International audienceMost studies of anopheline mosquito larval ecology have been done in rural settings. However, latest data based on two cross-sectional surveys in Antananarivo, the capitol of Madagascar, shown low rate of malaria cases among febrile episodes but autochthonous malaria cases exist. Anopheles funestus constitutes the main vector of malaria in the highlands of Madagascar. This paper described the determination of their potential breeding site using remotely sensed data. A supervised classification by the classical method of maximum likelihood was used for enhanced thematic mapper image of Landsat 7. Overall accuracy of the classification was 86% and kappa index was 0.835. Determination of landscape change by subtraction of images acquired on January and July was carried out for the Advanced Synthetic Aperture Image Precision images of Envisat. Increased backscatter coefficient between the two periods made possible to raise ambiguity between rice fields and other vegetation. That may improve the determination of potential anopheles breeding sites

Jolivet, Laurence

Rakotomanana, F.

Rudant, Jean-Paul

Vatosoa Randremanana, Rindra

English

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Remote sensing and urban malaria: radar Envisat contribution for the determination of potential Anopheles breeding site in Antananarivo (Madagascar)

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Remote sensing and urban malaria: radar Envisat
contribution for the determination of potential
Anopheles breeding site in Antananarivo (Madagascar)
F. Rakotomanana, Laurence Jolivet, Rindra Vatosoa Randremanana,
Jean-Paul Rudant
To cite this version:
F. Rakotomanana, Laurence Jolivet, Rindra Vatosoa Randremanana, Jean-Paul Rudant. Remote
sensing and urban malaria: radar Envisat contribution for the determination of potential Anopheles
breeding site in Antananarivo (Madagascar). Envisat Symposium, Apr 2007, Montreux, Switzerland.
￿halshs-02344456￿
 
F. Rakotomanana*1, L. Jolivet2, R.V. Randremanana1, J.P. Rudant3. 
 
* Corresponding author 
 
Affiliation 
1Cellule Système d’Information Géographique, Unité Epidémiologie, Institut Pasteur, Madagascar 
2Ecole Nationale des Sciences Géographique, Marne La Vallée, France 
3Institut Francilien des Sciences Appliquées, Université Marne La Vallée, France 
 
Abstract 
 
Most studies of anopheline mosquito larval ecology have been done in rural settings. However, latest data based on two 
cross-sectional surveys in Antananarivo, the capitol of Madagascar, shown low rate of malaria cases among febrile 
episodes but autochthonous malaria cases exist. Anopheles funestus constitutes the main vector of malaria in the 
highlands of Madagascar. This paper described the determination of their potential breeding site using remotely sensed 
data. A supervised classification by the classical method of maximum likelihood was used for enhanced thematic 
mapper image of Landsat 7. Overall accuracy of the classification was 86% and kappa index was 0.835. Determination 
of landscape change by subtraction of images acquired on January and July was carried out for the Advanced Synthetic 
Aperture Image Precision images of Envisat. Increased backscatter coefficient between the two periods made possible 
to raise ambiguity between rice fields and other vegetation. That may improve the determination of potential anopheles 
breeding sites.  
 
BACKGROUND  
In most of sub-Saharan Africa countries, 
malaria transmission is generally intense in rural 
settings. In contrast, malaria transmission occurs at 
significantly lower level in urban areas where 
population density is high, and where the number of 
mosquito breeding sites is reduced [1]. Central 
Highlands of Madagascar are known as a malaria 
epidemic-prone area. Several malaria cases have 
been reported during the last epidemic of the 80’s. 
In addition to a policy of early drug therapy, a 
vector control programme was launched by the 
“Ministère de la Santé, du Planning Familial et de 
la Protection Sociale”. It was based on indoor 
insecticide spraying. Anopheles funestus constitutes 
the main vector of malaria in the Central Highlands 
of Madagascar. Rice fields are known as their 
potential breeding sites [2-4].  
The latest data based on two cross-sectional 
surveys in 43 health centres in Antananarivo 
showed low rate of malaria cases. In February 2003 
(rainy season) and July 2003 (dry season), 1.9% 
positive cases and 1.5% positive cases were 
respectively detected. Only two cases of 15, both P. 
falciparum, were likely to have been autochthonous 
(0.26%). In July, three cases were considered to be 
of local origin (0.4%) [5].  
Antananarivo, like most of urban areas was 
considered as a malaria transmission free zone. 
However, the latest cross-sectional surveys had 
shown that autochthonous malaria cases exist. The 
issue is to know if these cases could induce an 
epidemic. Antananarivo landscape is characterized 
by both urban and agricultural area with vast rice 
field plains. Rapid change of urban area involved 
updating the map of potential mosquito breeding 
sites using remotely sensed data. It constitutes a 
relevant parameter to assess the malaria epidemic 
risk. This study aimed to determine the contribution 
of radar remote sensing to detect these mosquito-
breeding sites.  
MATERIALS AND METHODS 
The study area includes the urban area of 
Antananarivo and the immediate neighbourhoods, 
18°48’S and 47°24’E in the North West 19°00’S 
and 47°42’E in the South East. The landscape is 
characterized by both urban and agricultural area 
with vast rice field plains in the north and west.  
An Enhanced Thematic Mapper Plus (ETM +) 
image of Landsat 7, acquired on May 2000 and two 
Advanced Synthetic Aperture Image Mode 
Precision (ASA_IMP_1P) images of Envisat, 
acquired on January and July 2004, were used for 
the determination of the mosquito potential 
breeding sites (Tab. 1).   
A supervised classification of the ETM+ image 
by the classical method of maximum likelihood was 
used to map rice fields. The classification accuracy 
was estimated by calculating the Kappa coefficient. 
Adaptive filters were applied to improve the quality 
of ASA_IMP_1P images. Landscape change 
between January and July was compared by the 
REMOTE SENSING AND URBAN MALARIA: RADAR ENVISAT CONTRIBUTION FOR 
THE DETERMINATION OF POTENTIAL ANOPHELES BREEDING SITE IN 
ANTANANARIVO (MADAGASCAR) 
_____________________________________________________ 
Proc. ‘Envisat Symposium 2007’, Montreux, Switzerland 
23–27 April 2007 (ESA SP-636, July 2007) 
 
way of visual interpretation and backscatter 
coefficient analysis.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 1.Data specification 
 
