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#optical — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #optical, aggregated by home.social.

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  1. An optical link ‘internet’ to connect networks in space
    atlas.whatip.xyz/post.php?slug
    <p>In this episode, David Ariosto speaks with John Mackey, CEO, co-founder and director of Mbryonics
    #internet #networks #optical #connect

  2. Kepler books Neutron for 2028 optical relay launch
    atlas.whatip.xyz/post.php?slug
    <p>Kepler Communications plans to deploy next-generation optical relay satellites on Rocket Lab’s
    #neutron #optical #kepler #launch

  3. FCC drafts import ban on Chinese optical transceivers, the quiet backbone of AI data centers

    Like and share if you enjoyed this.

    1ban.news/fcc-optical-transcei

    #1ban #fcc #optical #transceiver #import #tech

  4. Glass Sphere

    A flawless glass orb rests at the precise horizontal fulcrum of a mirrored plane, its polished surface capturing and distorting the surrounding architecture of undulating neon-green light. The stark, symmetrical composition is anchored by the pillar-like reflection below, transforming the fluid wave patterns into a rigorous geometric study. This interplay of optical refraction and stark black void imbues the scene with a cool, hypnotic precision, evoking a sense of suspended digital time.

    gregurbano.com/2026/07/29/glas

  5. LEO-to-Ground Low-Elevation Optical Communication: Adaptive Optics for Satellite Downlinks

    Repost to help others discover this.

    1ban.news/leo-optical-communic

    #1ban #leo #optical #communication #adaptive #space

  6. LEO-to-Ground Low-Elevation Optical Communication: Adaptive Optics for Satellite Downlinks

    Follow us and never miss a story.

    1ban.news/sources-29-leo-optic

    #1ban #sources #leo #optical #communication #space

  7. Through the Looking Glass

    A crystal-clear glass orb acts as a lens, inverting and magnifying the typography and saturated hues of a magazine beneath it. The sharp focus within the sphere contrasts dynamically with the blurred, receding background, creating a playful interplay between clarity and obscurity. This optical distortion transforms mundane printed text into a curated, jewel-like object, evoking a sense of curiosity and whimsical discovery.

    gregurbano.com/2026/07/27/thro

  8. Chinese team develops technique that turns hours-long optical chip production into seconds

    Follow @1ban_news for daily coverage.

    1ban.news/china-optical-chip-f

    #1ban #china #optical #chip #fast #tech

  9. Chinese chip startup Biren unveils optical interconnects targeting 1,024-chip AI clusters

    Our best stories, delivered daily. Follow us.

    1ban.news/chinese-startup-opti

    #1ban #chinese #startup #optical #links #tech

  10. Chinese chip startup Biren unveils optical interconnects targeting 1,024-chip AI clusters

    Our best stories, delivered daily. Follow us.

    1ban.news/chinese-startup-opti

    #1ban #chinese #startup #optical #links #tech

  11. Chinese chip startup Biren unveils optical interconnects targeting 1,024-chip AI clusters

    Our best stories, delivered daily. Follow us.

    1ban.news/chinese-startup-opti

    #1ban #chinese #startup #optical #links #tech

  12. Chinese chip startup Biren unveils optical interconnects targeting 1,024-chip AI clusters

    Our best stories, delivered daily. Follow us.

    1ban.news/chinese-startup-opti

    #1ban #chinese #startup #optical #links #tech

  13. Chinese chip startup Biren unveils optical interconnects targeting 1,024-chip AI clusters

    Our best stories, delivered daily. Follow us.

    1ban.news/chinese-startup-opti

    #1ban #chinese #startup #optical #links #tech

  14. Electrical to Optical Converters Market in Japan | Report – IndexBox

    Japan Electrical to Optical Converters Market 2026 Analysis and Forecast to 2035 Executive Summary Key Findings Japan’s Electrical…
    #EuropeSays #Japan #JP #converters #electrical #forecast #marketanalysis #Nihon #optical #to
    europesays.com/japan/54708/

  15. Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    “HIGHLIGHTS:
    • [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
    • HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
    • Time-series minima and maxima are used to predict sowing, harvest, and tillage.
    • Validation is performed across several years, crop types, and European locations.
    • Phenology detection is improved compared to HRL-Cropland.
    ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
    #Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

  16. Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    “HIGHLIGHTS:
    • [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
    • HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
    • Time-series minima and maxima are used to predict sowing, harvest, and tillage.
    • Validation is performed across several years, crop types, and European locations.
    • Phenology detection is improved compared to HRL-Cropland.
    ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
    #Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

  17. Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    “HIGHLIGHTS:
    • [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
    • HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
    • Time-series minima and maxima are used to predict sowing, harvest, and tillage.
    • Validation is performed across several years, crop types, and European locations.
    • Phenology detection is improved compared to HRL-Cropland.
    ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
    #Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

  18. Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    “HIGHLIGHTS:
    • [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
    • HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
    • Time-series minima and maxima are used to predict sowing, harvest, and tillage.
    • Validation is performed across several years, crop types, and European locations.
    • Phenology detection is improved compared to HRL-Cropland.
    ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
    #Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

