Gensre Engineering & Research

?? ??????????'?? ???????????????? ??????????????: ?? ???????????? ???? ?????????????????????? ???????????? (2014 - 2024) Over the past decade, Kenya has experienced shifting temperature patterns, reflecting broader climate dynamics. To visualize these changes, I created a monthly time-lapse showcasing #Kenya’s #temperature variations from 2014 to 2024, using data from the #ClimateDataStore, the #KrigR library in #R, and #ECMWF reanalysis data. Thanks to Milos Popovic, PhD for another insightful tutorial. What this visualization reveals: ? Seasonal temperature trends over the years. ? Increasing temperature variability across different regions. ? A clear shift in temperature anomalies for 2024, highlighting warming patterns. To better understand these changes, I also generated a temperature anomaly map for 2024, comparing current temperatures to the past 10 years. Temperature anomalies can significantly impact #agriculture, water resources, and #biodiversity, making #climate resilience a key priority for #policymakers and researchers. Data-driven insights like these can help shape sustainable climate action plans for Kenya and beyond. #ClimateChange #GeospatialAnalysis #Kenya #RStats #ECMWF #Sustainability #GIS #ClimateAction

?????????????????? ???????????????????? ?????????????? ???? 3??: ???? ?????????????????????? ?????? ?????? Understanding population distribution is crucial for urban planning, resource allocation, and climate action. Leveraging open data from the #Kontur Population Dataset for the year 2023, the 3D interactive web map that visualizes #populationdensity across #Kenya in a more immersive way. Why a #3D Web Map? A 3D interactive map provides a richer perspective by representing population density as elevation. This means: ? High-density areas appear as tall spikes ? Sparse regions remain low ? Users can explore and interact with the data dynamically Tech Stack To bring this map to life, I used: ?? #deck.gl: for rendering the 3D polygons ?? sf package: for spatial data handling ?? #R & JavaScript: for data processing and visualization ?? #CARTO maps: for base-map styling How It Works: ?? The map uses quantile-based color scaling to visually differentiate population densities. ?? Each polygon’s elevation is proportional to the number of people living there. ?? Users can hover over areas to see population density values in real-time. Interact with the Map! ?? Live Map: https://lnkd.in/dsD8YeyB follow us at Gensre Engineering & Research for more key insights!! #GIS #Mapping #DataVisualization #3DMapping #PopulationDensity #OpenData #SpatialAnalysis #R

?????????????????? ?????????? ???????????????????? ???? 3??! I’m excited to share my latest project: 3D Building Height Maps for Nairobi, within 1 Kilometre of its focal point, created using #Google Open Buildings Temporal dataset, and visualized in #R with the power of #rgee and #rayshader. This project combines geospatial data analysis, 3D rendering, and R programming to bring the Nairobi urban landscape to life(#Art). From extracting building footprints to visualizing heights in stunning detail. A big shout out to Milos Popovic, PhD, for the detailed tutorial. It is amazing how open data and open-source tools can transform raw data into actionable insights. ?? What’s in the map??? Data Source: Google Open Buildings Temporal dataset?? Tools: R (rgee for Earth Engine API, rayshader for 3D rendering)?? Output: Interactive 3D visualizations of building heights? ?? Why does this matter?? Understanding urban structures is key for city planning, disaster management, and even environmental studies. Tech Stack: #R | #rgee | #rayshader | #GoogleEarthEngine? #Geospatial #3DVisualization #R #UrbanPlanning, #OpenData #GoogleEarthEngine

