Skip to content

Latest commit

 

History

History
168 lines (133 loc) · 4.08 KB

PITCHME.md

File metadata and controls

168 lines (133 loc) · 4.08 KB
Raw

---?image=assets/images/geo_depart.png&size=50%

Wildcat Eyes

---?image=assets/images/wildcat-eyes-logo.jpg&size=90%

---?image=assets/images/terrabytes27.gif

Lidar point clouds

46,105 tiles in Kentucky

> 20TB

---?image=assets/images/usgs.png

KY leads the way

[KyFromAbove](http://kyfromabove.ky.gov/)
<iframe src="https://www.outrageGIS.com/pointclouds/johnson" width="100%" height="600px"></iframe>

---?image=assets/images/dir.gif

[ftp://ftp.kymartian.ky.gov](ftp://ftp.kymartian.ky.gov/)

Reqs

@ul

  • Python 3
    • subprocess, urllib, and zipfile
  • For point clouds (on WinOS)
  • Tile index grids
  • QGIS @ulend

Find tiles

---?image=assets/images/q03.png&size=80%

Export URLs as CSV

---?image=assets/images/q04.png&size=80%

List of files

data_names = [
"ftp://ftp.kymartian.ky.gov/kyaped/DEMs_5FT/N115E318_DEM.zip",
"ftp://ftp.kymartian.ky.gov/kyaped/DEMs_5FT/N115E319_DEM.zip",
"ftp://ftp.kymartian.ky.gov/kyaped/DEMs_5FT/N115E320_DEM.zip",
"ftp://ftp.kymartian.ky.gov/kyaped/DEMs_5FT/N115E321_DEM.zip"]

Jupyter Notebook

Set data dirs

# Populate project folder with asset folders
downloads = f'{root}/{project}/downloads'
lidar = f'{root}/{project}/lidar'
naip_year = f'{root}/{project}/{year}'
dem = f'{root}/{project}/dem'

# Create folders
folders = [f'{root}/{project}', downloads, lidar, naip_year, dem]
for folder in folders:
    subprocess.run(f'mkdir {folder}', shell=True, stdout=subprocess.PIPE)
    print(f"mkdir {folder}")

Maintain asset name

@ul

  • Layer name based on grid size
    • 5k (lidar, DEM, <2ft img)
    • 10k (2 ft NAIP)
    • 20k (>2ft NAIP)
  • file extensions and year changes @ulend

Why?

@ul

  • Multiple queries
    • 7 years of NAIP
    • Soon 2 years of lidar
  • Download multiple years using same list
  • Must match same resolution @ulend
if "laz" in data_names[0][-3:].lower():
    name = url[-12:]
elif "naip" in data_names[0][-22:-18].lower():
    extension = "jpg"
    name = url[-12:-4]
    if year == "2016":
        naip_prefix = "ky_2ft_naip_2016_"
elif "dem" in data_names[0][-7:-4].lower():
    name = url[-16:-4]
elif "1ft" in data_names[0][-16:-13].lower():
    name = url[-12:-4]
# Download, extract, and move
with urllib.request.urlopen(url) as response: 
    with open(f'{downloads}/{name}.zip', 'wb') as outFile:
        data = response.read()
        outFile.write(data) 
with ZipFile(f'{downloads}/{name}.zip', 'r') as zip: 
    zip.extractall(f'{downloads}/{name}')
subprocess.run(f'mv {downloads}/{name}/*.* {naip_year}')

Merge tiles

ls -n1 dem/*.img > list.txt
gdal_merge.py -ot Float32 -of GTiff -o dem.tif --optfile list.txt

---?image=assets/images/q07.png&size=80%

QGIS menu > Raster > Miscellaneous > Merge

Potree Conversion

# Create interactive point cloudmap with PotreeConverter.exe
for i in names:
    if ".las" in i:
        with open(f'{root}\\{project}\\potree_las_list.txt', 'a+') as outFile:
            outFile.write(f"{root}\\{project}\\lidar\\{i}\n")
potreeOut = f"""{potree_tools} --list-of-files 
               {root}\\{project}\\potree_las_list.txt
               -o {root}\\{project}\\potree -p index"""
subprocess.run(potreeOut)

Thank you!

---?image=assets/images/geo_depart.png&size=50%