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<title>Yuxin Yang | Remote Sensing Sanyang Wetland</title>
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<p class=h1><strong>Y</strong>UXIN <strong>Y</strong>ANG</p>
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<ul><a href="project1.html" class=p--info>From Airport to HST Station: Bio Intermodality</a></ul>
<ul><a href="project2.html" class=p--info>Crosswind Data Center</a></ul>
<ul><a href="project3.html" class=p--info>Migration is Beautiful: Biophillic Boulevard</a></ul>
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<ul><a href="tech1.html" class=p--info>IoT Shoreline: Wave, Weave</a></ul>
<ul><a href="tech2.html" class=p--info>CityScope Module: Kendall Life-Work Crescendo</a></ul>
<ul><a href="tech3.html" class=p--info>Remote Sensing Sanyang Wetland</a></ul>
<ul><a href="tech4.html" class=p--info>Adaptive Rocking Lattice Stool</a></ul>
<ul><a href="tech5.html" class=p--info>Air-Pillow Attire for Haphephobia</a></ul>
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<p>Published on GitHub Page <br>© Yuxin Yang, Feb 2023</p>
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<p class=h2>Remote Sensing(RS) Sanyang Wetland</p>
<br>
<p class=p--caption> <strong>Info</strong> Yuxin Yang, Xi Cao, Qizheng Xie, Shifeng Zheng, 09/2017-11/2019, Academy<br>
My contributions include roadmap, RS image pre-processing, feature classification algorithms, and spatial density definition refinement
with the team<br>
<strong>Instructor</strong> Zhe Li, [email protected]<br>
<strong>Institution</strong> Southeast University, Nanjing, China<br>
<span class="hl"> National Fund Recipient of China’s Student Research Training Program (SRTP); Patented</span>
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<p class=p--info>This is a landscape element extraction and spatial density visualization flow
with ENVI, eCoginition, and Grasshopper.</p>
<br>
<p class=p--info><i>Spatial Density </i>is a concept that measures the level that landscape elements (terrain, vegetation, architecture etc.) dominates the absolute space, which reflects the livability of the environment. The research is based on granular element patches extracted from Remote Sensing images. With the refined spatial density index and R analysis correlation with vegetation index, NDVI, we propose a workflow of rapid visualization of environmental spatial density. Datasets for various environments, as wetland, mountain, plain, would yield different models of this rapid visualization.
This research takes Sanyang wetland environment as an example. The project explores:</p>
<p class=p--info>What are the <strong>REMOTE SENSING IMAGE POTENTIALS</strong> in unfolding the invisibility of the environment?
<br> How to define <strong>PERFORMANCE INDEX</strong> of a built environment?
<br>What is a potential <strong>visualization WORKFLOW</strong> for a remote sensing image?</p>
<p class=p--info>The landscape of Sanyang wetland features plain water network of rive and islands.
The buildings are crowded and disorganized, with the height of 2-3 stories. The vegetation is dominated by cash crops.
Orange 'ouguan' dominates, with a coverage of about 70%. Other cash crops include rape, cabbage, cabbage, etc., and some wasteland. There are often banyan, sequoia, camphor, weeping willow, cedar, sorrel, etc. around the building.
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<p class=h--img>Sanyang Wetland Spatial Density visualization</p><br>
<img src="./resources/images/1_Page_14.jpg" width="640" alt=""><br><br><br><br><br>
<p class=h--img>Workflow</p><br>
<img src="./resources/images/1_Page_15.jpg" height=640 alt=""><br>
<img src="./resources/images/1_Page_16.jpg" height=640 alt=""><br>
<img src="./resources/images/1_Page_17.jpg" height=640 alt=""><br>
<img src="./resources/images/1_Page_18.jpg" height=640 alt=""><br>
<br><br><br>
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<p class=p--info>Inquire via email: <a href="mailto:[email protected]">[email protected]</a><br>
Connect via LinkedIn: <a href="https://www.linkedin.com/in/yuxin-yang-78a671191/?originalSubdomain=cn">Here</a>
<footer>© Yuxin Yang, Feb 2023</footer> </p>
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