🛰Remote Sensing Innovators
#chatGPT
Masofadan zondlash orqali olingan qiymat (Crops : 631 058 gektar) haqiqiy qiymatga (748 428 gektar) nisbatan 84.32% aniqlikka ega.
Remote sensing va GIS bo'yicha online o'rganish uchun darslar :
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🛰Remote Sensing Innovators
Remote sensing va GIS bo'yicha online o'rganish uchun darslar :
1. GeoInfo.uz ArcGIS pro , Google earth engine O'zbek tilida dars o'tiladi
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🛰Remote Sensing Innovators
Remote sensing va GIS bo'yicha online o'rganish uchun darslar :
2. Study Huck, India institute of Remote sensing (IIRS)da dars beradi Google earth engine bo'yicha 7 kunlik traninglar tashkillashtiradi Ingliz tilida dars o'tadi.
Telegram
StudyHacks (Institute of GIS & Remote Sensing)
Join our official YouTube Channel: https://www.youtube.com/channel/UCmVAM92fX1ag8-6V1lsvH_w/
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3. UDEMY online platforma ichida zo'r kurslari bor ayniqsa bitta yunalishda projectlar qilib ko'rsatadi
Udemy
Udemy: Online Courses for Skills, Careers & AI
Learn in-demand skills with online courses, get professional certificates that advance your career, and explore courses in AI, coding, business and more.
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Forwarded from Jasmina
Добрый день. Объявляется набор на курс по программе SuperMap "Анализ 2Д и 3Д данных". Обучение онлайн, бесплатно. Желающие напишите мне в личку, пожалуйста. Нужно будет только сдавать отчёты в свободное от работы время
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#Dron uchirishga qiziqadigan lekin dron bo'yicha qayerda va kim o'qitishini bilmaydigan yoshlar bormi ? Kimda savollar bo'lsa comment ga yozinglar.....
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🌊 SAR Sentinel-1 VV Band orqali Kemalarni Aniqlash 🛰🚢
Sentinel-1 sun’iy yo‘ldoshi VV polarizatsiya kanali yordamida kemalarni aniqlash va kuzatish mumkin!
🔍 Qanday ishlaydi?
✅ SAR (Synthetic Aperture Radar) tungi va bulutli ob-havoda ham ishlaydi.
✅ VV band suv yuzasidagi harakatlanuvchi obyektlarni (kemalar, qayiq va platformalar) aniq ajratadi.
✅ AI va GIS yordamida kemalarning marshrutini kuzatish mumkin.
🌍 Foydali jihatlar:
📡 Dengiz xavfsizligi – noqonuniy kemalarni aniqlash.
🚢 Port va yuk tashish monitoringi – kemalar harakatini nazorat qilish.
🛑 Atrof-muhit muhofazasi – neft to‘kilishlari va noqonuniy baliq ovlashni kuzatish.
Masofaviy zondlash dengiz transporti va xavfsizligini yangi darajaga olib chiqmoqda! Sizning fikringiz qanday? 🌊🌍
📲RemoteSensing_Innovators
✍️@Davlatov_9959
#GIS #RemoteSensing #SAR1 #Sentinel1 #ShipDetection #DengizXavfsizligi
Sentinel-1 sun’iy yo‘ldoshi VV polarizatsiya kanali yordamida kemalarni aniqlash va kuzatish mumkin!
🔍 Qanday ishlaydi?
✅ SAR (Synthetic Aperture Radar) tungi va bulutli ob-havoda ham ishlaydi.
✅ VV band suv yuzasidagi harakatlanuvchi obyektlarni (kemalar, qayiq va platformalar) aniq ajratadi.
✅ AI va GIS yordamida kemalarning marshrutini kuzatish mumkin.
🌍 Foydali jihatlar:
📡 Dengiz xavfsizligi – noqonuniy kemalarni aniqlash.
🚢 Port va yuk tashish monitoringi – kemalar harakatini nazorat qilish.
🛑 Atrof-muhit muhofazasi – neft to‘kilishlari va noqonuniy baliq ovlashni kuzatish.
Masofaviy zondlash dengiz transporti va xavfsizligini yangi darajaga olib chiqmoqda! Sizning fikringiz qanday? 🌊🌍
📲RemoteSensing_Innovators
✍️@Davlatov_9959
#GIS #RemoteSensing #SAR1 #Sentinel1 #ShipDetection #DengizXavfsizligi
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📌 Dust Storm Analysis over Uzbekistan (May–June 2023)
🌪 A comprehensive dust storm analysis was carried out using Aerosol Optical Depth (AOD), 🌡 Land Surface Temperature (LST), and 🌧 Rainfall indicators. The analysis covers May–June 2023 and was conducted entirely through Google Earth Engine (GEE).
