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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

With recent advances in technology, personal aerial imagery acquired with unmanned aerial vehicles (UAVs) has transformed the wayecologists can map seasonal changes in wetland habitat. Here, we use a multi-rotor (consumer quad-copter, the DJI Phantom 2 Vision+)UAV to acquire a high-resolution (< 8 cm) composite photo of a coastal wetland in summer 2014. Using validation data collected in thefield, we determine if a UAV image and SWOOP (Southwestern Ontario Orthoimagery Project) image (collected in spring 2010) differ intheir classification of type of dominant vegetation type and percent cover of three plant classes: submerged aquatic vegetation, floatingaquatic vegetation, and emergent vegetation. The UAV imagery was more accurate than available SWOOP imagery for mapping percentcover of submergent and floating vegetation categories, but both were able to accurately determine the dominant vegetation type andpercent cover of emergent vegetation. Our results underscore the value and potential for affordable UAVs (complete quad-copter system< $3,000 CAD) to revolutionize the way ecologists obtain imagery and conduct field research. In Canada, new UAV regulations makethis an easy and affordable way to obtain multiple high-resolution images of small (< 1.0 km<sup>2</sup>) wetlands, or portions of larger wetlandsthroughout a year

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

UNMANNED AERIAL VEHICLES PRODUCE HIGH-RESOLUTION, SEASONALLY-RELEVANT IMAGERY FOR CLASSIFYING WETLAND VEGETATION