#mapping search results

๐Ÿ”ฅ๐ŸŒณ Optimizing Stacked Ensemble #MachineLearning Models for Accurate #Wildfire Severity #Mapping โœ๏ธ Linh Nguyen Van and Giha Lee ๐Ÿ”— brnw.ch/21x1in6

RemoteSens_MDPI's tweet image. ๐Ÿ”ฅ๐ŸŒณ Optimizing Stacked Ensemble #MachineLearning Models for Accurate #Wildfire Severity #Mapping

โœ๏ธ Linh Nguyen Van and Giha Lee
๐Ÿ”— brnw.ch/21x1in6

๐ŸŒพ๐ŸŒพ Detection of the Optimal #Temporal Windows for #Mapping Paddy #Rice Under a Double-Cropping System Using #Sentinel2 Imagery โœ๏ธ Li Sheng et al. ๐Ÿ”— brnw.ch/21x1cPT

RemoteSens_MDPI's tweet image. ๐ŸŒพ๐ŸŒพ Detection of the Optimal #Temporal Windows for #Mapping Paddy #Rice Under a Double-Cropping System Using #Sentinel2 Imagery

โœ๏ธ Li Sheng et al.
๐Ÿ”— brnw.ch/21x1cPT

๐Ÿ‡น๐Ÿ‡ณ๐Ÿ‡น๐Ÿ‡ณ #Soil #Salinity Detection and #Mapping by Multi-Temporal #Landsat Data: Zaghouan Case Study (#Tunisia) โœ๏ธ Karem Saad et al. ๐Ÿ”— brnw.ch/21x1aLw

RemoteSens_MDPI's tweet image. ๐Ÿ‡น๐Ÿ‡ณ๐Ÿ‡น๐Ÿ‡ณ #Soil #Salinity Detection and #Mapping by Multi-Temporal #Landsat Data: Zaghouan Case Study (#Tunisia)

โœ๏ธ Karem Saad et al.
๐Ÿ”— brnw.ch/21x1aLw

๐ŸŒณ๐ŸŒณ #Mapping Natural Populus euphratica #Forests in the Mainstream of the Tarim River Using Spaceborne Imagery and #GoogleEarth #Engine โœ๏ธ Jiawei Zou et al. ๐Ÿ”— brnw.ch/21x0Ow2

RemoteSens_MDPI's tweet image. ๐ŸŒณ๐ŸŒณ #Mapping Natural Populus euphratica #Forests in the Mainstream of the Tarim River Using Spaceborne Imagery and #GoogleEarth #Engine

โœ๏ธ Jiawei Zou et al.
๐Ÿ”— brnw.ch/21x0Ow2

๐Ÿ‘‰๐Ÿ‘‰ Practical Guidelines for Performing #UAV #Mapping #Flights with Snapshot Sensors โœ๏ธ Wouter H. Maes et al. ๐Ÿ”— brnw.ch/21x1gRE

RemoteSens_MDPI's tweet image. ๐Ÿ‘‰๐Ÿ‘‰ Practical Guidelines for Performing #UAV #Mapping #Flights with Snapshot Sensors
 
โœ๏ธ Wouter H. Maes et al.
๐Ÿ”— brnw.ch/21x1gRE

๐ŸŒณ๐ŸŒณ Multi-Decision Vector Fusion Model for Enhanced #Mapping of Aboveground Biomass in #Subtropical #Forests Integrating #Sentinel1, #Sentinel2, and Airborne #LiDAR Data โœ๏ธ Wenhao Jiang et al. ๐Ÿ”— brnw.ch/21x1GIF

RemoteSens_MDPI's tweet image. ๐ŸŒณ๐ŸŒณ Multi-Decision Vector Fusion Model for Enhanced #Mapping of Aboveground Biomass in #Subtropical #Forests Integrating #Sentinel1, #Sentinel2, and Airborne #LiDAR Data

