Urban Remote Sensing and Energy Planning
Doctoral Consortium Contribution
Arthur Lehner
1,2
and Klaus Steinnocher
1
1
Austrian Institute of Technology, Energy Department, Giefinggasse 2, 1210 Vienna, Austria
2
University of Salzburg, Department of Geoinformatics, Schillerstraße 30, 5020 Salzburg, Austria
1 RESEARCH PROBLEM
Although provision, transport and consumption of
energy are strongly spatial related topics, for a long
period of time energy planning was hardly part of
urban planning strategies or development plans.
City-wide energy-planning requires understanding
of the complex system interdependencies at urban
level with regards to demand and supply of energy
resources, including their spatial distribution. (Agug-
iaro, 2015)
In developing and emerging countries the acqui-
sition of data or information is challenging due to
the lack of resources, organizational, financial, legal
or social factors (Schneider et al., 2007). In addition
to limited capacities urban planners have to face fast
urban growth, informal settlements, informal eco-
nomic activities as well as colliding interests that are
carried out spatially. Contemporaneously energy
planning calls more and more attention to public
authorities in terms of Smart City and Smart
Growth.
Moreover in European cities the provision of
geo-spatial infrastructure is normally carried out by
the city administration, comprising digital infor-
mation on urban structure, housing, and infrastruc-
ture. In addition there is information available on
energy related issues, thus allowing for spatially
related analysis on energy demand and consumption
as well as on potentials of improvement. This is not
valid for developing and emerging countries, repre-
senting a serious lack of information when urban
planning or energy planning strategies are to be
developed.
In this context, remote sensing appears to have
the potential to bridge at least part of the above de-
scribed information gap.
This leads to the research question, if there is a
correlation between remote sensing derived urban
structural parameters and energy related issues and
which remote sensing products can bridge infor-
mation gaps, can emphasize spatial trends and can
enable city planners to implement energy planning
in a spatial context.
2 OUTLINE OF OBJECTIVES
Since no standardized remote sensing products for
energy planning exist, the overall objective is to
identify correlations between the consumption of
energy and the urban structure, to ascertain correla-
tions between urban inventory and inhabitants as
well as their economic activity. Further needs com-
prise the development of methodologies and the
design of corresponding geo-information products
derived from urban remote sensing.
Remote sensing systems shall be examined re-
garding their aptitude for urban planning and energy
planning. The wealth of scientific experience and
scientific research shall be consolidated and linked
to practical experience and demands of urban plan-
ning authorities and energy planning experts.
The objective is to enhance the quality of life for
residents of urban areas and to ease the work of
urban planners. Urban remote sensing shall facilitate
the implementation of energy planning in a spatial
context and bring together two entities that actually
have never been separated.
3 STATE OF THE ART
3.1 Application of Remote Sensing
The application area for remote sensing has continu-
ously grown during the last years. Both in disaster
management as well as in forestry and agriculture
remote sensing is a constant factor. Moreover, in
urban areas it is partially used, here mainly from
industrialized countries. In latter urban remote sens-
ing is a contribution to monitoring and surveillance.
In Austria e. g. remote sensing is used as a device
for a tree protective law or to control building regu-
lations manually by visual interpretation of aerial
8
Lehner, A. and Steinnocher, K.
Urban Remote Sensing and Energy Planning - Doctoral Consortium Contribution.
In Doctoral Consortium (DCGISTAM 2016), pages 8-11
photos or satellite images. Internationally remote
sensing is used e. g. by the United Nations to ob-
serve and to track the development of refugee
camps. The resulting data is used to estimate how
many people approximately reside in one camp.
(Bjorgo, 2000)
3.2 Urban Remote Sensing and Energy
Planning
Energy planning-related remote sensing activity
takes place e. g. in the creation of solar potential
maps or cadasters. These cadasters provide infor-
mation about the energetic potential for solar collec-
tors or photovoltaic modules (Agugiaro et al., 2012).
High-resolution LIDAR data or high-resolution
Radar data are used for site selection of wind gen-
erators (Arcidiacono, 2012; Klärle and Ludwig,
2005). Furthermore, multiresolution remote sensing
data is used for the assessment of small hydropower
potential (Dudhani et al., 2006).
Both, urban planning and energy planning al-
ways include statements about the future. Presently
it is very challenging to make statements about the
future when it comes to urban areas and population
change. Moreover, models and scenarios that were
developed by means of urban remote sensing are
often strongly adapted to the study areas where
models or scenarios were performed initially and
thus transferability remains complex and demand-
ing. (Hofmann et al., 2011, 2008)
Within the context of transferability the World
Urban Database and Portal Tool (WUDAPT) has
been conceived as an international collaborative
project for the academic work with climate relevant
data on the physical geographies of cities worldwide
(Mills et al., 2015) Data about form and function of
cities, e. g. surface cover, the consumption of ener-
gy, water etc. is acquired and local climate zones
(LCZ) can be mapped globally by local experts after
one publicly available method. (Mills et al., 2015)
One effect of densely built-up areas with lack of
open spaces and green spaces are urban heat islands
or generally differences in temperature between
different regions within the urban area. These differ-
ences can easily be monitored and visualized, e. g.
between parks and densely built-up area (Nichol,
2005). Based on the resulting knowledge, planning
actions can be applied that have influence on the
urban energy consumption whether for cooling or
heating.
Through data about impervious surface and its
change through population growth, scenarios can be
developed and remote sensing data about land use
can support efficient planning of infrastructure and
can therefore contribute to a more efficient use of
energy and less consumption of energy (Bhatta,
2010) This can happen through the adaption or im-
provement of the journeys to particular public facili-
ties, e. g. hospitals, doctors etc. (Barona and
Blaschke, 2015).
