Next Article in Journal
TSRC: A Deep Learning Model for Precipitation Short-Term Forecasting over China Using Radar Echo Data
Previous Article in Journal
Soil-Moisture Estimation Based on Multiple-Source Remote-Sensing Images
Previous Article in Special Issue
Actual Evapotranspiration from UAV Images: A Multi-Sensor Data Fusion Approach
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Correction

Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740

1
Department of Bioproducts and Biosystems Engineering, University of Minnesota Twin Cities, St. Paul, MN 55108, USA
2
Department of Soil, Water and Climate, University of Minnesota Twin Cities, St. Paul, MN 55108, USA
3
Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA
4
College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
5
National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(1), 141; https://doi.org/10.3390/rs15010141
Submission received: 20 September 2022 / Revised: 1 December 2022 / Accepted: 6 December 2022 / Published: 27 December 2022
(This article belongs to the Special Issue Remote Sensing for Crop Mapping)

Error in Figure

In the original article [1], there was a mistake in Figure 1 as published. The Kingdom of Morocco considers its Southern Provinces (what used to be referred to as Western Sahara) as an integral part of the country with total sovereignty. The USA is among the countries that have recognized this sovereignty with a proclamation signed in December 2020 [2]. The authors used a solid line in the map that may infer the non-sovereignty of Morocco over its Sahara and have updated the map. The corrected Figure 1 appears below. The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original article has been updated.

References

  1. Lin, C.; Jin, Z.; Mulla, D.; Ghosh, R.; Guan, K.; Kumar, V.; Cai, Y. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740. [Google Scholar] [CrossRef]
  2. The White House Proclamation on Recognizing the Sovereignty of the Kingdom of Morocco over the Western Sahara. Available online: https://trumpwhitehouse.archives.gov/presidential-actions/proclamation-recognizing-sovereignty-kingdom-morocco-western-sahara/ (accessed on 13 September 2022).
Figure 1. Map of the Northern part of Morocco and study sites. Subfigures show representative precipitation relative to the average from 1980–2018 (CHIRPS) and example images from DigitalGlobe (spatial resolution of 0.5 m). Red dots show nine sites of olive orchards from paper-based maps available from the Green Morocco Plan.
Figure 1. Map of the Northern part of Morocco and study sites. Subfigures show representative precipitation relative to the average from 1980–2018 (CHIRPS) and example images from DigitalGlobe (spatial resolution of 0.5 m). Red dots show nine sites of olive orchards from paper-based maps available from the Green Morocco Plan.
Remotesensing 15 00141 g001
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lin, C.; Jin, Z.; Mulla, D.; Ghosh, R.; Guan, K.; Kumar, V.; Cai, Y. Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740. Remote Sens. 2023, 15, 141. https://doi.org/10.3390/rs15010141

AMA Style

Lin C, Jin Z, Mulla D, Ghosh R, Guan K, Kumar V, Cai Y. Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740. Remote Sensing. 2023; 15(1):141. https://doi.org/10.3390/rs15010141

Chicago/Turabian Style

Lin, Chenxi, Zhenong Jin, David Mulla, Rahul Ghosh, Kaiyu Guan, Vipin Kumar, and Yaping Cai. 2023. "Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740" Remote Sensing 15, no. 1: 141. https://doi.org/10.3390/rs15010141

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop