%0 Conference Paper %1 dlr54680 %A Taubenböck, Hannes %A Wegmann, Martin %A Berger, Christian %A Breunig, Markus %A Roth, Achim %A Mehl, Harald %B ISPRS %D 2008 %J Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences %K Taubenboeck Wegmann conference inproceedings LSFE %N Part B %P 75-82 %T Spatiotemporal analysis of Indian megacities %U http://elib.dlr.de/54680/ %V 10 %X Urbanization is arguably the most dramatic form of highly irreversible land transformation. While urbanization is a worldwide phenomenon, it is exceptionally dynamic in India, where unprecedented urban growth rates have occurred over the last 30 years. In this uncontrolled explosive situation city planning lacks of data and information to measure, monitor, understand urban sprawl processes. The analysis of such changes has become an important use of multitemporal remote sensing data. Using a time-series of Landsat data to classify the urban footprints since the 1970s enables detection of temporal and spatial urban sprawl, redensification and urban development in the explosively growing large urban agglomerations of the mega cities Mumbai, Delhi and Kolkata in India. Combining gradient analysis with landscape metrics the spatiotemporal pattern of urbanization are quantified. Spatial parameters are the absolute areal growth, urbanization rates, built-up densities, landscape shape index, edge density, patch density, or largest patch index. The study aims to detect analogies and differences for spatial growth in Indian mega cities, cities in the same cultural area at about the same development stage regarding absolute population. The results paint a characteristic picture of spatial pattern gradients and landscape metrics of the three Indian mega cities.

@inproceedings{dlr54680, abstract = {Urbanization is arguably the most dramatic form of highly irreversible land transformation. While urbanization is a worldwide phenomenon, it is exceptionally dynamic in India, where unprecedented urban growth rates have occurred over the last 30 years. In this uncontrolled explosive situation city planning lacks of data and information to measure, monitor, understand urban sprawl processes. The analysis of such changes has become an important use of multitemporal remote sensing data. Using a time-series of Landsat data to classify the urban footprints since the 1970s enables detection of temporal and spatial urban sprawl, redensification and urban development in the explosively growing large urban agglomerations of the mega cities Mumbai, Delhi and Kolkata in India. Combining gradient analysis with landscape metrics the spatiotemporal pattern of urbanization are quantified. Spatial parameters are the absolute areal growth, urbanization rates, built-up densities, landscape shape index, edge density, patch density, or largest patch index. The study aims to detect analogies and differences for spatial growth in Indian mega cities, cities in the same cultural area at about the same development stage regarding absolute population. The results paint a characteristic picture of spatial pattern gradients and landscape metrics of the three Indian mega cities.}, added-at = {2020-09-11T12:04:50.000+0200}, author = {Taubenb{\"o}ck, Hannes and Wegmann, Martin and Berger, Christian and Breunig, Markus and Roth, Achim and Mehl, Harald}, biburl = {https://www.bibsonomy.org/bibtex/23a984c5c7cb650ec29640aec217df566/earthobs_uniwue}, booktitle = {ISPRS}, description = {electronic library - Spatiotemporal analysis of Indian megacities}, interhash = {a1e57310a98e9e56ecc83ce7c0648459}, intrahash = {3a984c5c7cb650ec29640aec217df566}, journal = {Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, keywords = {Taubenboeck Wegmann conference inproceedings LSFE}, month = {Juli}, number = {Part B}, pages = {75-82}, timestamp = {2020-11-18T22:08:33.000+0100}, title = {Spatiotemporal analysis of Indian megacities}, url = {http://elib.dlr.de/54680/}, volume = 10, year = 2008 }