We present an efficient method for monitoring woody (i.e., evergreen) and herbaceous (i.e., ephemeral) vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI) time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI in the dry season was attributed to the woody vegetation (NDVIW). A constant NDVI value was assumed for soil background during this period. In the wet season, changes in NDVI were attributed to the development of ephemeral herbaceous vegetation in the f...
The main goal of the present work within the context of the EBONE objectives is to investigate if le...
The performance of vegetation indexes derived from moderate resolution imaging spectroradiometer (MO...
Several methods exist for extracting plant phenological information from time series of satellite da...
Time series of vegetation indices (e.g. normalized difference vegetation index [NDVI]) and color ind...
Monitoring the health of forests has for many years been done using manual observations. More rece...
Vegetation phenology is the chronology of periodic phases of development. It constitutes an efficien...
Vegetation phenology is the st udy of the timing of seasonal events that are considered to be the re...
Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different bio...
The main objective here is to investigate if leaf phenology indicators as derived from SPOT and MODI...
The Mediterranean region is one of the most vulnerable regions to climate change. The majority of cl...
Traditionally fuel maps are built in terms of 'fuel types', thus considering the structural characte...
Current models of vegetation dynamics using the normalized vegetation index (NDVI) time series perfo...
Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characte...
Monitoring vegetation structure and functioning is critical for modelling terrestrial ecosystems and...
Time series analysis of satellite data can be used to monitor temporal dynamics of forested environm...
The main goal of the present work within the context of the EBONE objectives is to investigate if le...
The performance of vegetation indexes derived from moderate resolution imaging spectroradiometer (MO...
Several methods exist for extracting plant phenological information from time series of satellite da...
Time series of vegetation indices (e.g. normalized difference vegetation index [NDVI]) and color ind...
Monitoring the health of forests has for many years been done using manual observations. More rece...
Vegetation phenology is the chronology of periodic phases of development. It constitutes an efficien...
Vegetation phenology is the st udy of the timing of seasonal events that are considered to be the re...
Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different bio...
The main objective here is to investigate if leaf phenology indicators as derived from SPOT and MODI...
The Mediterranean region is one of the most vulnerable regions to climate change. The majority of cl...
Traditionally fuel maps are built in terms of 'fuel types', thus considering the structural characte...
Current models of vegetation dynamics using the normalized vegetation index (NDVI) time series perfo...
Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characte...
Monitoring vegetation structure and functioning is critical for modelling terrestrial ecosystems and...
Time series analysis of satellite data can be used to monitor temporal dynamics of forested environm...
The main goal of the present work within the context of the EBONE objectives is to investigate if le...
The performance of vegetation indexes derived from moderate resolution imaging spectroradiometer (MO...
Several methods exist for extracting plant phenological information from time series of satellite da...