khasi hills and Jaintia hills) manifest different landscape characteristics and present varying degree of degradation status. Garo hills, experiences maximum shifting cultivation and has shown highest dynamism in the study area followed by Jaintia and Khasi hills. Characterization of landscape dynamics is important in the perspective of decision makers and policy makers in order to prioritize conservation strategies, so that urgent and necessary action can be taken.     

Creation of DTM with ASTER Data and Statistical Verification of the Accuracy of the Model (Western Peloponnese,Greece)

Abstract

In this paper we present the use of ASTER data for the creation of a Digital Terrain Model (DMT) of high accuracy. Using a stereo pair of ASTER satellite images with 15m resolution we created two DMTs: one with a 30m pixel size and another one with a 15m pixel size. Then we made a statistical verification of the two DTMs accuracy. We created another DTM with 30m pixel size from digitized contours of 1:50000 scale topographic maps. We first made an optical comparison of the two DTMs with 30m pixel size. Then we subtracted the two DTMs and we presented their difference. Finally, we verified the DTMs accuracy using 68 points of a well‐known elevation. All the results demonstrated that DTMs derived from ASTER data have very good accuracy.     

3D Visualization for the Analysis of Forest Cover Change

Abstract

Visualization techniques have been developed to recreate natural landscapes, but little has been done to investigate their potential for illustrating land cover change using spatio‐temporal data. In this work, remote sensing, geographic information systems (GIS) and visualization techniques were applied to generate realistic computer visualizations depicting the dynamic nature of forested environments. High resolution digital imagery and aerial photography were classified using object‐oriented methods. The resulting classifications, along with preexisting land cover datasets, were used to drive the correct placement of vegetation in the visualized landscape, providing an accurate representation of reality at various points in time. 3D Nature's Visual Nature Studio was used to construct a variety of realistic images and animations depicting forest cover change in two distinct ecological settings. Visualizations from Yellowstone National Park focused on the dramatic impact of the 1988 fire upon the lodgepole pine forest. For a study area in Kansas, visualization techniques were used to explore the continuous human‐land interactions impacting the eastern deciduous forest and tallgrass prairie ecotone between 1941 and 2002. The resulting products demonstrate the flexibility and effectiveness of visualizations for representing spatio‐temporal patterns such as changing forest cover. These geographic visualizations allow users to communicate findings and explore new hypotheses in a clear, concise and effective manner.     

How does co-registration affect geomorphic change estimates in multi-temporal surveys?

ABSTRACT

High-Resolution Topography (HRT) data sets are becoming increasingly available, improving our ability and opportunities to monitor geomorphic changes through multi-temporal Digital Terrain Models (DTMs). The use of repeated topographic surveys enables inferring the sediment dynamics of hazardous geomorphic processes such as floods, debris flows, and landslides, and allows us to derive important information on the risks often associated with these processes. The topographic surveying platforms, georeferencing systems, and processing tools have seen important developments in the last two decades, in particular Light Detection And Ranging (LiDAR) technology used in Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS). Moreover, HRT data, produced through these techniques, changed a lot in terms of point cloud density, accuracy and precision over time. Therefore, old “legacy” data sets and recent surveys can often show comparison problems, especially when multi-temporal data are not homogeneous in terms of quality and uncertainties. In this context, data co-registration should be used to guarantee the coherence among multi-temporal surveys, minimizing, on stable areas, the distance between corresponding points acquired at different epochs. Although several studies highlight that this process is fundamental to properly compare multi-temporal DTMs, it is often not addressed in LiDAR post-processing workflows. In this paper we focus on the alignment of multi-temporal surveys in a topographically complex and rugged environment as the Moscardo debris-flow catchment (Eastern Italian Alps), testing various co-registration methods to align multi-temporal ALS point clouds (i.e. years 2003, 2009 and 2013) and the derived DTMs. In particular, we tested the pairwise registration with manual correspondences, the Iterative Closest Point (ICP) algorithm and a mathematical model that allows aligning simultaneously a generic number of point clouds, the so-called Generalized Procrustes Analysis (GPA), also in its GPA-ICP variant. Then, to correct the possible small inaccuracies generated from the gridding interpolation process, a custom-developed DTM co-registration tool (GRD-CoReg) was used to align gridded data. Both alignment phases (i.e. at point cloud and DTM level) proved to be fundamental and allowed us to obtain proper and reliable DTMs of Difference (DoDs), useful to quantify the debris mobilized and to detect the spatial and temporal patterns of catchment-scale erosion and deposition. The consistency of DoDs data was verified through the comparison between the erosion estimate of DoDs and the volumes of debris-flow events measured by the monitoring station close to the Moscardo torrent catchment outlet. The GPA-ICP algorithm followed by the GRD-CoReg tool proved to be the most effective solution for improving DoDs results with a decrease of systematic trend due to vertical and horizontal uncertainties between surveys, especially at steep slopes. The net volume difference (i.e. the sediment output from the catchment) of the 2003–2013 period changed from 3,237,896 m³ to 135,902 m³ in DoDs obtained from not co-registered and co-registered DTMs. The volume of debris flows measured at the catchment outlet during the same time interval amounts to 169,660 m³. The comparison with debris-flow volume measures at the monitoring station shows, therefore, that the DTMs obtained from the co-registration processes generate more reliable DoDs than those obtained from the raw DTMs (without the alignment).     