โœ๏ธ Wenhao Jiang et al.
๐Ÿ”— brnw.ch/21x1GIF

๐Ÿ‘‰๐Ÿ‘‰ #Landslide Susceptibility #Mapping Considering Landslide #Spatial #Aggregation Using the Dual-Frequency Ratio Method: A Case Study on the Middle Reaches of the Tarim #River #Basin โœ๏ธ Xuetao Yi et al. ๐Ÿ”— brnw.ch/21x1ygr

RemoteSens_MDPI's tweet image. ๐Ÿ‘‰๐Ÿ‘‰ #Landslide Susceptibility #Mapping Considering Landslide #Spatial #Aggregation Using the Dual-Frequency Ratio Method: A Case Study on the Middle Reaches of the Tarim #River #Basin

โœ๏ธ Xuetao Yi et al.
๐Ÿ”— brnw.ch/21x1ygr

๐ŸŒ๐Ÿ›ฐ๏ธ Refined #Landslide Susceptibility #Mapping Considering #LandUse Changes and #InSAR Deformation: A Case Study of Yulin City, Guangxi โœ๏ธ Pengfei Li et al. ๐Ÿ”— brnw.ch/21x0G2z

RemoteSens_MDPI's tweet image. ๐ŸŒ๐Ÿ›ฐ๏ธ Refined #Landslide Susceptibility #Mapping Considering #LandUse Changes and #InSAR Deformation: A Case Study of Yulin City, Guangxi

โœ๏ธ Pengfei Li et al.
๐Ÿ”— brnw.ch/21x0G2z

๐ŸŒณ๐ŸŒณ Classification and #Mapping of Fuels in Mediterranean #Forest Landscapes Using a #UAV- #LiDAR System and Integration Possibilities with Handheld #Mobile #Laser Scanner Systems โœ๏ธ Raรบl Hoffrรฉn et al. ๐Ÿ”— brnw.ch/21x0Q0N

RemoteSens_MDPI's tweet image. ๐ŸŒณ๐ŸŒณ Classification and #Mapping of Fuels in Mediterranean #Forest Landscapes Using a #UAV- #LiDAR System and Integration Possibilities with Handheld #Mobile #Laser Scanner Systems

โœ๏ธ Raรบl Hoffrรฉn et al.
๐Ÿ”— brnw.ch/21x0Q0N

๐Ÿ’ง๐Ÿ’ง #Flood #Susceptibility #Mapping of the #Kosi Megafan Using Ensemble #MachineLearning and #SAR Data โœ๏ธ Khaled Mahamud Khan et al. ๐Ÿ”— brnw.ch/21x1CBi

RemoteSens_MDPI's tweet image. ๐Ÿ’ง๐Ÿ’ง #Flood #Susceptibility #Mapping of the #Kosi Megafan Using Ensemble #MachineLearning and #SAR Data

โœ๏ธ Khaled Mahamud Khan et al.
๐Ÿ”— brnw.ch/21x1CBi

๐Ÿ”ฅ๐ŸŒณ #Burned Areas #Mapping Using #Sentinel2 Data and a Raoโ€™s Q Index-Based Change Detection Approach: A Case Study in Three Mediterranean Islandsโ€™ #Wildfires (2019โ€“2022) โœ๏ธ Rafaela Tiengo et al. ๐Ÿ”— brnw.ch/21x1EII

RemoteSens_MDPI's tweet image. ๐Ÿ”ฅ๐ŸŒณ #Burned Areas #Mapping Using #Sentinel2 Data and a Raoโ€™s Q Index-Based Change Detection Approach: A Case Study in Three Mediterranean Islandsโ€™ #Wildfires (2019โ€“2022)

