Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017
Analyzing time series data with remote sensing provides a better understanding of vegetation dynamics, since previous conditions and changes that have occurred over a given period are known. The objective of this paper was to analyze the current status and recent advances in the use of time series...
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Facultad de Ciencias Agrarias-UNCuyo
2020
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| Acceso en línea: | https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2981 |
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I11-R107article-29812020-07-03T13:03:57Z Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 Zúñiga-Vásquez, José Manuel Aguirre-Salado, Carlos Arturo Pompa-García, Marín fenología cobertura de la tierra análisis multi-temporal de teledetección análisis espacio-temporal fusión de imágenes phenology land cover analysis of multi-temporal remote sensing spatio-temporal analysis image fusion Analyzing time series data with remote sensing provides a better understanding of vegetation dynamics, since previous conditions and changes that have occurred over a given period are known. The objective of this paper was to analyze the current status and recent advances in the use of time series data obtained from remote sensors for vegetation monitoring. A systematic search of scientific papers was performed and 167 papers were found, published during the period 1996 to 2017. No significant difference in the amount of years analyzed was found between time series analyzed with a single sensor and those analyzed with a combination of several sensors (i.e. Landsat and SPOT, Landsat and Sentinel, among others). However, the combination of data from different sensors (fusion of images) can improve the quality of the results. Specialattention must also be given to the fusion of optical and radar data, since this offers more unique spectral and structural information for land cover and land use assessments. Highlights Remote sensing provides a better understanding of vegetation dynamics. The number of vegetation monitoring papers published using time series data are becoming more frequent. The fusion of Landsat and Sentinel-2 satellite data shows great potential for timely monitoring of rapid changes. The fusion of optical and radar data points to a new trend in remote sensing, including the use of geospatial open data sources. Analyzing time series data with remote sensing provides a better understanding of vegetation dynamics, since previous conditions and changes that have occurred over a given period are known. The objective of this paper was to analyze the current status and recent advances in the use of time series data obtained from remote sensors for vegetation monitoring. A systematic search of scientific papers was performed and 167 papers were found, published during the period 1996 to 2017. No significant difference in the amount of years analyzed was found between time series analyzed with a single sensor and those analyzed with a combination of several sensors (i.e. Landsat and SPOT, Landsat and Sentinel, among others). However, the combination of data from different sensors (fusion of images) can improve the quality of the results. Specialattention must also be given to the fusion of optical and radar data, since this offers more unique spectral and structural information for land cover and land use assessments. Highlights Remote sensing provides a better understanding of vegetation dynamics. The number of vegetation monitoring papers published using time series data are becoming more frequent. The fusion of Landsat and Sentinel-2 satellite data shows great potential for timely monitoring of rapid changes. The fusion of optical and radar data points to a new trend in remote sensing, including the use of geospatial open data sources. Facultad de Ciencias Agrarias-UNCuyo 2020-06-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/html https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2981 Revista de la Facultad de Ciencias Agrarias UNCuyo; Vol. 52 No. 1 (2020): January-June; 175-189 Revista de la Facultad de Ciencias Agrarias UNCuyo; Vol. 52 Núm. 1 (2020): Enero-Junio; 175-189 1853-8665 0370-4661 eng https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2981/2130 https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2981/2618 |
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Universidad Nacional de Cuyo |
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Revista de la Facultad de Ciencias Agrarias |
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Revista de la Facultad de Ciencias Agrarias |
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| language |
eng |
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Online |
| author |
Zúñiga-Vásquez, José Manuel Aguirre-Salado, Carlos Arturo Pompa-García, Marín |
| spellingShingle |
Zúñiga-Vásquez, José Manuel Aguirre-Salado, Carlos Arturo Pompa-García, Marín Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 fenología cobertura de la tierra análisis multi-temporal de teledetección análisis espacio-temporal fusión de imágenes phenology land cover analysis of multi-temporal remote sensing spatio-temporal analysis image fusion |
| author_facet |
Zúñiga-Vásquez, José Manuel Aguirre-Salado, Carlos Arturo Pompa-García, Marín |
| author_sort |
Zúñiga-Vásquez, José Manuel |
| title |
Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 |
| title_short |
Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 |
| title_full |
Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 |
| title_fullStr |
Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 |
| title_full_unstemmed |
Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 |
| title_sort |
monitoring vegetation using remote sensing time series data: a review of the period 1996-2017 |
| description |
Analyzing time series data with remote sensing provides a better understanding of vegetation dynamics, since previous conditions and changes that have occurred over a given period are known. The objective of this paper was to analyze the current status and recent advances in the use of time series data obtained from remote sensors for vegetation monitoring. A systematic search of scientific papers was performed and 167 papers were found, published during the period 1996 to 2017. No significant difference in the amount of years analyzed was found between time series analyzed with a single sensor and those analyzed with a combination of several sensors (i.e. Landsat and SPOT, Landsat and Sentinel, among others). However, the combination of data from different sensors (fusion of images) can improve the quality of the results. Specialattention must also be given to the fusion of optical and radar data, since this offers more unique spectral and structural information for land cover and land use assessments.
Highlights
Remote sensing provides a better understanding of vegetation dynamics.
The number of vegetation monitoring papers published using time series data are becoming more frequent.
The fusion of Landsat and Sentinel-2 satellite data shows great potential for timely monitoring of rapid changes.
The fusion of optical and radar data points to a new trend in remote sensing, including the use of geospatial open data sources.
|
| publisher |
Facultad de Ciencias Agrarias-UNCuyo |
| publishDate |
2020 |
| url |
https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2981 |
| topic |
fenología cobertura de la tierra análisis multi-temporal de teledetección análisis espacio-temporal fusión de imágenes phenology land cover analysis of multi-temporal remote sensing spatio-temporal analysis image fusion |
| topic_facet |
fenología cobertura de la tierra análisis multi-temporal de teledetección análisis espacio-temporal fusión de imágenes phenology land cover analysis of multi-temporal remote sensing spatio-temporal analysis image fusion |
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AT zunigavasquezjosemanuel monitoringvegetationusingremotesensingtimeseriesdataareviewoftheperiod19962017 AT aguirresaladocarlosarturo monitoringvegetationusingremotesensingtimeseriesdataareviewoftheperiod19962017 AT pompagarciamarin monitoringvegetationusingremotesensingtimeseriesdataareviewoftheperiod19962017 |
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1800220891013971968 |
