Comparison of Urbanization and Environmental Condition in Asian Cities using Satellite Remote Sensing Data
4. Influence of Season on ohe Indices UI and NDVI
Using Landsat TM data for Nagoya city of July 1985 (summer ) and November 1985 ( winter ) the change in UI and NDVI was computed for approximately 500m grid units for different types of land cover. Land cover information was obtained form TDT data of 1987. the grid units were assigned to a class of land cover if more than 60% of the TM piles within with the grid belonged to that class. The computed change in UI and NDVI due to seasonal change for these grids belonging to the different classes of land cover be seen in Fig. 5. this figure shows that except for paddy lands which changes form a vegetation area in summer to a bare land in winter the change in UI is relatively smaller than the change in NDVI due to seasonal change. This can be explained by liking at Fig. 6. which show the seasonal influence on bands 3,4 and 7 for commercial and industrial areas. This figure shows that the change in band3 is relatively larger than the change in band7.
Fig. 5 Seasonal change in index value
Fig. 6 Changes in Band 3, 7 and 4 in commercial and industrial areas
5. Influence of Region on the Indices UI and NDVI
The UI-NDVI relation for three cities computed by using a 500 by 400 TM pixel images is shown in fig. 7.8 and 9. the average UI and NDVI values have been competed for approximately 500cm grid units or 17 by 17 TM pixels . in the case of Colombo and Kuala Lumpur cities the TM images have been registered w3ith scanned 1:50000 land cover maps of the urban areas. In the case of Nagoya city land cover information has been obtained form TDT data. Each approximately 500m grid unit was considered to belong to category if more than 60% of the TM pixels within the grid unit belonged to that category.
Fig. 7 UI-NDVI Relation with land cover for colombo City
Fig. 8 UI-NDVI Relation with land cover for Kuala Lumpur City
Fig. 9 UI-NDVI Relation with land cover for Nagoya City
Form the land cover categories in these three urban areas categories common to at least two cities were selected. They are Built-up area, grassland, parks and rubber. All the pixels belonging to these categories were picked up and their UI and NDVI values are shown in Fig. 10. form this figure it can be seen that the indices UI and NDVI have ea similar range of values for the same class of land core even in very different regions. Therefore the UI-NDVI relation can be applied in different cities to compare the environmental condition in different urban areas provided that seasonal conditions are similar.
Fig. 10 UI-NDVI Relation of cities for common categories of land cover
6. Comparison of Cities using the UI-NDVI Relation
6.1 Comparison of cities using the UI-NDVI relation based on 500m grid.
The UI-NDVI relation for Colombo, Kuala Lumpur and Nagoya cities are shown in Fig.11(a) to (c). the TM images used are of the summer season. The area within the administrative boundaries of the cities was considered. Each point shown in the figure represent approximately 500m grid units. A land cover classification was done using a neural network program to separate the TM pixels belonging to urban areas and vegetation areas. The 500m girds were assigned as belonging to urban or vegetation classes based on this land cover classification. If more than 70% of the 17 by 17 TM pixels within the approximately 500m grid belong to a class, then the grid unit was classified ad belonging to that class. In the fig.11(a) to (c) the most of urban areas are located in the zone where UI is greater than 60 and NDVI is less than 120. on the other hand the vegetation area is in the zone where UI is less than 60 and NDVI is greater than 120. the UI-NDVI relation represents the intensity of urbanization in the city, that is, the number of urbanized units. The relation for Colombo city can be seen in Fig. 11(a). the absence of vegetation area pixels indicated that there are no larger areas of vegetation within the city limits. As shown in Fig. 11(b) Kuala Lumpur has large areas of both urban and vegetation classes within the city. The UI-NDVI relation for Nagoya city in Fig.11(c) shows that Nagoya city has large urban areas and a few vegetation areas. From these figures it can be seen that the relation between UI and NDVI cab be used to recognize and compare the urbanization condition of the different urban areas.
Fig. 11(a) UI-NDVI relation for Colombo City
Fig. 11(b) UI-NDVI relation for Kuala Lumpur
Fig. 11(c) UI-NDVI relation for Nagoya City
6.2 Comparison of cities using the average UI and DNVI values of cities
The average UI and NDVI values for the different cities are used to show the UI-NDVI relation for cities in Fig. 12. the city area considered in calculation comprises of the area enclosed within the administrative boundaries .Fig .12 . shows that the state of urbanization of the different cities can be recognized at a regional level using this UI-NDVI relation.
Fig. 12 UI-NDVI relation for Cities
7. Conclusion
In this study spatial characteristics of the proposed index UI and NDVI were examined UI was used to estimate urbanization and NDVI was used to estimate the environmental condition quantitatively in the different urban areas. Two classes of spatial units were considered in this study . one was the 500m grid units to estimate the urbanization conditions with in the cities and the other was larger administrative units of the cities to estimate urbanization conditions at a regional level. The relation between UI and NDVI for an urban area showed the relationship between urbanization and the environmental condition of an urban area quantitatively. It was shown that this relation for different cities can be use to compare the urbanization condition in the different urban areas quantitatively provided the seasonal conditions were similar. It showed the number of urbanized units and its balance with the vegetation area. It also showed how the urbanized area and the vegetation areas were spatially distributed.
Reference:
- Kawamur , M., Jayamanna .S.,Tsujiko, Y., ' Relation between social and environmental conditions in Colombo Sri Lanka and the Urban Index estimated by satellite remote sensing data', Internatonal archived of photogrammetry and remote sensing, 1996, Vol XXXI, part B7 ( commission VII), pp 321-326.