Very high resolution Earth Observation features for testing the direct and indirect effects of landscape structure on local habitat quality

Modelling the empirical relationships between habitat quality and species distribution patterns is the first step to understanding human impacts on biodiversity. It is important to build on this understanding to develop a broader conceptual appreciation of the influence of surrounding landscape structure on local habitat quality, across multiple spatial scales. Traditional models which report that ‘habitat amount’ in the landscape is sufficient to explain patterns of biodiversity, irrespective of habitat configuration or spatial variation in habitat quality at edges, implicitly treat each unit of habitat as interchangeable and ignore the high degree of interdependence between spatial components of land-use change. Here, we test the contrasting hypothesis, that local habitat units are not interchangeable in their habitat attributes, but are instead dependent on variation in surrounding habitat structure at both patch- and landscape levels. As the statistical approaches needed to implement such hierarchical causal models are observation-intensive, we utilise very high resolution (VHR) Earth Observation (EO) images to rapidly generate fine-grained measures of habitat patch internal heterogeneities over large spatial extents. We use linear mixed-effects models to test whether these remotely-sensed proxies for habitat quality were influenced by surrounding patch or landscape structure. The results demonstrate the significant influence of surrounding patch and landscape context on local habitat quality. They further indicate that such an influence can be direct, when a landscape variable alone influences the habitat structure variable, and/or indirect when the landscape and patch attributes have a conjoined effect on the response variable. We conclude that a substantial degree of interaction among spatial configuration effects is likely to be the norm in determining the ecological consequences of habitat fragmentation, thus corroborating the notion of the spatial context dependence of habitat quality.     

The comparison index: A tool for assessing the accuracy of image segmentation

Segmentation algorithms applied to remote sensing data provide valuable information about the size, distribution and context of landscape objects at a range of scales. However, there is a need for well-defined and robust validation tools to assessing the reliability of segmentation results. Such tools are required to assess whether image segments are based on ‘real’ objects, such as field boundaries, or on artefacts of the image segmentation algorithm. These tools can be used to improve the reliability of any land-use/land-cover classifications or landscape analyses that is based on the image segments.The validation algorithm developed in this paper aims to: (a) localize and quantify segmentation inaccuracies; and (b) allow the assessment of segmentation results on the whole. The first aim is achieved using object metrics that enable the quantification of topological and geometric object differences. The second aim is achieved by combining these object metrics into a ‘Comparison Index’, which allows a relative comparison of different segmentation results. The approach demonstrates how the Comparison Index CI can be used to guide trial-and-error techniques, enabling the identification of a segmentation scale H that is close to optimal. Once this scale has been identified a more detailed examination of the CI–H- diagrams can be used to identify precisely what H value and associated parameter settings will yield the most accurate image segmentation results.The procedure is applied to segmented Landsat scenes in an agricultural area in Saxony-Anhalt, Germany. The segmentations were generated using the ‘Fractal Net Evolution Approach’, which is implemented in the eCognition software.     

