PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
December 2016
921
Helmert (geocentric) transformation estimated to be better
than ±2 meters relative to the new geodetic framework. The
third level will be a polynomial algorithm with an accuracy
of better than ±0.2 meters relative to the new geodetic
framework. A new National Grid is contemplated based on
the GRS80 ellipsoid, and may be the UTM (Zones 29 & 30).
The Malin Head Vertical Datum of 1970 is the current
system for all 1:50,000 mapping in Ireland. Earlier maps
used the low water mark of the spring tide on the 8th of April,
1837 at Poolbeg Lighthouse, Dublin Bay. The Malin Head
(County Donegal) Datum is approximately 2.71 meters above
the Poolbeg Lighthouse Datum. All large scale mapping in
Northern Ireland uses mean sea level at Belfast which is
0.037 meters below the Malin Head Datum.
U
pdate
The Ordnance Survey of Ireland now has a Co-ordnate (sic)
Converter that will interactively convert the following co-or-
dinate reference systems: WGS84 (World Geodetic System
1984) / ETRF89 (European Terrestrial Reference Frame
1989), Irish Grid, ITM (Irish Transverse Mercator), UTM
(Universal Transverse Mercator). OSGM15 and OSTN15
have updated transformations for UK and Ireland. The
Ordnance Survey of Great Britain (OSGB), Ireland (OSi)
and Land & Property Services (LPS – Formerly OSNI) have
collaborated again to improve the OSGM02 geoid model cov-
ering the United Kingdom and Ireland. A new Geoid model
OSGM15 was launched on the 26th of August 2016.
The polynomial transformation for Ireland and Northern
Ireland has not changed however there are solutions avail-
able for download. Grid Inquest II took over from Grid In-
quest I on the 26th of August 2016.
There is also a developers pack available to download.
The contents of this column reflect the views of the author, who is
responsible for the facts and accuracy of the data presented herein.
The contents do not necessarily reflect the official views or policies of
the American Society for Photogrammetry and Remote Sensing and/
or the Louisiana State University Center for GeoInformatics (C
4
G).
This column was previously published in
PE&RS
.
and monitoring of wetlands. Chapters Six through Ten in
Section Two (
“Summaries of Remote Sensing technologies
and Their Application for Mapping Wetlands
”) are each
devoted to summarizing remote sensing technologies applied
to wetland mapping – such as SAR, InSAR, radar/optical
image fusion, OBIA and the use of the now pervasive UAS
for wetland mapping, and present a solid treatment of the
theoretical underpinnings of each technology.
Section Three (
“Applications of Remote Sensing for Mapping
Specific Wetland Habitats
”) contains Chapters Eleven through
Twenty-Four and presents examples of case studies, specific
and focused applications of remote sensing methods to a
highly diverse number of wetland systems – e.g. from prairie
potholes to Amazonian wetlands to wetlands in the Permafrost,
and from mangrove forests to coastal wetlands to peatlands,
understandably spanning geographies coveringmost continents.
The techniques featured include lidar (e.g. bathymetric), radar,
passive microwave, and multispectral imagery at moderate
resolution; sensors on aerial and satellite platforms are
addressed. Hydrology, geology and soils information come into
play in models utilizing sensor data. The fusion of geomorphic
and terrain derivative data with optical and radar data, and
the use of advanced classification algorithms – notably random
forests, are exemplified. The potentials and limitations of each
approach are explored in detail and supported adequately with
charts and graphs, in addition to maps.
Taking a look at the immediate future, Chapter Twenty-
Five –
“Promising Developments and Future Challenges for
Remote Sensing of Wetlands”
, makes up Section Four in its
entirety. In this chapter the authors take a brief look at each
of the most promising sensors and methodologies, some of
which were touched upon in previous chapters. Several areas
that need attention and development are also identified,
such as for example automated classification techniques and
algorithms, emerging sensors and platforms, wetland water
regime detection and the possibilities for a unified wetland
classification system.
This book represents an erudite compendium and also a
very readable exposition of the current body of knowledge
on this topic, making it valuable both as a course textbook
and as a reference for research.
“Remote Sensing of Wetlands
– Applications and Advances”
is a very suitable primer for
the person new to this domain, but should be required as
a definitive cornerstone for the development of academic
programs dealing with wetland mapping. The depth and
breadth of coverage achieved by the editors make this
volume indispensable and essential to any scholarly effort
aimed at applying remote sensing to the mapping, study,
understanding and preservation of these complex, valuable
and endangered ecosystems.
Book Review
