🗺️Unlock the power of precision with Zone Mapping! By using data like soil type, elevation, and satellite imagery, GCC helps growers manage field variability and maximize input efficiency across every acre. For the Full Article Click Here: https://lnkd.in/gN48dncD #ZoneMapping #AgTech #GCC #MovingForwardTogether
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Geospatial intelligence may be able to help farmers make data-driven decisions by quickly analyzing large amounts of spatial or location data (i.e., yield data, soil types, growth patterns, etc). #GeospatialIntelligence #SmartFarming #agtech #aiimage
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Today, we’re celebrating the game-changing technology that helps industries make smarter decisions—Geographic Information Systems (GIS). From precision agriculture to urban planning, GIS powers the insights that drive progress. Ready to learn how GIS transforms reality data capture? Check out our latest blog and discover how it’s shaping industries worldwide! https://hubs.la/Q02YYqs10 #NationwideDataCapture #FlyGuys #GISDay #GeographicInformationSystems
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How can geospatial analytics help your business? From monitoring crop health to accurately predicting insights for land assessment, the potential is enormous. Grow with Redleaf Technologies now. Contact us to explore more. #geospatial #data
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The variations of different resolution of satellite Imagery have higher impact in the estimation of crop type. Preparation of these type of samples would contribute a lot in the process mapping different crop types.
🌍🚀 How Does Satellite Imagery Resolution Impact Field Boundary Detection? 🛰️📊 Satellite imagery resolution plays a critical role in accurately detecting and mapping field boundaries. Here's a quick overview based on our recent finding based on a sample field boundary: 1. World Imagery Base Map - Resolution: 30cm - Impact: Provides the most precise boundary detection, with an area measurement of 1660.83m². Ideal for detailed mapping and small-scale agricultural management. 2. Sentinel-2 L2A - Resolution: 10m - Impact: Less precise with an area measurement of 3356.4m². Suitable for larger-scale monitoring but may miss finer details. 3. SkySat - Resolution: 50cm - Impact: Good balance of detail and coverage with an area measurement of 1671.64m². Effective for moderate detail requirements. 4. VENµS - Resolution: 5m - Impact: Provides intermediate detail with an area measurement of 2451.37m². Useful for medium-scale agricultural analysis. Higher resolution imagery, like that from the World Imagery Base Map and SkySat, offers more precise boundary detection, crucial for accurate field management and planning. Lower resolutions, such as those from Sentinel-2 L2A and VENµS, provide broader coverage but may compromise on detail, impacting precision in smaller fields. Understanding these differences helps in selecting the right satellite imagery for specific agricultural needs, optimizing both precision and efficiency in field boundary detection. 🌾📐 📄 View the detailed slide here:https://lnkd.in/duUgjcGe #SatelliteImagery #PrecisionAgriculture #FieldBoundaryDetection #Agriculture #Research #Sustainability #Innovation #CIMMYT
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✨ Feature Spotlight: The Comparison Tool! ✨ Have you tried the Comparison Tool in CropX yet? This powerful feature lets you easily compare data from various sources, like satellite imagery, machinery, and elevation maps, across different points in time. 🚜🌍 In the video below, we show how you can effortlessly compare an elevation map with an NDVI satellite image. 📊🌟 This helps you uncover how high and low areas impact your crop's growth patterns. Start exploring the insights hidden in your fields today! 🌱 www.cropx.com #PrecisionFarming #CropX #DataDrivenFarming
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🌍✨ Talk about a game-changer in geospatial analysis! Whether it's for disaster management, urban planning, or agriculture, SpatioSynth brings the power of advanced object detection straight to your fingertips. Get ready to see geospatial data like never before! 📊🌐 #innovation #SpatioSynth #Data #technology #artificialintelligence
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Comparing Top Satellite Image Providers: What to Consider for Your Needs Top 9 Factors to Compare Satellite Image Providers: 1. Resolution 2. Coverage Area 3. Frequency of Updates 4. Data Accessibility 5. Cost 6. Customer Support 7. Data Security & more 📕✔Read More: https://lnkd.in/dGM5mixU #SatelliteImagery #RemoteSensing #Geospatial #DataAnalysis #ImageResolution #Agriculture #DisasterManagement #GIS #DataSecurity #CustomSolutions #TechTrends #SatelliteProviders #Innovation
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We’ve just released the 2018 vector layer of the #CLCplus Backbone! This dataset is part of the CLCplus product suite, designed to complement the popular CORINE Land Cover product and provide high-resolution land cover information. 🗺️ What makes this vector dataset special? ✔️ Unique geometries: Features polygons that reflect aggregated landscape objects ✔️ Expanded classification: Includes 18 land cover classes for more detailed insights ✔️ Enhanced details: Integrates data from other datasets, such as proportion of impervious surfaces and details about slopes and elevation 🔗 Learn more: https://lnkd.in/dnKRP-Cj #CLMS #LandCover
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Can AGMRI be used to forecast my yield? Yes, you can use AGMRI to understand where your crop yield is based on the current state of the crop. As the season unfolds, see how it is impacting your final yield. How does it work? The model uses a machine learning approach that correlates the data listed below to yield outcomes to make predictions on fields. - Weather Information - Topography and Soil Types - Planter Information, if provided; All machine data may be used - Imagery Data and Analytics Along with the yield predictions will come a pixel-level map for each field - bushels per acre legend shows yield values across a field Yield Forecasting begins at 735 GDD, which is V7 to V8, and will make a prediction on each capture until harvest Learn more: https://lnkd.in/gP2zPdAz
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GIS & Remote Sensing Enthusiast | Environmental & Geographical Analysis | Passionate About Climate Action & Disaster Management | Event & Volunteer Management | Geography & Environmental Studies Student
Using the Google Earth Engine to monitor vegetation health and water resources, I filtered Sentinel-2 imagery to analyze the NDVI (Normalized Difference Vegetation Index) for the Rajshahi district. This analysis helps to understand vegetation conditions and monitor environmental changes. Key steps: 1️⃣ Filtered the region of interest to Rajshahi using administrative boundaries. 2️⃣ Selected cloud-free Sentinel-2 imagery for 2021 to ensure high-quality data. 3️⃣ Calculated NDVI and MNDWI indices to visualize vegetation health and water bodies. 4️⃣ Visualized the results with color-coded maps for better interpretation. Check out my code here: https://lnkd.in/gRAX-Vdt
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