NDVI_2016 runs from 2016-01-01T00:00:00 UTC to 2016-02-02T00:00:00 UTC

NDVI_2016 runs from 2016-01-01T00:00:00 to 2016-02-02T00:00:00 UTC every 16 days. The LAMMA Consortium maintains an archive of NDVI (Normalised Difference Vegetation Index) images from the MODIS (MODerate-resolution Imaging Spectroradiometer) satellite. The sensor (spectrometer capable of observing the planet with a frequency of 1-2 days through a set of 36 spectral bands) is part of the Earth satellite, one of the new remote sensing platforms built by NASA (National Aeronautics and Space Administration) dedicated to global environmental monitoring. The product “index of vegetation” derives from the elaboration of the data MODIS Terra surface reflectances (MOD09) correct for the atmosphere, i.e. scattering, ozone absorption and aerosols. The product that constitutes the archive of the LAMMA Consortium is the MODIS/Terra Vegetation Indices 16-Day L3 Global 250 m SIN Grid (MOD13Q1) generated by the global NDVI algorithm that refers to the existing archive derived from the NOAA-AVHRR satellite (National Oceanic and Atmospheric Administration — Advanced Very High Resolution Radiometer). The images have a time resolution of 16 days as they derive from the composition of the daily scenes using the CV-MVC (Constrained View Maximum Value Composite) method. The spatial resolution is 250 m. The images acquired before being archived are appropriately processed for the correction of outliers (anomalous values, often due to cloud cover) using a method of reconstruction of the data based on the values derived from the moving average starting from the two previous scenes and the next two of the image to be corrected. Many studies have shown that the vegetation index derived from satellite images is closely related to the fraction of radiation absorbed by plants in the photosynthetic process, and is therefore an excellent indicator of their production activity. Through the use of low-resolution NDVI images it is possible to estimate the variations of this parameter in response to any trends in the main limiting factors such as rains and temperatures. The use of vegetation indices, therefore, is an efficient analysis tool to evaluate phenomena of vegetation degradation due to drought, soil erosion, desertification, etc. and individual events such as fires, logging, floods. The use of NDVI images is of great interest, moreover, to detect the dynamics of plant cover compared to changes in biogeochemical cycles and in particular of carbon. Applications, in this latter case, are increasingly given the growing interest of the scientific community as a result of the Kyoto Protocol and the studies on global warming: it has become increasingly important to identify and quantify the role of forests (and in general all terrestrial ecosystems) within the global carbon cycle for the role of carbon reservoir (sink). Some of the most common applications include: — biogeochemical and hydrological models — monitoring of agricultural crops and production forecasts — vegetational characterisation — monitoring of land use change — estimation of CO2 flows — dynamics of plant cover NDVI_2016 runs from 2016-01-01T00:00:00 to 2016-02-02T00:00:00 UTC every 16 days. The LAMMA Consortium maintains an archive of NDVI (Normalised Difference Vegetation Index) images from the MODIS (MODerate-resolution Imaging Spectroradiometer) satellite. The sensor (spectrometer capable of observing the planet with a frequency of 1-2 days through a set of 36 spectral bands) is part of the Earth satellite, one of the new remote sensing platforms built by NASA (National Aeronautics and Space Administration) dedicated to global environmental monitoring. The product “index of vegetation” derives from the elaboration of the data MODIS Terra surface reflectances (MOD09) correct for the atmosphere, i.e. scattering, ozone absorption and aerosols. The product that constitutes the archive of the LAMMA Consortium is the MODIS/Terra Vegetation Indices 16-Day L3 Global 250 m SIN Grid (MOD13Q1) generated by the global NDVI algorithm that refers to the existing archive derived from the NOAA-AVHRR satellite (National Oceanic and Atmospheric Administration — Advanced Very High Resolution Radiometer). The images have a time resolution of 16 days as they derive from the composition of the daily scenes using the CV-MVC (Constrained View Maximum Value Composite) method. The spatial resolution is 250 m. The images acquired before being archived are appropriately processed for the correction of outliers (anomalous values, often due to cloud cover) using a method of reconstruction of the data based on the values