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eciraci committed Jan 20, 2024
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IRIDE Service Segment Lot 2
---
[![Language][]][1]
[![License][]][1]

---
### Naming Convention and Metadata

---

#### Naming Convention - SE-S3-01
**S3_01_SNT_01**

Expand Down Expand Up @@ -44,10 +50,23 @@ Naming convention:
Example:
ISS Product Name: ISS_S301SNT04_20180101_20220101_015A_01

---
**COSMO-SkyMed**

In this case, InSAR data generated per each of the considered CSK frames will be distributed employing a track-specific grid (i.e., once generated, the PS data is cropped using a grid aligned with the satellite track - see figures below).

A unique ID will identify each grid cell.

NOTE 1: PS/DS products will be cropped using the grid, not the input SAR data. The PS calculation will still be performed at the frame level.

NOTE 2: the case presented below constitutes an example of the grid we will generate and distribute. We will likely define a grid with larger cells.

<img src="images/csk_frame_grid.png" class="align-center" style="width:50.0%" alt="image" />
---

#### Sentinel-1
# Metadata
### Sentinel-1

#### Metadata
- **ISS_S301SNT01_2018-01-05_2022-12-28_08710208VVA_01.csv** - metadata file example for **S3-01-SNT-01** geospatial products.
- **ISS_S301SNT03_20180105_20221228_100ME43N18V_01.csv** - metadata file example for **S3-01-SNT-03** geospatial thematic products.

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| Mattinata_A | MTI_A |
| Mattinata_D | MTI_D |
| ColliAlbani_A | COA_A |
| ColliAlbani_D | COA_D |
| ColliAlbani_D | COA_D |

----
### Setup Python Environment

1. Setup minimal **conda** installation using [Miniconda][]

2. Create Python Virtual Environment

> - Creating an environment with commands ([Link][]);
> - Creating an environment from an environment.yml file
> ([Link][2]) -> **Recommended**;
#### PYTHON DEPENDENCIES:
- [gdal: Python's GDAL binding.][]
- [fiona: Fiona is GDAL’s neat and nimble vector API for Python programmers.][]
- [numpy: The fundamental package for scientific computing with Python.][]
- [pandas: Python Data Analysis Library.][]
- [geopandas: add support for geographic data to pandas objects.][]
- [matplotlib: Library for creating static, animated, and interactive visualizations in Python.][]


[Language]: https://img.shields.io/badge/python-%3E%3D%203.10-blue
[License]: https://img.shields.io/bower/l/MI
[1]: ..%20image::%20https://www.python.org/

[xarray: Labelled multi-dimensional arrays in Python.]:https://docs.xarray.dev
[rasterio: access to geospatial raster data]:https://rasterio.readthedocs.io/en/latest/
[gdal: Python's GDAL binding.]: https://gdal.org/index.html
[tqdm: A Fast, Extensible Progress Bar for Python and CLI.]: https://github.com/tqdm/tqdm
[necdft4: Provides an object-oriented python interface to the netCDF version 4 library.]:https://pypi.org/project/netCDF4/
[fiona: Fiona is GDAL’s neat and nimble vector API for Python programmers.]:https://fiona.readthedocs.io/en/latest/
[numpy: The fundamental package for scientific computing with Python.]:https://numpy.org
[PyTMD: Python package for the analysis of tidal data.]: https://github.com/tsutterley/pyTMD
[pandas: Python Data Analysis Library.]:https://pandas.pydata.org/
[geopandas: add support for geographic data to pandas objects.]:https://geopandas.org/en/stable/
[matplotlib: Library for creating static, animated, and interactive visualizations in Python.]:https://matplotlib.org

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