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GIS Data Analyst | Leveraging Spatial Insights for Informed Decision-MakingSummary: Diligent GIS Data Analyst with a passion for transforming geospatial data into actionable insights. Proficient in analyzing and interpreting spatial information, I specialize in utilizing advanced GIS tools to support strategic decision-making. Skilled in data visualization, spatial modeling, and geographical analysis, I am committed to delivering accurate and valuable insights. Let's connect to explore opportunities at the intersection of geography and data analysis.#GIS #DataAnalyst #SpatialAnalysis #GeospatialData #DecisionMaking #DataVisualization #LinkedIn(

Hi, Hope you are doing great. This side Anurag Pathak from iBridge Tech Soft I have some urgent requirements with one of my clients. If you are interested, share with me your resume. Role : GIS Analyst Location : Austin Tx Contract Role  A GIS (Geographic Information System) Analyst is a professional who collects, analyzes, and interprets geospatial data to help organizations make informed decisions. Their primary responsibilities include:   1. Data collection and management: Gathering and integrating geospatial data from various sources. 2. Mapping and visualization: Creating maps, 3D models, and other visualizations to communicate findings. 3. Spatial analysis: Applying techniques like spatial statistics, network analysis, and terrain analysis to identify patterns and trends. 4. Data modeling: Designing and implementing geodatabases to store and manage large datasets. 5. Project management: Collaborating with stakeholders to understand project requirements and deliver results. 6. Staying up-to-date with industry trends and emerging technologies like AI, machine learning, and cloud computing.   GIS Analysts work in various industries, including:   1. Urban planning and development 2. Environmental management and conservation 3. Emergency response and disaster management 4. Transportation and logistics 5. Natural resources management 6. Epidemiology and public health   Thanks and Regards,   Anurag Pathak Technical Recruiter iBridge Techsoft Pvt.Ltd 📞+1 9045871229 📧anuragpathak@ibridgetechsoft.com #gis #map #arcgis #mapping #maps #cartography #geospatial #qgis #remotesensing #geography #esri #sig #gps #survey #a #topography #geografia #surveyor #mapas #surveying #drone #d #geomatics #geoprocessamento #folgore #geoinformatics #cartografia #carabinieri #uav #goi #geographicinformationsystems #gis #map #gps #emprendeecuador #geography #maps #mapping #geospatial #arcgis #geolocation #sig #remotesensing #instagram #emprendeec #georreferenciamento #geolocalizacion #instagramforbusiness #shareblackstories #howto #tutorial #neop #geographicalinformationsystem #whatsapp #emprendedoresecuador #indonesia #geographicinformation #urbanplanning #harita #geospatialtechnology Anish Kumar Singh

Q&A: Good Governance in Minnesota Starts with Geospatial Data In this interview conducted by Pat Cummens, Minnesota’s chief geospatial information officer Alison Slaats discusses the state’s innovative approaches to visualize and analyze data with GIS, and make data more accessible. https://lnkd.in/gE4EQWMk

🌟 Excited to Bring My GIS and Remote Sensing Expertise to a New Opportunity! 🌟 As a passionate GIS Specialist and Remote Sensing Analyst, I've had the privilege of transforming complex geospatial data into actionable insights. My journey includes: 🌍 Mastering remote sensing image processing and GIS for environmental management 🖥️ Proficiency in Python, R, and MATLAB for data analysis and striking visualizations 📊 Managing and interpreting geospatial data for natural resource mapping I thrive on making technical information accessible and engaging for stakeholders, and I love collaborating with interdisciplinary teams to solve real-world problems. 🎯 I'm currently exploring new roles that will allow me to leverage my expertise in remote sensing, GIS, and data management to make meaningful contributions to innovative projects. If you know of any opportunities or connections that could benefit from my skills and enthusiasm, please feel free to share, tag them below, or reach out directly! Let's create something impactful together! 🚀 #GIS #RemoteSensing #JobSearch #Geospatial #EnvironmentalManagement #DataAnalysis

New blog post alert 🚨Head over to EasierData 👉 https://lnkd.in/eq_iHKXS and check out the initiative’s recently published posts to stay in the loop of Web3 & GIS exploration!

