Monitoring cropland LAI using Gaussian Process Regression and sentinel – 2 surface reflectance data in Google Earth Engine-Reference-Cited by-同舟云学术

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Monitoring cropland LAI using Gaussian Process Regression and sentinel – 2 surface reflectance data in Google Earth Engine

Published:2024-07-09 Issue:15 Volume:45 Page:5008-5027
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Sahoo Rabi N.¹,Kondraju Tarun¹,Rejith R. G.¹,Verrelst Jochem²^ORCID,Ranjan Rajeev¹,Gakhar Shalini¹,Bhandari Amrita¹,Chinnusamy Viswanathan³

Affiliation:

1. Division of Agricultural Physics, Indian Council of Agricultural Research (ICAR) – Indian Agricultural Research Institute (IARI), Pusa, New Delhi, India

2. Image Processing Laboratory (IPL), Parc Científic, Universitat de València, Paterna, València, Spain

3. Division of Plant Physiology, ICAR –IARI, Pusa, New Delhi, India

Funder

Indian Council of Agricultural Research

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2370503

Reference58 articles.

1. A Review of Hybrid Approaches for Quantitative Assessment of Crop Traits Using Optical Remote Sensing: Research Trends and Future Directions

2. Sustaining Indian Agriculture – Conservation Agriculture the Way Forward;Abrol I. P.;Current Science,2006

3. Machine learning methods’ performance in radiative transfer model inversion to retrieve plant traits from Sentinel-2 data of a mixed mountain forest

4. Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs

5. Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring

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