Organization profile

Profile Information

The department of Geo-information Processing (GIP) deals with the technological and methodological aspects of geo-information processing and infrastructure to solve complex application problems and to develop technology-oriented concepts for the new geo-information society.

Fingerprint The fingerprint is based on mining the text of the scientific documents related to the associated persons. Based on that an index of weighted terms is created, which defines the key subjects of research unit

ecosystem service Earth & Environmental Sciences

time series Earth & Environmental Sciences

modeling Earth & Environmental Sciences

Semantics Engineering & Materials Science

Processing Engineering & Materials Science

Sensors Engineering & Materials Science

smallholder Earth & Environmental Sciences

Earth (planet) Engineering & Materials Science

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Profiles

Ellen-Wien Augustijn

Department of Geo-information Processing - Lecturer, Researcher
Faculty of Geo-Information Science and Earth Observation - Researcher, Lecturer
UT-I-ITC-STAMP - Researcher

Person: Academic

Amsale Zelalem Bayih

Department of Geo-information Processing - Standard PhD Candidate, Foreign Scholarship PhD Candidate
Faculty of Geo-Information Science and Earth Observation - Standard PhD Candidate
UT-I-ITC-STAMP - Standard PhD Candidate

Person: Academic, PNUT

Luis Filipe Calisto

Person: Administrative

Research Output 1978 2019

Cyber Literacy for GIScience: Toward Formalizing Geospatial Computing Education

Shook, E., Bowlick, F. J., Kemp, K. K., Ahlqvist, O., Carbajeles-dale, P., Dibiase, D., Kim, E., Lathrop, S., Ricker, B. A., Rickles, P., Rush, J., Swift, J. N. & Wang, S., Jan 2019, In : The professional geographer. p. 1-18 18 p.

Research output: Contribution to journal › Article › Academic › peer-review

literacy

education

innovation

learning

citizen

Defining a Cartographer: column

Kraak, M. J., 2019, In : ARC news. Winter 2019, p. 33 1 p.

Research output: Contribution to journal › Article › Professional

Evaluating the performance of a Random Forest Kernel for land cover classification

Zafari, A., Zurita-Milla, R. & Izquierdo-Verdiguier, E., 1 Mar 2019, In : Remote sensing. 11, 5, p. 1-20 20 p., 575.

Research output: Contribution to journal › Article › Academic › peer-review

Open Access

File

land cover

support vector machine

vegetation index

AVIRIS

matrix

Activities 2018 2018

1 Oral presentation

Building a WebVR environment to bring historical shipping data alive

Luis Calisto (Speaker), Ieva Dobraja (Contributor), Yuhang Gu (Contributor), Andreas Weber (Contributor), Jelle van Lottum (Contributor), Marti Huetink (Contributor), Menno-Jan Kraak (Contributor)

31 Aug 2018

Activity: Talk or presentation › Oral presentation