Mapping the Diversity of Agricultural Systems in the Cuellaje Sector, Cotacachi, Ecuador Using ATL08 for the ICESat-2 Mission and Machine Learning Techniques

Author:

Fernando Garrido

Publisher

Springer International Publishing

Reference30 articles.

1. Neuenschwander, A.L., et al.: ATLAS/ICESat-2 L3A Land and Vegetation Height, Version 4. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center (2021). https://doi.org/10.5067/ATLAS/ATL08.004. Accessed Nov 2020

2. Helber, P., Bischke, A., Dengel1, A., Borth, D.: EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification: German Research Center for Artificial Intelligence (DFKI), Germany (2019). arXiv:1709.00029v2

3. Bischke, B., Bhardwaj, P., Gautam, A., Helber, P., Borth, D., Dengel, A.: Detection of flooding events in social multimedia and satellite imagery using deep neural networks. In: MediaEval (2017)

4. Neuenschwander, A.L.: ICESat-2 and ATL08 (Land/Vegetation) Data: University of Texas at Austin. NASA’s Applied Remote Sensing Training Program. 16 March 2021

5. Ice, Cloud, and Land Elevation Satellite-2, or ICESat-2, to access ICESat-2 data, visit the National Snow & Ice Data Center (NSIDC). https://icesat-2.gsfc.nasa.gov/how-it-works. Accessed 15 Feb 2021

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