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Institution

ITC Enschede

About: ITC Enschede is a based out in . It is known for research contribution in the topics: Geographic information system & Land cover. The organization has 231 authors who have published 244 publications receiving 7994 citations. The organization is also known as: University of Twente, Faculty of Geo-Information Science and Earth Observation.


Papers
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Journal ArticleDOI
01 Feb 2012-Sensors
TL;DR: The calibration of the Kinect sensor is discussed, and an analysis of the accuracy and resolution of its depth data is provided, based on a mathematical model of depth measurement from disparity.
Abstract: Consumer-grade range cameras such as the Kinect sensor have the potential to be used in mapping applications where accuracy requirements are less strict. To realize this potential insight into the geometric quality of the data acquired by the sensor is essential. In this paper we discuss the calibration of the Kinect sensor, and provide an analysis of the accuracy and resolution of its depth data. Based on a mathematical model of depth measurement from disparity a theoretical error analysis is presented, which provides an insight into the factors influencing the accuracy of the data. Experimental results show that the random error of depth measurement increases with increasing distance to the sensor, and ranges from a few millimeters up to about 4 cm at the maximum range of the sensor. The quality of the data is also found to be influenced by the low resolution of the depth measurements.

1,671 citations

Journal ArticleDOI
TL;DR: The results show that self-organized vegetation patterns observed in arid ecosystems might all be the result of spatial self-organization, caused by one single mechanism: water infiltrates faster into vegetated ground than into bare soil, leading to net displacement of surface water to vegetated patches.
Abstract: Scientists are still searching for possible unifying mechanisms to explain this range of spatial patterns (Tongway and Ludwig 2001), and an important question of this research is whether this range is the result of preexisting environmental heterogeneity, the result of spatial selforganization, or both (Klausmeier 1999; Couteron and Lejeune 2001; HilleRisLambers et al. 2001; Von Hardenberg et al. 2001). Here, we contribute to the ongoing debate about vegetation pattern formation in arid ecosystems by presenting novel, spatially explicit model analyses and results, extending on the work of HilleRisLambers et al. (2001). Our results show that these different vegetation patterns observed in arid ecosystems might all be the result of spatial self-organization, caused by one single mechanism: water infiltrates faster into vegetated ground than into bare soil, leading to net displacement of surface water to vegetated patches. This model differs from earlier model results (Klausmeier 1999; Couteron and Lejeune 2001; HilleRisLambers et al. 2001; Von Hardenberg et al. 2001) primarily in two ways: it is fully mechanistic, and it treats the lateral flow of water above and below the soil as separate, not independent, variables. Although the current model greatly simplifies the biophysics of arid systems, it can reproduce the whole range of distinctive vegetation patterns as observed in arid ecosystems, indicating that the proposed mechanism might be generally applicable. We further show that self-organized vegetation patterns can persist far into regions of high aridity, where plants would become extinct if homogeneously distributed, pointing to the importance of this mechanism for maintaining productivity of arid ecosystems (Noy-Meir 1973). Our analyses are based on the model first developed in HilleRisLambers et al. (2001)

641 citations

Journal ArticleDOI
01 Mar 2011-Sensors
TL;DR: The recent developments of the new generation of the Sensor Web Enablement specification framework are illustrated and related to other emerging concepts such as the Web of Things and point out challenges and resulting future work topics for research on Sensor Web enablement.
Abstract: Many sensor networks have been deployed to monitor Earth’s environment, and more will follow in the future. Environmental sensors have improved continuously by becoming smaller, cheaper, and more intelligent. Due to the large number of sensor manufacturers and differing accompanying protocols, integrating diverse sensors into observation systems is not straightforward. A coherent infrastructure is needed to treat sensors in an interoperable, platform-independent and uniform way. The concept of the Sensor Web reflects such a kind of infrastructure for sharing, finding, and accessing sensors and their data across different applications. It hides the heterogeneous sensor hardware and communication protocols from the applications built on top of it. The Sensor Web Enablement initiative of the Open Geospatial Consortium standardizes web service interfaces and data encodings which can be used as building blocks for a Sensor Web. This article illustrates and analyzes the recent developments of the new generation of the Sensor Web Enablement specification framework. Further, we relate the Sensor Web to other emerging concepts such as the Web of Things and point out challenges and resulting future work topics for research on Sensor Web Enablement.

