Mstafa.farahani@gmail.com 

wa.me/+989381272118

Youtube.com/GEEmap

T.me/geemap

Google Earth Engine toturial51 Soil Sand depths 0-200 (%Kg/Kg) growth Chart📈 Remotesensing satellite

#sand #soilsand #sanddetection #air #water #lulc #gis #EarthObservation #remotesensing

Google Earth Engine toturial48 Soil Water content at 33kpa (%) growth CHART📈 Remotesensing satellite

#Googleearthengine #Remotesensing #GIS #RS #EarthObserSDM_

https://youtu.be/vBy2ZzFatKU?si=wPt2VpI0zSZ-lp81

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.Google Earth Engine toturial50 Soil BULK Density area Km² growth CHART📈 Remotesensing GIS satellite

#soilbulkdensity #earth #gis #RS #satellite #lulc #water #air #soil

https://youtu.be/VTV3dWdxr8c?si=2pYk_C5Mox-VZSNe

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.Google Earth Engine toturial49 Soil TAXONOMY AREA Km² growth CHART📈 Remotesensing QGIS satellite

#soil #air #water #lulc #environmentalenginnering #satellite #RS #gis #soiltaxonomy #earth

https://youtu.be/k9sZnXffoEM?si=pLQ-8ltdVj5dqEIq

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Google Earth Engine toturial48 Soil Water content at 33kpa (%) growth CHART📈 Remotesensing satellite

#Googleearthengine #Remotesensing #GIS #RS #EarthObservation #satellite #environmentalenginnering #lulc #water #air #soil

https://youtu.be/0zAhATAZPLQ?si=gJDojrMFG_iRSDM_

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.https://s8.uupload.ir/files/47_carbon_storage_soil_growth_byot.jpg

Google Earth Engine toturial47 Soil CARBON STORAGE KG/m²/year growth CHART📈 Remotesensing GIS satellite

#satellite #carbon #carbonstorage #gis #Remotesensing #EarthObservation #landuse #earth #soil #GoogleEarthEngine

https://youtu.be/VbyXTG96ymc?si=XAVpjAThBK-2SpFO

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Google Earth Engine toturial46 ***🇮🇷 LAND COVER LULC km² growth CHART📈 Remotesensing GIS satellite

#lulc #landcover #landuse #satellite #Remotesensing #gis #EarthObservation

https://youtu.be/j0EPHETOo_o?si=teROxoMlHM1fBUrN.

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Google Earth Engine toturial 45 NDVI Area km² growth CHART📈 Remotesensing GIS satellite application

#remotesensing #ndvi #Normalizedifferencevegetationindex #gis #satellite #soil #air #water #earth #environmentalenginnering

https://youtu.be/s_GL9L6ABOE?si=ahy9_IAhdkYX3ohA

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Google Earth Engine toturial 44 SOIL TEXTURE AREA PIE CHART📈 Remotesensing GIS satellite application

#soil #soil_texture #soiltexture #Satellite #GEE #GOOGLEEARTHENGINE #QGIS #GIS #Remotesensing #AirPollution #waterpollution #Soilquality

https://youtu.be/Da1z30dT8Ic?si=n0iLtZ28QhpUa7w8.

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.Google Earth Engine toturial 43 world cover LULC km² growth  Remotesensing  application

#landcover #landuse #LULC #LANDUSE #LANDCOVER #worldcover  #satellite #gis #Qgis #MachineLearning #GoogleEarthEngine #GEE #climatechange #globalwarming #soil

https://youtube.com/watch?v=h_DKYnlnUec&si=Edr1JxofYIBkd0jg.

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Google Earth Engine toturial 40 Built-up Animation    Remotesensing GIS satellite  City Development

#Built-up #CityDevelopment  #GIS #Remotesensing #satellite #air #water #soil #buildingarea #Qgis #Arcgis #climatechange #globalwarming #soilpollution

https://youtube.com/watch?v=Fo843wTIaBI&si=mJGWilOcq1b94jNE.

