Miranda, Nuno

Rohner, Christoph

Rüetschi, Marius

Schaepman, Michael E

Small, David

Vögtli, Marius

Waser, Lars

ZORA

Zurich Open Repository andArchiveUniversity of ZurichMain LibraryStrickhofstrasse 39CH-8057 Zurichwww.zora.uzh.chYear: 2018Level 3 wide-area backscatter time-series for wet-snow mapping and forestclassificationSmall, David; Rohner, Christoph; Miranda, Nuno; Rüetschi, Marius; Waser, Lars; Vögtli, Marius;Schaepman, Michael EPosted at the Zurich Open Repository and Archive, University of ZurichZORA URL: https://doi.org/10.5167/uzh-152174Published Version  Originally published at:Small, David; Rohner, Christoph; Miranda, Nuno; Rüetschi, Marius; Waser, Lars; Vögtli, Marius; Schaep-man, Michael E (2018). Level 3 wide-area backscatter time-series for wet-snow mapping and forestclassification. In: EGU General Assembly 2018, Vienna, 8 April 2018 - 13 April 2018.Geophysical Research AbstractsVol. 20, EGU2018-15538, 2018EGU General Assembly 2018© Author(s) 2018. CC Attribution 4.0 license.Level 3 wide-area backscatter time-series for wet-snow mapping andforest classificationDavid Small (1), Christoph Rohner (1), Nuno Miranda (2), Marius Rüetschi (3), Lars Waser (3), Marius Vögtli(1), and Michael Schaepman (1)(1) University of Zurich, Remote Sensing Laboratories, Zurich, Switzerland (david.small@geo.uzh.ch), (2) European SpaceAgency, Frascati, Italy (nuno.miranda@esa.int), (3) Swiss Federal Institute for Forest, Snow and Landscape Research WSL(marius.rueetschi@wsl.ch)Standard level 1 (L1) radar backscatter products are currently the basic unit of data access for most scientists todata from radar satellites such as Sentinel-1A (S-1A), Sentinel-1B (S-1B), Radarsat-2 (RS2). L1 data are typicallydelivered in either slant or ground range geometry (e.g. SLC: single-look-complex, or GRD: ground range detectedin the case of Sentinel-1 data).CEOS defines level 3 products as “data or retrieved environmental variables that have been spatially and/or tempo-rally re-sampled (i.e. derived from level 1 or 2 products). Such re-sampling may include averaging and composit-ing”. We apply terrain geocoding to transform L1 products into our L3 reference map geometry. Both the geometryand radiometry of the L1 backscatter values are corrected for terrain distortions, ensuring that the backscatter esti-mates can be compared on a “level playing field”. These radiometrically-terrain-corrected (RTC) products are theninput into a compositing stage, whereby all observations available from within a given time-window are combinedinto a composite backscatter map representing the time-span. When multiple observations are available within thetime window, then weighting is applied based on the reciprocal of the local area (i.e. the local resolution) of eachRTC value. This enables the generation of seamless wide-area backscatter composites.We demonstrate such products generated over the Alps, Arctic Canada, Iceland, and forested regions withinSwitzerland. We then show examples of applications that can use such products as input, e.g. wet-snow mapping,storm damage assessment, classifying mixed temperate forest through comparison of summer vs. winter compositemaps, and monitoring forest phenology through time series analysis in spring and autumn. Were standardized L3products to be made available to users, then many applications could be developed in relatively simple 2D imagegeometry, and users would be freed from the necessity of grappling with multiple (and relatively complex) individ-ual L1 slant or ground range geometries. In addition, data quality is enhanced by mitigating unwanted propertiesof single-acquisition data such as variable local resolution, noise, speckle and short-term environmental variations.Building reliable L3 products requires the availability of a sufficiently accurate DEM, and that the L1 productsused as input meet strict quality standards, esp. concerning their (a) geolocation accuracy, and (b) radiometriccalibration. We demonstrate wide area backscatter time-series derived from single-sensor composites as well as S-1A/S-1B combinations and finally S-1/RS2. The latter demonstration helps indicate the types of opportunities thatwill become possible after the launch of the Radarsat-Constellation-Mission (RCM) composed of three C-bandRadar satellites due for launch later this year. We illustrate how, by ensuring high standards of geometric and ra-diometric calibration, wide-area coverage could be obtainable with unprecedented near-daily temporal resolution,even at temperate latitudes.

Level 3 wide-area backscatter time-series for wet-snow mapping and forest classification

http://www.zora.uzh.ch/id/eprint/152174/1/2018_EGU2018-15538.pdf

Level 3 wide-area backscatter time-series for wet-snow mapping and forest classification

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