3 group surveys to fix floating point issue

.gitignore

@@ -1,5 +1,7 @@
-#survey content
-/surveys/*
-/output_las/*
+surveys
+converted_surveys
+temp_cells
+metadata
+h3_cells
 .DS_Store
 .venv

README.MD

@@ -1,25 +1,79 @@
+# Las Converter
+
+`lasConverter.py` converts survey CSV files into LAS files using EPSG:4978 and groups/crops them by H3 cells.  
+The main steps are:
+
+1. Prepare H3 Cells and Assign Surveys
+2. Convert CSV Surveys to LAS using EPSG:4978
+3. Group and Crop by H3 Cells
+
 # How to run
 
-## Activate python environment
+## 1. Prepare Files and Folders
+
+Before running the script, make sure your project folder has the following structure:
+
+```text
+lasConverter.py
+surveys/
+    ├── survey_name_1/
+    │     ├── file1.csv
+    │     └── file2.csv
+    ├── survey_name_2/
+    │     └── ...
+    └── ...
+metadata/
+    ├── metadata.csv
+    └── level1_h3_cells.csv
+```
+
+### `surveys/`
+- Contains **one folder per survey**, using the **survey name** as the folder name.
+- Each survey folder contains the CSV files for that survey (arbitrarily named).
+
+### `metadata/metadata.csv`
+- Must include the columns: `fid`, `survey_name`, `survey_area`, `geom`, `epsg`.
+- Script assumes bounding polygons in `geom` use EPSG:4258.
+- Each row corresponds to a survey.
+
+### `metadata/level1_h3_cells.csv`
+- Must contain a single column `cell_id`, listing all relevant **level 1 H3 cells**.
+
+
+## 2. Activate python environment
 
-Create a python environment with
+Create a python virtual environment with
 ```zsh
 python -m venv <environment_name>
 ```
 
-and run it with:
+Activate it:
 
-Windows: `<environment_name>\Scripts\activate`
+* **Windows:**
+```zsh
+<environment_name>\Scripts\activate
+```
+
+* **macOS/Linux:** 
+```zsh
+source <environment_name>/bin/activate
+```
 
-macOS/Linux: 
-`source <environment_name>/bin/activate`
+## 3. Install requirements
 
-## Run script
-First ensure that all requirements are installed: `pip install -r requirements.txt`
+Install the required Python packages:
+
+```zsh
+pip install -r requirements.txt
+```
 
-Then run the command below to create the potree structure.
 
+## 4. Run the script
+
+Run the converter:
 
 ```zsh
-python lasConverter.py <input_directory> <output_directory>
+python lasConverter.py
 ```
+
+The processed LAS files, cropped to level 2 H3 cells, will be saved in the `./h3_cells` folder.