Remote Sensing Python Script
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Post a project like this1467
€222(approx. $238)
- Posted:
- Proposals: 10
- Remote
- #2779343
- OPPORTUNITY
- Completed
WordPress Expert/Woocommerce Expert/Data Scientist/Python Expert/Auto-CAD/3D/2D Animation/ White Board Animation
Rawalpindi
⭐ TOP RATED ⭐ Graphic Designer| WordPress / WIX |2D Animator| Video Editing |Photoshop Expert
Karachi
software engineer|Full-Stack Software Developer| web developer| App developer | AI Engineer | WordPress
Indore
250936135147028411512896411315100533061743427171371366838843444001258
Description
Experience Level: Intermediate
Develop a standalone python code that can run on a Linux machine (crontab) every time new Sentinel-2 satellite data becomes available. The script analyses vegetation and generating the stats and maps for a certain project extent.
Example code (https://github.com/PhillRob/RS/blob/master/sentinel-v0.py). The code needs to do the following:
1. Data
* check for new Sentinel-2 data
* download data, check if polygon is fully covered, eventually merge two tiles if not the case, check for cloud cover, only accept data if cloud cover is smaller than 5%
* unzip, do atmospheric correction
2. NDVI
* calculate NDVI, apply threshold (0.2) for veg vs non-veg cells
* crop NDVI map to polygon, save NDVI map to disk in TIFF
* Map NDVI on aerial image (google) in PNG
* calculate relative veg cover for polygon
* store on disk in CSV or other tabular data and update data frame every time the code is executed run
3. Compare two NDVI results
* compare with last output, image and stats
* map with cells with veg and no veg in last assessment in PNG and TIF
* stats with cells with veg and no veg in last assessment in CVS or other tabular data
Example code (https://github.com/PhillRob/RS/blob/master/sentinel-v0.py). The code needs to do the following:
1. Data
* check for new Sentinel-2 data
* download data, check if polygon is fully covered, eventually merge two tiles if not the case, check for cloud cover, only accept data if cloud cover is smaller than 5%
* unzip, do atmospheric correction
2. NDVI
* calculate NDVI, apply threshold (0.2) for veg vs non-veg cells
* crop NDVI map to polygon, save NDVI map to disk in TIFF
* Map NDVI on aerial image (google) in PNG
* calculate relative veg cover for polygon
* store on disk in CSV or other tabular data and update data frame every time the code is executed run
3. Compare two NDVI results
* compare with last output, image and stats
* map with cells with veg and no veg in last assessment in PNG and TIF
* stats with cells with veg and no veg in last assessment in CVS or other tabular data
Philipp R.
98% (27)Projects Completed
28
Freelancers worked with
26
Projects awarded
41%
Last project
15 Apr 2023
Australia
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