derived from the moving average starting from the two previous scenes and the next two of the image to be corrected. Many studies have shown that the vegetation index derived from satellite images is closely related to the fraction of radiation absorbed by plants in the photosynthetic process, and is therefore an excellent indicator of their production activity. Through the use of low-resolution NDVI images it is possible to estimate the variations of this parameter in response to any trends in the main limiting factors such as rains and temperatures. The use of vegetation indices, therefore, is an efficient analysis tool to evaluate phenomena of vegetation degradation due to drought, soil erosion, desertification, etc. and individual events such as fires, logging, floods. The use of NDVI images is of great interest, moreover, to detect the dynamics of plant cover compared to changes in biogeochemical cycles and in particular of carbon. Applications, in this latter case, are increasingly given the growing interest of the scientific community as a result of the Kyoto Protocol and the studies on global warming: it has become increasingly important to identify and quantify the role of forests (and in general all terrestrial ecosystems) within the global carbon cycle for the role of carbon reservoir (sink). Some of the most common applications include: — biogeochemical and hydrological models — monitoring of agricultural crops and production forecasts — vegetational characterisation — monitoring of land use change — estimation of CO2 flows — dynamics of plant cover NDVI_2016 runs from 2016-01-01T00:00:00 to 2016-02-02T00:00:00 UTC every 16 days. The LAMMA Consortium maintains an archive of NDVI (Normalised Difference Vegetation Index) images from the MODIS (MODerate-resolution Imaging Spectroradiometer) satellite. The sensor (spectrometer capable of observing the planet with a frequency of 1-2 days through a set of 36 spectral bands) is part of the Earth satellite, one of the new remote sensing platforms built by NASA (National Aeronautics and Space Administration) dedicated to global environmental monitoring. The product “index of vegetation” derives from the elaboration of the data MODIS Terra surface reflectances (MOD09) correct for the atmosphere, i.e. scattering, ozone absorption and aerosols. The product that constitutes the archive of the LAMMA Consortium is the MODIS/Terra Vegetation Indices 16-Day L3 Global 250 m SIN Grid (MOD13Q1) generated by the global NDVI algorithm that refers to the existing archive derived from the NOAA-AVHRR satellite (National Oceanic and Atmospheric Administration — Advanced Very High Resolution Radiometer). The images have a time resolution of 16 days as they derive from the composition of the daily scenes using the CV-MVC (Constrained View Maximum Value Composite) method. The spatial resolution is 250 m. The images acquired before being archived are appropriately processed for the correction of outliers (anomalous values, often due to cloud cover) using a method of reconstruction of the data based on the values derived from the moving average starting from the two previous scenes and the next two of the image to be corrected. Many studies have shown that the vegetation index derived from satellite images is closely related to the fraction of radiation absorbed by plants in the photosynthetic process, and is therefore an excellent indicator of their production activity. Through the use of low-resolution NDVI images it is possible to estimate the variations of this parameter in response to any trends in the main limiting factors such as rains and temperatures. The use of vegetation indices, therefore, is an efficient analysis tool to evaluate phenomena of vegetation degradation due to drought, soil erosion, desertification, etc. and individual events such as fires, logging, floods. The use of NDVI images is of great interest, moreover, to detect the dynamics of plant cover compared to changes in biogeochemical cycles and in particular of carbon. Applications, in this latter case, are increasingly given the growing interest of the scientific community as a result of the Kyoto Protocol and the studies on global warming: it has become increasingly important to identify and quantify the role of forests (and in general all terrestrial ecosystems) within the global carbon cycle for the role of carbon reservoir (sink). Some of the most common applications include: — biogeochemical and hydrological models — monitoring of agricultural crops and production forecasts — vegetational characterisation — monitoring of land use change — estimation of CO2 flows — dynamics of plant cover