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Google Earth Engine toturial #12 Shrubland land cover land use Remotesensing GIS app

#shrubland #shrublandareagrowth #landcover #lulc #landuse #landcover #satellite #modis #gee #googleearthengine #Qgis #arcgis

#Remotesensing

https://youtu.be/GWhiEPVsrE8?si=c8xoCVG1W33W22Yj

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 Google Earth Engine toturial #10 Cropland Agricultural Area growth Land Cover use  Remotesensing GIS

#GIS #Remotesensing 

#agriculturalarea #croplandarea #GEE #javascript #python #R #satellite #croplandgrowth

https://youtu.be/GMdL99owlco?si=9B_I3-6VARvLYd2D

Google Earth Engine toturial #9 Urban Built-up growth

Land Cover USE Remote Sensing GIS application

Video and code in my

Youtube.com/@GEEmap p

Google Earth Engine toturial #9 Urban Built-up growth Land Cover USE Remote Sensing GIS application

#urbanareagrowth #Builtupareagrowth #Landuse #LandCover #gis #remotesensing #googleearthengine #GEE #Citygrowth #Climate #urbangrowth

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GIS ., Remote Sensing ., LULC Mapping ., Urban Area ., Built-up Area ., Land Use Analysis ., Urban Growth ., Satellite Imagery ., Google Earth Engine ., Remote Sensing Applications ., GIS Analysis ., Satellite Data ., Climate Change ., Global Warming ., Urban Planning ., Urban Development ., Spatial Analysis ., Remote Sensing Technology ., GIS Mapping ., Earth Observation ., Geographic Information Systems ., Urban Heat Island ., Sustainable Urbanization ., Land Cover ., Land Use Change ., Urban Expansion ., Urban Monitoring ., Remote Sensing Tools ., GIS for Urban Planning ., Satellite Images ., Change Detection ., Environmental Monitoring ., Climate Data ., GIS for Climate Studies ., Remote Sensing for Land Use ., GIS Techniques ., Satellite Technology ., Global Urbanization ., Remote Sensing Software ., Urbanization Trends ., Urban Sprawl ., Smart Cities ., Urban Sustainability ., GIS in Environment ., Remote Sensing for Environment ., GIS for Agriculture ., Remote Sensing for Agriculture ., GIS for Natural Resources ., Satellite Remote Sensing ., GIS Data Analysis ., GIS for Beginners ., GIS Applications ., Urban Studies ., GIS for Land Cover ., Remote Sensing for LULC ., Satellite Imagery Analysis ., GIS for Monitoring ., GIS for Urban Growth ., Remote Sensing for Climate ., GIS in Education ., Remote Sensing Tutorials ., Satellite Monitoring ., GIS Technology ., GIS Visualization ., Urban Landscape ., GIS for Land Use Planning ., Remote Sensing for Urban Analysis ., GIS for Sustainable Development ., Climate Adaptation ., Remote Sensing for Environment ., GIS in Climate Science ., Remote Sensing for Global Warming ., GIS for Disaster Management ., Remote Sensing for Monitoring ., Remote Sensing for Mapping ., GIS for Decision Making ., Urban Development Planning ., Land Use Models ., Climate Resilience ., Satellite Image Processing ., GIS for Remote Sensing ., Satellite Observations ., Remote Sensing Data ., GIS for Smart Cities ., GIS for Urban Areas ., Remote Sensing for Built-up Areas ., GIS for Urban Studies ., Climate Impact Analysis ., GIS for Policy Making ., Remote Sensing for Environment ., GIS for Risk Assessment ., Satellite Imagery for LULC ., GIS for Climate Change ., Remote Sensing for Urbanization ., GIS for Infrastructure ., Remote Sensing Innovations .,

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Google Earth Engine toturial #8 Formaldehyde HCHO Air quality Remote Sensing GIS application

#GoogleEarthEngine #Air #airpollution #remote_sensing #gis #Formaldehyde #HCHO #GEE #airQuality #airpollutant #Climate #globalwarming

https://youtu.be/q4bGEgBDNnk?si=y4udoSaQ-VsWGwzy

Video and code in my youtube.com/@geemap

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Toturial #3 #Methan #CH4 #Airpollurion by #GoogleEarthEngine #RemoteSensing #GIS

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Here is the plain text of keywords in English, formatted as keyword ., keyword and spanning approximately 30 pages, covering remote sensing, GIS, CH4, air quality, air pollution, air pollutants, and methane:

remote sensing ., GIS ., CH4 ., air quality ., air pollution ., air pollutant ., methane ., satellite imagery ., spatial analysis ., GIS mapping ., methane emissions ., atmospheric methane ., air quality monitoring ., air pollution control ., air pollutant sources ., methane concentration ., air pollution monitoring ., GIS applications ., satellite data ., methane detection ., environmental GIS ., spatial data analysis ., GIS tools ., air quality mapping ., pollution control ., remote sensing applications ., atmospheric pollution ., methane flux ., air pollutant tracking ., GIS spatial analysis ., methane mitigation ., atmospheric science ., CH4 emissions ., air quality models ., GIS for environment ., pollution monitoring ., satellite remote sensing ., GIS for air quality ., methane gas ., air pollutant analysis ., GIS-based tools ., air pollution modeling ., remote sensing GIS ., air quality assessment ., methane mapping ., air pollutant sensors ., remote sensing technology ., 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Toturial #3 #Methan #CH4 #Airpollurion by #GoogleEarthEngine #RemoteSensing #GIS

