Ladies of Landsat

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All are welcome! We are an affinity group working to make the field of #EarthObservation more #inclusive for #underrepresented scientists. #ScienceMastodon

We work alongside other groups like Sisters of SAR, Women of Waveforms and Dames of Drones. #EOChat #GISChat

Tune in here for updates on the #LoLManuscriptMonday series and new episodes of the #SceneFromAbove podcast.

Account run by @morganahcrowley & @flaviamendes

LoL Manuscript Mondayhttps://github.com/ladiesoflandsat/LOLManuscriptMonday
LinkedInhttps://www.linkedin.com/company/ladies-of-landsat

@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

Detecting and excluding disturbed forest areas improves site index determination using bitemporal airborne laser scanner data

Abstract. Bitemporal airborne laser scanning (ALS) data are increasingly being used in forest management inventories for the determination of site index (SI). S

OUP Academic
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
Forest Cover and Change Classification Using ALOS PALSAR Mosaic Data and Decision Tree Classifiers

The “Climate-relevant Modernization of the National Forest Policy and Piloting of REDD Measures in the Philippines” project developed a remote sensing methodology for forest cover and forest cover change mapping. This methodology was applied to the

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
Alternative states in the structure of mountain forests across the Alps and the role of disturbance and recovery - Landscape Ecology

Context Structure is a central dimension of forest ecosystems that is closely linked to their capacity to provide ecosystem services. Drivers such as changing disturbance regimes are increasingly altering forest structure, but large-scale characterizations of forest structure and disturbance-mediated structural dynamics remain rare. Objectives Here, we characterize large-scale patterns in the horizontal and vertical structure of mountain forests and test for the presence of alternative structural states. We investigate factors determining the occurrence of structural states and the role of disturbance and recovery in transitions between states. Methods We used spaceborne lidar (GEDI) to characterize forest structure across the European Alps. We combined GEDI-derived structural metrics with Landsat-based disturbance maps and related structure to topography, climate, landscape configuration, and past disturbances. Results We found two alternative states of forest structure that emerged consistently across all forest types of the Alps: short, open-canopy forests (24%) and tall, closed-canopy forests (76%). In the absence of disturbance, open-canopy forests occurred at high elevations, forest edges, and warm, dry sites. Disturbances caused a transition to open-canopy conditions in approximately 50% of cases. Within 35 years after disturbance, 72% of forests recovered to a closed-canopy state, except in submediterranean forests, where recovery is slow and long-lasting transitions to open-canopy conditions are more likely. Conclusions As climate warming increases disturbances and causes thermophilization of vegetation, transitions to open-canopy conditions could become more likely in the future. Such restructuring could pose a challenge for forest management, as open-canopy forests have lower capacities for providing important ecosystem services.

SpringerLink

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

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

Discovering Inclusivity in Remote Sensing: Leaving No One Behind

Innovative and beneficial science stems from diverse teams and authorships that are inclusive of many perspectives. In this paper, we explore the status of inclusivity in remote sensing academic publishing, using an audit of peer-reviewed journal editorial board composition. Our findings demonstrate diversity deficiency in gender and country of residence, limiting the majority of editors to men residing in four countries. We also examine the many challenges underrepresented communities within our field face, such as implicit bias, harsher reviews, and fewer citations. We assert that in the field of remote sensing, the gatekeepers are not representative of the global society and this lack of representation restricts what research is valued and published, and ultimately who becomes successful. We present an action plan to help make the field of remote sensing more diverse and inclusive and urge every individual to consider their role as editor, author, reviewer, or reader. We believe that each of us have a choice to continue to align with a journal/institution/society that is representative of the dynamic state of our field and its people, ensuring that no one is left behind while discovering all the fascinating possibilities in remote sensing.

Frontiers

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 ✨

S13E5: Empowering geospatial innovation with Sabrina Szeto | The Scene From Above Podcast

