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Universidad Nacional de Rosario – Facultad de Ciencias Exactas, Ingeniería y Agrimensura – Centro de Sensores Remotos – CONICET – CONAE – NASA
UniversidadNacional deRosario
Centro de Sensores Remotos
Researchers: Arq. Carlos Cotlier Dr. Ernesto SeselovskyAgrim. Benito Vicioso Dra. Cristina PacinoIng. Cecilia Cornero Ing. Maria José MilicichTec. Diego A. G. López
Monitoring Urban Night-Time Lights Related to Economic Activity (Gross
Domestic Product) using the Observatory SAC-D/Aquarius Satellite
data.
Facultad deCiencias Exactas,
Ingenieríay Agrimensura
2011 Satellite Direct Readout Conference
Satellite and Instruments
SAC-D HSCARGENTINA
SAC-C HSTCARGENTINA
NOAA-DMSP-OLSDefense MeteorologicalSatellite Program – OperationalLinescan System.
USA
Spatial Res. 300 mADC Res. 8 bitsSNR 50Swath Width 700 Km
Spatial Res. 200 mADC Res. 10 bitsSNR 200Swath Width 830 Km
Spatial Res. 0.55 KmADC Res. 6 bitsSNR Swath Width 3000 Km
Relationship between Night-time Lights.
* Night-time lights remote sensing data can be used to analyze Gross Domestic Product (GDP) by monitoring night-time radiance (urban energy dome) and linear energy detection over roads.
* By means of the analysis of multitemporal data, can be correlated the economic activities by means of the relation between energy consumption and the national economy, regional or county level.
* Argentina had different periods where economy has been up and down, is our intention to correlate archive data from SAC-C and NOAA DSMP and try to add new information from SAC-D HSC sensor, especially from years where economy was in low performance and to compare this urban night-time energy data with periods where the economy of Argentina where going up and GDP was growing up in unusual levels.
Proposed Cities for Urban and Sub-Urban Monitoring
A. Buenos Aires – La Plata.
B. Rosario.
C. Córdoba.
D. Santa Fe – Paraná.
E. Resistencia – Corrientes.
F. San Luis
Cities
A
B
C D
E
F
Methodology I
1. We will have to mask the images (SAC-D, SAC-C, DMSP data) in order following the criteria for get the best night-time data for analysis (Elvidge et al, 2007):
a. No presence of sunlight.b. No presence of moonlightc. No presence of solar glared. Cloud free based on thermal detection of clouds and lightning.
2. To counteract illumination glare that exceeds urban city limits a “threshold calculation” must be done (Imhoff, 1997) and will be applied to clean the images data.
3. With the processed data and several data like social, economic and urban variables, the following methodology will be addressed in order to correlate them and to obtain correlation coefficients.
3D Representation of the Night-Time Lights Dome
Energy Distribution Pattern of an Urban Area resembles a dome, x,y plane represents the illuminated area and z axis the energy utilization
x
yz
Rainbow Palette B/W Palette
Methodology II
Social and urban variables:
a. Generate the 3D model surface with the z axis (energy values) to obtain the energetic dome and Calculate the volume of the dome using remote sensing and GIS software.
b. Compare the illuminated area with urban shapes by superimposing both layers, in order to determine the relationship between the illuminated with georeferenced urbanized area maps of the city.
c. Scattergrams to show relationship between: dome volume and population density of the urbanized area, dome volume and energy consumption (in kw/h), consumption (in kw/h) and population of the urbanized area, illuminated area and gross domestic product will be constructed and find an equation that best fit the mentioned relationship, performed with math software like R or Mathlab (Welch, 1980).
Methodology III
Social and urban variables:
d. For each of the four relationships will be obtained the correlation coefficient R.
e. As results, the correlation coefficient R will allow to determinate if the variables researched are related with the economical statistical data and the remote sensing nightlights processed data.
f. Color composite multitemporal study images will allow to detect changes in nighttime lights in the city urban core.
g. To follow temporal roads illumination evolution in the Province of San Luis with SAC-D, SAC-C and DMSP image data creating RGB color composite images. If possible anothers areas from Argentina will be analyzed.
Methodology IV
Economic variables:
a. Determine relationships between economic activity values and the radiance measured for determined geographical (urban-industrial) areas and the economic variables. For this, will be used regression models that can be linear or logarithmic. Logaritmic tend to be more precise, especially when trying to make comparisons, both temporal and geographical space.
b. Gross Domestic Product (GDP) and other "proxy" variables will be used, by approximation to substitutes GDP. The “proxy” variable can be classified such as when there is a high correlation between it (proxy) and the GDP variable.
Methodology V
Economic variables:
c. From the temporal point of view, to analyse two different periods:
1. The period 2000-2009, where we will try to make a comparative historical analysis.
2. From 2010 onwards.
d. From the spatial point of view, first we will analyze macro relationships that could be established using the national and provincial values. In these cases the IVA (gross income taxes) and the energy consumption variable can be sensible as “proxy" variables for this type of relationship.
Rosario
Night-time Lights SAC-C HSTC – 27 May 2003 – 1:30 am UT
National Route 9
Industrial Fringe(Rosario - San Lorenzo)
• Pto. San Martín• San Lorenzo City• Fray Luis Beltrán• Granadero Baigorria• Capitán Bermudez
Cities
V. G. Galvez
Night-time Lights SAC-C HSTC – 27 May 2003 – 1:30 am UT
Easter border due Parana River
Lights due Rosario-VictoriaBridge
Lights patterns due illuminated avenues and populated neighborhoods
San Luis
National Route 7(The National Route 7 in San Luis’s territory
is an illuminated highway)
Night-time Lights SAC-C HSTC – 27 May 2003 – 1:30 am UT
Villa Mercedes
Provincial Route 9(Highway)
The beginning and end of the illuminated road and highways are the San Luis State borders.
San Luis
National Route 7(The National Route 7 in San Luis’s territory
is an illuminated highway)
Villa Mercedes
Provincial Route 9(Highway)
The beginning and end of the illuminated road and highways are the San Luis State borders.
SAC-C HSTC RGB Composition: 27/05/03-15/04/02-24/08/01
Santa Fe
Paraná
Rafaela
Night-time Lights SAC-C HSTC – 27 May 2003 – 1:30 am UT
Ciudad Autónomade Buenos Aires
(Buenos Aires City)
La Plata
Panamericana Highway
Night-time Lights SAC-C HSTC – 27 May 2003 – 1:30 am UT
Zárate
Campana
Valdez Peninsula
Argentina Coastline
Night-time Lights SAC-C HSTC – 13 Jun 2004 – 1:30 am UT
Puerto Deseado
Trelew
Rawson
Fishing Boats predig squid
Argentina Coastline
Night-time Lights SAC-C HSTC – 25 Dec 2008 – 1:30 am UT
Puerto DeseadoCity
Note the intensity of the fishing boats compared with Puerto Deseado City – Argentina (population 12000)
Continental Argentina - Patagonia Atlantic Ocean
Inhabitantsper Hectare
Relationship between Night-time Lightsand Population Density of the city of Rosario