โœ๏ธ Rafaela Tiengo et al.
๐Ÿ”— brnw.ch/21x1EII

๐Ÿ‘‰๐Ÿ‘‰ High-Accuracy #Mapping of #Soil #Organic #Carbon by #Mining Sentinel-1/2 #Radar and Optical Time-Series Data with Super Ensemble Model โœ๏ธ Zhibo Cui et al. ๐Ÿ”— brnw.ch/21x1PL8

RemoteSens_MDPI's tweet image. ๐Ÿ‘‰๐Ÿ‘‰ High-Accuracy #Mapping of #Soil #Organic #Carbon by #Mining Sentinel-1/2 #Radar and Optical Time-Series Data with Super Ensemble Model

โœ๏ธ Zhibo Cui et al.
๐Ÿ”— brnw.ch/21x1PL8

๐Ÿ’ง๐Ÿ’ง #Mapping River Flow from #Thermal Images in Approximately Real Time: Proof of Concept on the Sacramento #River, #California, #USA โœ๏ธ Carl J. Legleiter et al. ๐Ÿ”— brnw.ch/21x19mk

RemoteSens_MDPI's tweet image. ๐Ÿ’ง๐Ÿ’ง #Mapping River Flow from #Thermal Images in Approximately Real Time: Proof of Concept on the Sacramento #River, #California, #USA

โœ๏ธ Carl J. Legleiter et al.
๐Ÿ”— brnw.ch/21x19mk

1 Flight. 7 Outputs ๐Ÿ”„ One LiDAR mission with DJI Zenmuse L3 and Matrice 400 can generate point clouds, meshes, terrain models, and more, maximizing data from every flight. #djienterprise #lidar #mapping


๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Towards High-Resolution #Population #Mapping: Leveraging Open Data, Remote Sensing, and #AI for #Geospatial Analysis in Developing Country Citiesโ€”A Case Study of #Bangkok โœ๏ธ Kittisak Maneepong et al. ๐Ÿ”— brnw.ch/21x1TQa

RemoteSens_MDPI's tweet image. ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Towards High-Resolution #Population #Mapping: Leveraging Open Data, Remote Sensing, and #AI for #Geospatial Analysis in Developing Country Citiesโ€”A Case Study of #Bangkok

โœ๏ธ Kittisak Maneepong et al.
๐Ÿ”— brnw.ch/21x1TQa

๐ŸŒฝ๐Ÿ–ผ๏ธ Enhancing #Cropland #Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for #Image #SuperResolution Models โœ๏ธ Xiaofeng Jia et al. ๐Ÿ”— brnw.ch/21x18gd

RemoteSens_MDPI's tweet image. ๐ŸŒฝ๐Ÿ–ผ๏ธ Enhancing #Cropland #Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for #Image #SuperResolution Models

โœ๏ธ Xiaofeng Jia et al.
๐Ÿ”— brnw.ch/21x18gd

๐Ÿ†•๐Ÿ”ฅColonic motility #mapping reveals a meal-induced #RectosigmoidBrake in healthy individuals that is disrupted, disorganized, or exaggerated following #surgery & in #MotilityDisordersโ€ผ๏ธ #ileus #PseudoObstruction #FecalIncontinence ๐Ÿ‘‰onlinelibrary.wiley.com/doi/10.1111/nmโ€ฆ @ANMSociety @esnm_eu

NGMJournal's tweet image. ๐Ÿ†•๐Ÿ”ฅColonic motility #mapping reveals a meal-induced #RectosigmoidBrake in healthy individuals that is disrupted, disorganized, or exaggerated following #surgery & in #MotilityDisordersโ€ผ๏ธ #ileus #PseudoObstruction #FecalIncontinence
๐Ÿ‘‰onlinelibrary.wiley.com/doi/10.1111/nmโ€ฆ
@ANMSociety @esnm_eu

right here in Nigeria today. Accuracy = Profit. Don't let old gear slow down your projects in Lagos or Port Harcourt. Check the deals here: geoinfostore.com Cubana Chief Priest | #GIS #Mapping #Lagos | Gbenga Daniel | Eazi


