M.S. University of Hawaii at Manoa 2013.Includes bibliographical references.Improving our understanding of Earth's terrestrial environmental changes requires longterm data records constructed from multiple satellite sensors. Recently, a multi-sensor normalized difference vegetation index (NDVI) translation algorithm has been developed for the Land Long-Term Data Record (LTDR) NDVI data, and used to converted a historic LTDR Advanced Very High Resolution Radiometer (AVHRR/2) NDVI (1981--1999) dataset into a LTDR Moderate Resolution Imaging Spectroradiometer (MODIS) (2000--present) compatible NDVI. The objectives of this study were to develop a methodology to evaluate the continuity of nonoverlapping NDVI products and to assess the performanc...
We developed a novel spatio-temporal fusion method to downscale the AVHRR NDVI products to the Moder...
The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) ha...
AVHRR data record is well alive and continue to improve and be used by a large land user community.M...
The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and thos...
Advanced Very High Resolution Radiometer (AVHRR) data with their long-term (1981-current) global cov...
Advanced Very High Resolution Radiometer (AVHRR) data with their long-term (1981-current) global cov...
The earth surface is monitored periodically by numerous satellite sensors which have different spect...
Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acqui...
Land surface temperature (LST) products of two different sensors – the Advanced Very High Resolution...
(LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments fo...
The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing ...
To evaluate accuracy of low resolution vegetation mapping for hydrological purposes, a comparative s...
Land surface temperature (LST) products of two different sensors – the Advanced Very High Resolution...
Remote sensing of long-term vegetation monitoring relies on the analysis of multisensor and multitem...
Global products of remote sensing Normalized Difference Vegetation Index (NDVI) are critical to asse...
We developed a novel spatio-temporal fusion method to downscale the AVHRR NDVI products to the Moder...
The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) ha...
AVHRR data record is well alive and continue to improve and be used by a large land user community.M...
The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and thos...
Advanced Very High Resolution Radiometer (AVHRR) data with their long-term (1981-current) global cov...
Advanced Very High Resolution Radiometer (AVHRR) data with their long-term (1981-current) global cov...
The earth surface is monitored periodically by numerous satellite sensors which have different spect...
Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acqui...
Land surface temperature (LST) products of two different sensors – the Advanced Very High Resolution...
(LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments fo...
The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing ...
To evaluate accuracy of low resolution vegetation mapping for hydrological purposes, a comparative s...
Land surface temperature (LST) products of two different sensors – the Advanced Very High Resolution...
Remote sensing of long-term vegetation monitoring relies on the analysis of multisensor and multitem...
Global products of remote sensing Normalized Difference Vegetation Index (NDVI) are critical to asse...
We developed a novel spatio-temporal fusion method to downscale the AVHRR NDVI products to the Moder...
The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) ha...
AVHRR data record is well alive and continue to improve and be used by a large land user community.M...