@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
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 🛰️🌳🥳
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.
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
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.
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 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.
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...
RT @LadiesOfLandsat: .@cstraubresearch 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 https://pubs.er.usgs.gov/publication/ofr20191112
🐦🔗: https://n.respublicae.eu/CopernicusEU/status/1626848159337947137
Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). A previous USGS study estimated that Landsat imagery provided users an annual benefit of $2.19 billion in 2011, with U.S. users accounting for $1.79 billion of those benefits. That study, published in 2013, surveyed users in 2012 about Landsat imagery they retrieved in 2011. But since then, many changes have altered the demand for and supply of remotely sensed imagery and have made the analysis complex. This report updates these estimates, surveying users in 2018 about Landsat images they retrieved in 2017. The report discusses changes in the value per scene in 2017 when compared to 2011 and analyzes the potential consequences of charging fees. Landsat imagery has been available at no cost to the public since 2008, resulting...
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 🎉🛰️
It is well-known that Earth observation (EO) data plays a critical role in scientific understanding about the global environment. There is also growing support for the use of EO data to provide context-specific insights, with significant implications for their use in decision support systems. Technological development over recent years, including cloud computing infrastructure, machine learning techniques, and rapid expansion of the velocity, volume, and variety of space-borne data sources, offer huge potential to provide solutions to the myriad environmental problems facing society and the planet. The USGS/NASA Landsat Program, the longest continuously gathered source of land surface data, has played a central role in our understanding of environmental change, particularly for its contribution of longitudinal products that offer greater context for present research and decision support activities. The challenge facing the Landsat and EO data community, however, now lies in moving beyond context-specific knowledge generation to translating such knowledge into tangible value for society. Drawing from an open data ecosystem framework and qualitative social science methods, we map the Landsat data ecosystem (LDE) and the relationships linking multiple actors responsible for processing, indexing, analyzing, synthesizing, and translating raw Landsat data into information that is useful, useable, and used by end users in particular social-environmental contexts. Both the role of...
Ladies of Landsat
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