Design of sample units to the inventory of afforestation of streets in

Transcription

THE DES IGN OF SAMPLE UNITS FOR INVENTORY OF URB AN AFFORES TATION IN CURITIB A
CITY, PARANÁ STATE, B RAZIL
Everaldo Marques de Lima Neto 1 2 , Daniela Biondi 3
ABSTRACT
Inventories of urban trees are carried out by using sampling methods, which are often complex because they
require delineation of fields for data collection and the city structure can be an obstacle to delineate a plot. The
objective of this research was to compare the area of p lots measured in the conventional way with areas
calculated in a GIS environ ment. We used three square-shaped plots of an inventory conducted in 1984 (500 x
500 meters). We used the street map of the city of Curit iba, Paraná State, Brazil, containing streets, blocks and
neighborhoods in a vector format. The areas of the plots were stored in the polygon type in GIS and measured
with a measuring tape. The differences in the measurement of three parcels in a GIS environ ment with those
found in the conventional inventory were 0.005, 0.638 and 0.723 ha. These differences occurred due to limit ing
factors in field measurements related to systematic and random errors of observation in conventional inventories,
such as topographic conditions and equipment defects. We observed that GIS programs greatly facilitate
fieldwork, especially in the plots delineation.
Key words: Geographic Informat ion System; Samp ling; inventory costs.
DELINEAMENTO DE UNIDADES AMOSTRAIS PARA O INVENTÁRIO DA ARBORIZAÇÃO DE
RUAS EM CURITIBA, PR
RES UMO
Os inventários de arborização urbana feitos por métodos de amostragem são, muitas vezes, complexos porque
necessitam da delimitação de parcelas para as coletas de dados e a estrutura da cidade pode ser uma barreira para
o caminhamento da parcela. O objetivo desta pesquisa foi comparar a área de parcelas medidas em inventário
convencional co m áreas calcu ladas em ambiente SIG. Foram ut ilizadas 03 parcelas de u m inventário realizado
em 1984 com forma de um quadrilátero (500 x 500 m). Utilizou-se o mapa de arruamento de Curitiba, contendo
ruas, quadras e bairros em fo rmato vetorial. As áreas das parcelas foram armazenadas com o tipo polígono em
amb iente SIG e mensuradas em campo com trena. As diferenças na medição das 3 parcelas em amb iente SIG
com as encontradas no inventário convencional foram: 0,005, 0,638 e 0,723 ha. A obtenção destas diferenças foi
devido aos fatores limitantes para med ições que ocorrem em campo relacionado com os erros sistemáticos e
aleatórios de observação em inventários convencionais, tais como: a topografia do terreno e defeitos em
equipamentos. Constatou-se que os programas de SIG facilitam muito a execução dos trabalhos de campo,
principalmente na delimitação de parcelas a serem inventariadas na forma convencional.
Palavras-chave: Sistema de informações geográficas; Amostragem; Custos do inventário.
1
2
3
Eng. Florestal, Doutorando em Engenharia Florestal, UFPR - Curitiba – PR, everaldo.limaneto@gmail.com
Data recebimento: 06/10/2011 - Data de publicação: 15/12/2012
Drª. Profa Associada, UFPR - Departamento de Ciências Florestais, Curitiba – PR, dbiondi@ufpr.br
Soc. Bras. de Arborização Urbana
REVSBAU, Piracicaba – SP, v.7, n.4, p.107-117, 2012
INTRODUCTION
The completion of an inventory of street trees is the
population structure. S.U. can be a street, block,
surest way to know the city’s tree asset, providing
street sections, a block group, or it may be the result
informat ion to priorit ize interventions, such as
of a process of dividing areas in maps of the city or
phytosanitary treatments, removal and/or planting
area to be inventoried (SILVA et al., 2005).
and replanting of trees. It also indicates the need for
Schreuder et al. (1993) state that a sample unit
pruning procedures.
should have a size that can includes a representative
A conventional inventory of afforestation requires a
number of trees, but small enough that does not
large nu mber of variables to be measured in the
demand long time for data collection and does not
streets demanding high costs, once it involves
increase costs.
walking along the streets, a number of people for
The inventory accuracy will depend on the
data collection, in addition to a great amount of
variability of the tree population represented in the
time required to measure variables.