For anyone interested in the intersection of decentralized systems and geo-spatial data, check out the latest entries from my colleagues and me! Tiered storage systems using LRU cache for decentralized content retrieval 👉 https://lnkd.in/ePXUbDEy Explore a POC using geohash spatial indexing to query content from IPFS 👉 https://lnkd.in/ecA6WQ4z Get a first look at our Web3 Geospatial Dashboard (https://lnkd.in/eKXZWn5x) and dive into the details of our implementation 👉 https://lnkd.in/e6N9_uRX Learn about the practical advantages of organizing, managing and dissemination of large geospatial sets in decentralized systems using Content Addressable aRchives (CAR) 👉 https://lnkd.in/eDsciPdq

Mastering Spatial Queries Spatial queries are essential for geographic data analysis. These queries allow you to retrieve and manipulate data like points, lines, and polygons. Commonly used in GIS, mapping, and location-based services, spatial queries help analyze geospatial data efficiently. 1. Finding Nearby Locations (ST_DWithin) ST_DWithin retrieves locations within a specific distance from a point. SELECT location_name FROM locations WHERE ST_DWithin(geom, ST_MakePoint(106.84513, -6.21462), 1000); This query finds locations within 1 km of (106.84513, -6.21462). 2. Finding Locations Inside an Area (ST_Within) ST_Within identifies geometries inside a boundary. SELECT location_name FROM locations WHERE ST_Within(geom, ST_GeomFromText('POLYGON((...))')); This query retrieves all locations inside a polygon, useful for zoning analysis. 3. Identifying Intersecting Geometries (ST_Intersects) ST_Intersects finds geometries that intersect with a line or area. SELECT street_name FROM streets WHERE ST_Intersects(geom, ST_MakeLine(ST_MakePoint(106.84513, -6.21462), ST_MakePoint(106.85000, -6.22000))); This query identifies streets that intersect a line. 4. Calculating Area (ST_Area) ST_Area calculates the area of a polygon. SELECT area_name, ST_Area(geom) AS area_size FROM areas; This query calculates the area of each polygon, useful for land management. 5. Finding Adjacent Geometries (ST_Touches) ST_Touches identifies geometries sharing a boundary. SELECT location_name FROM locations WHERE ST_Touches(geom, ST_GeomFromText('POLYGON((...))')); This query retrieves locations that touch a polygon's boundary. 6. Finding Centroids (ST_Centroid) ST_Centroid finds the center of a polygon. SELECT ST_Centroid(geom) FROM areas WHERE area_name = 'National Park'; This query returns the centroid of 'National Park,' useful for mapping. 7. Creating Buffers (ST_Buffer) ST_Buffer creates a buffer around a geometry. SELECT ST_Buffer(geom, 500) FROM locations WHERE location_name = 'Monas'; This query creates a 500-meter buffer around 'Monas.' 8. Measuring Distance (ST_Distance) ST_Distance calculates the shortest distance between two points. SELECT ST_Distance( ST_MakePoint(106.84513, -6.21462), ST_MakePoint(107.6114, -6.9345) ) AS distance; This query calculates the distance between two points, useful for logistics. 9. Finding Overlapping Geometries (ST_Overlaps) ST_Overlaps identifies geometries that partially overlap. SELECT area_name FROM areas WHERE ST_Overlaps(geom, ST_GeomFromText('POLYGON((...))')); This query finds areas overlapping a polygon. 10. Transforming Coordinate Systems (ST_Transform) ST_Transform changes the spatial reference system of a geometry. SELECT ST_Transform(geom, 4326) FROM locations WHERE id = 1; This query transforms geometry to SRID 4326 (WGS 84), the GPS standard.

Location Analytics are HIGHLY relevant to data scientists. Since most data is location – related, they can significantly leverage geospatial, technologies and practices to gain significant uplift on their models, discover previously ignored trends and patterns, and communicate results more effectively with stakeholders.

The dynamic fusion of Data Science, GIS Innovation, and Location Data defines a new era in evidence-based, climate-resilient urban planning.