Spent 5 minutes turning scattered reports into something you can actually see Plot it on a map โ†’ patterns start to emerge. Sometimes It takes one clear question to turn chaos into insight. science4data.com #DataViz #Mapping #GeoData #DataStorytelling #Insights #NoCode

S4DInsights's tweet image. Spent 5 minutes turning scattered reports into something you can actually see 

Plot it on a map โ†’ patterns start to emerge.
Sometimes It takes one clear question to turn chaos into insight. science4data.com
#DataViz #Mapping #GeoData #DataStorytelling #Insights #NoCode

1 Flight. 7 Outputs ๐Ÿ”„ One LiDAR mission with DJI Zenmuse L3 and Matrice 400 can generate point clouds, meshes, terrain models, and more, maximizing data from every flight. #djienterprise #lidar #mapping


This is what our users are saying about Correlator3D ensuring consistent results. Learn more about the solutionโžก๏ธ hubs.ly/Q04f6J2Z0 #LiDAR #mapping #photogrammetry #Correlator3D #drones


OpenTrafficMap gathers real-time traffic data to map road conditions globally. Insights: community-driven, open-source-style traffic view can help travelers and planners spot congestion trends fast. #OpenData #Traffic #Mapping #OpenSource ๐Ÿšฆ๐Ÿ“


Join Don Cummins, from Air Data Solutions, as he shares how Kaula Island surveys supported U.S. Navy environmental monitoring using advanced sensors and Correlator3Dโžก๏ธ hubs.ly/Q04d_y970 #LiDAR #mapping #photogrammetry #Correlator3D #drones


Setup complete. Base locked. GCPs set. ๐Ÿš Out in the field getting ready to lift off for a LiDAR scanโ€”turning farmland into high-precision data. Letโ€™s fly. #lidar #drone #mapping


Correlator3D just got even more powerful. With its new Gaussian splatting feature, you can turn your image sets into stunning, photo-realistic 3D scenes. Give it a tryโžก๏ธ hubs.ly/Q04cvNxw0 #LiDAR #mapping #photogrammetry #Correlator3D #drones


right here in Nigeria today. Accuracy = Profit. Don't let old gear slow down your projects in Lagos or Port Harcourt. Check the deals here: geoinfostore.com Cubana Chief Priest | #GIS #Mapping #Lagos | Gbenga Daniel | Eazi


This projectโ€”over 500 images captured with an RX1 RII Wingtra sensor at 5 cm GSDโ€”was processed on a single standard PC using Correlator3Dโžก๏ธ hubs.ly/Q049d5dH0 #LiDAR #mapping #photogrammetry #Correlator3D #drones

SimActiveInc's tweet image. This projectโ€”over 500 images captured with an RX1 RII Wingtra sensor at 5 cm GSDโ€”was processed on a single standard PC using Correlator3Dโžก๏ธ hubs.ly/Q049d5dH0

#LiDAR #mapping #photogrammetry #Correlator3D #drones
SimActiveInc's tweet image. This projectโ€”over 500 images captured with an RX1 RII Wingtra sensor at 5 cm GSDโ€”was processed on a single standard PC using Correlator3Dโžก๏ธ hubs.ly/Q049d5dH0

#LiDAR #mapping #photogrammetry #Correlator3D #drones
SimActiveInc's tweet image. This projectโ€”over 500 images captured with an RX1 RII Wingtra sensor at 5 cm GSDโ€”was processed on a single standard PC using Correlator3Dโžก๏ธ hubs.ly/Q049d5dH0

#LiDAR #mapping #photogrammetry #Correlator3D #drones
SimActiveInc's tweet image. This projectโ€”over 500 images captured with an RX1 RII Wingtra sensor at 5 cm GSDโ€”was processed on a single standard PC using Correlator3Dโžก๏ธ hubs.ly/Q049d5dH0

