A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River
Wetlands are one of the most productive yet altered ecosystems due to human activities across the world. They rely largely on their water flow to provide several ecosystem functions. Then, to develop a land use plan that allows a productive use maintaining the ecological integrity it is critical to...
| Autores principales: | , |
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| Formato: | info:ar-repo/semantics/artículo |
| Lenguaje: | Inglés |
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Gerencia de Comunicación e Imagen Institucional, DG-SICyP, INTA
2020
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| Materias: | |
| Acceso en línea: | http://ria.inta.gob.ar/contenido/ria-46-no-1-abril-2020 http://hdl.handle.net/20.500.12123/7307 |
| _version_ | 1855035833999949824 |
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| author | Durante, Martin Di Bella, Carlos Marcelo |
| author_browse | Di Bella, Carlos Marcelo Durante, Martin |
| author_facet | Durante, Martin Di Bella, Carlos Marcelo |
| author_sort | Durante, Martin |
| collection | INTA Digital |
| description | Wetlands are one of the most productive yet altered ecosystems due to human activities across the world. They rely largely on their water flow to provide several ecosystem functions. Then, to develop a land use plan that allows a productive use maintaining the ecological integrity it is critical to understand the flooding patterns. In that sense, the capability of remote sensors to estimate water cover for large areas at detailed spatial and temporal scales can help to develop managerial decision tools. However, the temporal and spatial variation of water components may alter it spectral properties. We studied the capability of different MODIS derived spectral indices to estimate water cover or water presence-absence. The study region was the Paraná Delta River, which is a 2 Mha wetland area. Between all the models evaluated, one based on the spectral index NDWI1 ((Red – SWIR) / (Red + SWIR)) was the most accurate. A NDWI1 = -0.2 threshold allowed to separate those pixels with less than those with more than 60% of water cover with an accuracy of 91%. By this model, we described the flooding patterns of different landscape units of the region during the last 12 years and classified the region according to the impact of ordinary and extraordinary flooding events. We consider this information can help to improve the knowledge about the hydrodynamics, monitor the impact of some activities and develop a more sustainable regional planning. |
| format | info:ar-repo/semantics/artículo |
| id | INTA7307 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Gerencia de Comunicación e Imagen Institucional, DG-SICyP, INTA |
| publisherStr | Gerencia de Comunicación e Imagen Institucional, DG-SICyP, INTA |
| record_format | dspace |
| spelling | INTA73072020-05-26T12:52:40Z A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River Durante, Martin Di Bella, Carlos Marcelo Tierras Húmedas Inundación Imágenes por Satélites Espectrorradiómetro de Imágenes de Resolución Moderada Agua Wetlands Flooding Satellite Imagery Moderate Resolution Imaging Spectroradiometer Water Humedales MODIS Delta del Paraná, Argentina Wetlands are one of the most productive yet altered ecosystems due to human activities across the world. They rely largely on their water flow to provide several ecosystem functions. Then, to develop a land use plan that allows a productive use maintaining the ecological integrity it is critical to understand the flooding patterns. In that sense, the capability of remote sensors to estimate water cover for large areas at detailed spatial and temporal scales can help to develop managerial decision tools. However, the temporal and spatial variation of water components may alter it spectral properties. We studied the capability of different MODIS derived spectral indices to estimate water cover or water presence-absence. The study region was the Paraná Delta River, which is a 2 Mha wetland area. Between all the models evaluated, one based on the spectral index NDWI1 ((Red – SWIR) / (Red + SWIR)) was the most accurate. A NDWI1 = -0.2 threshold allowed to separate those pixels with less than those with more than 60% of water cover with an accuracy of 91%. By this model, we described the flooding patterns of different landscape units of the region during the last 12 years and classified the region according to the impact of ordinary and extraordinary flooding events. We consider this information can help to improve the knowledge about the hydrodynamics, monitor the impact of some activities and develop a more sustainable regional planning. Los humedales están entre los ecosistemas más productivos y, a su vez, están fuertemente alterados por el ser humano. Los múltiples servicios que proveen dependen en gran medida del flujo de agua. Por ello, para desarrollar un plan de uso de la tierra que permita un uso productivo manteniendo la integridad ecológica es fundamental comprender los patrones de inundación. En ese sentido, la capacidad de los sensores remotos de estimar la cobertura de agua en áreas grandes a escalas espaciales y temporales detalladas contribuirían a desarrollar herramientas que favorezcan la toma de decisiones. Sin embargo, la variación temporal y espacial de los componentes del agua puede alterar sus propiedades espectrales. Se estudió la capacidad de diferentes índices espectrales derivados del sensor MODIS para estimar la cobertura de agua o la presencia/ ausencia de agua. La región de estudio fue el Delta del Río Paraná, un humedal de 2 millones de hectáreas. Entre todos los modelos evaluados, uno basado en el índice espectral NDWI1 ((Rojo - SWIR) / (Rojo + SWIR)) fue el más preciso. Un valor umbral de NDWI1 = -0,2 permitió separar píxeles con menos de 60% de cobertura de agua de aquellos con más del 60% con una precisión del 91%. Mediante este modelo se describieron los patrones de inundación de diferentes unidades de paisaje de la región durante los últimos 12 años y se clasificó la región de acuerdo al impacto de los eventos de inundación ordinarios y extraordinarios. Consideramos que esta información puede ayudar a mejorar el conocimiento sobre la hidrodinámica, monitorear el impacto de algunas actividades y desarrollar una planificación regional más sostenible. EEA Concepción del Uruguay Fil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; Argentina Fil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina 2020-05-26T12:40:19Z 2020-05-26T12:40:19Z 2020-04 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://ria.inta.gob.ar/contenido/ria-46-no-1-abril-2020 http://hdl.handle.net/20.500.12123/7307 0325-8718 1669-2314 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Gerencia de Comunicación e Imagen Institucional, DG-SICyP, INTA RIA 46 (1) : 96-107 (abril 2020) |
| spellingShingle | Tierras Húmedas Inundación Imágenes por Satélites Espectrorradiómetro de Imágenes de Resolución Moderada Agua Wetlands Flooding Satellite Imagery Moderate Resolution Imaging Spectroradiometer Water Humedales MODIS Delta del Paraná, Argentina Durante, Martin Di Bella, Carlos Marcelo A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River |
| title | A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River |
| title_full | A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River |
| title_fullStr | A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River |
| title_full_unstemmed | A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River |
| title_short | A MODIS based tool to assess inundation patterns: an example for the Paraná Delta River |
| title_sort | modis based tool to assess inundation patterns an example for the parana delta river |
| topic | Tierras Húmedas Inundación Imágenes por Satélites Espectrorradiómetro de Imágenes de Resolución Moderada Agua Wetlands Flooding Satellite Imagery Moderate Resolution Imaging Spectroradiometer Water Humedales MODIS Delta del Paraná, Argentina |
| url | http://ria.inta.gob.ar/contenido/ria-46-no-1-abril-2020 http://hdl.handle.net/20.500.12123/7307 |
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