Urban Remote Sensing and Energy Planning

Doctoral Consortium Contribution

Arthur Lehner

1,2

and Klaus Steinnocher

Austrian Institute of Technology, Energy Department, Giefinggasse 2, 1210 Vienna, Austria

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

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

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

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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Urban Remote Sensing and Energy Planning - Doctoral Consortium Contribution