#!/usr/bin/env python
# coding: utf-8

# # Landsat-8 Level1 (GeoTIFF)
# 
# Landst 8 is a unique resource for those who work in agriculture, geology, forestry, regional planning, education, mapping, and global change research. It is a multi-spectral imaging mission, capturing visible, infrared bands, and thermal bands since February 2013. This block is a L1 (TOA) data block that is AOI-clipped, which outputs a single GeoTIFF file and will store the AOI within the output feature geometry.

# In[2]:


import up42


# In[3]:


# Authenticate and initialize project
up42.authenticate(project_id="1234", 
                  project_api_key="abcd")
project = up42.initialize_project()


# In[4]:


# Define the aoi 
namib_desert_aoi = {"type": "FeatureCollection","features": [{"type": "Feature","properties": {},
      "geometry": {"type": "Polygon","coordinates": [[[14.610298,-24.516841],
                                                      [14.622478,-24.516841],
                                                      [14.622478,-24.50833],
                                                      [14.610298,-24.50833],
                                                      [14.610298,-24.516841]]]}}]}


# In[5]:


# Construct the workflow
workflow = project.create_workflow(name="Landsat8-Geotiff-example", use_existing=True)
input_tasks = ["sentinelhub-landsat8-aoiclipped"]
workflow.add_workflow_tasks(input_tasks)


# In[7]:


# Define the aoi and input parameters of the workflow to run it
input_parameters = workflow.construct_parameters(geometry=namib_desert_aoi, 
                                                 geometry_operation='bbox', 
                                                 start_date="2018-11-07",
                                                 end_date="2020-12-31")
input_parameters["sentinelhub-landsat8-aoiclipped:1"].update({"max_cloud_cover":100})  


# In[8]:


# Estimate parameters
workflow.estimate_job(input_parameters)


# In[9]:


# Run a test job to query data availability and check the configuration.
test_job = workflow.test_job(input_parameters, track_status=True)


# In[10]:


# Run the actual live job
job = workflow.run_job(input_parameters, track_status=True)


# In[ ]:


# Download results
job.download_results()


# #### B04, B03, B02 are equivalent to RGB, for visualisation, we chose these bands for better aesthetics

# In[12]:


# Plot the results
job.plot_results(figsize=(6,6), bands=[4,3,2])