Research and Development in Roof-Top Solar Potentiality Using LiDAR Technology Mr. Radhey Shyam Meena M.Tech Scholar (Power System) Student Member -The Institute of Engineering & Technology (IET), UACEE Dept. Of Electrical Engineering Sri Balaji College Of Engineering & Technology Jaipur Rajasthan Technical University Kota 4th International conference on “Advance Trend in Engineering, Technology and Research (ICATETR-2015)” Date: 19-20 June-2015 Venue: Bal Krishna Institute of Technology, Kota IPC-15, RIICO Institutional Area, Ranpur Kota (Rajasthan) (India)

1. Research and Development in Roof-Top Solar Potentiality Using
LiDAR Technology
Mr. Radhey Shyam Meena
M.Tech Scholar (Power System)
Student Member -The Institute of Engineering & Technology (IET), UACEE
Mr. Jeetendra S Rathore Mr. Mukesh Lodha Mr. Manish Agarwal Ms. Shivani Johari
M.Tech Scholar Asst. Prof. EED Asst. Prof. EED Head & Asst. Prof. EED
Dept. Of Electrical Engineering
Sri Balaji College Of Engineering & Technology Jaipur
Rajasthan Technical University Kota
Abstract: Energy security and its application is the key for
economic growth to any country and state. The conventional
generation is also the source of greenhou se gas emission
attributing to global warming and has has adverse impact on
climate. Therefore, a global shift towards sustainable
renewable energy generation is being witnessed. India is
blessed with abundant solar energy and if harnessed
efficiently, Solar energy is extremely beneficial as it is non
polluting and its generation can be decentralized. The state
of Rajasthan receives maximum solar radiation Intensity in
India with very low average rainfall. It also has desert land
available in abundance. The refore, Rajasthan is likely to
emerge as the global hub for solar power in the country.
Challenge of climate change and global warming
properties tha t could not be achieved before. LiDAR is
extremely useful in atmospheric and environmental research
as well as space exploration. It also have wide application in
industry, defense, and military. LiDAR mapping is an
accepted method of generating precise an d directly
referenced spatial information about the shape and surface
characteristics of the earth. Recent advancement in mapping
systems and their enabling technologies allow scientists and
professionals to examine natural and built environments
across a wide range of scales with greater accuracy,
precision, and flexibility then ever before. There are many
considerations and trade offs that must be understood in
order to make sound decisions about the procurement,
processing, and application of LiDAR data. This paperChallenge of climate change and global warming
continuously threaten the world community, and Rajasthan
govt. Has also recognized the urgent need to tackle these
challenges. In this paper a methodology is provided for the
application of Light Detection and Ranging (LiDAR) to
automated solar photovoltaic (PV) deployment analysis on
the regional scale. Challenges in urban information extraction
and management for solar PV deployment assessment are
determined and quantitative solutions are offered. This paper
highlights a need for connectivity between demographic
information, electrical engineering schemes and geographical
information systems (GIS) and a typical factor of so lar PV
suitable roof area that can be extracted per method.
conclusions are developed to provide guidelines for a final
methodology with the most useful information in situations of
incomprehensive GIS data to facilitate the processing of
LiDAR, low budgets for both time and finance, and personnel
with diverse expert in computer vision. The methodology can
processing, and application of LiDAR data. This paper
provide introductory and review information for application
of LiDAR Technology in solar PV system. It has become an
established method in todays technology for information
collecting and elevation data across landscapes different
project sites including for solar system , wind , and other
new renewable energy sources. This is sensing technique as
similar to radar but in radar we use radio wave and here we
use laser light pulses. It collected ground based stationary
and mobile collect points in site areas. Three dimensional
representation also possible for new system of rail road and
building development structures. LiDAR, which is
commonly spelled and also known as LADAR or laser
altimetry, is an acronym for light detection and ranging. It
refer s to a remote sensing technology that emits intense,
focused beams oflightand measures the time it takes for the
reflections to bedetectedby the sensor. This information is
used to computeranges, or distances, to objects. In thiswith diverse expert in computer vision. The methodology can
be adapted for use anywhere that LiDAR and urban GIS data
is available.
Key Words : Light Detection and Ranging (LiDAR),
Renewable Energy Source , Photovo ltaic, Computing
Sensing, New Generation Technology.
