added images and modified the readme

Author: behzad-vahedi

README.md

@@ -3,3 +3,52 @@
 
 ![FIREDpy - NRT - Page 2](https://github.com/earthlab/FIREDpy-NRT/assets/67020853/e56abc54-99d4-490a-ade0-994b63c8fbfb)
 Project funded by NASA Applied Sciences Program and developed by ESOC and Earth Lab, CIRES - CU Boulder
+
+
+## Fist Stage (Summer 2023)
+### Done by [Behzad Vahedi](mailto:[email protected])
+
+Our project aims to extende the EarthLab’s "Fire Event Delineation for Python (FIREDpy)" library by updating it for Near-Real-Time (NRT) fire event perimeter mapping through the fusion of optical and radar remote sensing data. Our main motivations are twofold: to achieve closer-to-real-time temporal resolution and to improve the spatial resolution of the FIREDpy outputs. 
+
+In the first stage of the project, we focused on answering two questions:
+- Is applying BRDF correction necessary to generated NRT fire perimeters?
+- How does fire affect the signal in Sentinel-2 and Landsat-8 images and how do these satellites compare?
+
+### BERDF Correction
+The flowchart below demonstrates the steps I took to answer the first question, with the caveat that I only tested BRDF on Sentinel-2 images (using the Sen2nbar package) since I couldn't find any python implementation of this correction for Landsat images.
+
+<img src="./images/Flowchart.jpg" width=800>
+
+__Now, let's go through the different steps in the flowchart__
+
+The steps in the first row of this flowchart are done using the [FiredPy](https://github.com/earthlab/firedpy) package. This resulted in a shapefile of 20 fire events in the Americas which you can find in the [fire_events](./fire_events/) folder.
+
+Once the fire events are extracted, you need to __get pre- and post-fire image pairs__ for each event. This is done using the [optical_scenes.py](./scripts/optical_scenes.py) script. This script uses the footprint of the fire as well as its start and end date to search for optical images. It can download the images and/or save their footprints. You can run this script using the command below:
+
+`python optical_scenes.py --event_id "202" --satellite "sentinel"`
+
+or alternatively, 
+
+`python optical_scenes.py -id "202" -s "sentinel"`
+
+In these commands, the value of the `event_id` (or `id`) argument must be the ID of the fire event for which satellite images are to be searched. This comes from the id field of the [fire events shapefile](./fire_events/Fire_events.zip). The value of the `satellite` (or `s`) argument must be the name of the satellite, either "sentinel" or "landsat".
+
+You can set or change the search criteria in the `config.py` file. These parameters are:
+- `max_cloud_cover`: Maximum cloud cover percentage. default: 40%.
+- `delta_days_landsat`: The number of days to use as a buffer before and after the fire event when searching for Landsat images. default: 70 days.
+- `delta_days_sentinel`: The number of days to use as a buffer before and after the fire event when searching for Sentinel-2 images. default: 40 days.
+- `download_scenes`: Whether to download images or not. default: False. __CAUTION: depending on the number of the images found, this could take a long time and might reqiure a huge amount of storage__
+- `save_footprints`: Whether to save image footprints or not. default: False.
+- `update_json`: deprecated.
+- `data_dir`: The directory where the images and/or their footprints will be saved. See below for more information.
+
+#### Directory Organization
+`data_dir` is the directory where the you would want the images to be saved. Once you create this directory, extract (unzip) the `Fire_events.zip` there. This will (should) create a new subdirectory called Fire_events. Per each fire id you run the `optical_scenes.py` script for, a new subdirectory will be created within "Fire_events". Also, depending on what the `-s` parameter is, the corresponding subdirectory will be created within the fire_id folder where the footprints and images will be saved.
+
+<img src="./images/directory_tree.png" width="300">
+
+
+#### Important Note:
+Before running the `optical_scenes.py` script, you should create separate accounts for Landsat and Sentinel API and set your username and password in the corresponidng variables in the `config.py` file.
+
+### Optical Signal Evaluation

fire_events/Fire_events.zip

@@ -5,28 +5,28 @@ class Config():
     def __init__(self):
         # [credential_landsat]
         # landsat API
-        self.username_landsat = "behzad69"
-        self.password_landsat = "Realeblis@69"
+        self.username_landsat = "YOUR_USERNAME"
+        self.password_landsat = "YOUR_PASSWORD"
 
 
         # [credential_sentinel]
         # Copernicus Open Access Hub (SciHub) username and password
-        self.username_sentinel = "behzadseaice"
-        self.password_sentinel = "lion15th"
+        self.username_sentinel = "YOUR_USERNAME"
+        self.password_sentinel = "YOUR_PASSWORD"
 
         # [params]
         self.max_cloud_cover = 40
         self.delta_days_landsat = 70
-        self.delta_days_sentinel = 20
+        self.delta_days_sentinel = 40
         # Sentinel-2: S2MSI2A,S2MSI1C, S2MS2Ap
         self.producttype_sentinel = "S2MSI2A"
 
-        # [directory]
-        self.data_dir = os.path.abspath(os.path.join(os.path.dirname( __file__ ), '..', 'data')) # ("../data/") 
         # whether to download the scenes or not
         self.download_scenes = False
         self.save_footprints = True
         self.update_json = False
+        # [directory]
+        self.data_dir = os.path.abspath(os.path.join(os.path.dirname( __file__ ), '..', 'data')) # ("../data/") 
 
         if os.name == 'nt':  # Windows
             self.dir_sep = '\\'