High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques
Normalized difference vegetation index (NDVI) derived from satellites has been ubiquitously utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations in NDVI time series because of the atmospheric disturbance, cloud cover, sensor failure, and so on. It is crucial...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0303243421003470 |
| _version_ | 1828197779776733184 |
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| author | Shuang Li Liang Xu Yinghong Jing Hang Yin Xinghua Li Xiaobin Guan |
| author_facet | Shuang Li Liang Xu Yinghong Jing Hang Yin Xinghua Li Xiaobin Guan |
| author_sort | Shuang Li |
| collection | DOAJ |
| description | Normalized difference vegetation index (NDVI) derived from satellites has been ubiquitously utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations in NDVI time series because of the atmospheric disturbance, cloud cover, sensor failure, and so on. It is crucial to remove the noises prior to further applications. Numerous techniques have been proposed to alleviate this issue in the last few decades. To the best of our knowledge, there hasn’t been a systematical study to summarize and analyze the status of NDVI time series reconstruction techniques since 1980s. As a result, our goal is to recapitulate the current approaches for reconstructing high-quality NDVI time series, followed by an interpretation on the principle, merits and demerits of different kinds of methods. They were mainly classified into temporal-based methods, frequency-based methods and hybrid methods. The evaluation approaches on the quality of NDVI reconstruction were introduced, accompanied with the future development tendency. |
| first_indexed | 2024-04-12T10:25:16Z |
| format | Article |
| id | doaj.art-c69c8df8b49b48438c9552e3b2997284 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-12T10:25:16Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-c69c8df8b49b48438c9552e3b29972842022-12-22T03:36:59ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322021-12-01105102640High-quality vegetation index product generation: A review of NDVI time series reconstruction techniquesShuang Li0Liang Xu1Yinghong Jing2Hang Yin3Xinghua Li4Xiaobin Guan5School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaThird Institute of Oceanography, MNR, Xiamen 361005, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; Corresponding authors.School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China; Corresponding authors.Normalized difference vegetation index (NDVI) derived from satellites has been ubiquitously utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations in NDVI time series because of the atmospheric disturbance, cloud cover, sensor failure, and so on. It is crucial to remove the noises prior to further applications. Numerous techniques have been proposed to alleviate this issue in the last few decades. To the best of our knowledge, there hasn’t been a systematical study to summarize and analyze the status of NDVI time series reconstruction techniques since 1980s. As a result, our goal is to recapitulate the current approaches for reconstructing high-quality NDVI time series, followed by an interpretation on the principle, merits and demerits of different kinds of methods. They were mainly classified into temporal-based methods, frequency-based methods and hybrid methods. The evaluation approaches on the quality of NDVI reconstruction were introduced, accompanied with the future development tendency.http://www.sciencedirect.com/science/article/pii/S0303243421003470NDVI time seriesHigh-quality dataReconstructionSpatio-temporal |
| spellingShingle | Shuang Li Liang Xu Yinghong Jing Hang Yin Xinghua Li Xiaobin Guan High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques International Journal of Applied Earth Observations and Geoinformation NDVI time series High-quality data Reconstruction Spatio-temporal |
| title | High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques |
| title_full | High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques |
| title_fullStr | High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques |
| title_full_unstemmed | High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques |
| title_short | High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques |
| title_sort | high quality vegetation index product generation a review of ndvi time series reconstruction techniques |
| topic | NDVI time series High-quality data Reconstruction Spatio-temporal |
| url | http://www.sciencedirect.com/science/article/pii/S0303243421003470 |
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