English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We synthesize both optical RGB and synthetic aperture radar (SAR) remotesensing images from land cover maps and auxiliary raster data using generativeadversarial networks (GANs). In remote sensing, many types of data, such asdigital elevation models (DEMs) or precipitation maps, are often not reflectedin land cover maps but still influence image content or structure. Includingsuch data in the synthesis process increases the quality of the generatedimages and exerts more control on their characteristics. Spatially adaptivenormalization layers fuse both inputs and are applied to a full-blown generatorarchitecture consisting of encoder and decoder to take full advantage of theinformation content in the auxiliary raster data. Our method successfullysynthesizes medium (10 m) and high (1 m) resolution images when trained withthe corresponding data set. We show the advantage of data fusion of land covermaps and auxiliary information using mean intersection over unions (mIoUs),pixel accuracy, and Fr\'echet inception distances (FIDs) using pretrained U-Netsegmentation models. Handpicked images exemplify how fusing information avoidsambiguities in the synthesized images. By slightly editing the input, ourmethod can be used to synthesize realistic changes, i.e., raising the waterlevels. The source code is available at https://github.com/gbaier/rs_img_synthand we published the newly created high-resolution dataset athttps://ieee-dataport.org/open-access/geonrw.

Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster Data