🛰 The project leverages MODIS and CHIRPS satellite datasets for large-scale, cloud-based geospatial processing.
🔍 Key Findings:
🔴 AOD > 0.3 indicates areas highly affected by aerosols, i.e., potential dust storm zones (visualized in red and purple).
🔥 Regions with elevated land surface temperature suggest dry and heat-prone conditions.
☔️ Rainfall distribution adds additional insight into local climate impacts during the dust events.
📍 Study Region: Uzbekistan
🌪 A comprehensive dust storm analysis was carried out using Aerosol Optical Depth (AOD), 🌡 Land Surface Temperature (LST), and 🌧 Rainfall indicators. The analysis covers May–June 2023 and was conducted entirely through Google Earth Engine (GEE).
🛰 The project leverages MODIS and CHIRPS satellite datasets for large-scale, cloud-based geospatial processing.
🔍 Key Findings:
🔴 AOD > 0.3 indicates areas highly affected by aerosols, i.e., potential dust storm zones (visualized in red and purple).
🔥 Regions with elevated land surface temperature suggest dry and heat-prone conditions.
☔️ Rainfall distribution adds additional insight into local climate impacts during the dust events.
📍 Study Region: Uzbekistan
👨💻 Author: Abdullajon Davlatov
🗺 Web Map
📲@RemoteSensing_Innovators
📄 Report
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📌 O‘zbekistonda chang bo‘ronlarini tahlil qilish (2023-yil May–Iyun)
🌪 2023-yilning may–iyun oylarida O‘zbekiston hududida yuz bergan chang bo‘ronlari holati Aerosol Optical Depth (AOD), 🌡 Yer yuzasi harorati (LST) va 🌧 yog‘ingarchilik ko‘rsatkichlari asosida tahlil qilindi. Ushbu tahlil to‘liq Google Earth Engine (GEE) platformasi orqali amalga oshirildi.
🛰 Loyihada MODIS va CHIRPS sun’iy yo‘ldosh ma’lumotlari asosida katta hududlarni bulutli hisoblash imkoniyati bilan geotahlil qilindi.
🔍 Asosiy natijalar:
🔴 AOD > 0.3 bo‘lgan joylar aerozollar bilan kuchli ifloslangan bo‘lib, bu chang bo‘roni xavfini bildiradi (qizil va binafsha ranglar bilan ifodalangan).
🔥 Yuqori yer harorati kuzatilgan hududlar qurg‘oqchil va issiqlikka moyil ekani ko‘rsatildi.
☔️ Yog‘ingarchilik tarqalishi esa chang hodisalarining mahalliy iqlimga ta’sirini chuqurroq tushunishga yordam beradi.
📍 Tadqiqot hududi: O‘zbekiston
🌪 2023-yilning may–iyun oylarida O‘zbekiston hududida yuz bergan chang bo‘ronlari holati Aerosol Optical Depth (AOD), 🌡 Yer yuzasi harorati (LST) va 🌧 yog‘ingarchilik ko‘rsatkichlari asosida tahlil qilindi. Ushbu tahlil to‘liq Google Earth Engine (GEE) platformasi orqali amalga oshirildi.
🛰 Loyihada MODIS va CHIRPS sun’iy yo‘ldosh ma’lumotlari asosida katta hududlarni bulutli hisoblash imkoniyati bilan geotahlil qilindi.
🔍 Asosiy natijalar:
🔴 AOD > 0.3 bo‘lgan joylar aerozollar bilan kuchli ifloslangan bo‘lib, bu chang bo‘roni xavfini bildiradi (qizil va binafsha ranglar bilan ifodalangan).
🔥 Yuqori yer harorati kuzatilgan hududlar qurg‘oqchil va issiqlikka moyil ekani ko‘rsatildi.
☔️ Yog‘ingarchilik tarqalishi esa chang hodisalarining mahalliy iqlimga ta’sirini chuqurroq tushunishga yordam beradi.
📍 Tadqiqot hududi: O‘zbekiston
📄Voqea haqida
👨💻 Muallif: Abdullajon Davlatov
🗺 Veb-xarita
📲 @RemoteSensing_Innovators
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