@inproceedings{be581add71be427582f08b11c92bdd34,
title = "LARGE-scale fine-resolution products of forest disturbance using new approaches from spacborne sar interferometry",
abstract = "Spaceborne SAR interferometry (InSAR) has the potential of detecting forest change on a global scale with fine (meter-level) spatial resolution as well as on a monthly/weekly basis regardless of day or night. This is significant to characterize the land-use change and its impact on climate change. In this paper, both single-pass and repeat-pass SAR interferometry from spaceborne sensors are combined in order to detect and quantify (with Normalized RMSE ≤ 30%) forest disturbance at a large scale (dozens of kilometers) however with a fine spatial resolution (< 1 hectare) based on two newly developed approaches. The single-pass InSAR approach is not only able to detect forest disturbance but also capable of characterizing meter (or even sub-meter) level change of forest phase-center (mean) height due to forest growth and/or degradation. These methods are extensively validated with the past and current spaceborne single-pass and repeat-pass InSAR missions (i.e. JAXA's ALOS-1, ALOS-2 and DLR's TanDEM-X) over subtropical forests in Australia as well as tropical forests in Brazil. Such techniques also serve as observing prototypes for the fusion of the future spaceborne InSAR missions (such as NASA-ISRO's NISAR and DLR's TanDEM-L).",
keywords = "Fine-resolution, Forest disturbance, Interferometry, Large-scale, Repeat-pass, SAR, Single-pass, Spaceborne",
author = "Yang Lei and Robert Treuhaft and Michael Keller and Richard Lucas and Paul Siqueira and Michael Schmidt",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 ; Conference date: 23-07-2017 Through 28-07-2017",
year = "2017",
month = dec,
day = "1",
doi = "10.1109/IGARSS.2017.8127957",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "IEEE Press",
pages = "4318--4321",
booktitle = "2017 IEEE International Geoscience and Remote Sensing Symposium",
address = "United States of America",
}