TY - JOUR
T1 - Toward utilizing multitemporal multispectral airborne laser scanning, Sentinel-2, and mobile laser scanning in map updating
AU - Matikainen, Leena
AU - Pandžić, Miloš
AU - Li, Fashuai
AU - Karila, Kirsi
AU - Hyyppä, Juha
AU - Litkey, Paula
AU - Kukko, Antero
AU - Lehtomäki, Matti
AU - Karjalainen, Mika
AU - Puttonen, Eetu
PY - 2019/10/14
Y1 - 2019/10/14
N2 - The rapid development of remote sensing technologies provides interesting possibilities for the further development of nationwide mapping procedures that are currently based mainly on passive aerial images. In particular, we assume that there is a large undiscovered potential in multitemporal airborne laser scanning (ALS) for topographic mapping. In this study, automated change detection from multitemporal multispectral ALS data was tested for the first time. The results showed that direct comparisons between height and intensity data from different dates reveal even small changes related to the development of a suburban area. A major challenge in future work is to link the changes with objects that are interesting in map production. In order to effectively utilize multisource remotely sensed data in mapping in the future, we also investigated the potential of satellite images and ground-based data to complement multispectral ALS. A method for continuous change monitoring from a time series of Sentinel-2 satellite images was developed and tested. Finally, a high-density point cloud was acquired with terrestrial mobile laser scanning and automatically classified into four classes. The results were compared with the ALS data, and the possible roles of the different data sources in a future map updating process were discussed.
AB - The rapid development of remote sensing technologies provides interesting possibilities for the further development of nationwide mapping procedures that are currently based mainly on passive aerial images. In particular, we assume that there is a large undiscovered potential in multitemporal airborne laser scanning (ALS) for topographic mapping. In this study, automated change detection from multitemporal multispectral ALS data was tested for the first time. The results showed that direct comparisons between height and intensity data from different dates reveal even small changes related to the development of a suburban area. A major challenge in future work is to link the changes with objects that are interesting in map production. In order to effectively utilize multisource remotely sensed data in mapping in the future, we also investigated the potential of satellite images and ground-based data to complement multispectral ALS. A method for continuous change monitoring from a time series of Sentinel-2 satellite images was developed and tested. Finally, a high-density point cloud was acquired with terrestrial mobile laser scanning and automatically classified into four classes. The results were compared with the ALS data, and the possible roles of the different data sources in a future map updating process were discussed.
KW - ITC-ISI-JOURNAL-ARTICLE
KW - ITC-HYBRID
UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2019/isi/li_tow.pdf
U2 - 10.1117/1.JRS.13.4.044504
DO - 10.1117/1.JRS.13.4.044504
M3 - Article
VL - 13
SP - 1
EP - 35
JO - Journal of applied remote sensing
JF - Journal of applied remote sensing
SN - 1931-3195
IS - 4
M1 - 044504
ER -