@inproceedings{c52cfe945d5041b990954061504107ce,
title = "Integration of region growing and morphological analysis with super-resolution land cover mapping",
abstract = "Converting probability maps derived from indicator cokriging (ICK) to a specific land cover classification map is the second step of super-resolution mapping (SRM) under the geostatistical framework. In this study, two image segmentation strategies, namely mathematical morphology and region growing, were applied on the ICK-derived probability maps in order to take into account spatial characteristics such as shape and connectivity. A case study in South Carolina (USA) showed that the thematic map created by the proposed method had an overall accuracy improved by 2% and Kappa improved by 6% compared to the map derived from the existing sequential generation process. This indicates our methodology as a promising alternative that can be embedded into SRM tasks.",
keywords = "Morphological analysis, Probability maps, Region Growing, Super-resolution mapping (SRM)",
author = "Huiran Jin and Peijun Li",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7730329",
language = "English (US)",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5099--5102",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
address = "United States",
}