469 citations

Journal ArticleDOI
TL;DR: It is argued that cognitive and usability issues should be considered in the context of six major research themes: 1) geospatial virtual environments (GeoVEs); 2) dynamic representations (including animated and interactive maps); 3) metaphors and schemata in user interface design; 4) individual and group differences; 5) collaborative geovisualization; and 6) evaluating the effectiveness of geov isualization methods.
Abstract: We provide a research agenda for the International Cartographic Association's Commission on Visualization and Virtual Environment Working Group on Cognitive and Usability Issues in Geovisualization. Developments in hardware and software have led to (and will continue to stimulate) numerous novel methods for visualizing geospatial data. It is our belief that these novel methods will be of little use if they are not developed within a theoretical cognitive framework and iteratively tested using usability engineering principles. We argue that cognitive and usability issues should be considered in the context of six major research themes: 1) geospatial virtual environments (GeoVEs); 2) dynamic representations (including animated and interactive maps); 3) metaphors and schemata in user interface design; 4) individual and group differences; 5) collaborative geovisualization; and 6) evaluating the effectiveness of geovisualization methods. A key point underlying our use of theoretical cognitive principles is tha...

343 citations

Journal ArticleDOI
Isaak S. Zonneveld1
TL;DR: A land unit survey is a method for efficient survey of land attributes, such as soils, vegetation, landform, expressed in either separate or combined maps; a means of stimulating integration among separate land attribute sciences; an efficient basis for land evaluation.
Abstract: The land unit, as an expression of landscape as a system, is a fundamental concept in landscape ecology. It is an ecologically homogeneous tract of land at the scale at issue. It provides a basis for studying topologic as well as chorologic landscape ecology relationships. A land unit survey aims at mapping such land units. This is done by simultaneously using characteristics of the most obvious (mappable) land attributes: land-form, soil and vegetation (including human alteration of these three). The land unit is the basis of the map legend but may be expressed via these three land attributes. The more dynamic land attributes, such as certain animal populations and water fluxes, are less suitable as diagnostic criteria, but often link units by characteristic information/energy fluxes. The land unit survey is related to a further development of the widely accepted physiographic soil survey see Edelman (1950). Important aspects include: by means of a systems approach, the various land data can be integrated more appropriately; geomorphology, vegetation and soil science support each other during all stages (photo-interpretation, field survey, data processing, final classification); the time and costs are considerably less compared with the execution of separate surveys; the result is directly suitable as a basis for land evaluation; the results can be expressed in separate soil, vegetation, land use and landform maps, or even single value maps. A land unit survey is therefore: a method for efficient survey of land attributes, such as soils, vegetation, landform, expressed in either separate or combined maps; a means of stimulating integration among separate land attribute sciences; an efficient basis for land evaluation. For multidisciplinary projects with applied ecologic aims (e.g., land management), it is therefore the most appropriate survey approach. Within the land unit approach there is considerable freedom in the way in which the various land attribute data are ‘integrated’. It is essential, however, that: during the photo-interpretation stage, the contributions of the various specialists are brought together to prepare a preliminary (land unit) photo-interpretation map; the fieldwork data are collected at exactly the same sample point, preferably by a team of specialists in which soil, vegetation and geomorphology are represented; the final map is prepared in close cooperation of all contributing disciplines, based on photo-interpretation and field data; the final map approach may vary from one fully-integrated land unit map to various monothematic maps.

288 citations


Authors

Showing all 231 results

NameH-indexPapersCitations
Xiang Zhang1541733117576
Andrew K. Skidmore8452929944
Emmanuel John M. Carranza5926210898
Alfred Stein5848813146
Zhongbo Su5237711914
George Vosselman5021911244
Paul J.M. Havinga4944911299
Jan G. P. W. Clevers482238616
Lalit Kumar4738111014
Norman Kerle441606491
Wenzhong Shi444248376
Victor Jetten421456033
Jantien Stoter402795820
C.J. van Westen392008213
Sisi Zlatanova382695278
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20201
20191
20182
20172
20152
20142