Lmst

@sonaguliyeva et al. (2023) applied #machinelearning algorithms in mapping #croptypes using high resolution #Azersky imagery & demonstrated the value of #opensource platforms like #GoogleEarthEngine in the #classification of crops #LoLManuscriptMonday https://bit.ly/Guliyeva_2023

Shout out to Sona's co-authors & affiliated organizations #Azercosmos #NationalAviationAcademy #Azerbaijan #EOChat #GISChat

Maria Åsnes Moan et al. (2023) use bi-temporal airborne laser scanner data in #PRFSS to improve forest site index determination by detecting & excluding disturbed areas, which helps understand forest growth patterns & management planning. #CFSEFI #LoLManuscriptMonday https://bit.ly/Moan_2023

This research was done at the Petawawa Research Forest using data from the PRF remote sensing supersite! #PRFSS #CFSEFI #EOChat #GISChat

Predicted suitable areas (green) and predicted unsuitable areas (red) for disturbance scenario 1 (upper panel). Black grid cells indicate no predictions because they had ALS metrics outside the range of the model’s training data. Predictions were made with the logistic regression model. In the lower panels, predictions are represented by squares whilst the circles are observed suitable (green) and unsuitable (red) field plots.

A detailed report on the methodologies in this paper on the #decisiontree classifiers for mapping #forestcover & change was also published by Trix Estomata in 2018: https://bit.ly/Estomata_2018

Mari Trix Estomata & Klaus Schmitt (2019) used #decisiontree classification & unbiased area estimation to map #forestcover extent & change in the #Philippines using #ALOS #PALSAR mosaic data in support of #REDD+ initiatives. #LoLManuscriptMonday http://bit.ly/Estomata_2019

Cheers to Estomata & Schmitt’s affiliation & supporting organizations for this #LoLManuscriptMonday feature: GIZ Philippines, the K&C Initiative of JAXA & the Forest Management Bureau of DENR Philippines #EOChat #GISChat 🛰️🌳🥳

Stritih et al. (2023) use #GEDI #lidar to characterize large-scale patterns in mountain forest structure in the European Alps & investigate the role of disturbance & recovery in forest state transitions using #Landsat-based maps. #LoLManuscriptMonday https://bit.ly/Stritih_2023

Map of the proportion of GEDI footprints classified as open-canopy forest across the Alps. Country borders are shown in black, and major rivers and lakes in grey.

Ursa Kanjir et al. (2018) investigated the use of #opticalsatelliteimagery in #vesseldetection & the most common factors influencing the #accuracy of the methodologies by reviewing 119 papers published until 2017 #LoLManuscriptMonday https://bit.ly/Kanjir_2018

Cheers to Dr. Kanjir’s co-authors & affiliations, ZRC SAZU, European Joint Research Centre & the University of Ljublana for this awesome #LoLManuscriptMonday publication! 🛰️🚢#EOChat #GISChat

Ladies of Landsat boosted:

Very cool to see @LadiesOfLandsat here. Remote sensing, especially public domain sensing like Landsat, is going to be crucial for adapting to our climate future. https://mapstodon.space/@LadiesOfLandsat/109308575719751104

📣Hey #LadiesofLandsat friends!

There is still time to join this amazing USGS study as a participant. #gischat #eochat

👉Email us at ladiesoflandsat@gmail.com to get more information!

Karen Joyce et al. (2022) quantify the lack of diversity on scientific editorial boards in remote sensing, thus leaving underrepresented scientists behind. They provide an action plan to improve inclusivity at all levels of publishing. #LoLManuscriptMonday https://bit.ly/Joyce2022

Cheers to Dr. Joyce's co-authors for this manuscript: Catherine Nakalembe, Cristina Gómez, @gopikasuresh, Kate Fickas, Meghan Halabisky, Michelle Kalamandeen & @morganahcrowley! #EOChat #GISChat

FIGURE 2. Global distribution of editorial board members (n = 1055) within 30 peer reviewed journals in the remote sensing discipline. (A) Count of editors per country (including Special Administrative Regions). (B) World cartogram (Gastner et al., 2018) weighted by number of editors demonstrating the skew towards the United States, China, Italy, and Germany with negligible contribution from South America and Africa. Note that regions identified in yellow each have between two and eight editors identified, while those in green have one editor.

Ladies of Landsat boosted:

@MapScaping Also good to check in with @LadiesOfLandsat for suggestions.

