Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update README.md #77

Merged
merged 1 commit into from
Oct 10, 2024
Merged

Update README.md #77

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
61 changes: 26 additions & 35 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,11 +38,11 @@ using Extents
granules = search(:ICESat2, :ATL08)

# Find only ATL03 granules in a part of Vietnam
vietnam = Extent(X = (102., 107.0), Y = (8.0, 12.0))
vietnam = Extent(X=(102.0, 107.0), Y=(8.0, 12.0))
granules = search(:ICESat2, :ATL08; extent=vietnam, version=6)

# Find GEDI granules in the same way
granules = search(:GEDI, :GEDI02_A)
granules = search(:GEDI, :GEDI02_A; extent=vietnam)

# A granule is pretty simple
granule = granules[1]
Expand All @@ -54,54 +54,45 @@ granule.info # derived information from id
# we provide a helper function, that creates/updates a ~/.netrc or ~/_netrc
SpaceLiDAR.netrc!(username, password) # replace with your credentials

# Afterward you can download the dataset
fn = SpaceLiDAR.download!(granule)
# Afterward you can download the dataset.
# Note: download! updated granule url to local path
granule = SpaceLiDAR.download!(granule)

# You can also load a granule from disk
granule = granule(fn)
path2file = granule.url
granule = SpaceLiDAR.granule(path2file)

# Or from a folder
local_granules = granules(folder)

# Instantiate search results locally (useful for GEDI location indexing)
local_granules = instantiate(granules, folder)
(folder, fn) = splitdir(path2file)
local_granules = SpaceLiDAR.granules(folder)
```

Derive points
```julia
using DataFrames
fn = "GEDI02_A_2019242104318_O04046_01_T02343_02_003_02_V002.h5"
g = SpaceLiDAR.granule(fn)
df = DataFrame(g)
149680×15 DataFrame
Row │ longitude latitude height height_error datetime intensity sensitivity surface quality nmo ⋯
│ Float64 Float64 Float32 Float32 DateTime Float32 Float32 Bool Bool UIn ⋯
────────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ 153.855 -47.2772 -13.3536 0.307976 2019-08-30T10:48:21.047 393.969 -0.0671094 true false ⋯
2 │ 153.855 -47.2769 -11.2522 0.307978 2019-08-30T10:48:21.055 797.26 0.533529 true true
3 │ 153.856 -47.2767 -13.775 0.307981 2019-08-30T10:48:21.063 1010.39 0.695938 true true
4 │ 153.857 -47.2765 -11.729 0.307983 2019-08-30T10:48:21.071 852.614 0.544849 true true
5 │ 153.857 -47.2763 -13.2443 0.307985 2019-08-30T10:48:21.080 980.66 0.620767 true true ⋯
6 │ 153.858 -47.2761 -12.1813 0.307987 2019-08-30T10:48:21.088 937.441 0.620531 true true
7 │ 153.859 -47.2758 -11.9011 0.30799 2019-08-30T10:48:21.096 1235.02 0.73815 true true
8 │ 153.859 -47.2756 -12.3796 0.307992 2019-08-30T10:48:21.104 854.127 0.545655 true true
granule = SpaceLiDAR.granule(fn)

df = DataFrame(granule)
760156×15 DataFrame
Row │ longitude latitude height height_error datetime intensity sensitivity surface quality nmodes track strong_beam classification sun_angle height_reference
│ Float64 Float64 Float32 Float32 DateTime Float32 Float32 Bool Bool UInt8 String Bool String Float32 Float32
────────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ 26.6923 51.823 169.045 0.313182 2019-04-18T10:22:23.996 -857.388 1.38006 true false 1 BEAM0000 false ground 49.0315 169.752
2 │ 26.7006 51.823 165.783 0.31319 2019-04-18T10:22:24.078 853.56 0.694586 true false 1 BEAM0000 false ground 49.0312 167.354
3 │ 26.7023 51.823 162.871 0.313192 2019-04-18T10:22:24.095 110.071 -0.480232 true false 1 BEAM0000 false ground 49.0311 164.785
⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
760155 │ 110.661 -0.194184 171.157 0.258848 2019-04-18T10:45:33.900 7702.96 0.945006 true true 2 BEAM1011 true ground -1.94442 176.333
760156 │ 110.662 -0.195451 167.176 0.258852 2019-04-18T10:45:33.925 9595.64 0.981322 true true 2 BEAM1011 true ground -1.94564 173.691
```


Derive linestrings
```julia
using DataFrames
fn = "ATL03_20181110072251_06520101_003_01.h5"
g = SpaceLiDAR.granule(fn)
tlines = DataFrame(SpaceLiDAR.lines(g, step=10000))
Table with 4 columns and 6 rows:
geom sun_angle track datetime
┌───────────────────────────────────────────────────────────────────────────
1 │ wkbLineString25D geometry 38.3864 gt1l_weak 2018-11-10T07:28:01.688
2 │ wkbLineString25D geometry 38.375 gt1r_strong 2018-11-10T07:28:02.266
3 │ wkbLineString25D geometry 38.2487 gt2l_weak 2018-11-10T07:28:04.474
4 │ wkbLineString25D geometry 38.1424 gt2r_strong 2018-11-10T07:28:07.374
5 │ wkbLineString25D geometry 38.2016 gt3l_weak 2018-11-10T07:28:05.051
6 │ wkbLineString25D geometry 38.1611 gt3r_strong 2018-11-10T07:28:06.344
fn = "GEDI02_A_2019108093620_O01965_03_T05338_02_003_01_V002.h5"
granule = SpaceLiDAR.granule(fn)
tlines = DataFrame.(SpaceLiDAR.lines(granule; step=10000))

SpaceLiDAR.GDF.write("lines.gpkg", tlines)
```
Loading