Another area of research represents the gathering
of building parameters by means of active sensors or
stereo photogrammetry. Building height, area, vol-
ume, style of roof or other building parameters are
acquired to calculate the heating demand and the
cooling demand of a particular building (Agugiaro,
2015).
Many of the aforementioned approaches focus on
research questions that correspond less to the holistic
principles of energy planning rather than on the
solution of particular challenges. The solar potential
cadaster e. g. can visualize the energetic potential of
existing roofs of buildings. However, the influence
of remote sensing data on land use plans, building
plans or other planning instruments remains low.
The most usable building orientation for photovolta-
ic modules could be recommended or negative influ-
ence of additional buildings in a wind corridor could
be calculated and additional constraints for the con-
struction of new buildings within this wind corridor
could be given.
It can be summarized that research in the field of
urban remote sensing, urban planning and energy
planning has led to diverse new approaches and
researches worldwide face the complexity of urban
growth, growth of population and increasing demand
of energy.
4 METHODOLOGY
The methodological development will focus on the
derivation of urban parameters from urban remote
sensing data. It is expected that the parameters re-
quired will rather be of a complex nature combining
object information such as buildings or infrastruc-
ture and attribute information such as object func-
tions and energy related information.
Depending on spatial, spectral and radiometric
resolution of remotely sensed data, the acquisition of
object information varies in accuracy and usability.
Moreover, spatial information in imagery includes
aspects such as image texture, contextual infor-
mation, pixel proximity, and geometric attributes of
features (Blaschke, 2010).
The multiple approaches of increasing the out-
come of image data has led to different methods, e.
Urban Remote Sensing and Energy Planning - Doctoral Consortium Contribution
9
g. sub-pixel techniques, pixel-by-pixel techniques,
the regionalization of pixels into groups of pixels
and the aggregation of pixels to objects. In urban
areas especially, it appears that object-based ap-
proaches have several advantages when mapping
land cover change, monitoring a city for building
code compliance, quantification of sealed surface
(Blaschke and Strobl, 2001) or other energy plan-
ning relevant approaches. However, most of the
current applications rely on simple per-pixel classi-
fication of the imagery (Bhatta, 2010).
The election of a proper method depends on the
requirements and on the level of detail, whereby
only the integration of urban remote sensing derived
objects and ancillary information derived from sta-
tistics will certainly enhance the information content
significantly and thus allows us to get closer to the
overall objective of an all-embracing energy plan-
ning. In order to achieve best results with object-
based image classification (OBIA) the use of (very-)
high resolution images is obligatory.
The goal of the methodological development will
be to evolve functional and structural classes from
the classification of the urban area using a diverse
set of socioeconomic and statistical data as addition-
al input. Test sites will be defined, which will be
located in developing and emerging countries. Data
acquisition will be based on requirements and avail-
ability. However, since urban remote sensing has the
potential to bridge information gaps, methods and
workflows will be developed that enable the substi-
tution of missing data from the ground by remote
sensing, e. g. the estimation of inhabitants within a
particular area. (Aminipouri et al., 2009; Galeon,
2008)
5 EXPECTED OUTCOME
The expected outcome will depend on the applica-
tion of the methodologies on the data of test sites
that will ultimately result in reference geo-
information products.
A breakdown of existing remote sensing systems
will be given which will provide support for urban
planners within planning tasks. Geo-information
products will be evaluated after their thematic reso-
lution. Thematic resolution means an assessment of
the suitability of specific geo-information products;
e. g. for the compilation of precise building outlines
high resolution image data is essential whereas data
with a coarser resolution is more suitable for the
computation of climate models because of the result-
ing large amount of data and its global availability.
Depending on data availability and on other fac-
tors, geo-information products can be suggested that
can be used for green zone plans or other planning
instruments. For strategic plans like green zone
plans the land surface temperature within a specific
urban area can be developed from remote sensing
data (Figure 1). In particular, hot or cool areas can
be identified. This information can be used to visual-
ize the cooling effect of the expanse of water, parks
or other open spaces that may be relevant for the
urban climate. Hotspots can easily be identified;
changes and impacts through time can be monitored
through time series analysis of remote sensing data.
Further scenarios about urban growth can be
generated. By means of an object-based approach
the future energy consumption or the future land
consumption resulting from urban growth can be
related to particular units or referred to individual
buildings.
Figure 1: Comparison of land surface temperatures (LST)
in degrees centigrade of a study area in Ahmedabad, Guja-
rat, India.
Finally these geo-information products will be
evaluated against the user requirements and the
feasibility of the entire process, they will be critical-
ly analyzed and the potential of improvements will
be defined. The final result will describe the design
DCGISTAM 2016 - Doctoral Consortium on Geographical Information Systems Theory, Applications and Management
10
of the reference geo-information product and contain
guidelines of how to use the information product for
supporting energy planning.
6 STAGE OF THE RESEARCH
One of the first stages of research is the literature
review that has almost been completed; the sheer
amount of particular methodologies and approaches
within the field of energy planning and urban plan-
ning makes a concentrated approach quite challeng-
ing though. Presently urban remote sensing products
are analyzed and are assigned to a particular themat-
ic order.
So far, a verification method for demographic
forecast with the use of remote sensing data could be
evolved (previously unreleased). Within this case
study it could be proven that with a minimum of
freely available data planning authorities can be
supported.
The development of a continuous exchange with
experts from the field of urban remote sensing and
energy planning as well as the transfer of
knowledge, complement the base for further re-
search.
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