S.U. and on the intensity of sampling emp loyed.
Many techniques have been disseminated in order
Among the S.U. used are sizes, shapes and
to promote the implementation, maintenance and
arrangements that better represent the several
monitoring
variations of tree populations. This allows to
of
afforestation,
including
data
computerization that allows analysis, updating and
inventory
storage of the large amount of informat ion
accuracy at reduced cost (SOARES, 1980). S.U. are
generated by an inventory. Data computerizat ion
mostly found in square and rectangular shapes.
reduces
an
Inventories demand huge amounts of resources, and
indispensable tool for management of urban trees
the greater the number of variab le studied, the
(SILVA et al., 2007).
higher the costs to carry out the inventory (SILVA
Thus, the use of Geographic Informat ion Systems
et al., 2007).
(GIS) has been an efficient tool in many urban
Thus, when planning an inventory, we should avoid
studies to minimize the difficult ies encountered in
oversizing S.U. Therefore, it is necessary to
collecting data in loco, although research on GIS
establish a pilot sampling to prevent the final
applications in urban forestry inventories is still
product
scarce. For Lima Neto et al. (2010), GIS integrates
representativeness. Another problem is to establish
a number of trees with large capacity of storage and
objective criteria in the delineation of S.U., i.e.,
spatial representation of data at multip le levels of
those S.U. must have well-defined and accessible
detail. Therefore, it is important to have available
vertices when the fieldwork is performed. Access to
satellite imag ing and/or aerial photographs of high
the sample units is relevant regard ing in loco survey
spatial resolution and quality to obtain area
for inventory implementation. In urban areas,
delineation
corners and vertices of the parcels that are located
costs,
and
providing
city
dendrometric
managers
variab les
in
each tree
from
being
population
measured
with
greater
beyond
its
inventories of urban afforestation.
in lots and/or residences hamper an efficient
Furthermore, it is essential to mark the areas to be
execution of the inventory.
surveyed. The first step when planning an inventory
Study on S.U. is also important for adequate
is to identify Sample Units (S.U.) and tree
planning of human and financial resources in the
Everaldo Marques de Lima Neto and Daniela Biondi
108
qualitative and quantitative surveys and inventories
In this sense, this research aims to compare the area
of urban afforestation (SILVA et al., 2005). Such
of S.U. measured in conventional inventories with
importance is justified by the need to increase
areas delineated in the GIS environ ment in order to
probability of better distribution of S.U., reduce
facilitate inventory implementation by reducing
survey time, and obtain maximu m efficiency of
time spent for measurements with greater accuracy.
work teams, among other aspects (MILANO et al.,
1992).
MATERIALS AND METHODS
Location and characterization of the study area
(1984). The author divided the map of Curit iba at a
scale 1:20.000, using 15 S.U. with a dimension of
The municipality of Curitiba, capital city of Paraná
500 x 500 meters. Based on the 15 S.U. used by
State, Brazil, is located in the southern region of
Milano (1984), we selected three S.U. (Figure 2) in
Brazil. It is situated in the east of the state at
our study due to the limited orthophotos provided
latitude 25o 25'40”S and longitude 49o 16'23”W
by IPPUC.
(Ground Zero – Tiradentes Square) (Figure 1).
The S.U. chosen had the greatest number of trees
In the Köppen classification, Curitiba has Cfb
and highest species diversity in the inventory
climate, defined as temperate (sub-tropical) humid,
carried out by Milano (1984), which are Samp le
mesothermal,
cool
Unit Bigorrilho; Sample Un it Água Verde and
summers and winters with frequent frosts and
Sample Unit Jard im Social. All data on the trees
occasional snowfalls. The average temperatures
that comprise these three S.U. were updated in an
range fro m 20.87 ºC in the summer (2000-2009) to
inventory carried out in 2010.
without
dry season
with
14.77 ºC in the winter (2000-2009). The average
altitude is 934.6m above sea level and the area of
Spatial delineation of the S.U.
the municipality covers 435 km², stretching 35 km
fro m south to north and 20 km fro m east to West
Based on the map of the area elaborated by Milano
(IPPUC, 2009).
