Manasa Tallapaka的动态

AI and ML are not just tools; they're game-changers. At SVK Systems Information Technology, we leverage these technologies to push the boundaries of GIS, creating smarter, faster, and more intuitive solutions #AIandML #GISinnovation #SpatialAnalytics #DataProcessing #ImageRecognition #PredictiveModeling #AssetManagement #AutomatedMapping #GeoAwareness #FutureofGIS #TechTrends #DataPrivacy #GISCareerAdvice #GIS #arcgis #AgTech #SVKSystems

Today, on World GIS Day, we celebrate the transformative power of Geographic Information Systems (GIS)?in shaping the world around us. At Altz Technologies, we’re proud to be at the forefront of leveraging advanced GIS technologies?to drive innovation across industries. Here’s to the future of geospatial innovation! #WorldGISDay #AltzTech #GIS #Innovation #AI #Digitaltwin #MakeInIndia #Geospatial #TechnologyForGood #DataVisualization

A moment to appreciate the transformative power of Geographic Information Systems (GIS). GIS has revolutionized the way we understand and interact with spatial data. The integration of #GIS with data science, particularly #machinelearning and #AI, has further expanded its potential. These technologies enhance the capabilities of spatial analysis, enabling us to more efficiently process and interpret complex datasets. From predictive modelling in #flood and #drought hazards mapping to real-time urban planning and precision agriculture. This synergy delivers deeper insights across diverse fields. The advancements of uncovering hidden trends and patterns in geospatial data using machine learning models and AI help address pressing global challenges like climate change and disaster resilience. Again, today, we celebrate #GISDay. We recognize GIS vital role in mapping our world and shaping a sustainable and smarter future. #GISDAY #mappingourminds #mappingourworld #shapingabetterfuture

????????-???????????????? ?????????? ???????????? ???? ???????????? ?????? ?? It is interesting to watch the evolution of ArcGIS Pro as more artificial intelligence is added to the tool. A new update improves image analysis. This is particularly good news for those studying climate change, since it improves the integration of advanced AI models for climate and environmental analysis. ?????????????????? ???? ???????????????????? ??.??: These advancements are highly relevant to Geospatial 2.0 since they emphasize combining AI and geospatial technologies. By simplifying complex analyses and integrating intelligent tools, this update helps unlock new applications for environmental monitoring, urban planning, and disaster management, accelerating geospatial innovation. Credit to ABDULLAH ALYAMANI for the original animation imagery. How do you see this shaping climate change analysis? ?? ???????? ???? ???? ???????? ???????? ?????? ???????????? ???????????????????? ??.?? ???????? ?????? ???????????????????? ??.?? ??????????????????: https://lnkd.in/gvfayQs3 #geospatial #geospatial2point0 #gis Esri #arcgis #climatechange Pavan Yadav

Transforming mapping and transportation with road surface data HeiGIT has created a global road surface classification dataset. This dataset is powered by deep learning technology and enriched with data from Mapillary. It aims to address challenges related to: ? ??? Transportation Safety: Better routing for emergency vehicles like ambulances and fire trucks. ?? Logistics Optimization: Reduced delays and costs in supply chains and agriculture. ?? Mapping Enhancements: Improved data for OpenStreetMap and GPS systems, especially in rural and underdeveloped regions. ? Key Highlights: ? Achieved 98.5% accuracy using the SWIN-Transformer model. ? Crowdsourced data from 39 countries, improving global representation. ? Openly available dataset to support urban planning, humanitarian response, and economic development. ? ?? Learn more about this project and its impact for geospatial world. ? ?? Read the full article on Geoawesome: https://lnkd.in/efS-3wfX ? #Geospatial #DeepLearning #Transportation #Innovation #Mapping #OpenData #Geoawesome

GeoAI is offering a fresh perspective and vision for geospatial solutions in today’s world. GeoAI is set to revolutionize multiple sectors: ???Urban Planning: Integrating AI, geospatial data, and sustainable practices is becoming essential for creating smart, resilient cities. ?? Environmental Monitoring: GeoAI is driving innovation in tracking and addressing environmental challenges, contributing to a more sustainable future. ?? Human Geography: The increasing use of GeoAI in human geography studies is opening new avenues for research and a deeper understanding of societal patterns. As GeoAI continues to evolve, it promises to deliver new insights in geospatial analysis, streamline workflows, and provide innovative solutions to complex spatial problems. The integration of AI and geographic information systems will lead to more efficient and innovative outcomes. #GeoAI #UrbanPlanning #Sustainability #EnvironmentalMonitoring #GIS #AI

