> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/thareUSGS/GDAL_scripts/llms.txt
> Use this file to discover all available pages before exploring further.

# Planetary-Specific Scripts

> Specialized tools for planetary data processing and coordinate systems

# Planetary-Specific Scripts

Specialized utilities for planetary science data processing, including slope analysis, coordinate system definitions, and format conversions.

## gdal\_baseline\_slope.py

Calculates slope from DEMs using specialized baseline lengths or Horn's method.

### Usage

```bash theme={null}
python gdal_baseline_slope.py [options] infile outfile.tif
```

### Parameters

<ParamField path="infile" type="string" required>
  Input DEM file
</ParamField>

<ParamField path="outfile.tif" type="string" required>
  Output slope file (GeoTIFF)
</ParamField>

### Options

<ParamField path="-baseline" type="integer">
  Baseline length in pixels for slope calculation. If not specified, uses Horn's method (equivalent to gdaldem slope).

  ```bash theme={null}
  -baseline 5  # Use 5-pixel baseline
  ```
</ParamField>

<ParamField path="-ot" type="datatype">
  Output data type (default: same as input)

  Options: `Byte`, `Int16`, `UInt16`, `Int32`, `UInt32`, `Float32`, `Float64`

  ```bash theme={null}
  -ot Byte  # Output as 8-bit with scaling
  ```
</ParamField>

<ParamField path="-crop" type="flag">
  Crop output to remove edge effects from baseline calculation
</ParamField>

<ParamField path="-q" type="flag">
  Quiet mode - suppress progress output
</ParamField>

### Slope Calculation Methods

#### Horn's Method (Default)

When `-baseline` is not specified:

* Uses 3x3 kernel (standard GIS slope calculation)
* Equivalent to `gdaldem slope`
* No shift in geotransform

```python theme={null}
dz_dx = ((c + 2f + i) - (a + 2d + g)) / (8 * cellsize_x)
dz_dy = ((g + 2h + i) - (a + 2b + c)) / (8 * cellsize_y)
slope_degrees = atan(sqrt(dz_dx² + dz_dy²)) * 180/π
```

#### Baseline Method

When `-baseline N` is specified:

* Uses corner points of N×N footprint
* Follows Kirk's method for planetary analysis
* Even baselines shift geotransform by half pixel

```python theme={null}
dz_dx = ((b + d) - (a + c)) / (2 * baseline * cellsize_x)
dz_dy = ((a + b) - (c + d)) / (2 * baseline * cellsize_y)
slope_degrees = atan(sqrt(dz_dx² + dz_dy²)) * 180/π
```

### Byte Output Scaling

When `-ot Byte` is used:

* Slopes are scaled to 1-255 range
* Formula: `DN = (slope + 0.2) × 5.0`
* Slopes >50° map to 255
* NoData = 0
* Set offset = -0.2, scale = 0.2 in output

### Example

```bash theme={null}
# Standard Horn's method
python gdal_baseline_slope.py input_dem.tif output_slope.tif

# 5-pixel baseline
python gdal_baseline_slope.py -baseline 5 input_dem.tif output_slope_5px.tif

# 8-bit output with 10-pixel baseline
python gdal_baseline_slope.py -baseline 10 -ot Byte input_dem.tif output_slope_8bit.tif

# With cropping to remove edge effects
python gdal_baseline_slope.py -baseline 5 -crop input_dem.tif output_slope_cropped.tif
```

### Cropping Behavior

When `-crop` is used with `-baseline`:

| Baseline | Pixels Removed   | Geotransform Shift |
| -------- | ---------------- | ------------------ |
| 1        | 1 (right/bottom) | +1 pixel X/Y       |
| 2        | 1 (each edge)    | +1 pixel X/Y       |
| 5        | 2-3 (edges)      | +3 pixels X/Y      |

### Requirements

<Warning>
  **Dependencies:**

  * Python 2.7+ or Python 3.x
  * GDAL Python bindings
  * NumPy
  * SciPy (for `generic_filter`)
</Warning>

```bash theme={null}
conda install -c conda-forge gdal numpy scipy
```

***

## create\_IAU2000\_wkt\_v3.py

Generates OGC WKT (Well-Known Text) projection strings for IAU planetary coordinate systems.