#LiDAR #mapping #photogrammetry #Correlator3D #drones

Coffee sector leaders launch industry-first global #mapping initiative to accelerate the transition towards a deforestation-free #coffee sector #CoffeeCanopyPartnership jdepeets.com/news-containerโ€ฆ


๐Ÿ—บ๏ธ New in the latest beta: GridLayer! Overlay a coordinate grid on your Mapsui map with just one line of code: map.Layers.Add(new GridLayer { ShowCoordinateLabels = true }); Try the live sample ๐Ÿ‘‡ mapsui.com/v5/samples/#/Sโ€ฆ #dotnet #csharp #mapping #opensource


Sistema de Informaciรณn Geogrรกfica con QGIS โฑ๏ธ 3.4 hours โญ 4.17 ๐Ÿ‘ฅ 72 ๐Ÿ”„ Jul 2024 ๐Ÿ’ฐ $14.99 โ†’ 100% OFF comidoc.com/udemy/sig_qgisโ€ฆ #QGIS #GIS #Mapping #udemy

comidoc's tweet image. Sistema de Informaciรณn Geogrรกfica con QGIS

โฑ๏ธ 3.4 hours
โญ 4.17
๐Ÿ‘ฅ 72
๐Ÿ”„ Jul 2024
๐Ÿ’ฐ $14.99 โ†’ 100% OFF

comidoc.com/udemy/sig_qgisโ€ฆ

#QGIS #GIS #Mapping #udemy

At Goliath Resourcesโ€™ย Surebetย Shear Zone in northern BC, steep cliffs and extreme terrain make traditional #structural #mapping impossible. The solution? Combining #fieldwork, drone #photogrammetry, and digital mapping withย #HiveMap. ๐Ÿ‘‰Read case study: mirageoscience.com/goliath-resourโ€ฆ

MiraGeoscience's tweet image. At Goliath Resourcesโ€™ย Surebetย Shear Zone in northern BC, steep cliffs and extreme terrain make traditional #structural #mapping impossible. The solution? Combining #fieldwork, drone #photogrammetry, and digital mapping withย #HiveMap. 
๐Ÿ‘‰Read case study: mirageoscience.com/goliath-resourโ€ฆ

Advocacy and pressure, @7amleh has secured important changes across #Microsoftโ€™s #mapping platforms: correcting how #Palestinian #geography is represented. - Removal of misleading #Israeli labels like โ€œ#Judea and #Samariaโ€ - Adoption of the accurate term โ€œ#WestBankโ€

๐ŸšจAfter months of advocacy and pressure, 7amleh has secured important changes across Microsoftโ€™s mapping platforms: correcting how Palestinian geography is represented. -Removal of misleading Israeli labels like โ€œJudea and Samaria, ILโ€ -Adoption of the accurate term โ€œWest Bankโ€

7amleh's tweet image. ๐ŸšจAfter months of advocacy and pressure, 7amleh has secured important changes across Microsoftโ€™s mapping platforms: correcting how Palestinian geography is represented.

-Removal of misleading Israeli labels like โ€œJudea and Samaria, ILโ€
-Adoption of the accurate term โ€œWest Bankโ€


Design maps your way. Control every layer โ€” from colors to POIs to land use โ€” so your map guides users exactly where they need to go. Explore whatโ€™s possible: mapbox.com/your-map?utm_sโ€ฆ #BuiltWithMapbox #UXDesign #Mapping

Mapbox's tweet image. Design maps your way.

Control every layer โ€” from colors to POIs to land use โ€” so your map guides users exactly where they need to go.

