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Remote sensing based approach for monitoring urban growth in Mexico city, Mexico: A case study
Unformatted Document Text:  Figure 2: Principal component analysis from the NDVI Figure 3: Principal component analysis from the thermal band From the maximum likelihood classification results (Table 1, Figure 6 and 7), Mexico city expanded spatially towards the South and West, between 1989 and 2000. From the “no null” classification, the area classified as urban in the imagery, increased by 235574 hectares , while the area occupied by water reduced by 14874 hectares between 1989 to 2000. However, the “with null classification”, urban area increased by 165624 hectares while water increased by 4620 hectares (Table 1). 6

Authors: Obade, Vincent.
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Figure 2: Principal component analysis from the NDVI
Figure 3:  Principal component analysis from the thermal band
From the maximum likelihood classification results (Table 1, Figure 6 and 7), Mexico 
city expanded spatially towards the South and West, between 1989 and 2000. From the “no null” 
classification, the area classified as urban in the imagery, increased by 235574 hectares , while 
the area occupied by water reduced by 14874 hectares between 1989 to 2000.  However, the 
with null classification”, urban area increased by 165624 hectares while water increased by 
4620 hectares (Table 1).
6


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