I. Introduction
A.LiDAR
LiDAR stand for Light Detection and Ranging, commonly
known as Laser Radar. It is not only replacing conventional
sensors, but also creating new methods with unique
used to computeranges, or distances, to objects. In this
manner, LiDAR is anal ogous to RaDAR (Radio Detecting
And Ranging), except that it is based on discrete pulses of
laser light. The three - dimensional coordinates (e.g., x,y,z or
latitude, longitude, and elevation) of the target objects are
computed from
The time difference betw een the laser pulse being
emitted and returned,
The absolute location of the sensor on or above the
surface of the Earth.

2. F i gu r e 1. Sc he m ati c d i ag ram o f A ir bo r n e L iD A R p er fo rmi n g l i ne s can ni n g r e s u l ti n g i n pa r all e l l in es of m e as u re d po i n ts
(oth er s c an pa tte rn s e x i st , bu t th i s o n e is fa i rl y c o mmo n)
T h er e ar e tw o cl a ss es of r em o t e se n s in g t echn ol o gi es tha t
ar e dif f er en t i at ed b y th e so ur ce of en er gy us ed t o det ec t a
t ar get :
Pa s si v e S y st em s
A ct i v e Sy s t em s .
Pa s s iv e s y s t em s det ect r ad i at i o n t h at i s ge n era t ed by a n
ext ern al s ou r ce o f en e rgy , s uch as th e su n, w hil e a ct i ve
S o la r P h o t ovo l t ai c (PV ) e n e rgy c on ver si o n o ff e rs a
s us t ai nab l e m et h o d o f pro duci n g el ec tr i ci ty to prov i de for
S o ci et y n ee ds. T h e adv an ta ge o f PV i n ge n era t i on o f
e le ct r ic i ty are -
L o n g t e rm e co n o mi c g ro w t h i m p ro v em en t f or a n y
c oun tr y t h at agg re s si v el y devel o ps t h e t ec hn ol o g y .
P ro v i de a as s i st a n ce in e n er gy s ec uri t y .
No at m o s ph e ri c em i s s i o n s o r ra d i o act i v e w as t e
ge n era t io n du ri n g us e.
It a ct s a s a dis t ri b ut ed el ec tri cal gen e rat i o n s our ce a nd h e n ce
r ed uc es t h e de pen de n c e a n d p re ss ur e o n t h e cen t ra l uti l i t y
ext ern al s ou r ce o f en e rgy , s uch as th e su n, w hil e a ct i ve
s ys t em s ge n e ra t e an d d i re ct e n e r gy t ow a rd a t arge t a n d
s ubs e quen t l y de te ct t h e ra di at i on. L iD A R s ys t em s a re
ac t iv e s ys t em s be caus e t h ey em i t p ul s es o f l i ght (i . e. th e
l as er b e am s ) an d det ect th e r ef l e ct ed l ig ht . T h i s
ch a ra ct eri s t i c a l lo w s l id ar da ta t o b e co ll e ct ed at n i g ht
w h en t h e ai r i s us ua l ly cl ea r er a n d th e sky c on ta i n s le s s a ir
tr a f fi c t h an i n t h e da yt i m e. I n fa ct , m o s t l ida r dat a ar e
co l l ect e d at ni ght . U n li ke r adar, l i da r c ann o t pe n et rat e
cl o uds , ra in , or de n s e h az e a n d mus t be f l ow n du ri n g fa ir
wea th er. L i DA R i n s tr u m ent s c an ra p idl y m eas u r e th e
E art h s u rf ace , at s am p l in g ra te s g r eat er t h an 150 ki l o h e rt z
(i . e., 15 0, 00 0 pu ls e s pe r s eco n d). T h e r es ul ti n g p ro duct i s a
den s e ly s pa ced n et w or k o f h i gh ly a ccur at e geo re f er en ce d
el ev a ti o n po i nts o f t en cal l ed a po in t cl o ud th a t c an be
r ed uc es t h e de pen de n c e a n d p re ss ur e o n t h e cen t ra l uti l i t y
l i n es in s ys t em s wi t h h ig h pot e nti a l f o r b la cko ut s an d
ov er l o ads . T his has l ed t o i n t erna t io n al c oo p e ra ti o n an d
t ec hn o l og y in ve st m e nt o v er t h e pa s t 2 5 ye ar s , w h i c h in t u rn
