The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
There is a scientific need to present an objective, spatially explicit and quantitative measure for sensitivity of vegetation toward precipitation in dry land. It will be helpful to understand the spatial and temporal interaction between them. In the study, we used 1km-monthly MODIS (Moderate Resolution Imaging Spectro-radiometer) NDVI time-series (2001–2013 year) as proxy to indicate temporal context...
The MODIS vegetation continuous fields (VCF) product has a percent tree cover layer; hence it could potentially be used to detect hotspots of deforestation and forest degradation, if data accuracy is high. This paper assesses the accuracy of the VCF percent tree cover layer by comparing it with land cover maps in two areas in Mexico. Specifically, we assess whether it can (1) differentiate forest...
SPOT-VGT NDVI datasets were used to analyze spatial and temporal changes of NDVI in vegetation growing seasons from 1998 to 2012 in Hebei Province, China. Vegetation types were come from MODIS product MCD12Q1 in 2004. The slope of liner regression equation was used to analyze the change trend of NDVI. The results showed that NDVIs in vegetation growing seasons showed a trend of fluctuating increase...
Traditional monitoring method of PM2.5 concentrations with field campaigns cannot accurately identify the spatial pattern of air pollution in urban areas. Remote sensing techniques have been applied to monitor the distribution of atmospheric particulate pollution. However, remotely sensed aerosol data products with low spatial-resolution cannot reveal the spatial variations of urban air pollution...
Forest ecosystems have a great potential in mitigation of carbon concentration in the atmosphere. Thus, generating its spatially explicit estimates at national, regional and global scale becomes very important. In Southern China, mapping forest carbon is often conducted by combining ground plot data from national forest inventory and remotely sensed images from Landsat and MODIS (Moderate Resolution...
Vegetation phenology tracks plants' lifecycle events, revealing the response of vegetation to global climate changes. Microwave backscatter is insensitive to signal degradation from solar illumination and atmospheric effects and could provide an alternative data source to optical remote sensing in phenology studies. In this study, we analyzed a time series of Ku-band radar backscatter measurements...
Wetland, as a unique ecological system with highest productive forces on earth, is one of the most important environmental resources, which are named “kidney of the earth”. Wetland mapping plays an important role on the scientific exploitation and conservation of wetland resources. It is convenient for a big range of wetlands extraction based on MODIS and one of the most significant advantages of...
Because of high spectral and temporal resolutions, large coverage and low cost, MODIS (Moderate Resolution Imaging Spectroradiometer) data has been widely used to extract information of forest types at regional, national and global scales. However, its coarse spatial resolution often leads to mixed pixels and impedes increasing classification accuracy of forest types. Spectral unmixing can, to some...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.