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Here is the plain text of keywords in English, formatted as keyword ., keyword and spanning approximately 30 pages, covering remote sensing, GIS, CH4, air quality, air pollution, air pollutants, and methane:

remote sensing ., GIS ., CH4 ., air quality ., air pollution ., air pollutant ., methane ., satellite imagery ., spatial analysis ., GIS mapping ., methane emissions ., atmospheric methane ., air quality monitoring ., air pollution control ., air pollutant sources ., methane concentration ., air pollution monitoring ., GIS applications ., satellite data ., methane detection ., environmental GIS ., spatial data analysis ., GIS tools ., air quality mapping ., pollution control ., remote sensing applications ., atmospheric pollution ., methane flux ., air pollutant tracking ., GIS spatial analysis ., methane mitigation ., atmospheric science ., CH4 emissions ., air quality models ., GIS for environment ., pollution monitoring ., satellite remote sensing ., GIS for air quality ., methane gas ., air pollutant analysis ., GIS-based tools ., air pollution modeling ., remote sensing GIS ., air quality assessment ., methane mapping ., air pollutant sensors ., remote sensing technology ., environmental pollution ., GIS in remote sensing ., air pollution research ., methane data ., atmospheric monitoring ., GIS for methane ., methane sources ., air quality standards ., GIS remote sensing ., methane analysis ., satellite CH4 ., air pollutant impact ., air quality trends ., GIS environment ., remote sensing data ., air pollution index ., air pollutant studies ., methane distribution ., air quality sensors ., GIS air pollution ., methane trends ., air pollutant modeling ., air quality simulation ., spatial pollution ., methane observation ., air quality datasets ., air pollutant GIS ., CH4 modeling ., GIS-based mapping ., air quality metrics ., air pollution satellite ., methane in atmosphere ., GIS technology ., air pollutant mapping ., remote sensing tools ., air quality sensors ., methane GIS ., CH4 detection ., GIS science ., air pollution mapping ., air quality software ., CH4 modeling tools ., GIS pollution ., methane air quality ., remote sensing monitoring ., air pollutant remote sensing ., GIS and CH4 ., air pollution studies ., methane climate impact ., GIS in pollution ., satellite air quality ., remote sensing solutions ., air pollutant satellites ., methane pollution ., CH4 research ., GIS methane detection ., satellite GIS ., air pollution CH4 ., GIS for air ., remote sensing methane ., methane pollutant ., air pollution maps ., methane dynamics ., remote sensing for air ., GIS pollutant tracking ., atmospheric methane data ., CH4 monitoring tools ., air quality modeling ., methane detection GIS ., air pollutant datasets ., remote sensing air pollution ., GIS tools for pollution ., methane environmental ., GIS analysis methane ., air quality and GIS ., remote sensing and CH4 ., air pollution and GIS ., GIS in air quality ., methane remote sensing ., CH4 concentration ., GIS technology applications ., air quality GIS ., air pollutant mitigation ., remote sensing applications GIS ., methane tracking ., CH4 in atmosphere ., GIS and air ., air pollution GIS tools ., air pollutant impacts ., methane dynamics tracking ., GIS-based pollutant ., remote sensing for CH4 ., GIS air quality monitoring ., methane environmental analysis ., CH4 mapping GIS ., air pollutant research ., GIS pollution mapping ., remote sensing for methane ., air pollutant metrics ., atmospheric pollution GIS ., methane GIS mapping ., GIS satellite data ., remote sensing of air ., GIS for pollutant ., air quality technology ., methane standards ., remote sensing applications methane ., air pollutant CH4 ., GIS solutions for air ., methane GIS data ., air quality impact ., air pollution datasets ., methane and GIS ., air pollutant satellite ., CH4 environmental tools ., GIS for pollution control ., methane air pollution ., atmospheric science GIS ., remote sensing CH4 mapping ., GIS atmospheric data ., CH4 tracking tools ., air quality software solutions ., methane environmental metrics ., GIS air monitoring ., pollutant mapping GIS ., methane global 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quality pollutant GIS ., methane and air data ., pollutant GIS metrics ., atmospheric methane modeling ., air pollution trends GIS ., remote sensing pollutant tracking ., air quality and methane ., pollutant mapping solutions ., GIS pollution solutions ., air pollutant mitigation GIS ., atmospheric pollution data ., CH4 dynamics GIS ., air quality GIS solutions ., methane tracking GIS tools ., remote sensing for air data ., GIS for CH4 research ., pollutant mapping standards ., methane tools GIS ., air quality pollutant modeling ., atmospheric pollutant GIS ., remote sensing datasets ., GIS methane tools ., pollutant research trends GIS ., air quality environmental research ., methane remote sensing technology ., pollutant monitoring solutions ., air data GIS mapping ., pollutant analysis tools ., methane satellite ., air pollutant modeling solutions ., remote sensing air ., GIS pollutant air ., methane in air ., CH4 pollutant GIS ., GIS for remote sensing ., air quality tracking GIS 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PM2.5 and Air Pollution Analysis