  19. Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    “HIGHLIGHTS:
    • [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
    • HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
    • Time-series minima and maxima are used to predict sowing, harvest, and tillage.
    • Validation is performed across several years, crop types, and European locations.
    • Phenology detection is improved compared to HRL-Cropland.
    ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”

  20. I did a speech yesterday

    I'm in a public speaking class and yesterday I had to do a "demonstrative" speech. I chose to demonstrate, using some physical analogs since I can't help my class see into the quantum space, how we've generated electricity for the last hundred-twenty-ish years (ignoring photovoltaics, I wanted to touch on them but I only had 8 minutes). I used a bicycle as my analog, likening the chain-links to electrons on a wire and the gear teeth to the magnetic flux which causes them to move. It was […]

    snowebell.cc/i-did-a-speech-ye

  21. I did a speech yesterday

    I'm in a public speaking class and yesterday I had to do a "demonstrative" speech. I chose to demonstrate, using some physical analogs since I can't help my class see into the quantum space, how we've generated electricity for the last hundred-twenty-ish years (ignoring photovoltaics, I wanted to touch on them but I only had 8 minutes). I used a bicycle as my analog, likening the chain-links to electrons on a wire and the gear teeth to the magnetic flux which causes them to move. It was […]

    snowebell.cc/i-did-a-speech-ye

  22. Elon Musk recebeu aprovação da FTC para adquirir a Mesh Optical Technologies. Startup criada por ex-funcionários da SpaceX focada em hardware de comunicações em servidores. 📈

    🔗 tugatech.com.pt/t86362-elon-mu

    #compra #dados #elon #musk #optical 

  23. Elon Musk recebeu aprovação da FTC para adquirir a Mesh Optical Technologies. Startup criada por ex-funcionários da SpaceX focada em hardware de comunicações em servidores. 📈

    🔗 tugatech.com.pt/t86362-elon-mu

    #compra #dados #elon #musk #optical 

  24. Elon Musk recebeu aprovação da FTC para adquirir a Mesh Optical Technologies. Startup criada por ex-funcionários da SpaceX focada em hardware de comunicações em servidores. 📈

    🔗 tugatech.com.pt/t86362-elon-mu

    #compra #dados #elon #musk #optical 

  25. Elon Musk recebeu aprovação da FTC para adquirir a Mesh Optical Technologies. Startup criada por ex-funcionários da SpaceX focada em hardware de comunicações em servidores. 📈

    🔗 tugatech.com.pt/t86362-elon-mu

    #compra #dados #elon #musk #optical 

  26. Elon Musk recebeu aprovação da FTC para adquirir a Mesh Optical Technologies. Startup criada por ex-funcionários da SpaceX focada em hardware de comunicações em servidores. 📈

    🔗 tugatech.com.pt/t86362-elon-mu

    #compra #dados #elon #musk #optical 

  27. How Artemis II livestreamed hi-def videos and images from the moon to Earth
    atlas.whatip.xyz/post.php?slug
    Latest: <p>The Orion Artemis II Optical Communications System (O2O)
    #artemis #optical #videos #images

  28. How Artemis II livestreamed hi-def videos and images from the moon to Earth
    atlas.whatip.xyz/post.php?slug
    Latest: <p>The Orion Artemis II Optical Communications System (O2O)
    #artemis #optical #videos #images

  29. #optical : relating to sight or light

    - French: optique

    - German: optisch

    - Italian: ottico

    - Portuguese: ótico

    - Spanish: óptico

    ------------

    Guess the next word of the hour @ 24hippos.com

  30. #optical : relating to sight or light

    - French: optique

    - German: optisch

    - Italian: ottico

    - Portuguese: ótico

    - Spanish: óptico

    ------------

    Guess the next word of the hour @ 24hippos.com

  31. #optical : relating to sight or light

    - French: optique

    - German: optisch

    - Italian: ottico

    - Portuguese: ótico

    - Spanish: óptico

    ------------

    Guess the next word of the hour @ 24hippos.com

  32. #optical : relating to sight or light

    - French: optique

    - German: optisch

    - Italian: ottico

    - Portuguese: ótico

    - Spanish: óptico

    ------------

    Guess the next word of the hour @ 24hippos.com

  33. #optical : relating to sight or light

    - French: optique

    - German: optisch

    - Italian: ottico

    - Portuguese: ótico

    - Spanish: óptico

    ------------

    Guess the next word of the hour @ 24hippos.com

  34. New: Why NVIDIA Spent $500M on a Glass Company

    Corning (GLW) announced a $500M partnership with NVIDIA on May 6: three new US factories, 10x capacity increase, and a warrant deal. Why the world's largest AI company is spending half a billion dollars on fiber optic cable.

    telegra.ph/Why-NVIDIA-Spent-50

    #Corning #NVIDIA #Optical #AIInfrastructure