Explore whatโ€™s possible: mapbox.com/your-map?utm_sโ€ฆ

#BuiltWithMapbox #UXDesign #Mapping

๐ŸŒณ๐ŸŒณ #Mapping Natural Populus euphratica #Forests in the Mainstream of the Tarim River Using Spaceborne Imagery and #GoogleEarth #Engine โœ๏ธ Jiawei Zou et al. ๐Ÿ”— brnw.ch/21x0Ow2

RemoteSens_MDPI's tweet image. ๐ŸŒณ๐ŸŒณ #Mapping Natural Populus euphratica #Forests in the Mainstream of the Tarim River Using Spaceborne Imagery and #GoogleEarth #Engine

โœ๏ธ Jiawei Zou et al.
๐Ÿ”— brnw.ch/21x0Ow2

๐ŸŒพ๐ŸŒพ Detection of the Optimal #Temporal Windows for #Mapping Paddy #Rice Under a Double-Cropping System Using #Sentinel2 Imagery โœ๏ธ Li Sheng et al. ๐Ÿ”— brnw.ch/21x1cPT

RemoteSens_MDPI's tweet image. ๐ŸŒพ๐ŸŒพ Detection of the Optimal #Temporal Windows for #Mapping Paddy #Rice Under a Double-Cropping System Using #Sentinel2 Imagery

โœ๏ธ Li Sheng et al.
๐Ÿ”— brnw.ch/21x1cPT

๐Ÿ‘‰๐Ÿ‘‰ High-Accuracy #Mapping of #Soil #Organic #Carbon by #Mining Sentinel-1/2 #Radar and Optical Time-Series Data with Super Ensemble Model โœ๏ธ Zhibo Cui et al. ๐Ÿ”— brnw.ch/21x1PL8

RemoteSens_MDPI's tweet image. ๐Ÿ‘‰๐Ÿ‘‰ High-Accuracy #Mapping of #Soil #Organic #Carbon by #Mining Sentinel-1/2 #Radar and Optical Time-Series Data with Super Ensemble Model

โœ๏ธ Zhibo Cui et al.
๐Ÿ”— brnw.ch/21x1PL8

๐ŸŒณ๐ŸŒณ Multi-Decision Vector Fusion Model for Enhanced #Mapping of Aboveground Biomass in #Subtropical #Forests Integrating #Sentinel1, #Sentinel2, and Airborne #LiDAR Data โœ๏ธ Wenhao Jiang et al. ๐Ÿ”— brnw.ch/21x1GIF

RemoteSens_MDPI's tweet image. ๐ŸŒณ๐ŸŒณ Multi-Decision Vector Fusion Model for Enhanced #Mapping of Aboveground Biomass in #Subtropical #Forests Integrating #Sentinel1, #Sentinel2, and Airborne #LiDAR Data

โœ๏ธ Wenhao Jiang et al.
๐Ÿ”— brnw.ch/21x1GIF

๐Ÿ’ง๐Ÿ’ง #Flood #Susceptibility #Mapping of the #Kosi Megafan Using Ensemble #MachineLearning and #SAR Data โœ๏ธ Khaled Mahamud Khan et al. ๐Ÿ”— brnw.ch/21x1CBi

RemoteSens_MDPI's tweet image. ๐Ÿ’ง๐Ÿ’ง #Flood #Susceptibility #Mapping of the #Kosi Megafan Using Ensemble #MachineLearning and #SAR Data

โœ๏ธ Khaled Mahamud Khan et al.
๐Ÿ”— brnw.ch/21x1CBi

๐Ÿ‘‰๐Ÿ‘‰ #Landslide Susceptibility #Mapping Considering Landslide #Spatial #Aggregation Using the Dual-Frequency Ratio Method: A Case Study on the Middle Reaches of the Tarim #River #Basin โœ๏ธ Xuetao Yi et al. ๐Ÿ”— brnw.ch/21x1ygr

RemoteSens_MDPI's tweet image. ๐Ÿ‘‰๐Ÿ‘‰ #Landslide Susceptibility #Mapping Considering Landslide #Spatial #Aggregation Using the Dual-Frequency Ratio Method: A Case Study on the Middle Reaches of the Tarim #River #Basin