### Usage

```bash theme={null}
python create_IAU2000_wkt_v3.py input_csv [output.wkt]
```

### Parameters

<ParamField path="input_csv" type="string" required>
  Input CSV file with IAU body radii

  Must be named: `naifcodes_radii_m_wAsteroids_IAU{YEAR}.csv`

  Supported years: 2000, 2009, 2015
</ParamField>

<ParamField path="output.wkt" type="string">
  Output WKT file (default: stdout)
</ParamField>

### Input CSV Format

```csv theme={null}
Naif_id,Body,IAU2000_Mean,IAU2000_Semimajor,IAU2000_Axisb,IAU2000_Semiminor
199,Mercury,2439700.00,2439700.00,2439700.00,2439700.00
299,Venus,6051800.00,6051800.00,6051800.00,6051800.00
399,Earth,6371000.00,6378140.00,6378140.00,6356750.00
301,Moon,1737400.00,1737400.00,1737400.00,1737400.00
499,Mars,3389500.00,3396190.00,3396190.00,3376200.00
```

### Generated Coordinate Systems

For each body, generates multiple coordinate system definitions:

#### Geographic Systems

* **X00** - Planetocentric
* **X01** - Planetographic

#### Static Projections

* **X10-X13** - Equirectangular (ocentric/ographic, clon 0/180)
* **X14-X17** - Sinusoidal (ocentric/ographic, clon 0/180)
* **X18-X21** - Polar Stereographic (North/South, ocentric/ographic)
* **X22-X29** - Mollweide and Robinson variants

#### AUTO Projections (Variable Center)

* **X60-X61** - Sinusoidal AUTO
* **X62-X63** - Stereographic AUTO
* **X64-X65** - Transverse Mercator AUTO
* **X66-X67** - Orthographic AUTO
* **X68-X69** - Equirectangular AUTO
* **X70-X71** - Lambert Conformal Conic AUTO
* **X72-X73** - Lambert Azimuthal Equal Area AUTO
* **X74-X75** - Mercator AUTO
* **X76-X77** - Albers AUTO
* **X78-X79** - Oblique Cylindrical Equal Area AUTO
* **X80-X83** - Mollweide and Robinson AUTO

Where X = NAIF\_ID \* 100 + code

### Example

```bash theme={null}
# Generate IAU 2015 definitions
python create_IAU2000_wkt_v3.py naifcodes_radii_m_wAsteroids_IAU2015.csv iau2015.wkt

# Output to stdout
python create_IAU2000_wkt_v3.py naifcodes_radii_m_wAsteroids_IAU2015.csv
```

### Output Format

```
#IAU2015 WKT Codes for Mars
49900,GEOGCS["Mars 2015",DATUM["D_Mars_2015",...],AUTHORITY["IAU2015","49900"]]
49901,GEOGCS["Mars 2015",DATUM["D_Mars_2015",...],AUTHORITY["IAU2015","49901"]]
49910,PROJCS["Mars_Equidistant_Cylindrical",...,AUTHORITY["IAU2015","49910"]]
...
```

### Use Cases

* Configuring WMS/WCS services for planetary data
* Creating custom projections for planetary mapping
* Supporting GDAL/MapServer planetary coordinate systems
* Generating ESRI .prj files for planetary data

### IAU Reports Supported

* **IAU 2000** - Seidelmann et al. (2002)
* **IAU 2009** - Archinal et al. (2011)
* **IAU 2015** - Archinal et al. (2018)

***

## isis3\_to\_pds4\_LOLA\_pvl.py

Converts ISIS3 cube labels to PDS4 format using GDAL's PDS4 driver.

### Usage

```bash theme={null}
python isis3_to_pds4_LOLA_pvl.py [options] input.cub output_config.txt
```

### Parameters

<ParamField path="input.cub" type="string" required>
  Input ISIS3 cube file
</ParamField>

<ParamField path="output_config.txt" type="string" required>
  Output GDAL configuration file for PDS4 conversion
</ParamField>

### Options

<ParamField path="-run" type="flag">
  Automatically execute gdal\_translate after creating config
</ParamField>

<ParamField path="-template" type="string">
  Path to custom PDS4 XML template

  Default: `$GDALDATA/pds4_template.xml`

  ```bash theme={null}
  -template custom_template.xml
  ```
</ParamField>

### How It Works

1. Reads ISIS3 label using Python PVL library
2. Extracts metadata: target, mission, instrument, product ID
3. Creates GDAL configuration file with PDS4 variables
4. Optionally runs `gdal_translate` to create PDS4 product