(1984), we used GPS Garmin to obtain geographic
coordinates at the vertices of the S.U. analyzed.
The data plotting provided by GPS Garmin was
Methodol ogy
carried out in the Geoprocessing software ArcView
The selection of sample units (S.U.) was based on
9.2, adopting the UTM (Universal Transversal de
the qualitative and quantitative analysis of urban
Mercator) and Datum SAD 69 (South American
afforestation in Curitiba City carried out by Milano
Datum), 22S.
THE DESIGN OF SAMPLE UNITS FOR…
109
Figure 1 – Location of Curitiba City – Paraná State, Brazil.
Figure 2 – Location of S.U. chosen for construction of cartographic databases and analysis of street trees
Source: LIMA NETO (2011)
110
We used a map of Curitiba City containing streets,
to their respective data plans, allowing to define the
blocks and neighborhoods in vectorial format
plots analyzed. For the delineation of S.U., we used
provided by IPPUC, wh ich allo wed to delineate the
maps elaborated by Milano (1984) in his field work.
areas of the S.U. These areas were stored in
Next, we performed a vectorial representation of
vectorial format. The shapefile is an archive format
the delineations of the S.U., grouping them under
of ArcView that is capable of storing a point, a line
layers with the orthophotos, establishing the
or a polygon. For the vectorial representation, we
classification area of street afforestation.
defined the polygon type to represent the area of the
Therefore, the areas obtained from processing in a
S.U. selected.
GIS environ ment were similar to the area used in
Sequentially, we started to import vectorial data
the study of 1984 and in the follo w-up inventory in
(.shp) containing streets, blocks and neighborhoods
2010.
RES ULTS AND DISCUSS ION
In his study on street afforestation, Milano (1984)
found 46 species (Table 1), represented for 554
arboreal and shrub individuals.
TABLE 1 – Species studied in the tree streets of Curitiba city in 1984
Scientific name
Popular name
Acacia mearnsii
Acacia podalyriaefolia
Acacia polyphyla
Acer negundo
Araucaria angustifolia
Caesalpinia peltophoroides
Cassia leptophylla
Cassia macranthera
Cassia multijuga
Chorisia especiosa
Citrus reticulata
Cryptomeria japonica
Cunninghamia lanceolata
Cytharexylum myrianthum
Enterelobium contortisiliquum
Eryobotrya
Erythrina
Erythrina falcata
Eucalyptus cinerea
Eucalyptus viminalis
Eugenia
Eugenia uniflora
Euphorbia cotinifolia
Ficus elastica
Hibiscus rosasinenses
Jacaranda mimosifolia
Acácia-negra
Acácia-mimosa
Monjoleiro
Acer
Araucária
Sib ipiruna
Cassia-fastuosa
Cassia-manduirana
Cassia-multijuga
Paineira
Limoeiro
Cedro-japonês
Pinheiro-chinês
Pau-de-tamanco
Tamboril
Nêspera
Água
Verde
Bigorrilho
X
X
X
X
X
X
X
X
X
X
Jardim
Social
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Corticeira-da-serra
Eucalipto-prateado
Eucalipto
X
X
X
Pitangueira
Leiteiro-vermelho
Ficus
Hib isco
Jacarandá
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
111
Jacaranda purberula
Lafoensia pacari
Lagerstroemia indica
Ligustrum lucidum
Magnolia gradiflora
Melia azedarach
Hovenia dulcis
Nerium oleander
Palmeira
Paraptadenia
Pinus eliottii
Populus
Prunus persica
Psidium catleianum
Salix babylonica
Schinus terebentifolius
Sebastiana klotzchiana
Sesbanea punicia
Spathodea campanulata
Tabebuia
Tabebuia alba
Tabebuia avellanedae
