PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
May 2018
231
PHOTOGRAMME TR I C ENG I NE ER I NG & REMOT E SENS I NG
The official journal for imaging and geospatial information science and technology
May 2018 Volume 84 Number 5
FEATURES
PEER-REVIEWED ARTICLES
COLUMNS
This month we look at The Republic of Poland.
ANNOUNCEMENTS
Join us in welcoming our newest members to
ASPRS.
DEPARTMENTS
Karsten Vogt, Andreas Paul, Jörn Ostermann, Franz Rottensteiner,
and
Christian Heipke
The creation of training sets for supervised machine learning.
Alina E. Maas, Franz Rottensteiner, Christian Heipke,
and
Abdalla
Alobeid
A method that helps to distinguish between real changes over time and false detections
caused by misclassification.
Lukas Drees, Ribana Roscher,
and
Susanne Wenzel
The quantification of land cover fractions in an urban area using simulated hyperspectral
EnMAP data.
C. Becker, E. Rosinskaya, N. Häni, E. d’Angelo,
and
C. Strecha
A powerful method to extract per-point semantic class labels from aerial photogramme-
try data.
Timo Hackel, Jan Dirk Wegner, Nikolay Savinov, Lubor Ladicky, Konrad
Schindler,
and
Marc Pollefeys
A review of current state-of-the-art 3D point cloud classification.
C. H. Yang, B. K. Kenduiywo,
and
U. Soergel
A novel technique to identify disappearing and emerging PS points, which are regarded
as building changes in cities.
By Yuri Raizman, Phase One Industrial, Denmark
uest Editors Christian Heipke, Karsten Jacobsen, and Franz
Rottensteiner, Uwe Stilla, Michael Ying Yang, Jan Skaloud, Ismael Colomina, and
Michael Cramer
FOV
2α1
2α2
Orthophoto area
L1
L2