ha s gi v en ri s e t o fan t a st i c gai n s in s o l ar P V c el l pe rfo r ma n ce
a n d a p re dic t ed c h angi n g l an ds ca pe in R& D act i v i ti e s fo r
s o l ar c el l t ec hn o l ogi e s . S o la r ce l ls ma de f r o m a v ar i et y of
m a te ri al s hav e dem o n s t rat e d ef f i ci en ci es ov er t en pe r cent an d
a re c urr e nt ly m an uf a ct u re d gl ob a l ly . A s th e t echn ol o gi ca l
pr o fi ci en c y of t h e s o l ar cel l in dus t ry m at u re d , t h e t ot a l
s h i pm e n t s o f s o l ar cel l s in cre as ed r api d l y. In th e l as t dec ade
gl o b al s o l ar PV de plo y m en t h a s in c r ea s ed f r o m 1 G W t o 16
G W w i t h an annua l gr o w t h ra t e o f m or e tha n 40% , T h i s
gr o w th r at e, w h i l e i m pr es s i v e, m us t b e ke pt i n co n t ext of t h e
gl o b al en e rgy ma rke t. T h e in cre as in g t echn ol o gi ca l
c om pe ti t i v en e ss o f s o l a r P V , am o n g o t h er ki nds o f ren ew ab l e
e n ergi es , ha s co n t ri b ut ed t o-
A n ew l o gi c o f i n f ras t ruc t ur e P r ov i s i on al .
A para d igm sh i f t in en e rgy po l ic y .el ev a ti o n po i nts o f t en cal l ed a po in t cl o ud th a t c an be
us ed t o ge n era t e thr ee- di me n si o n al rep r es ent at i o n s o f th e
E art h s u rf a ce a n d i t s f ea t ure s. M an y L i D AR s y s te m s
o pera t e i n t h e n ea r-i n fra r ed regi o n o f t h e e l ect ro m a gn et ic
s pect r um, a lt h o ug h s o m e s en s o rs a ls o ope ra te i n t h e gr ee n
b an d t o pen et rat e w a te r an d det ec t b ot t o m fea tu r es . T h e se
b at h y m et ri c l i dar s y st e ms ca n b e us ed in ar ea s w i t h
re la t i ve l y cl ea r w at er t o m e as u re s ea f l o or e l ev at i o n s .
B. P ho tovo l tai c S yste m
A para d igm sh i f t in en e rgy po l ic y .
H ow e ver, i n th e deb a te s on u rb an a n d r egi o nal dev el opm e n t
a n d r egi o nal in fr a st ruc tu r e po li c y , t h e in t eg rat i o n of di f fe re n t
di s ci pl i n es (G eo gra p h i c I n fo rm at i on S y s t em (G IS ),
e n v i ro n m en t al m o del in g, u rb an pl a nnin g , el ec tr i cal an d
m e ch ani ca l e n gi n e eri n g) and t h ei r ro l es in th e de li v er y of
ut i l i ty s erv i ce s s t i l l s eem s t o b e t ake n f or g r ant ed by t h e
pub l i c and w i thi n ea ch si n gl e di sc i pl i n e an d to b e l ef t t o
e n gin ee r s, n et w or k ope ra to rs and na t io n a l u t il i t y re gul at o rs .
Co n s equen tl y , t h e re ha s b ee n li t t l e r es ea rc h o n t h e u rb an an d
r egi o n al i mp a ct s of uti l i t y r es tr uct u ri n g and t h e c h a n g in g
e n v i ro n m en t f o r u rb an and r eg i o n al go vern an c e w i t h a

3. large -scale introduction of PV. To take advantage of PV
anding of
the urban local potential (roof space and solar exposure
among others) is critical for utility planning, accommodating
grid capacity, deploying financing schemes and formulating
future adaptive policies .
The paper describes a methodology that is part of the complex
process of assessing solar PV potential for a region using the
Renewable Energy Region (RER). Specifically the
methodology provides an application of Light Detection and
Ranging (LiDAR) of urban to automated solar PV
deployments on a municipal unit, which can be scaled up first
to the level of a city and then the cities within the RER region.