Tabebuia chrysotricha
Tibouchina
Tibouchina granulosa
Tibouchina pulchra
Tibouchina sellowiana
Tipuana tipu
Taxodium distichum
TOTA L
Carobinha
Dedaleiro
Extremosa
Alfeneiro
Magnólia
Cinamo mo
Uva-do-japão
Espirradeira
Palmeira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Pinus
Pessegueiro
Araçá-rosa
Chorão
Aroeira
Branquilho
Acácia-vermelha
Tulipeira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Ipê-amarelo
Ipê-ro xo
Ipê-amarelo-miúdo
Quaresmeira
Manacá-da-Serra
Quaresmeira
Tipuana
Pinheiro-do-brejo
X
X
X
X
X
X
X
X
X
X
X
X
X
35
24
46
Source: Adapted fro m MILA NO (1984)
established for the height of the buildings, but they
Sample Unit Bigorrilho
must comply with restrictions imposed by the
This sample
unit
covers two neighborhoods
Ministry
of
Aeronautics
and
Protection
of
Bigorrilho and Mercês (Figure 3), both located in
Microwave Channels of Telecommunication for the
the Matriz region. The neighborhood Bigorrilho
Paraná State.
covers an area of 350.30 ha with a population of
In the Sample Un it Bigorrilho, Milano (1984) found
30,065 inhabitants. The neighborhood Mercês is
24 species (Table 1), represented by 381 arboreal
also situated in the same region, covering an area of
and shrub individuals (MILANO, 1984).
327.60 ha with 14,191 inhabitants (IPPUC, 2010).
Sample Unit Água Verde
This neighborhood is situated in the Residential
This sample un it is situated in the neighborhood
Zone of Mercês (ZR-M). In this region, there are
Água Verde (Figure 4) located in the Portão
axes of urban growth, characterized as expansion
Region. It covers an area of 476.40 ha with 53,228
area of the tradit ional city center and as corridors
inhabitants, which shows the highest demographic
for co mmerce, services and transportation, using as
density of the municipal territory.
support a trinary circulation system (IPPUC, 2010).
The buildings are high and alternate with two or
three-floored
build ings. There
are
no
limits
112
Figure 3 – Representation in GIS environ ment of the area o f Samp le Unit Bigorrilho
Legend
Parcel
Neighborhood Bigorrilho
Neighborhood
Mercês
The zoning typology in this S.U. is Residential
Zone 4 (ZR-4) where constructions of six floors are
Sample Unit Jardi m Social
allo wed (IPPUC, 2010). The use of the area is
predominantly residential and there are houses and
This sample unit is located in the neighborhood
residential buildings.
Jardim Social (Figure 5) wh ich is situated in the
Milano (1984) found 35 different species (Table 1)
Matriz reg ion. According to IPPUC (2009), this
corresponding
neighborhood has 6,113 inhabitants and covers an
to
341
arboreal
and
shrub
area of 188.5 ha.
individuals.
113
Figure 4 – Representation in GIS environ ment of the area o f Samp le Unit Água Verde
Legend
Parcel
Neighborhood Água
Verd e
This is a Residential Zone considered as ZR-1,
according to the criteria
Comparison of the methods
for land use and
is
As mentioned in the methodology, the S.U. were
predominantly residential are constructions of up to
selected based on the study conducted by Milano
two floors are permitted (IPPUC, 2010).
(1984) with 500 x 500 meters.
occupation.
The
pattern
of
constructions
In the relocation of the S.U. in a GIS environment,
we observed a difference in size of the S.U.
delineated in the imaging than the inventory carried
out in 1984 (Table 2).