### Output Files

Generated configuration file contains:

```
-co VAR_TARGET_TYPE=Satellite
-co VAR_TARGET=MOON
-co VAR_INVESTIGATION_AREA_NAME="LUNAR RECONNAISSANCE ORBITER"
-co VAR_LOGICAL_IDENTIFIER=LRO_LOLA_DEM
-co VAR_OBSERVING_SYSTEM_NAME=LOLA
-co VAR_TITLE=LRO_LOLA_DEM_TILE_01
```

### Example

```bash theme={null}
# Create config file only
python isis3_to_pds4_LOLA_pvl.py input.cub output.config

# Create config and run conversion
python isis3_to_pds4_LOLA_pvl.py -run input.cub output.config

# Use custom template
python isis3_to_pds4_LOLA_pvl.py -template my_template.xml input.cub output.config
```

### Manual Conversion

After creating config file:

```bash theme={null}
gdal_translate -of PDS4 -co IMAGE_FORMAT=GEOTIFF \
  -co TEMPLATE=pds4_template.xml \
  --optfile output.config \
  input.cub output_pds4.xml
```

### Requirements

<Warning>
  **Dependencies:**

  * Python 3.x
  * GDAL 2.2.0+ with PDS4 driver support
  * PVL library: `pip install pvl`
</Warning>

```bash theme={null}
# Install PVL library
pip install pvl

# Verify GDAL PDS4 support
gdalinfo --format PDS4
```

***

## fix\_jp2\_v2

Corrects GeoJP2 projection keywords for Equirectangular projections (C++ utility).

### Purpose

Fixes HiRISE and other JPEG2000 files where `CenterLatGeoKey` was incorrectly used instead of `StandardParallel1GeoKey` in Equirectangular projections.

### Usage

```bash theme={null}
fix_jp2_v2 targetfile.jp2
```

### Parameters

<ParamField path="targetfile.jp2" type="string" required>
  Input/output JPEG2000 file to fix (modified in place)
</ParamField>

### How It Works

1. Opens the JPEG2000 file
2. Locates the GeoTIFF metadata section
3. Changes `CenterLatGeoKey` tag to `StandardParallel1GeoKey`
4. Writes changes (only a few bytes modified)
5. Does **not** decompress/recompress imagery

### Safety

<Warning>
  Version 2 update (Jan 10, 2023):

  * Skips files already corrected by HiRISE team
  * Only modifies files that need correction
  * Always backup files before running
</Warning>

### Example

```bash theme={null}
# Backup original file
cp PSP_001234_1234_RED.jp2 PSP_001234_1234_RED.jp2.backup

# Fix projection
fix_jp2_v2 PSP_001234_1234_RED.jp2

# Verify fix
gdalinfo PSP_001234_1234_RED.jp2 | grep -i projection
```

### Compilation

```bash theme={null}
# Linux/Mac
g++ -o fix_jp2_v2 fix_jp2_v2.cpp

# Windows (Visual Studio)
# Open in Visual Studio and build as console application
```

### Use Cases

* Fixing older HiRISE JPEG2000 files
* Correcting GeoJP2 files with incorrect projection parameters
* Batch processing of archived data

### Technical Details

Addresses GDAL ticket: [http://trac.osgeo.org/gdal/ticket/2706](http://trac.osgeo.org/gdal/ticket/2706)

***

## Common Workflows

### Planetary Slope Analysis Workflow

```bash theme={null}
# 1. Calculate baseline slope
python gdal_baseline_slope.py -baseline 5 -ot Byte mars_dem.tif mars_slope.tif

# 2. Generate histogram
python gdal_hist.py -hist mars_slope.tif > mars_slope_hist.txt

# 3. Create visualization
python slope_histogram_cumulative_graph.py -name "Mars Site" \
  mars_slope_hist.txt mars_slope_graph.png
```

### PDS4 Archive Workflow

```bash theme={null}
# 1. Convert to ISIS3 if needed
python Astropedia_gdal2ISIS3.py input.tif temp.cub

# 2. Create PDS4 configuration
python isis3_to_pds4_LOLA_pvl.py temp.cub pds4.config

# 3. Generate PDS4 product
gdal_translate -of PDS4 -co IMAGE_FORMAT=GEOTIFF \
  --optfile pds4.config temp.cub output_pds4.xml
```

## Requirements

All planetary scripts require:

* Python 2.7+ or Python 3.x (varies by script)
* GDAL/OGR Python bindings
* Script-specific dependencies (NumPy, SciPy, pvl)

## Author

Developed by Trent Hare and contributors at USGS Astrogeology Science Center.

## License

Public domain (Unlicense) unless otherwise specified.