Ladies of Landsat boosted:

Ahead of tomorrow’s International Women’s Day, we put the spotlight on @geoladiesph. Happy #IWD2023 to them and all women in OSM! To join the celebration, check the post for a list of events around #InternationalWomensDay2023 #EmbraceEquity #OpenStreetMap

https://blog.openstreetmap.org/2023/03/07/international-womens-day-meet-geoladies-ph/

Ladies of Landsat boosted:

Happy Women's Day to all the amazing women in Earth Observation! Your vision for a better world is out of this world! 🌍🛰️👩‍🔬

#WomenInScience #WomenInSTEM #EarthObservation #InternationalWomensDay

Ladies of Landsat boosted:

✨Hey #LadiesOfLandsat community!✨

Some social scientists from the USGS hope to interview @LadiesOfLandsat members about the impact of professional organizations on underrepresented scientists in #EarthObservation sciences. #EOchat #GISchat

If you’re interested in learning more about the study or participating in the interviews, email us at ladiesoflandsat@gmail.com and we will connect you directly with the researchers! 🚀🛰️

✨Hey #LadiesOfLandsat community!✨

Some social scientists from the USGS hope to interview @LadiesOfLandsat members about the impact of professional organizations on underrepresented scientists in #EarthObservation sciences. #EOchat #GISchat

If you’re interested in learning more about the study or participating in the interviews, email us at ladiesoflandsat@gmail.com and we will connect you directly with the researchers! 🚀🛰️

Ladies of Landsat boosted:

Exciting new #climate position at #ECMWF #CopernicusClimate

https://jobs.ecmwf.int/displayjob.aspx?jobid=131

Two weeks left to apply.

Ping me if interested

#EOchat #ClimateCrisis #meteorology #earthobservation #satellite
@LadiesOfLandsat

Our newest episode of #SceneFromAbove with special guest @sabrinaszeto has launched TODAY! 🚀✨

Tune in to hear about Sabrina's work with #GoogleEarthEngine & #EarthEngineUserMeetup, advocacy through Women+ in Geospatial, & more! 🎉🛰️ #EOChat #gischat

⭐ S13E5 link ⭐ :
https://scenefromabove.podbean.com/e/s13e5-empowering-geospatial-innovation-with-sabrina-szeto/

Thanks to Sabrina for joining us! And thanks to @rafaelatiengo, @morganahcrowley & @flaviamendes for your efforts this episode! 🛰️

✨Season 13 of #SceneFromAbove is brought to you by Geoawesomeness and UP42 ✨

Buitre, Zhang & Lin (2019) use #timeseries analysis of #Landsat imagery using four #landscapemetrics to examine the impacts of #tropicalcyclones in #mangroves in Coron & Eastern Samar #Philippines. #LoLManuscriptMonday https://bit.ly/Buitre_2019

Shout-out to Mary Joy Buitre’s affiliated organizations and collaborators for this #LoLManuscriptMonday feature: DOST-PCIEERD, and CUHK! #EOChat 🎉🛰️

.@IleanaCallejas et al. (2021) analyze imagery from #MODIS #Aqua from #GoogleEarthEngine with marine traffic & precipitation data to establish an improvement in water quality in Belize Coastal Lagoon during the #COVID19 anthropause. #LoLManuscriptMonday https://bit.ly/Callejas_2021

FIGURE 3. Percent Difference Kd(490) Maps and MERRA-2 Model Outputs. (A) Monthly percent difference maps comparing 2020 Kd(490) values against those of the 2002–2019 (baseline) time period. (B) MERRA-2 precipitation output for the country of Belize from 2002 to 2020 in kg m–1 s–1. (C) MERRA-2 runoff output for Belize from 2002 to 2020 in kg m–1 s–1.

Molder & Schenkein et al. (2022) apply qualitative social science methods to map value creation within the #Landsat data ecosystem and identify relationships between the #Landsat data intermediaries and end users. #LoLManuscriptMonday https://bit.ly/Schenkein_2022

Shout-out to Ned Molder & Sarah Schenkein’s affiliated organizations and collaborators for this #LoLManuscriptMonday feature: Abby McConnell, Karl Benedict, Crista Straub, and USGS! #EOChat 🎉🛰️

FIGURE 1. Illustration of the relationships between actors that have different roles in the Landsat Data Ecosystem (LDE). Arrows point from users to providers of products and services. The actor roles are arranged with the upstream actors at the top and downstream actors and end users at the bottom. There is increasing alignment with specific end user needs going down the value chain, as indicated by the arrow on the right.

FIGURE 2. Illustration of value chain connections and actor types for the interviewed Landsat ecosystem actors. Value chain length increases from left to right and represents the maximum value chain length to each actor when there exist multiple upstream connections. The symbology for each actor represents the one or more roles that the actor plays within the examined value chains. EROS, U.S. Geological Survey Earth Resources Observation and Science Center; USGS, U.S. Geological Survey; NASA, National Aeronautics and Space Administration.

Straub et al. (2019) estimated that #Landsat imagery provided $3.45 billion in benefits to domestic & international users in 2017, and established that any new fees for images would result in a major loss in users/downloads. #LoLManuscriptMonday #EOChat 🛰️🥳

🔗
https://www.bit.ly/Straub_2019

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