#LandChange hashtag - Bluesky

@kiwiincolorado.bsky.social

6 months ago

Thirty Years Of The #US #NationalLandCoverDatabase #NLCD
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doi.org/10.14358/PER...
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#GIS #spatial #mapping #history #LandCover #Landuse #change #Landsat #remotesensing #landchange #monitoring #fedscience #fedopendata #opendata #history #MRLCC #USA #national #multiple #usecase
@USGS | @EROS

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WSL Umweltforschung

@wslresearch.bsky.social

10 months ago

Within an SNSF funded project, the Remote Sensing group is offering a 4 year position as of September 1, 2025 or by arrangement, as a PhD student in Habitat change mapping with historical aerial imagery and deep learning 100% (f/m/d) You will map Swiss-wide distributions of habitat types at multiple time steps using historical aerial imagery and artificial intelligence methods for image classification including machine learning and deep learning. You will determine changes in Swiss habitats since the 1940s and investigate the implications for biodiversity and ecological connectivity. You will develop a flexible habitat typology that allows consistent mapping of habitat types over multiple time steps, despite differences in the quality and specifications of available remote sensing imagery. Furthermore, you will exchange and collaborate with relevant experts both inside and outside of the research group. You will present your results to professional audiences, and both publish in scientific journals and contribute to project reports or outreach publications. You have a Master’s degree in environmental science, spatial ecology, computer vision or an equivalent field. Your sound understanding of land change science is complemented by your knowledge of artificial intelligence methods for image classification (e.g. CNN). Furthermore, you are skilled in the analysis of large extent Earth Observation data, where experience with black and white aerial imagery is an advantage. You work comfortably with statistical computing and scripting languages (e.g. R, Python, MATLAB). You are highly motivated to analyse and understand spatial data using sophisticated modelling methods and tools. Good communication and organisation skills, an excellent team spirit and fluency in English is fundamental, knowledge of a Swiss national language is an advantage.

🖥️ #PhDAlert! MSc in a #NaturalScience, good understanding of land change science & #AI methods for image classification? #Statistics & #computing language skills? Our #RemoteSensing group is offering a 4 year #PhD position in #habitat change mapping. #LandChange apply.refline.ch/273855/1737/...