The primary stakeholders for this research are local and
002
2
)()()( TALTR
R
A
RRTR
t
RP
fovrbg
r
a
t
r
Here
Pr(R)=Optical power received from range R in J/s
t
= Transmitted pulse energy in J
Ta= Atmospheric one way path transmittance time in s
w
= Angular scattering coefficient in m- 1
sr1
Ar/R2
= Projected solid angle of r eceiver as seen from
scatterer at range R in sr
=
Overlap function
L A = Incident back ground power in WThe primary stakeholders for this research are local and
regional utilities companies,municipal government and
academic research on regional ener gy modeling. Challenges
in urban information extraction and management for solar PV
deployment assessment are determined and quantified. This
study provides the following contributions:
A methodology that integrated the cross -disciplinary
competences in remote sensing (RS), GIS, computer
vision and urban environmental studies.
A robust methodology that can work with
low - resolution, spatially and temporally inconsistent
and incomprehensive data and reconstruct vegetation
and buildings separately and concur rently.
Recommendations for future generations of software.
II. Main Equations Concept
LbgArfov= Incident back ground power in W
The LiDAR equation for analog detection or photon
counting
bg
r
a
t
r
NTR
R
A
RRTR
h
RN
02
2
)()()(
Here
Nr(R) = Number of photons received from range R
t
= Transmitted pulse energy in J
Ta
= Atmospheric one way path transmittance time in s
w= Angular scattering coefficient in m- 1
sr1
Ar
/R2
= Projected solid angle of receiver as seen from
scatterer at range R in sr
=
Overlap function
Range calculated from light travel time
dt
Rn
c
dR
)(
Minimum range resolution, is the range uncertainty, which
=
Nbg= Received background photons in ph
III. Technical Platforms
Airborne topographic LiDAR systems are the most
common LiDAR systems used for generating digital
elevation models for large areas. The combination of an
airborne platform and a scanning LiDAR sensor is an
effective and efficient technique for collecting elevation
data across tens t o thousands of square miles. For smaller
areas, or where higher density is needed, LiDAR sensors
can also be deployed on helicopters and ground -based (or
water -based) stationary and mobile platforms. LiDAR was
first developed as a fixed -position ground - based instrument
for studies of atmospheric composition, structure, clouds,
Minimum range resolution, is the range uncertainty, which
results from the smaller of the laser pulse width or the A/D
sample rate:
n
tclengthpulse
R
22
t = Optical pulse width or interval, n = Reference index of
medium
The LiDAR equation that is used for solution of optical
power received from range R is given blow -
for studies of atmospheric composition, structure, clouds,
and aerosols and remains a powerful tool for climate
observations around the world. Modern navigation and
positioning systems enable the use of water - based and
land -based mobile platf orms to collect data.
IV. Installation Story
A. LiDAR & PV
In order to determine PV potential for a city the ideal
circumstance is having access to a 3D urban model , which
requires that individual buildings are represented, next to
urban vegetation, st reets, and other objects of the city

4. in fra str ucture such as wa terc our ses, power supply lin es, and
in dividual obje cts like str eet signs or f oun ta in s. A Digital
Sur fa ce Mode l (D SM) derived from point c louds a cqui re d by
LiDAR or ste re o- photogr ammetry will indirec tly repr esent
buildi ngs. While such models ca n be gener ated e asily a nd
even automa tic ally, they on ly repre se nt the a ppr oxima te roof
shape s without ge neraliz ation a nd without distinguishing
betwee n in dividual buildi ngs on the one hand and betwee n
buildi ngs a nd other ob jects like ground and vegetatio n on the
other ha nd. If building or building block outline s (e.g., from
ca dastral maps) are pr ovide d, mode ls ext rac ted fr om the
combined LiDA R and G IS data a re enhan ced and sur fac e
models ca n be gene rate d forindividual buildi ngs o r blocks.