?????????? ???????????? & ???????????? ?????????????? ???????????????????? ???????? ?????????? ???????? ?????????????????? ???????????????????? ?? _... ??. ???????????? ????????????: Provides the highest accuracy (±2-5 mm) but requires long observation times, often several hours. Best for precise geodetic control. ??. ?????????? ???????????? ????????????: Achieves ±1-5 cm accuracy with shorter observation times (5-20 minutes). Ideal for medium baselines up to 20 km. ??. ?????? ????????????: Delivers real-time accuracy of ±1-3 cm but is limited to short baselines (10-15 km). Requires a continuous data link. ??. ?????? (?????????????? ?????????? ??????????????????????): Offers global coverage with ±5-10 cm accuracy but requires long observation times and precise satellite data. ???????? ???? ?????? ?????????? ???????????? ????????????? ?? 1. ???????????????? ?????????????? ???????????????? – Establishing control points for engineering and mapping projects. 2. ?????????????????? ?????? ???????? ?????????????? – Precise boundary definition without lengthy observations. 3. ???????????????????????????? ???????????????? – Roads, bridges, and construction projects where accuracy is crucial. 4. ?????????????????????????? ?????? ?????????????????????? ?????????????? – Elevation and terrain analysis in remote areas. ?????????????????????? ???? ???????????????? ?? I. Requires Post-Processing – Unlike RTK, results are not available in real-time. II. Dependent on Satellite Geometry – Poor satellite visibility can reduce accuracy. III. Baseline Limitations – Less effective for baselines beyond 20 km. ????Share your perspective ???? ?? Follow: Gensre Engineering & Research #GNSS #Surveying #LandSurveying #Geodesy #Geomatics #Engineering #Mapping #GIS #RTK #PPP #PrecisionSurveying #TopographicMapping #GeospatialTechnology #GPS #RemoteSensing

?????????????????? ?????????????? ?????????????????? ?????????????? ???????????????? ???????? ????????! ?? ?????????????? ?? #?????????????????? ?????? ???? ??????????, ?????????????????????? ?????? ?????????????????????? ?????????????? #?????????????????????????? ?????? #?????????????????????? ???????? 1973 ???? 2023. ???????? ?????? ???????????????????? ????????????????????, ?????????????? ???????????????????????? ???? ?????? ?????? ?????????????????? ???? ?????????????????????????? #?????????????? ????????-???????????? ???????????????? ???????? ?????????? ?????? ?????????????? ?????? ???????????????? #???????????????????????????? ???? #??????????????????????, ?????????? ????????????????????, ?????? ???????????????? ?????????????? ????????????????????. #?????????????????????????? #?????????????????????????????????? #?????????? #?????? #???????????? #R

?????????????? ??????????'?? 2024 ???????? ?????????? ???????? ???????????? ?????????????? ?????????? ???? & ??3 ???????????????? ?????????????? ???? ?????????? ???? ???????????????????????? ?????????? ?????? ???? ?????????? ???????????????????????? ???????? ?????????? ?????? the year 2024. ?????????? #????????????’?? ?????????????? ?????????? ???? ???????? ?????? #??3 ????????????????, ?? ???????????????????? ?????? ?????????????? ???????????????????????? ???? ?????????? ???????????? ?????? ??????????????, ?????????????????? ???????????????? ???????? ???????????????????????? ???????????????? ?????? ???????? ??????. ???????? ?????????????? ???????????????? ???????????????????? ????????????????, ???????? ??????????????????????????, ?????? ???????????????????????????? ????????????????. ?????????????????? ???? ???????? ?? ??????: - ?????????????????? ?????????????? ?????????? ???? ?????? ????????-???????????????????? ???????? ?????????? ?????? ???????? ????????????????????????????. - ???????????????? ??3 ???????????????? (???????????????????? 6) ?????? ???????????????? ?????? ?????????????????? ?????????????? ????????????????. ?????? ?????????????? ?????? ???????? ?????????????????? ??????????’?? ???????????????????????? ???????????????????????? ?????? ???????? ?????????????????????? ?????? ???????????????????? ?????????? ?????? ?????????????? ?????????????????????? ???????? ???????????????????? ?????? ???????? ???????????????? ??????????????????????. (???????????????? ???? ???? ??????????????) #???????????????????????????????????? #???????????????????????????????????????? #???????????????????????????? #?????????????????????????????????? #?????????? #???????????????????????? #??3???????????????? #?????? #???????????????????????? #??

