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Python bindings for the Julia packageRQADeforestation.jl.It provides functions for fast recurrence quantification analysis (RQA), accelerated using Julia.This library is part of theFAIRSenDD project that utilize Sentinel-1 data for FAIR deforestation detection.

Install:

pip install rqadeforestation

Run RQA analysis on a single time series:

fromrqadeforestationimportrqatrendimportnumpyasnpx=np.arange(1,30,step=0.01)y=np.sin(x)+0.1*xrqatrend(y,0.5,10,1)# -0.14028027430322332

Use in openEO:

# Import required packagesimportopeneofromopeneo.processesimportprocess# Connect to the back-endconnection=openeo.connect("https://openeo.eodc.eu/openeo/1.2.0/")connection.authenticate_oidc()bbox=  {"west":11.655947222212369,"east":11.715643117926051,"south":50.87929082462556,"north":50.92129080534822}datacube1=connection.load_collection(collection_id="SENTINEL1_SIG0_20M",spatial_extent=bbox,temporal_extent= ["2020-01-01T00:00:00Z","2020-02-01T00:00:00Z"],bands=None,properties= {})defreducer1(data,context):rqadeforestation1=process("rqadeforestation",data=data,threshold=0.4)returnrqadeforestation1reduce3=datacube1.reduce_dimension(reducer=reducer1,dimension="t")save4=reduce3.save_result(format="NETCDF")# The process can be executed synchronously (see below), as batch job or as web service nowresult=connection.execute(save4)

Analyzing high resolution sattelite images at global scale requires to optimize the execution efficiency.Python is required for most openEO workflows in which performance critical parts of the code are written in a compiled programming language.Usually, this is done in C, e.g., array operations in numpy.Julia provides an alternative to accellerate code using a more user-friendly language.

Development workflow:

1. Write Julia code athttps://github.com/EarthyScience/RQADeforestation.jl
2. Compile usingStaticCompiler
3. Put the binary libraries atrqadeforestation/lib
4. Add python binding functions to this package
5. Install this package in openEO and use it in anUser-Defined-Function

F. Cremer, M. Urbazaev, J. Cortés, J. Truckenbrodt, C. Schmullius and C. Thiel, "Potential of Recurrence Metrics from Sentinel-1 Time Series for Deforestation Mapping," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 5233-5240, 2020, doi:10.1109/JSTARS.2020.3019333.

This project was funded by the European Space Agency in the Science Result Long-Term Availability & Reusability Demonstrator Initiative.In addition, this project was supported by the ESA Network of Resources.