This episode features Sabrina Szeto, who is a geospatial consultant who empowers organizations to use geospatial data and technology. She is a Google Developer Expert for Earth Engine. Sabrina has a Masters in Forestry from Yale University and a BA in Anthropology from Princeton University. She also has volunteered as a Director with Women in Geospatial+ and is currently based near Munich, Germany. Website: https://sabrinaszeto.com/our-work Twitter: https://twitter.com/SabrinaSzeto Mastodon: https://fosstodon.org/@sabrinaszeto Season 13 of Scene from Above is brought to you by Geoawesomeness and UP42. Be sure to check out the EO Hub article by Aleks Buczkowski: ‘https://geoawesomeness.com/eo-hub/understanding-the-earth-observation-value-chain/’ -------- Show notes: Earth Engine User Meetup YouTube: https://youtube.com/@EarthEngineUserMeetup Fostering user-driven learning communities in-person and virtually: Examples from Earth Engine meetups: https://figshare.com/articles/poster/Fostering_user-driven_learning_communities_in-person_and_virtually_Examples_from_Earth_Engine_meetups/21803250 Earth Engine Community Tutorials: https://sabrinaszeto.com/talks-and-outreach/creating-community-tutorials-for-earth-engine https://github.com/google/earthengine-community/tree/master/tutorials Ten Steps to Build an Inclusive Future for the Geo for Good Community: https://medium.com/google-earth/ten-steps-to-build-an-inclusive-future-for-the-geo-for-good-community-9f808000ab28 Women+ in Geospatial: Women+ in Geospatial Website: https://www.womeningeospatial.org/ Women+ in Geospatial Twitter: https://twitter.com/geospatialwomen Women+ in Geospatial LinkedIn: https://www.linkedin.com/company/women-in-geospatial/   Hosts: Dr. Flavia de Souza Mendes https://twitter.com/flasmendes Dr. Gopika Suresh https://twitter.com/Go__pika Dr. Morgan Crowley https://twitter.com/morganahcrowley News correspondent: Rafaela Tiengo https://twitter.com/RafaelaTiengo_ Rafaela's newsletter: https://www.getrevue.co/profile/rafaelatiengo   Previewing our next guest on S13E6: They are a remote sensing research scientist with NASA, They have used SAR, LiDAR and passive optical data in their research, They created the first 3D mangrove forest structure map for Africa.

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 🎉🛰️

The Mangrove Forests Change and Impacts from Tropical Cyclones in the Philippines Using Time Series Satellite Imagery

The Philippines is rich in mangrove forests, containing 50% of the total mangrove species of the world. However, the vast mangrove areas of the country have declined to about half of its cover in the past century. In the 1970s, action was taken to protect the remaining mangrove forests under a government initiative, recognizing the ecological benefits mangrove forests can bring. Here, we examine two mangrove areas in the Philippines—Coron in Palawan and Balangiga-Lawaan in Eastern Samar over a 30-year period. Sets of Landsat images from 1987 to 2016 were classified and spatially analyzed using four landscape metrics. Additional analyses of the mangrove areas’ spatiotemporal dynamics were conducted. The impact of typhoon landfall on the mangrove areas was also analyzed in a qualitative manner. Spatiotemporal changes indicate that both the Coron and Balangiga-Lawaan mangrove forests, though declared as protected areas, are still suffering from mangrove area loss. Mangrove areal shrinkage and expansion can be attributed to both typhoon occurrence and management practices. Overall, our study reveals which mangrove forests need more responsive action, and provides a different perspective in understanding the spatiotemporal dynamics of these mangrove areas.

MDPI
.@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
Effect of COVID-19 Anthropause on Water Clarity in the Belize Coastal Lagoon

The Coronavirus disease 2019 (COVID-19) pandemic halted human activities globally in multiple sectors including tourism. As a result, nations with heavy tourism, such as Belize, experienced improvements in water quality. Remote sensing technologies can detect impacts of “anthropauses” on coastal water quality. In this study, moderate resolution imaging spectroradiometer (MODIS) satellite data were employed along the Belizean coast to investigate impacts of the COVID-19 shutdown on water quality. The attenuation coefficient at 490 nm, Kd(490), was used as an indicator of water quality, with a lower Kd(490) indicating increased water clarity. Four Coastal Management Zones were characterized by marine traffic as high traffic areas (HTAs) and two as low traffic areas (LTAs). Monthly composites for two periods, 2002–2019 (baseline) and 2020 were examined for Kd(490). For months prior to the COVID-19 shutdown in Belize, there was generally no significant difference in Kd(490) (p > 0.05) between 2020 and baseline period in HTAs and LTAs. Through the shutdown, Kd was lower in 2020 at HTAs, but not for LTAs. At the LTAs, the Kd(490)s observed in 2020 were similar to previous years through October. In November, an unusually active hurricane season in 2020 was associated with decreased water clarity along the entire coast of Belize. This study provides proof of concept that satellite-based monitoring of water quality can complement in situ data and provide evidence of significant wat...

Frontiers