Toward an integrated framework for geosensor grid

Abstract

Grid computing is deemed as a good solution to the digital earth infrastructure. Various geographically dispersed geospatial resources can be connected and merged into a ‘supercomputer’ by using the grid-computing technology. On the other side, geosensor networks offer a new perspective for collecting physical data dynamically and modeling a real-time virtual world. Integrating geosensor networks and grid computing in geosensor grid can be compared to equipping the geospatial information grid with ‘eyes’ and ‘ears.’ Thus, real-time information in the physical world can be processed, correlated, and modeled to enable complex and advanced geospatial analyses on geosensor grid with capability of high-performance computation. There are several issues and challenges that need to be overcome before geosensor grid comes true. In this paper, we propose an integrated framework, comprising the geosensor network layer, the grid layer and the application layer, to address these design issues. Key technologies of the geosensor grid framework are discussed. And, a geosensor grid testbed is set up to illustrate the proposed framework and improve our geosensor grid design.     

High Resolution DEM Generation in High‐Alpine Terrain Using Airborne Remote Sensing Techniques

Up‐to‐date and accurate digital elevation models (DEMs) are essential for many applications such as numerical modeling of mass movements or mapping of terrain changes. Today the Federal Department of Topography, swisstopo, provides Digital Terrain Models (DTMs) and Digital Surface Models (DSMs) derived from airborne LiDAR data with a high spatial resolution of 2 m covering the entire area of Switzerland below an elevation of 2000 m a.s.l.. However, above an elevation of 2000 m a.s.l., which is typical for high‐alpine terrain, the best product available is the a DTM with a spatial resolution of 25 m. This spatial resolution is insufficient for many applications in complex terrain. In this study, we investigate the quality of DSMs derived from opto‐electronic scanner data (ADS80; acquired in autumn 2010) using photogrammetric image correlation techniques based on the multispectral nadir and backward looking sensor data. As reference, we take a high precision airborne LiDAR data set with a spatial resolution of ca. 0.5 m, acquired in late summer 2010, covering the Grabengufer/Dorfbach catchment near Randa, VS. We find the deviations between the two datasets are surprisingly low. In terrain with inclination angles of less than 30° the RMSE is below 0.5 m. In extremely steep terrain of more than 50° the RMSE goes up to 2 m and outliers increase significantly. We also find dependencies of the deviations on illumination conditions and ground cover classes. Finally we discuss advantages and disadvantages of the different data acquisition methods.     

Generation and evaluation of multitemporal digital terrain models of the Mt. Everest area from different optical sensors

Multitemporal digital terrain models (DTM) are an important source for many purposes such as the detection of areas, which are susceptible to natural hazards such as landslides and glacial lake outburst floods, or for the examination of changes in glacier thickness. To exploit the potential of stereo satellite and aerial imagery for time series analysis, the employed methodology and software can be critical. A statistical analysis based on quartiles is presented to eliminate the influence of registration and elevation errors in DTMs. For our analysis, we used multi-temporal airborne and spaceborne stereoscopic images. The oldest images were recorded in the 1960s by the US American reconnaissance satellite Corona, while the most recent imagery are 2007 Cartosat-1 stereo scenes, along with one ASTER stereo pair. Complex panoramic distortion and limited spatial resolution resulted in the Corona and ASTER DTMs having the highest RMSEz. Due to differing acquisition techniques, applied software packages and temporal differences DTMs will never be identical. Therefore, we propose a relative vertical accuracy assessment with a master DTM. We chose the Cartosat-1 DTM as it showed the highest absolute accuracy. Inaccuracies between the master and the slave DTMs were adjusted by means of trend surfaces and outliers were successfully eliminated applying the interquartile range.     

SPIRIT. SPOT 5 stereoscopic survey of Polar Ice: Reference Images and Topographies during the fourth International Polar Year (2007–2009)

