Remote Sensing(RS) Sanyang Wetland
Info Yuxin Yang, Xi Cao, Qizheng Xie, Shifeng Zheng, 09/2017-11/2019, Academy
My contributions include roadmap, RS image pre-processing, feature classification algorithms, and spatial density definition refinement
with the team
Instructor Zhe Li, lizheseu@seu.edu.cn
Institution Southeast University, Nanjing, China
National Fund Recipient of China’s Student Research Training Program (SRTP); Patented
This is a landscape element extraction and spatial density visualization flow with ENVI, eCoginition, and Grasshopper.
Spatial Density 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:
What are the REMOTE SENSING IMAGE POTENTIALS in unfolding the invisibility of the environment?
How to define PERFORMANCE INDEX of a built environment?
What is a potential visualization WORKFLOW for a remote sensing image?
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.
Sanyang Wetland Spatial Density visualization
Workflow
Inquire via email: yuxiny0822@gmail.com
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