114
Figure 5 – Representation in GIS environ ment of the area o f Samp le Unit Jardim Social
Legend
Parcel
Neighborhood Jardim
Social
Table 2 – Area of S.U. obtained in GIS co mpared to inventory of afforestation of 1984
Sample
Units
Jardim Social
Água Verde
Bigorrilho
(1)
Established area in 1984
25
25
25
(2)
Sample area
24.99
25.63
25.72
Difference between (1) and (2)
(m²)
50
6.83
7.23
We observe that the Samp le Unit Jardim Social
The inaccuracy of delineation of the S.U. in the
showed smaller area than in the inventory of 1984,
inventory carried out in 1984 is attributed to
and the difference was 50m². The other S.U.
scarcity of large-scale cartographic resources, such
showed a larger area (Table 2). The differences
as data on topography, curves of level, detailed
observed in the streets of Sample Unit Bigorrilho
maps of streets, roads, blocks and sidewalks axes.
and Água Verde may be considered high, given that
Furthermore, the mapping was carried out manually
many street trees may be embedded in these
on graph paper with cm incurring errors in field
differences causing extrapolation in the results and
measurements by the user. Currently, GIS programs
therefore alterations in the representativeness of the
have made the accomplishment of fieldwo rk easier
inventory.
through delineation inventories of S.U. in a GIS
environment.
115
Silva (2003) states that it is very important to
and OLIVEIRA FILHO, 2002; DISPERATI et al.
measure the representativeness of the data in
2007a; DISPERATI et al., 2007b ).b
projects developed with GIS. A mong spatial data,
Oliveira Filho et al. (2005) applied GIS to support a
there is always uncertainty and errors.
forestry experiment conducted at the municipality
To ensure the data quality in a GIS environ ment, it
of Irat i, Paraná State, Brazil, and implemented a
is essential that tests be performed to ensure data
spatial database for two distinct objects: trees and
accuracy, since it is virtually impossible for GIS to
plots. They authors confirmed that the geo-objects
work with inaccurate data.
provided
Despite errors, the applicat ion of GIS techniques
enriching the research and its results.
a
greater amount
of combinations
for delineation of geo-objects in images has a better
performance than measurement of areas in the field
(OLIVEIRA, 1980; LOBÃO, 1996; DISPERATI
CONCLUS IONS
The differences between the data obtained in the
We recommend the elaboration and use of
distinct collection methods are attributed to the
cartographic data of quality for use in studies on
quality of cartographic databases used and/or errors
urban forestry. Furthermore, the use of stereoscopy
of observation and measurement in conventional
techniques can help or improve exact delimitat ion
inventories.
of areas of S.U.
ACKNOWLEDGEMENTS
The authors wish to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico – fo r the financial
support to carry out this research.
REFERENCES
DISPERATI, A. A. SANTOS, J. R.; OLIVEIRA FILHO, P. C.; NEEFF, T. Aplicação da técnica “filtragem de
locais máximas” em fotografia aérea dig ital para a contagem de copas em reflorestamento de Pinus elliottii.
Piracicaba, Scientia Forestalis, n. 76, p. 45-55, 2007.
DISPERATI, A. A.; AMARAL, R. F. do; SCHULER, C. A. B. Fotografi as aéreas de pequeno formato:
Aplicações ambientas. Guarapuava: UNICENTRO, 2007. 262 p.
DISPERATI, A. A.; OLIVEIRA -FILHO, P. C. Delineação automática de copas de árvores em imagens de alta
resolução: potencialidades e limitações. In: SEMINÁ RIO DE ATUA LIZA ÇÃO EM SENSORIAM ENTO
REM OTO E SISTEMASDE INFORMA ÇÕES GEOGRÁFICAS APLICADOS Á ENGENHA RIA
FLORESTA L, 5., 2002. Curitiba. Anais… Curitiba: 2002. p.81- 88.
INSTITUTO DE PESQUISA E PLANEJAMENTO URBANO DE CURITIBA - IPPUC. Uso e Ocupação do
Solo de Curiti ba. Disponível em: http://www.ippuc.org.br. Acesso em 25 de outubro de 2010.