Monitoring the evolution of polar glaciers, ice caps and ice streams is of utmost importance because they constitute a good indicator of global climate change and contribute significantly to ongoing sea level rise. Accurate topographic surveys are particularly relevant as they reflect the geometric evolution of ice masses. Unfortunately, the precision and/or spatial coverage of current satellite missions (radar altimetry, ICESat) or field surveys are generally insufficient. Improving our knowledge of the topography of Polar Regions is the goal of the SPIRIT (SPOT 5 stereoscopic survey of Polar Ice: Reference Images and Topographies) international polar year (IPY) project. SPIRIT will allow (1) the acquisition of a large archive of SPOT 5 stereoscopic images covering most polar ice masses and, (2) the delivery of digital terrain models (DTM) to the scientific community.Here, we present the architecture of this project and the coverage achieved over northern and southern polar areas during the first year of IPY (July 2007 to April 2008). We also provide the first accuracy assessments of the SPIRIT DTMs. Over Jakobshavn Isbrae (West Greenland), SPIRIT elevations are within ±6 m of ICESat elevations for 90% of the data. Some comparisons with ICESat profiles over Devon ice cap (Canada), St Elias Mountains (Alaska) and west Svalbard confirm the good overall quality of the SPIRIT DTMs although large errors are observed in the flat accumulation area of Devon ice cap. We then demonstrate the potential of SPIRIT DTMs for mapping glacier elevation changes. The comparison of summer-2007 SPIRIT DTMs with October-2003 ICESat profiles shows that the thinning of Jakobshavn Isbrae (by 30–40 m in 4 years) is restricted to the fast glacier trunk. The thinning of the coastal part of the ice stream (by over 100 m) and the retreat of its calving front (by up to 10 km) are clearly depicted by comparing the SPIRIT DTM to an ASTER April-2003 DTM.     

Virtual Australia: its key elements – know,think, communicate

Abstract

Virtual Australia is not a well-defined or agreed concept. This discussion paper conceptualises Virtual Australia as a ‘virtual [digital] model containing and representing all non-trivial objects and their contextual environment – from blue sky to bedrock – in real world Australia’. It describes a scenario for Virtual Australia, one or two decades from now, in which the locations and conditions of non-trivial objects and their environment are updated automatically through a combination of remote sensing and wireless communication technologies in support of a ‘Supranet’. It then examines the concept of the ‘Supranet’ – a pervasive information network based largely on wireless technology linking the physical world to a virtual model in real time – and develops and discusses three principal characteristics of the Supranet: the ability to have or collect specific information (know); the ability to process information (think); and the ability to communicate that information. If, in the near future, any or all non-trivial devices are to some extent able to know, think and communicate, the potential for object autonomy will be realised.     

Obituary

Abstract

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In the area of volunteered geographical information (VGI), the issue of spatial data quality is a clear challenge. The data that are contributed to VGI projects do not comply with standard spatial data quality assurance procedures, and the contributors operate without central coordination and strict data collection frameworks. However, similar to the area of open source software development, it is suggested that the data hold an intrinsic quality assurance measure through the analysis of the number of contributors who have worked on a given spatial unit. The assumption that as the number of contributors increases so does the quality is known as ‘Linus’ Law’ within the open source community. This paper describes three studies that were carried out to evaluate this hypothesis for VGI using the OpenStreetMap dataset, showing that this rule indeed applies in the case of positional accuracy.     

The Bulger Case: A Spatial Story

Abstract

This paper contributes to debates in the emerging field of cinematic cartography () by exploring the ways in which strategies of digital cinemapping can function as tools of critical spatial practice and urban wayfinding. More specifically, the paper considers the scope for digital video technologies to reshape, contest and ‘ground’ spaces of urban representation and the ‘spatial stories’ these bring into play. Basing my analysis on the mediation of the events surrounding the abduction and murder of the 2-year-old boy James Bulger in 1993, I examine the case as a constellation of spatial narratives within which I weave my own spatial story in the form of a video mapping of the abduction route (in Bootle near Liverpool) and the responses and issues this further mediation has provoked. Methodological reflections on the map-making process are discussed alongside narratives generated by the video on YouTube. The paper argues that, by adopting practices of wayfinding, and by being critically attentive to the ways in which film and video-making practices are also spatial practices, moving image cartographies can provide insights into lived and embedded spaces of memory, and the hidden or muted spatial stories to which they play host.     

Digital Archiving and On-line Publishing of Old Relief Models

Abstract

Although people rarely think of relief models when speaking about cartographic products, these artefacts are probably the most impressive way of visualizing landscapes. Unlike traditional maps or globes, most relief models are unique, vulnerable hand-made objects. Digital archiving is an important step in their preservation. There are special tools for this task, but these equipments are rather expensive, and libraries or other institutes that usually own these models cannot spend too much. The authors examined various on-line tools to create digital 3D representation of relief models using a set of photographs as source. These tools create point cloud and textured triangle mesh based on matching patterns on the photos. A workflow was developed which uses these web services and produces the digital 3D version of relief models. This paper introduces the method, discusses the details of successful photographing, the possible post-processing of the results. A new web site, using the X3DOM technology to show the digitized models to the general public, is also introduced.     

