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    Moving Beyond the Geospatial Machine Learning Hype

    ckamusoko
    By ckamusoko,
    Land cover classification remains challenging. However, more very high-resolution images are available to create quality reference data. In addition, efforts to improve transparency and accountability in the machine learning model are becoming an important research topic. I have published a book on ‘Data-centric Explainable Machine Learning for Land Cover Classification: A Practical Guide in R.’ The book is for those interested in improving land cover classification using a data-centric explaina

    Tonga volcano eruption triggers tsunami warnings in Japan, Pacific islands

    Lurker
    By Lurker,
    An underwater volcano off Tonga erupted on Saturday, triggering tsunami warnings and evacuation orders in Japan and causing large waves in several South Pacific islands, where footage on social media showed waves crashing into coastal homes. Japan's meteorological agency issued tsunami warnings in the early hours on Sunday and said waves as high as three metres (9.84 feet) were expected in the Amami islands in the south. Waves of more than a metre were recorded there earlier.   Pub

    retrieve coastline map wrapped onto 3d globe

    ggml
    By ggml,
    Hi. What is a basic method to export worldmap layers such as coastlines, but wrapped on a 3d globe, for further use with computer graphics tools ?

    A Deadly Day on Mount Semeru

    Lurker
    By Lurker,
    Mount Semeru, the tallest and most active volcano on the Indonesian island of Java, has routinely spit up small, mostly harmless plumes of ash and gas for years. The circumstances changed on December 4, 2021. Following a partial collapse of the summit lava dome early in December, sensors began to detect elevated seismic activity, according to the Volcanological Survey of Indonesia (PVMBG). After more of Semeru’s lava dome gave way, billowing fronts of superheated ash, tephra, soil, and othe

    Help to host an ArcGIS StoryMap

    windu
    By windu,
    Dear GIS users/colleagues, I have been learning how to use GIS and more specifically ArcGIS for more than a year (online course). I was able to build in my free time a portfolio of maps on topics which interest me or are related to my area of expertise. I displayed most of them in a StoryMap online, which I intend to use as my online portfolio to showcase my work to potential future employers. The only issue is that, my ArcGIS licence is expiring soon (end December/early Jan). I contac

Portal by DevFuse · Based on IP.Board Portal by IPS
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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?
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