Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resoluti...

This study in Western Ghats, India, investigates the relation between nesting sites of ants and a single remotely sensed variable: the Normalised Difference Vegetation Index (NDVI). We carried out sampling in 60 plots each measuring 30 x 30 m and recorded nest sites of 13 ant species. We found that NDVI values at the nesting sites varied considerably between individual species and also between ...

Medium Resolution NDVI( Normalized Difference Vegetation Index) from different sensor systems such as Landsat, SPOT, ASTER, CBERS and HJ-1A/1B satellites provide detailed spatial information for studies of ecosystems, vegetation biophysics, and land cover. Limitation of sensor designs, cloud contamination, and sensor failure highlighted the need to normalize and integrate NDVI from multiple sen...

The global land-surface temperature (LST) and normalized difference vegetation index (NDVI) products retrieved fromModerate Resolution Imaging Spectroradiometer (MODIS) data in 2001 were used in this study. The yearly peak valuesof NDVI data at 5km grids were used to define six NDVI peak zones from -0.2 to 1 in steps of 0.2, and the monthlyNDVI values at each grid were sorted in dec...

Consistent Normalized Difference of Vegetation Index (NDVI) time series, as paramount and powerful tool, can be used to monitor ecological resources that are being altered by climate and human impacts, since its temporal evolution is strongly linked to changes in the state of land surface. However, the noise caused mainly by cloud contamination, heavy aerosol, atmospheric variability and signal...

The Normalized Difference Vegetation Index (NDVI) was used to characterize the seasonal variation of land cover over the Northeastern Brazil (NEB) with the NOAA/NASA Pathfinder AVHRR Land (PAL) data set. Twenty years of monthly spatial-aggregated NDVI climatology was determined by calculating lower, mean, and upper NDVI values using a 0.5 lat by 0.5 log grid cell size. The results indicated tha...

The data used in the present study is a 21-year GIMMS-NDVI dataset, surface data on phenology of birch, and temperature data from meteorological stations, all for the period 1982 to 2002. For each pixel a 21-year mean and a mean of peak NDVI value was computed. Threshold values related to this mean, and mean of peak NDVI values, which show the best correlations with the phenological field data ...

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend e...

Sampling of herbivorous stink bugs in southeastern U.S. cotton remains problematic. Remote sensing was explored to improve sampling of these pests and associated boll injury. Two adjacent 14.5-ha cotton fields were grid sampled in 2011 and 2012 by collecting stink bug adults and bolls every week during the third, fourth, and fifth weeks of bloom. Satellite remote sensing data were collected dur...