Howeve r, th ese models still do n ot a llow a distinc tion
B. S ys t em De t ec ti on
R el i ab l e an d a ccu r at e b ui l d in g ge n era t i on f ro m L i DA R dat a
r equi re s a n u m b er o f pr oc es s es be yo n d ca pt u re o f a ccur at e
ra w da t a. T h es e a re b uil di ng det ect i o n , o b je ct s egm ent at i o n ,
b ui l din g ext ra ct i o n , r o of s h a pe r eco n s t ruc ti o n a nd m o del in g
qua li t y a n al y s is . T h e m a j o ri t y of av a i la b l e l i t e ra t ur e:
Co n ce n tra t es o n i ndi v i dua l as pec ts o nl y an d h e n ce
de ta ch es t h e rea de r f r om th e b i g pi c tu r e;
O nl y us e s (a ss o ci a t ed) dat a of cer t ai n (e xce ll e nt) qual i t y
o r c us to m i ze d c la s s if i e rs tha t a re o n l y pr of es s i on al l y
kn ow n o r n o t publ i cl y av ai l a bl e (e Co gn i t i o n , F e at u re
A na l ys t ); an d
H a s li m it e d a ppli c at i on s i n te r m s o f t h e degr ee o fHow eve r, th es e m o del s s t il l do n ot a l lo w a d i s t in c ti o n
b et w ee n in d i v i dual r o of f a ce s , n o r b et w ee n r o of a n d dorm e rs
o r ot h e r o bj ect s , w h i c h is im po rt ant i n t h e co n t ext o f s ol a r PV
in s ta l la ti o n s b e caus e a w h o le r o of PV i n st a ll a ti o n i s n o t
al w a ys f ea s i bl e . Furt h e rm o re, art i fa ct s o f dat a ac qui si t i o n ,
e. g. , ca us ed by o c cl uded a re as , s am pl ing di s t an ce , o r
re ma i nin g geo -r ef e re n ci n g e rro r s, ar e t y pi cal l y fo un d in s uc h
m o del s. Ve rt i ca l w al l s m ay a ppea r sl ant ed o r n ot appea r a t al l
duet o t h e 2. 5D g ri d r ep re se nt at i on. Af t er t h e c l ean -up of suc h
err o rs , ro of s i zes w i ll gen e r al l y be s m al l e r th an th e ir a ct u al
s i zes , t h e r eby r educi n g th e ir s h ado w i n g po t en ti al . I n t h e
ext r em e ca s es , s hado w e f fec ts of adj ace n t bui l di n gs m a y n o t
b e capt ur ed.
T o in c rea s e th e re l ia b il i t y of th e b ui l di n g m o del s as w el l as
th e r an ge o f po ss i b l e appl i ca ti o n s , add i t io n a l k n o w l edge o n
b uil di n gs ha s t o b e i n co r po rat e d i nt o t h e m ode li n g pr o ces s .
T y pi ca l a s sum p t i o n s ar e t o de f in e w al l s a s be in g v er t i cal an d
ro o fs a s b ei n g a c om po s i te of pl a n ar f a ces . T hi s l eads to an
H a s li m it e d a ppli c at i on s i n te r m s o f t h e degr ee o f
c om pl exi t y t h a t t h e pr o duct a ll o w s .
A l t h o ug h u r ba n t ext u re m o del in g i s hig h l y d y n a mi c (due t o
t h e nat u r e o f th e m o del ed o bje ct ) an d c o mpl i ca t ed (due t o t h e
r equi re d pr ec is i o n and i n t e r di sc i pl i nar y i n th e n um be r o f
i n v o l ved e xpert i s e and t h e inh e re n t int era c ti o n b e tw een
h um a n s a nd th e ur b an e n vi r o n me n t). T h e m e th o do l o g y for
b ui l din g de te ct i on sub s equen t ly der i ve d a n d des cri b ed h e r e
w a s de s ign ed t o co m pr om i s e b et w e en co s t sa v in gs an d t h e
s m o o th es t a n d m o s t ef fe ct i ve l y e st a b li s h e d l ea rni n g c urv e
po s s i bl e for an a udi e n ce as s u me d t o h av e n o p r ev i o us t ra i nin g
i n co m put e r p r og r am mi n g , r em o t e s en s in g o r d i git a l i m age
pr o ces s i n g. A n u n de rs t andi n g o f t h e c om pl exi t y of GIS dat a
i n t eg r at i o n in e n ergy m o del i n g m ea n s an i m p ro v ed
i n t er - di sc i pl i nar y app re ci at i o n fo r th e v al ue o f a s t rea m li n e d
a n d co m pre h e n s i ve da ta s ys t em . F u r th e r, th e ab i l it y t o ca rr y
o ut pa rt o f t h e p ro ce dure w i l l h el p f a ci l it a te t h e pe n et rat i o n o f
s o l ar PV in to t h e cu rr e n t el ect ri c i ty gri d . I n t h e ab s en ce ofro o fs a s b ei n g a c om po s i te of pl a n ar f a ces . T hi s l eads to an
i dea li z at i o n of t h e bui l d in gs. T h e tra n s i t io n z o n e o f t w o
n ei g h b o ri ng ro o f f ace s , f o r exa m ple , b ec o me s a s t ra ig h t l i n e
defi n e d by t h e i n t e rs ec t io n o f t w o r o of pl an es . T h e
i m port an ce o f th es e co n s i de ra ti o n s i s r ai s ed w h e n it co m es t o
PV s ys t em des i gn an d pe r ro o f i n st al l at i o n : t his enhan c ed
m o del i s s uf fi ci en t i nput f o r ra pi d r o of as s es s m en t . H en c e a
m o del i ng m et h o d i s n e eded f o r PV app l i cat i o n s t ha t i s:
A cc ura t e,i. e., i t s h o uld p ro duce s i m pl e pol y gon al
m ode l s f i tt i n g t h e i n pu t po in t cl o uds i n a p r eci s e m ann e r .