ETM + Landsat 7 
    Date 
    Preprocessing level 
    Band 
 
2000/05/12 
1G 
1-7, P 
ASAR Envisat 
    Date 
     
    Product type 
    Polarisation  
    Band  
 
2004/01/19  
2004/07/12 
ASAR_IMP_1P 
VV 
C 
Digital Elevation Model 
(EO Epidemio Project) 
Date 
Product type 
 
 
       2004 
       ASAR_IM4 
       ASAR_IM5 
Topographic maps 
Date 
Scale 
 
       1970 
       1:10 000 
       1:50 000 
 
Topographic maps and GPS location were used 
to complete visual interpretation of the images and 
for supervised classification of the image ETM+ 
Landsat7. There were used especially for 
identifying the training sites, the test sites location 
and for the ground truth validation. Geographical 
coordinates of these sites were positioned using 
handheld Global Positionning System (GPS). 
Digital Elevation Model (DEM) was acquired 
by the way of Epidemioproject). It was used to 
assert from their location the rice fields in the plain 
and the vegetation located on the crests. 
RESULTS 
Composite image, with near infrared (band 4) 
in red channel the mid-infrared (band 5) in the 
channel of green and red (band 3) in the channel of 
blue, shows vegetation type and condition 
characterized by colour hues (Fig 2).  
 
 
 
 
 
 
 
 
 
 
 
 
Antananarivo 
 
 
 
Figure 2. Infrared false colour composite  
of the image ETM+ Landsat7 
The supervised classification by the method of 
maximum likelihood showed confusion between 
rice fields and chlorophyllous trees. Similar 
confusion was observed between lakes and flooded 
rice fields. Overall accuracy of the classification 
was 86%. Kappa coefficient was 0.835. 
Determination of landscape change was carried out 
by subtraction images of Envisat after 
normalization (Fig 3 and 4).  
Figure 1. Location of study zone 
 
 
 
 
 
 
 
 
 
 
 
 
 
●Lake
●Built Area
●Rice fields
●Urban area  
 Figure3. Image of January 2004  
(ASA_IMP_1P Envisat)  
 
Rice fields present higher response in July than 
in January. Low backscatter coefficients 
characterized the flooded rice field in January. 
Young rice shoot in the seedbeds, cut plants after 
the harvest and rough ground of rice fields in 
ploughing were characterized by high backscatter 
coefficient in July. Turbid water body in January, 
rainy season, present higher backscatter coefficient. 
Change between the two periods made possible to 
raise ambiguity between rice fields and other 
vegetation (Fig 5). 
It allowed removing commission error 
observed with optical data. However, the results 
cannot map rice fields only from other potential 
breeding sites like marsh and other wetland.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CONCLUSION 
In health application, remote sensing is 
commonly used to identify vector habitats e.g. 
vector borne diseases. Kaya et al. reported that the 
combined use of remote sensing and GIS provides a 
strong tool for monitoring environmental conditions 
that are conducive to malaria, and for mapping the 
disease risk to human population [6]. Results shows 
that supervised classification of optical data by the 
method of maximum likelihood may present 
confusion between rice fields and other vegetation 
so such study showed interest in using high spatial 
resolution combining passive and active data 
acquisition [7, 8]. Uneven aspect of the highlands 
of Madagascar constitutes the limitation of using 
radar remotely sensed data. In so far as rice fields 
located at the bottom of small valleys or in terrace, 
following hill round, using radar data is not really 
suitable for reliable extraction of rice fields.  That 
was not the case of the plain of Antananarivo where 
the signal change of rice fields was easily 
detectable even if their intensity varied, due to the 
lag of cultivation calendar and the problem of water 
management. The contribution of radar imagery 
allows (i) data acquisition during wet season which 
eases the comparison of different periods [9, 10] 
and (ii) erasing confusion between larval habitats 
and other vegetation such as reeds, trees.  Hence 
radar remote sensing is the obvious choice as the 
most appropriate data source for multidate 
acquisition. This work showed the interest of using 
high spatial resolution image combining passive 
and active data acquisition. The results contribute to 
the malaria vector control in epidemiological 
application.  
●Lake  
●Built Area
●Rice fields  
●Urban area  
 
Acknowledgments: 
We are grateful for the financial and collaborative 
support from the Action Concertée 
InterPasteurienne (ACIP), the European Spacial 
agency by the way of Project CAT 1-2320 and 
Earth Observation in Epidemiology, the Ecole 
Nationale des Sciences Géographique (ENSG) and 
Institut Pasteur de Madagascar. 
Figure 4. Image of July 2004 
 (ASA_IMP_1P Envisat) 
 
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Trees 
Water bodies  
Soil 
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Remote sensing and urban malaria: radar Envisat contribution for the determination of potential Anopheles breeding site in Antananarivo (Madagascar)

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