A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization
Climate change and population growth risk the world’s food supply. Annual crop yield production is one of the most crucial components of the global food supply. Moreover, the COVID-19 pandemic has stressed global food security, production, and supply chains. Using biomass estimation as a reliable yi...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/22/5633 |
| _version_ | 1797464105378906112 |
|---|---|
| author | Hazhir Bahrami Heather McNairn Masoud Mahdianpari Saeid Homayouni |
| author_facet | Hazhir Bahrami Heather McNairn Masoud Mahdianpari Saeid Homayouni |
| author_sort | Hazhir Bahrami |
| collection | DOAJ |
| description | Climate change and population growth risk the world’s food supply. Annual crop yield production is one of the most crucial components of the global food supply. Moreover, the COVID-19 pandemic has stressed global food security, production, and supply chains. Using biomass estimation as a reliable yield indicator, space-based monitoring of crops can assist in mitigating these stresses by providing reliable product information. Research has been conducted to estimate crop biophysical parameters by destructive and non-destructive approaches. In particular, researchers have investigated the potential of various analytical methods to determine a range of crop parameters using remote sensing data and methods. To this end, they have investigated diverse sources of Earth observations, including radar and optical images with various spatial, spectral, and temporal resolutions. This paper reviews and analyzes publications from the past 30 years to identify trends in crop monitoring research using remote sensing data and tools. This analysis is accomplished through a systematic review of 277 papers and documents the methods, challenges, and opportunities frequently cited in the scientific literature. The results revealed that research in this field had increased dramatically over this study period. In addition, the analyses confirmed that the normalized difference vegetation index (NDVI) had been the most studied vegetation index to estimate crop parameters. Moreover, this analysis showed that wheat and corn were the most studied crops, globally. |
| first_indexed | 2024-03-09T18:03:11Z |
| format | Article |
| id | doaj.art-9acd2469c0bf42f5820f1422911079fb |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T18:03:11Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-9acd2469c0bf42f5820f1422911079fb2023-11-24T09:47:59ZengMDPI AGRemote Sensing2072-42922022-11-011422563310.3390/rs14225633A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop CharacterizationHazhir Bahrami0Heather McNairn1Masoud Mahdianpari2Saeid Homayouni3Centre Eau Terre Environnement, Institut National de la Recherche Scientifique, Québec, QC G1K 9A9, CanadaOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, CanadaC-CORE, St. John’s, NL A1B 3X5, CanadaCentre Eau Terre Environnement, Institut National de la Recherche Scientifique, Québec, QC G1K 9A9, CanadaClimate change and population growth risk the world’s food supply. Annual crop yield production is one of the most crucial components of the global food supply. Moreover, the COVID-19 pandemic has stressed global food security, production, and supply chains. Using biomass estimation as a reliable yield indicator, space-based monitoring of crops can assist in mitigating these stresses by providing reliable product information. Research has been conducted to estimate crop biophysical parameters by destructive and non-destructive approaches. In particular, researchers have investigated the potential of various analytical methods to determine a range of crop parameters using remote sensing data and methods. To this end, they have investigated diverse sources of Earth observations, including radar and optical images with various spatial, spectral, and temporal resolutions. This paper reviews and analyzes publications from the past 30 years to identify trends in crop monitoring research using remote sensing data and tools. This analysis is accomplished through a systematic review of 277 papers and documents the methods, challenges, and opportunities frequently cited in the scientific literature. The results revealed that research in this field had increased dramatically over this study period. In addition, the analyses confirmed that the normalized difference vegetation index (NDVI) had been the most studied vegetation index to estimate crop parameters. Moreover, this analysis showed that wheat and corn were the most studied crops, globally.https://www.mdpi.com/2072-4292/14/22/5633crop characterizationbiomassleaf area indexyieldagricultureremote sensing |
| spellingShingle | Hazhir Bahrami Heather McNairn Masoud Mahdianpari Saeid Homayouni A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization Remote Sensing crop characterization biomass leaf area index yield agriculture remote sensing |
| title | A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization |
| title_full | A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization |
| title_fullStr | A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization |
| title_full_unstemmed | A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization |
| title_short | A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization |
| title_sort | meta analysis of remote sensing technologies and methodologies for crop characterization |
| topic | crop characterization biomass leaf area index yield agriculture remote sensing |
| url | https://www.mdpi.com/2072-4292/14/22/5633 |
| work_keys_str_mv | AT hazhirbahrami ametaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT heathermcnairn ametaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT masoudmahdianpari ametaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT saeidhomayouni ametaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT hazhirbahrami metaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT heathermcnairn metaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT masoudmahdianpari metaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization AT saeidhomayouni metaanalysisofremotesensingtechnologiesandmethodologiesforcropcharacterization |