116
INSTITUTO DE PESQUISA E PLA NEJAM ENTO URBANO DE CURITIBA - IPPUC. Mapas de
Arruamento. Cu rit iba: IPPUC, jun. 2005. Disponível em: http://www.ippuc.org.br/informando/index_
mapasarruamento.htm. Acesso em 25 de junho de 2009.
LIMA NETO, E. M. Aplicação do sistema de informações geográficas para o inventário da ar borização de
ruas de Curiti ba, PR. Dissertação (Mestrado em Engenharia Florestal), UFPR, Cu rit iba, Paraná, 2011. 124 p.
LIMA NETO, E. M. L.; BIONDI, D.; A RAKI, H. Aplicação do SIG na arborização viária – Unidade Amostral
em Cu rit iba-PR. In: SIM PÓSIO BRASILEIRO DE CIÊNCIAS GEODÉSICA S E TECNOLOGIAS DA
GEOINFORMA ÇÃO, 3., 2010, Recife. Anais... Recife: UFPE – Departamento de Geo mát ica, 2010.
LOBÃO, S. M. F. Entrada de Fotografias Aéreas Coloridas de Médio Formato em SIG. Salvador. In: SIMPÓSIO
BRASILEIRO DE SENSORIAMENTO REM OTO, 8, Anais..., INPE, p. 707-710, 1996.
MILA NO, M S. Avaliação e Análise da Arborização de Ruas de Curiti ba-PR. Dissertação (Mestrado em
Ciências Flo restais), UFPR, Curitiba, Paraná, 1984. 130 p.
MILA NO, M. S.; SARNOWSKI FILHO; ROBA YO, J. A. M. Estudo comparativo de unidades amostrais
utilizadas para inventário qualiquantitativo de arborização de ruas em Curitiba. In: CONGRESSO BRASILEIRO
SOBRE A RBORIZAÇÃ O URBA NA, 1., 1992, Vitória, ES. Anais... Vitória: SBAU, 1992. p. 343-350
OLIVEIRA FILHO, P. C.; DISPERATI, A. A.; LISBOA, G. S.; VENANCIO, T. L. Um sistema de informações
geográficas como suporte a um experimento florestal na FLONA de Irati-PR. In: XII Simpósio Brasileiro de
Sensoriamento Remoto - SBSR, 2005, Go iânia. Anais... São José dos Campos: INPE, 2005.
OLIVEIRA, Y. M. M. Correlações entre parâmetros dendrométricos em Araucari a angustifolia, utilizando
fotografias aéreas. 1980. Dissertação (Mestrado em Engenharia Florestal) – Universidade Federal do Paraná,
Curitiba, 1980, 133 p.
SCHREUDER, H. T.; GREGOIRE, T. G.; WOOD, G. B. Sampling methods for multire-source Forest
inventory. New Yo rk: Jonh Wiley & Sons, In., 1993.
SILVA , A. B. Sistemas de Informações Geo-Referenciadas. Campinas, SP. Ed itora: UNICAMP, 2003.
SILVA , A. G.; GONÇALVES, W.; LEITE, H. G.; SANTOS, E. dos. Estudo do tamanho e da forma de unidades
de amostra, utilizando a amostragem casual simp les para inventariar a arborização urbana viária. Natureza &
Desenvol vi mento, v. 1, n. 1, p. 59-66, 2005.
SILVA , A. G.; PAIVA , H. N.; GONÇA LVES, W. Avali ando a arborização urbana. Série Arborização
Urbana. Coleção Jardinagem e paisagismo, Vo lu me 5. Viçosa – MG : Ed. Aprenda Fácil, 2007. 346p.
SOA RES, V. P. Eficiência rel ati va de tamanhos e de formas de uni dades de amostra em pl antações de
Eucalyptus grandis de origem hí bri da, na região de B om Despacho, Minas Gerais. 1980. 80 f. Dissertação
(Mestrado em Ciência Florestal), Un iversidade Federal de Viçosa, Viçosa, 1980.
117

Design of sample units to the inventory of afforestation of streets in

Transcription

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