| Abstrak/Abstract |
The phenomenon of urban ecology is very comprehensive, for example, rapid land-use
changes, decrease in vegetation cover, dynamic urban climate, high population
density, and lack of urban green space. Temporal resolution and spatial resolution of
remote sensing data are fundamental requirements for spatial heterogeneity research.
Remote sensing data is very effective and efficient for measuring, mapping, monitoring,
and modeling spatial heterogeneity in urban areas. The advantage of remote sensing
data is that it can be processed by visual and digital analysis, index transformation,
image enhancement, and digital classification. Therefore, various information related
to the quality of urban ecology can be processed quickly and accurately. This study
integrates urban ecological, environmental data such as vegetation, built-up land,
climate, and soil moisture based on spectral image response. The combination of
various indices obtained from spatial data, thematic data, and spatial heterogeneity
analysis can provide information related to urban ecological status. The results of
this study can measure the pressure of environment caused by human activities
such as urbanization, vegetation cover and agriculture land decreases, and urban
micro-climate phenomenon. Using the same data source indicators, this method is
comparable at different spatiotemporal scales and can avoid the variations or errors
in weight definitions caused by individual characteristics. Land use changes can
be seen from the results of the ecological index. Change is influenced by human
behavior in the environment. In 2002, the ecological index illustrated that regions with low ecology still spread. Whereas in 2017, good and bad ecological indices are clustered. |