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PM2.5 and Its Impact on Air Quality

PM2.5 Visualization (JPG)

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PM2.5 Analysis (MP4)

Description

Particulate Matter (PM2.5) is a major air pollutant that poses serious health risks, particularly for vulnerable populations. These tiny particles can penetrate deep into the respiratory system, causing respiratory and cardiovascular diseases.

Over the years, rapid urbanization and industrialization have increased PM2.5 levels, particularly in metropolitan areas. Remote sensing technologies such as Google Earth Engine provide a revolutionary way to monitor and analyze these pollutants globally.

This analysis leverages satellite imagery to identify high-concentration areas, providing data-driven insights for policymakers. Mapping tools allow for tracking pollution sources, understanding temporal variations, and proposing mitigation strategies.

PM2.5 also contributes to global warming by affecting the radiation balance. Thus, reducing PM2.5 is not only essential for human health but also for combating climate change.

One effective approach includes integrating spatial data into urban planning. For example, green belts and emission regulations can significantly reduce local PM2.5 levels.

Moreover, PM2.5 data can be combined with health records to study long-term impacts on public health. This is critical for prioritizing resources in affected areas.

Researchers are also developing advanced algorithms to improve the accuracy of PM2.5 estimations using satellite data. These innovations can enhance monitoring capabilities globally.

With accessible platforms like GEE, even small organizations can now analyze and visualize air pollution effectively. This democratization of technology is key to addressing global challenges.

However, challenges remain, including data gaps in rural regions and limitations in ground truth verification. Collaboration between researchers and local authorities is crucial to fill these gaps.

In conclusion, understanding and mitigating PM2.5 pollution requires a multidisciplinary approach, integrating environmental science, health studies, and cutting-edge technology.

Keywords

#GoogleEarthEngine #GIS #RemoteSensing #PM25 #AirQuality #PollutionMonitoring #EnvironmentalHealth #MappingTools #SatelliteImagery #AirPollution #ClimateChange #Sustainability #EnvironmentalAwareness

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NDVI Animation + Code with Google Earth Engine

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NDVI Animation + Code

Google Earth Engine Analysis

NDVI Analysis and Animation in Google Earth Engine

#RemoteSensing #NDVI #GoogleEarthEngine #GIS #ClimateChange

Description:

NDVI (Normalized Difference Vegetation Index) is a widely used indicator for monitoring vegetation health and coverage. Utilizing Google Earth Engine, NDVI can be calculated and animated over time, providing valuable insights for environmental and agricultural studies.

Historical Context:

The concept of NDVI emerged in the 1970s with the advent of satellite technology. It has since evolved into a critical tool for remote sensing, allowing researchers to track vegetation changes globally.

Impact on Environment:

NDVI helps monitor deforestation, drought conditions, and urbanization impacts on eغير مجاز مي باشدystems. By assessing vegetation health, it contributes to sustainable land management practices.

Impact on Humans:

NDVI data supports agriculture by predicting crop yields, managing irrigation, and identifying areas affected by pests or diseases. It also informs policymakers in addressing climate change challenges.

Challenges:

Despite its benefits, NDVI has limitations, including sensitivity to soil background and atmospheric conditions. Combining it with other indices enhances its reliability.

Technological Integration:

Platforms like Google Earth Engine enable efficient NDVI computation and visualization, making it accessible to researchers and decision-makers worldwide.

Future Prospects:

Advances in machine learning and big data are expected to refine NDVI analyses, enabling more accurate predictions of vegetation dynamics and environmental changes.

Applications:

NDVI is widely used in environmental monitoring, urban planning, disaster management, and climate change studies. Its applications span across agriculture, forestry, and water resource management.

Conclusion:

NDVI remains an indispensable tool for understanding and preserving our planet's eغير مجاز مي باشدystems. Its integration with emerging technologies holds the promise of greater precision and impact.

Call to Action:

Explore NDVI animations and data analysis with Google Earth Engine. Join the community of researchers and professionals utilizing this powerful tool for a sustainable future.

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#GIS #VegetationMonitoring #RemoteSensingApplications

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