A comparative analysis of different phenological information retrieved from Sentinel-2 time series images to improve crop classification: a machine learning approach-Reference-Cited by-同舟云学术

A comparative analysis of different phenological information retrieved from Sentinel-2 time series images to improve crop classification: a machine learning approach

Published:2020-05-20 Issue: Volume: Page:1-24
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Htitiou Abdelaziz¹²^ORCID,Boudhar Abdelghani¹³,Lebrini Youssef¹²^ORCID,Hadria Rachid²,Lionboui Hayat²,Benabdelouahab Tarik²^ORCID

Affiliation:

1. Water Resources Management and Valorisation and Remote Sensing Team, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, Morocco;

2. National Institute of Agronomic Research, Rabat, Morocco;

3. Center for Remote Sensing Application (CRSA), Mohammed VI Polytechnic University, Ben Guerir, Morocco

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1768593

Reference110 articles.

1. Parcel-Level Identification of Crop Types Using Different Classification Algorithms and Multi-Resolution Imagery in Southeastern Turkey

2. Phenologic metrics derived from MODIS NDVI as indicators for Plant Available Water-holding Capacity

3. Mapping the Spatial Distribution of Winter Crops at Sub-Pixel Level Using AVHRR NDVI Time Series and Neural Nets