The Segment Anything Model (SAM) and Its Impact on Geospatial Analysis The Segment Anything Model (SAM), introduced by Meta AI, represents a groundbreaking advancement in geospatial technology. By providing precise and flexible segmentation across a variety of datasets, SAM has revolutionized workflows in GeoAI, tackling challenges like object detection, land classification, and temporal change analysis. This innovative tool has enhanced the efficiency of extracting essential spatial features, reduced reliance on labor-intensive processes, and paved the way for more accurate analysis of complex geospatial phenomena. How SAM Enhances GeoAI Applications 1. Object Detection in Remote Sensing Technical Aspect: Identifying features such as roads, buildings, and water bodies in aerial or satellite imagery. SAM's Contribution: Facilitates instant segmentation of these features from high-resolution geospatial data, drastically reducing the time required for manual annotations. 2. Land Cover Classification (LCC) Objective: Classify regions into categories such as forests, urban areas, wetlands, and farmlands. SAM's Contribution: Streamlines the segmentation of varied land cover types by leveraging its pretrained algorithms, even in challenging geographies. 3. Change Detection Objective: Monitor changes in land use, deforestation, or urban development over time. SAM's Contribution: Enables automated change detection by accurately segmenting objects in sequential imagery datasets. 4. Spatiotemporal Analysis Objective: Examine dynamic events like glacier movement or flooding patterns. SAM's Contribution: Delivers precise segmentation in time-series imagery, allowing for deeper insights into spatial and temporal trends. 5. Automated Map Updates Objective: Maintain updated geospatial datasets using the latest satellite imagery. SAM's Contribution: Extracts features like new roads and buildings, ensuring maps remain accurate and current. Follow: Gensre Engineering & Research #GeoAI #ArtificialIntelligence #MachineLearning #SegmentAnythingModel #RemoteSensing #GeospatialAnalysis #GIS #Automation #InnovationInAI #LandCoverMapping #ChangeDetection Software: Esri ArcGIS Pro Video Credit: Esri Canada

?? "Traditionally, analysing satellite or aerial imagery involved painstaking manual processes [...] with the advent of AI-powered automated image recognition, this laborious task has been transformed into a swift and accurate process." - this is told by Dean Howell in the article below. ?? This AI processing has applications across multiple industries: urban planning and infrastructure development, environmental monitoring and conservation, disaster response and management, and agriculture and land management, are just a few to exemplify. ?? Both satellite imagery or drone missions photogrammetry are good options and at Digital Twins we have just the right option for you. ?? All drone flights for Digital Twins are performed by a certified pilot, so we always minimize risk for people, constructions, and vehicles. Safety first! #AI #imageprocessing #remotesensing #dronepilot #photogrammetry #digitaltwins #4Dplus #3Dmapping

Geocoding is an essential geospatial function underpinning a variety of analytics applications, from property risk assessment to network planning to emergency response and more. The most precise geocoders pinpoint address locations using rooftops or building footprints, which are a more accurate representation of where a structure is located than traditional street or parcel centroid geocoding. Ecopia’s AI-based mapping systems produce the first and only complete map of US buildings, laying the foundation of our best-in-class geocoder. ??Learn more about Ecopia AI’s Building-Based Geocoding here: https://lnkd.in/ghgAYxiT #Geocoding #BuildingFootprints #AI #GIS #Geospatial

Machine Learning is revolutionizing how we understand the world through GIS, pushing it far beyond traditional mapping. Forget static maps—now, it’s about real-time intelligence. ML-powered GIS doesn't just show what’s happening; it predicts, analyzes, and uncovers insights that traditional methods never could. With up to 90% more accuracy, the fusion of ML and GIS is opening up endless possibilities for smarter, data-driven decisions. Are you ready to harness its full potential and stay ahead of the curve? #GIS #geospatial #MachineLearning #GeospatialIntelligence #DataDrivenDecisions #FutureOfTech #Innovation #SmartMapping #scstech #scstechindia