?? ?????????????????? ??????????'?? ???????? ?????????????? ?????????????????? #Soil texture plays a critical role in agriculture, water management, and ecosystem health. By mapping Kenya's soil texture classes, we can better understand the distribution of various sandy, loamy, and clay soils across the country. This insight is invaluable for #farmers, #researchers, and #policymakers working to improve #food security and #sustainable land use. This map was created using #OpenLandMapSoilTextureClass (USDA System) data, combined with #R plotting libraries to visualize the #spatial patterns of soil texture across Kenya. From the fertile loams of the highlands to the sandy soils of arid regions, each texture class tells a story about the land and its potential. Hope this resource contributes to more informed decisions in #agriculture and #environmental management. ?? #SoilScience #R #Agriculture #Kenya #Sustainability #Mapping #SoilMapping

?? Mapping Wildfire Impacts: A Look at the Palisades Fire. It is essential to comprehend and visualize the effects of natural disasters. We made an animation using #Google Earth Engine that used a split-pane display to highlight the #Palisades Fire's effect: ?? Left Panel: A baseline of the landscape based on pre-fire #COPERNICUS #Sentinel2 imagery. ?? Right Panel: A #NormalizedBurnRatio (NBR) and post-fire imagery are used to show the severity of the fires. ?? #NBR Analysis: A useful method for determining the severity of fire and vegetation health. This method highlights the value of #remotesensing technologies in monitoring and responding to #wildfire occurrences by providing visual comparison of the #spatial extent from #space. #RemoteSensing #GIS #Geospatial #ClimateMapping

?? Mapping Wildfire Impacts: A Look at the Palisades Fire. It is essential to comprehend and visualize the effects of natural disasters. We made an animation using #Google Earth Engine that used a split-pane display to highlight the #Palisades Fire's effect: ?? Left Panel: A baseline of the landscape based on pre-fire #COPERNICUS #Sentinel2 imagery. ?? Right Panel: A #NormalizedBurnRatio (NBR) and post-fire imagery are used to show the severity of the fires. ?? #NBR Analysis: A useful method for determining the severity of fire and vegetation health. This method highlights the value of #remotesensing technologies in monitoring and responding to #wildfire occurrences by providing visual comparison of the #spatial extent from #space. #RemoteSensing #GIS #Geospatial #ClimateMapping

?????????????????????????? ?????????????? ?????????????? ?? _... ? Dynamic heights provide a geopotential-based framework for measuring vertical positioning. This approach offers unparalleled precision, essential for addressing contemporary challenges in global water resource management, environmental monitoring, and geospatial applications. 1?? ?????? ???????????????????????? ???????????????????? ???? ?????????????? ?????????????? ??Dynamic heights, derived from the geopotential difference between a point and a reference equipotential surface (the geoid), remain invariant along an equipotential plane. This invariance distinguishes them from orthometric heights, which are susceptible to variations caused by gravitational anomalies. ? ?????????????? ?????????????? ?????? ???? ?????????????????? ???? ?????? ?????????? ???? ?????? ???????????????????????? ???????????????????? ?????????????? ?? ?????????? ?????? ?? ?????????????????? ?????????????? ???? ?????? ???????????????? ?????????????? ???? ???? ?????????????? ????????????????. 2?? ???? ?????????? ???????????????? ???????????????????? ??Dynamic heights enable a precise determination of ?????????????????? ????????, ensuring robust solutions for: i. Hydroelectric power generation. ii. Flood prediction and mitigation. iii. Coastal and inland navigation. ? Their integration into geoid-based datums like ???????? (????????) addresses longstanding issues, such as systematic errors in leveling, and adapts to vertical crustal motion, including glacial isostatic adjustments. 3?? ???????????? ?????????????????? ???? ???????????????? ???????????????????????? ??In a geoid-referenced framework, dynamic heights facilitate: i. Seamless ???????? ?????????????????????? ?????? ?????????????????????? ?????????????????????? ??????????????. ii. The ?????????????????????? ???? ?????????????????????? ?????????????? ?????????? ????????-???????????????? ?????????? ????????????. iii. ?????????????????????????????? ?????????????? ???????????????? ????????????, enhancing global interoperability. 4?? ???????????????? ?????????????? ?????????????? ?????????????????????? will standardize hydraulic head measurements, improve water management systems worldwide, and support sustainable development in vulnerable regions. Their global implementation demands multidisciplinary collaboration, leveraging advances in GNSS, geoid modeling, and dynamic geodetic solutions. ?????????? ???????? ?????????????????????? ???? ??Follow: Gensre Engineering & Research #DynamicHeights #Geodesy #GlobalGeospatialSolutions #WaterManagement #SustainableDevelopment #GIS #GNSSApplications #ClimateAdaptation ?? Image Credit : ----https://lnkd.in/dCsWZq_s