โœ๏ธ Xuetao Yi et al.
๐Ÿ”— brnw.ch/21x1ygr

๐ŸŒณ๐ŸŒณ Classification and #Mapping of Fuels in Mediterranean #Forest Landscapes Using a #UAV- #LiDAR System and Integration Possibilities with Handheld #Mobile #Laser Scanner Systems โœ๏ธ Raรบl Hoffrรฉn et al. ๐Ÿ”— brnw.ch/21x0Q0N

RemoteSens_MDPI's tweet image. ๐ŸŒณ๐ŸŒณ Classification and #Mapping of Fuels in Mediterranean #Forest Landscapes Using a #UAV- #LiDAR System and Integration Possibilities with Handheld #Mobile #Laser Scanner Systems

โœ๏ธ Raรบl Hoffrรฉn et al.
๐Ÿ”— brnw.ch/21x0Q0N

๐Ÿ”ฅ๐ŸŒณ Optimizing Stacked Ensemble #MachineLearning Models for Accurate #Wildfire Severity #Mapping โœ๏ธ Linh Nguyen Van and Giha Lee ๐Ÿ”— brnw.ch/21x1in6

RemoteSens_MDPI's tweet image. ๐Ÿ”ฅ๐ŸŒณ Optimizing Stacked Ensemble #MachineLearning Models for Accurate #Wildfire Severity #Mapping

โœ๏ธ Linh Nguyen Van and Giha Lee
๐Ÿ”— brnw.ch/21x1in6

๐Ÿ‡น๐Ÿ‡ณ๐Ÿ‡น๐Ÿ‡ณ #Soil #Salinity Detection and #Mapping by Multi-Temporal #Landsat Data: Zaghouan Case Study (#Tunisia) โœ๏ธ Karem Saad et al. ๐Ÿ”— brnw.ch/21x1aLw

RemoteSens_MDPI's tweet image. ๐Ÿ‡น๐Ÿ‡ณ๐Ÿ‡น๐Ÿ‡ณ #Soil #Salinity Detection and #Mapping by Multi-Temporal #Landsat Data: Zaghouan Case Study (#Tunisia)

โœ๏ธ Karem Saad et al.
๐Ÿ”— brnw.ch/21x1aLw

๐Ÿ’ง๐Ÿ’ง #Mapping River Flow from #Thermal Images in Approximately Real Time: Proof of Concept on the Sacramento #River, #California, #USA โœ๏ธ Carl J. Legleiter et al. ๐Ÿ”— brnw.ch/21x19mk

RemoteSens_MDPI's tweet image. ๐Ÿ’ง๐Ÿ’ง #Mapping River Flow from #Thermal Images in Approximately Real Time: Proof of Concept on the Sacramento #River, #California, #USA

โœ๏ธ Carl J. Legleiter et al.
๐Ÿ”— brnw.ch/21x19mk

๐ŸŒ๐Ÿ›ฐ๏ธ Refined #Landslide Susceptibility #Mapping Considering #LandUse Changes and #InSAR Deformation: A Case Study of Yulin City, Guangxi โœ๏ธ Pengfei Li et al. ๐Ÿ”— brnw.ch/21x0G2z

RemoteSens_MDPI's tweet image. ๐ŸŒ๐Ÿ›ฐ๏ธ Refined #Landslide Susceptibility #Mapping Considering #LandUse Changes and #InSAR Deformation: A Case Study of Yulin City, Guangxi

โœ๏ธ Pengfei Li et al.
๐Ÿ”— brnw.ch/21x0G2z

๐ŸŒฟ๐ŸŒฟ Parcel-Based #Sugarcane #Mapping Using Smoothed #Sentinel1 Time Series Data โœ๏ธ Hongzhong Li et al. ๐Ÿ”— brnw.ch/21x0Cgc

RemoteSens_MDPI's tweet image. ๐ŸŒฟ๐ŸŒฟ Parcel-Based #Sugarcane #Mapping Using Smoothed #Sentinel1 Time Series Data

