I will do geospatial analysis using google earth engine, gis, rs and python

I will deliver a wide range of Google Earth Engine (GEE) products, covering both raw and processed images. The raw images include data from various sources such as Landsat, Sentinel, MODIS, GEDI, and more. On the other hand, the processed images comprise diverse analyses like vegetation index, land use/land cover (LULC), deforestation, crop phenology, meteorological parameters, and others.

My expertise lies in utilizing Python libraries like geemap, ee (GEE Python API), and folium for this purpose. Moreover, I can handle more advanced tasks such as running machine learning (ML) and deep learning (DL) algorithms for classification, time series prediction, and change detection.

With over 5 years of experience in geospatial data mining, I am well-versed in spatial analysis using tools like GEE, ArcGIS Pro, Python API, QGIS, Web GIS with Django, and Google Earth Pro. My skill set also includes statistics and spatial statistics, making me capable of delivering comprehensive geospatial solutions for both academic and industry projects.