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How GIS is Revolutionizing the Real Estate Industry
By IRES,
Introduction
The real estate industry encompasses a broad range of activities related to the buying, selling, renting, and development of properties. This may include land, residential, commercial, and industrial buildings. It is therefore a significant industry that plays a crucial role in both the economy and society.
It comprises key stakeholders like real estate developers, agents, brokers, investors, property managers, and construction companies, all working together to meet the divers
Leica Geosystems unveils Leica TerrainMapper-3
By Lurker,
Leica Geosystems, part of Hexagon, introduces the Leica TerrainMapper-3 airborne LiDAR sensor, featuring new scan pattern configurability to support the widest variety of applications and requirements in a single system.
Building upon Leica Geosystems’ legacy of LiDAR efficiency, the TerrainMapper-3 provides three scan patterns for superior productivity and to customise the sensor’s performance to specific applications. Circle scan patterns enhance 3D modelling of urban areas or steep terr
How Upskilling in GIS Aids Educational Policy Research
By IRES,
How Upskilling in GIS Aids Educational Policy Research
Understanding the distribution of student demographics is crucial for making informed decisions. This is where Geographic Information Systems (GIS) and remote sensing technologies play a vital role. By upskilling in GIS, researchers can harness the power of spatial analysis and mapping to gain valuable insights into student populations and educational disparities.
GIS is a powerful tool that allows researchers to visualize, analyze
The role of ExtSpecR in streamlining UAV-based tree phenomics and spectral analysis
By EmperoR,
Due to their ability to collect tree phenotypic trait data in large quantities, unmanned aerial vehicles, or UAVs, have completely changed the forestry industry. Even with the progress made in object detection and remote sensing, precise identification and extraction of spectral data for individual trees continue to be major obstacles, frequently necessitating tedious manual annotation.
For better tree detection, current research focuses on developing segmentation algorithms and convolution
OpenLayers 9.0.0 Released
By Lurker,
The 9.0 release add several new features, including a Google Maps source (finally!), improved WebGL line rendering, and a new symbol and text decluttering implementation. We also improved and broadened flat styles support for both WebGL and Canvas 2D renderers. For better developer experience, we made more types generic and fixed some issues with types.
Backwards incompatible changes
Improved render order of decluttered items
Decluttered items in Vector and VectorTile layers now maintai
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Hello folks! I am trying to use the Lyzenga Algorithm for estimating the depth of water in shallower areas, probably depths under 8-10 meters of lakes. First of all, how accurate is this algorithm in practice? Secondly, lets say i have the band values. can someone explain me how to retrieve those depths? I am following the "Lyzenga Algorithm for Shallow Water Mapping Using Multispectral Sentinel-2 Imageries in Gili Noko Waters" paper, but there are 3 steps of getting NDWIs, NDCIs and after filtering the Sun Glint Correction, then it finally comes to the depth calculating. it end ups in a formula of following: 𝑧 = 28.32 ∗ 𝑋1 − 36.25 ∗ 𝑋2 + 9.42 ∗ 𝑋3 + 16.35 x1 , x2, x3 are RGB values respectively. What do you guys think? can i just apply this formula ? if not, what is the purpose of all the previous steps, and will they change the rgb values anyways? -
Hello folks! I am trying to use the Lyzenga Algorithm for estimating the depth of water in shallower areas, probably depths under 8-10 meters of lakes. First of all, how accurate is this algorithm in practice? Secondly, lets say i have the band values. can someone explain me how to retrieve those depths? I am following the "Lyzenga Algorithm for Shallow Water Mapping Using Multispectral Sentinel-2 Imageries in Gili Noko Waters" paper, but there are 3 steps of getting NDWIs, NDCIs and after filtering the Sun Glint Correction, then it finally comes to the depth calculating. it end ups in a formula of following: 𝑧 = 28.32 ∗ 𝑋1 − 36.25 ∗ 𝑋2 + 9.42 ∗ 𝑋3 + 16.35 x1 , x2, x3 are RGB values respectively. What do you guys think? can i just apply this formula ? if not, what is the purpose of all the previous steps, and will they change the rgb values anyways?
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