Rob us t : re ga rdl es s o f th e d i ve rs i t y an d c om pl exi t y o f
b uil di n g r o of s h ape s t h e me th od s h o uld al w ay s g e n era t e
b uil di n g m ode ls co m p ri s ed o f fl at p la n es tha t ar e as
co n t i n uo usl y an d s mo o t h l y c o nn ect e d a nd t ra n si t i o n ed
as po s s i bl e even w it h t h e e xi st en ce o f un des ir ed
el em en t s s uch a s re s idua l n o i s e and s m al l r oof f e at ure s .
Com pl em ent a ry t o t h e 2 . 5D c hara ct eri st i c: th e m et h o d
s h o ul d c rea t e 2 .5D po l y g o n al m o del s co mpo s e d of
det a il e d ro of s and ve rt i ca l w al l s c o nn ect i ng r o of l ay er s .
s o l ar PV in to t h e cu rr e n t el ect ri c i ty gri d . I n t h e ab s en ce of
c ada s tra l dat a, th e re are s ev era l ef f e ct i v e m et h o ds fo r
b ui l din g det ect i o n t hat w o rk we l l on la rger b uil d i n gs al t h o ugh
s m a ll er b ui l di n gs ar e of te n m i ss ed . Bui l d in g det ect i o n ca n b e
c arri ed o ut s o l el y on t h e L i DA R dat a o r i n h y br i d w it h o th er
da ta s uc h as ae ri al p h o t os an d e xi st i n g bui l di ng out l i n es .
B ui ldi n g o utl i n es are t h e int er s ect i o n o f t h e b uil d i n gs w i th i t s
s urr o u n dings , in ge n era l t h e t erra in . T h e o ut l i n es t hat ar e us ed
fo r th e ap p ro a ch us ed h e re h a v e t w o a dv ant age s : f i r st l y , t h e y
r ep r es en t t h e re al s hape a nd s iz e o f t h e ro o f , a n d n o t t h e
di m e n s i o n o f t h e ba s em en t . A nd s eco n dl y , a ppl yi n g th e s am e
da ta a s us ed f or t h e ev al uat i o n e n s ur es t h e co m para b i li t y of
t h e r es ult s d ur i n g t h e p ro ces s of t h e ev al u a ti o n . T h e y
c on cl uded t ha t la s er sc anni n g i s m o r e s ui t ab l e t h a n tr adi t io na l
ph ot o gra mm e tr y fo r de ri v i n g b ui l d in g h ei g ht s , ext ra ct in g
pl ana r ro o f f ac es an d ri dges o f th e r o of s . H ow e ve r,
ph ot o gra mm e tr y a n d a e ri al i ma ges l ea d to b et t er re sul t s in
b ui l din g o ut l in e an d l e n g t h det e rm ina t io n.
det a il e d ro of s and ve rt i ca l w al l s c o nn ect i ng r o of l ay er s .