โœ๏ธ Hongzhong Li et al.
๐Ÿ”— brnw.ch/21x0Cgc

๐Ÿ‘‰๐Ÿ‘‰ Practical Guidelines for Performing #UAV #Mapping #Flights with Snapshot Sensors โœ๏ธ Wouter H. Maes et al. ๐Ÿ”— brnw.ch/21x1gRE

RemoteSens_MDPI's tweet image. ๐Ÿ‘‰๐Ÿ‘‰ Practical Guidelines for Performing #UAV #Mapping #Flights with Snapshot Sensors
 
โœ๏ธ Wouter H. Maes et al.
๐Ÿ”— brnw.ch/21x1gRE

๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Towards High-Resolution #Population #Mapping: Leveraging Open Data, Remote Sensing, and #AI for #Geospatial Analysis in Developing Country Citiesโ€”A Case Study of #Bangkok โœ๏ธ Kittisak Maneepong et al. ๐Ÿ”— brnw.ch/21x1TQa

RemoteSens_MDPI's tweet image. ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ Towards High-Resolution #Population #Mapping: Leveraging Open Data, Remote Sensing, and #AI for #Geospatial Analysis in Developing Country Citiesโ€”A Case Study of #Bangkok

โœ๏ธ Kittisak Maneepong et al.
๐Ÿ”— brnw.ch/21x1TQa

๐Ÿ”ฅ๐ŸŒณ #Burned Areas #Mapping Using #Sentinel2 Data and a Raoโ€™s Q Index-Based Change Detection Approach: A Case Study in Three Mediterranean Islandsโ€™ #Wildfires (2019โ€“2022) โœ๏ธ Rafaela Tiengo et al. ๐Ÿ”— brnw.ch/21x1EII

RemoteSens_MDPI's tweet image. ๐Ÿ”ฅ๐ŸŒณ #Burned Areas #Mapping Using #Sentinel2 Data and a Raoโ€™s Q Index-Based Change Detection Approach: A Case Study in Three Mediterranean Islandsโ€™ #Wildfires (2019โ€“2022)

โœ๏ธ Rafaela Tiengo et al.
๐Ÿ”— brnw.ch/21x1EII

๐ŸŒฝ๐Ÿ–ผ๏ธ Enhancing #Cropland #Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for #Image #SuperResolution Models โœ๏ธ Xiaofeng Jia et al. ๐Ÿ”— brnw.ch/21x18gd

RemoteSens_MDPI's tweet image. ๐ŸŒฝ๐Ÿ–ผ๏ธ Enhancing #Cropland #Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for #Image #SuperResolution Models

โœ๏ธ Xiaofeng Jia et al.
๐Ÿ”— brnw.ch/21x18gd

Design maps your way. Control every layer โ€” from colors to POIs to land use โ€” so your map guides users exactly where they need to go. Explore whatโ€™s possible: mapbox.com/your-map?utm_sโ€ฆ #BuiltWithMapbox #UXDesign #Mapping

Mapbox's tweet image. Design maps your way.

Control every layer โ€” from colors to POIs to land use โ€” so your map guides users exactly where they need to go.

Explore whatโ€™s possible: mapbox.com/your-map?utm_sโ€ฆ

#BuiltWithMapbox #UXDesign #Mapping

The map shows the vast deposits of Iran's major oil and natural gas deposits which lie mostly in the south-west and south of the country. Much of Iran's south-east and east has not been extensively explored. Direct Map Link: soaratlas.com/maps/140385 #Iran #Oil #Mapping

SoarAtlas's tweet image. The map shows the vast deposits of Iran's major oil and natural gas deposits which lie mostly in the south-west and south of the country. Much of Iran's south-east and east has not been extensively explored. Direct Map Link: soaratlas.com/maps/140385

#Iran #Oil #Mapping

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