Sensors,empowerment, and accountability: a Digital Earth view from East Africa

Abstract

Several innovative ‘participatory sensing’ initiatives are under way in East Africa. They can be seen as local manifestations of the global notion of Digital Earth. The initiatives aim to amplify the voice of ordinary citizens, improve citizens' capacity to directly influence public service delivery and hold local government accountable. The popularity of these innovations is, among other things, a local reaction to the partial failure of the millennium development goals (MDGs) to deliver accurate statistics on public services in Africa. Empowered citizens, with access to standard mobile phones, can ‘sense’ via text messages and report failures in the delivery of local government services. The public disclosure of these reports on the web and other mass media may pressure local authorities to take remedial action. In this paper, we outline the potential and research challenges of a ‘participatory sensing’ platform, which we call a ‘human sensor web.’ Digital Africa's first priority could be to harness continent-wide and national data as well as local information resources, collected by citizens, in order to monitor, measure and forecast MDGs.     

基于多分辨率方向预测的LIDAR点云滤波方法

为了快速提取LIDAR点云中的地面点,生成高精度的DTM,提出了一种基于多分辨率方向预测的LIDAR点云滤波方法。该方法首先构建多种分辨率数据集,然后基于方向预测法以分辨率由低到高的顺序逐层进行数据集的平滑处理,最后以最高分辨率数据集的平滑结果为基准标记原始LIDAR点云。本方法通过分析反距离权重插值模型的不足,利用改进的模型进行裸露地面点的插值,得到高精度的DTM。实验表明,本文方法能有效地滤除地物,并保持原有的地形特征,算法效率高,具有一定的实用价值。     

Impact of land-cover layout on particulate matter 2.5 in urban areas of China

ABSTRACT

Urbanization in China is closely connected with ambient particulate matter 2.5 (PM_2.5). However, the potential for altering PM_2.5 through the urban landscape characteristics is uncertain. In this study, we analyzed the urban PM_2.5 pollution situation for 2014–2016 and investigated the impact of landscape factors on urban PM_2.5 in China at the city level. All the prefecture-level cities were stratified by urban population size into small (<500,000), medium (500,000–1,000,000), and large (>1,000,000), and the other second-level administrative cities were assigned as ‘other’ cities. The multivariate regression model including both urban landscape factors and social-economic variables explained 70.0%, 32.8%, 19.2%, and 12.4% of the arithmetic mean PM_2.5 concentration (AMC-PM_2.5) for the other, small, medium, and large cities, respectively. With regard to the configuration of land cover, agricultural activity is a major contributor of PM_2.5 pollution, for which the explanatory power ranged from 7.6% (for the large cities) to 64% (for the other cities). In addition, grassland aggregation also has a limited but negative effect on urban PM_2.5 pollution, despite the negligible effect on dry deposition. Overall, these findings likely reflect the interaction between urban air quality and urbanization, and will have implications for air quality control strategies.     

Cloud computing for integrated stochastic groundwater uncertainty analysis

Abstract

One of the major scientific challenges and societal concerns is to make informed decisions to ensure sustainable groundwater availability when facing deep uncertainties. A major computational requirement associated with this is on-demand computing for risk analysis to support timely decision. This paper presents a scientific modeling service called ‘ModflowOnAzure’ which enables large-scale ensemble runs of groundwater flow models to be easily executed in parallel in the Windows Azure cloud. Several technical issues were addressed, including the conjunctive use of desktop tools in MATLAB to avoid license issues in the cloud, integration of Dropbox with Azure for improved usability and ‘Drop-and-Compute,’ and automated file exchanges between desktop and the cloud. Two scientific use cases are presented in this paper using this service with significant computational speedup. One case is from Arizona, where six plausible alternative conceptual models and a streamflow stochastic model are used to evaluate the impacts of different groundwater pumping scenarios. Another case is from Texas, where a global sensitivity analysis is performed on a regional groundwater availability model. Results of both cases show informed uncertainty analysis results that can be used to assist the groundwater planning and sustainability study.