V. Me th od o l o gy
As o ut l in ed a bov e, a w i de r an ge of te ch ni ques h a v e b ee n us ed
t o ext ra ct bui l di n g geo m et r y , an d in p ar ti cul a r r o of ge om e tr y ,

5. from LiDAR point clouds and from ima ger y with or with out
in depen dent buildin g outline data. Our focus is on rapid,
models to assess photovoltaic solar potential of
neighborhoods. Unlike most of th e methods de scribed above,
exa ctness is n ot deemed as esse ntia l a s is generality to a wide
var iety of situations and e fficienc y in spi te of rea listically
mixed data quality. The me thodology used here is base d on
th e following five a ssumpt ion s: (i) in dividual building r oof
ar ea s c an be modeled pr ope rly by a composition of plane r
faces; (i i) anything below a chosen eleva tion cutoff is
irre levant for sola r PV potential assessment; (iii) tre e
ca nopies are opaque ; (i v) sma ll windo ws on the roofs,
overha ngs on th e wa lls, Heating, Vent and Air Conditioning
free for P V pa nels; (v) the h eight of the obje ct an d
subseque ntly th e altimetr y of th e Digital Surf ace Model
(D SM) is the differen ce betwe en LiDARs z value s an d an
a vailable D EM and (vi) ther e is no discrepan cy in the form of
ur ban structure s betwe en Aer ial Photos (A P) a nd LiDAR
(i . e., t h e se dat as e ts w e re co l le ct ed a t or n ear t o th e s am e t i me ).
A m o n g m ult i pl e l ev el s of re tu rn s t hat L i D AR of f er s, th e la s t
r et u rns of t h i s ar ea w er e use d fo r r oo f co n s t ruc t io n si n c e t h e y
w e re co n s i der ed t o m o s t l i kel y rea ch t h e cl o s es t t o t h e gr o un d
h e n ce t h e la s t o b je ct o n th e g r oun d o r t h e g ro u n d i t s el f wo uld
b e pi cke d up by t h e l as t pul s es . E spe ci al l y fo r b ui ld i n gs la s t
a n d f i r st ret u rns ar e t h e sa m e ( in z v al ues ), w h i c h w as
c h ecke d w it h th e cu rr e n t da t as et . A c om pl et e f low c h ar t
s h o w i n g t h e s t eps t hat pr ec ede t h e c re at i on of a DS Mov erha n gs o n th e w a ll s , H eat i n g , Vent an d A i r Co n di t io ni n g
f a ci l it i es (H VACs) an d a n t e nnas do n o t o ccup y s o l a rge a
s pace t h at i t s o mi s s i o n adds s i gn if ic an t ar ea t o t h e ro o f a re a
s h o w i n g t h e s t eps t hat pr ec ede t h e c re at i on of a DS M
pr es ent ed in t hi s pape r an d a pp li e d fo r t hi s s im ul at i on is gi v en
i n Fi gu re s. -
F ig. 1(a). Th e c l ass i fi cati on o f p oi n ts b as ed o n th e o b je c ts th ey co rr es p on d to was c a rri e d o u t
Fi g. 2 (b ) R oo f s egr egati o n was do ne u s i n g MatL ab
(a ) (b)

6. F i g. 1(c ) C o ns tr u c ti o n and I r rad i an ce Mo d el i ng
P V R oof F i tti ng
T h e s ub po i n t s a t thi s po in t ar e r ea dy t o b e s egm en te d an d
us ed f o r rec on st r uct io n . I n a m at h em a ti c al s e n s e, s in c e t h e
as s um pt io n is th a t ea ch pl a n e can b e r ep r es ent ed b y a di st i n ct
i n t e r pol a ti o n i n r egi o n g ro w i n g . E q uat i o n s fo r h ori z o n t al ro of
f a ce s ar e rel a ti v el y ea s y to c o n s truc t , b ut t h o se f o r s l an t e d
f a ce s h a ve f i r st t o b e re co gn i z ed b y R A NSAC be for e bei n g
l i n ea rl y re gr es s ed by th e S in gul ar v a lue Dec om po s i t io nas s um pt io n is th a t ea ch pl a n e can b e r ep r es ent ed b y a di st i n ct
equa t io n i n t h e Ca rt es i an coo r dina t es , s egm e nta t i on is t o
der i ve s uch e quat i on s , w h i ch are i n t u rns us ed f or
l i n ea rl y re gr es s ed by th e S in gul ar v a lue Dec om po s i t io n
( SVD ) a l gor i thm .
F i g. 3 . A v e rti c a l cu t o f an e x ampl e h ou se ne xt to a tre e s h o w i ng the bu ffe r an d th e e l ev ati o n c u to ff. I n add i t i on i t s ho w sF i g. 3 . A v e rti c a l cu t o f an e x ampl e h ou se ne xt to a tre e s h o w i ng the bu ffe r an d th e e l ev ati o n c u to ff. I n add i t i on i t s ho w s
th e v er t i ca l ex te nt o f th e fo u r ri n gs u s ed fo r cl as s if i c ati o n.
