Machine learning model ensemble for predicting sugarcane yield through synergy of optical and SAR remote sensing

Author:

Das AyanORCID,Kumar MukeshORCID,Kushwaha Amit,Dave Rucha,Dakhore Kailash KamajiORCID,Chaudhari Karshan,Bhattacharya Bimal Kumar

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference68 articles.

1. Estimating Leaf Area Index and biomass of sugarcane based on Gaussian process regression using Landsat 8 and Sentinel 1A observations;Abebe;Int. J. Image. Data Fusion.,2022

2. Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island;Baghdadi;Remote Sens. Environ.,2009

3. Multitemporal observations of sugarcane by TerraSAR-X images;Baghdadi;Sensors,2010

4. Inequality, control rights, and rent seeking: sugar cooperatives in Maharashtra;Banerjee;J. Polit. Econ.,2001

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