V I. Di sc u s s i on and F u t u r e W o rk
As c an be s ee n th e re s ult s a re w i th in n u ll err or g i v en fi v e key
as s um pt io n s : (i ) i ndi vi du al b ui l di n gs ca n be m ode l ed
pro perl y by a co m po s i ti o n o f pl a n e r f ac es ; (i i ) an y t h i ng b el ow
a ch o s en e l ev at i o n cu t o ff i s i rr el ev a nt f or s o l ar PV po t ent i al
as s es s m en t ; (i i i ) t ree can opi e s a re o paque; ( i v ) sm a ll w i n do w s
o n t h e ro of s , o ver han gs on t h e w al l s ,
H V ACs a n d ant enna s do n o t o ccup y s o la rge a s pac e t h at t h ei r
o m i s si o n a dds s i gn i f i can t ar ea t o th e r o of ar ea f ree fo r PV
pa n el s ; (v ) t h e h ei g ht of t h e ob jec t a n d s ubs eque n t l y t h e
a l ti m et r y of t h e D S M i s t h e dif f e re n ce b et w e en L iD A R s Z
v a l ues and t h e D E M ; an d (v i ) n o di sc r epa n c y i n rea l ti m e
ur b an st r uct u res b et w een a eri al p h o to s (AP ) a n d L i DA R .
Ne i t h er w i l l i t af fe ct t h e v al i d it y of th e D SM a s t h e el e va t i on
i s pr es er v ed. T h e r oo f ar ea , h o w ev er , w i l l b e s m al l er , s i n ce
t h e ro of ar ea w a s t w i ce r educe d: t h e f i rs t t i m e by th e use o f a
b u f f er a l on g t h e e dges a n d th e se co n d t i me by t h e po in t

7. thinning effective in the RANSAC script. That means the
output would be a conservative estimation of area available
for PV panels.
The methodology presented here is a continuation of previous
attempts made urban rooftop data for determination of the
regional PV potential on rooftops. However, this method is
more inter disciplinarily transparent, comprehensive and has
the advantage of relaxing the mandatory data quality. On its
own it is the next piece of the pyramidal procedure to estimate
solar photovoltaic potential from a regional level, to a
municipal level and now a household scale. Given these
qualities, it is suitable for use in regions without good LiDAR
data and part of it is possible for utilities in the developing
countries where these techniques are at an early stage of
VIII. References
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[4] Olz, S.; Sims, R.; Kirchner, N. Contribution ofcountries where these techniques are at an early stage of
development. The weakness of this methodology is a
compromise between mat hematical sophistication and
technical adaptability, between automation and intensive
supervision.The aspects mentioned in this paper, mainly
pertaining to the integration of spatial information in energy
modeling, are among the bottlenecks to the process of
integrating solar PV (and other forms of renewable energy)
into the current electricity grid.
VII. Conclusions
The paper provides a methodology for the application of
LiDAR to automated solar photovoltaic deployment analysis
on the regional scale. Ch allenges in urban information
extraction and management for solar PV deployment
assessment are determined and quantified. First, a
comprehensive examination and comparisons of existing
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[8] Fthenakis, V.M.; Kim, H.C.; Alsema, E. Emissions from
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algorithms and approaches to turn LiDAR point cloud into
2.5D urban sce nes was provided. A more cross -disciplinarily
transparent methodology that attains a 95% accurate
segmentation from raw and randomly chosen data was
demonstrated. The methodology implements what previous
literature recommends in terms of integrating cross
disciplinary competences in remote sensing, GIS, computer
vision and urban environmental studies. It is a robust
methodology that can work with poor -quality data and
reconstruct vegetation and building separately but
concurrently. Since the coarse selectio n of building regions is
crucial to reliable results considerable attention was focused
on this first step.The approach was data driven hence the
whole attempt can be regarded as a large scale optimization
problem aiming at best approximating the point clo ud.
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and Triangular Irregular Network were confirmed as essential
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1 48.
tools for the task. Rules of thumb were collected to
incorporate in the development of such scripts for extracting
rooftops for solar pho tovoltaic potential. But there is still
room for the more mathematically rigorous or biologically
minded audience to contribute and orient the workflow to suit
their needs. Hence this can be regarded as the next step
towards a new generation of urban analysis software.