Abstract
This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having unique phenological and topographic characteristics. Cross-comparison of the pheno-classes with the 2001 National Land Cover Database indicates that the new map contains additional phenological and climate information. The pheno-class framework may be a suitable basis for the development of an Advanced Very High Resolution Radiometer (AVHRR)-MODIS NDVI translation algorithm and for various biogeographic studies.
Highlights
Phenology is the study of the timing of recurring biological events [1] and examines the causes and consequences of biotic and environmental interactions
The main goal of this study is to introduce a new geographical framework that identifies a set of regions with similar phenological patterns based on land surface phenological metrics and elevation gradients
This study introduces a new geographic framework that is based on phenology and elevation characteristics
Summary
Phenology is the study of the timing of recurring biological events [1] and examines the causes and consequences of biotic and environmental interactions. The phenology of ecosystems and its connection to climate is a key to understanding ongoing global climate and land surface changes [5]. Phenology has historically been studied using ground-based observations of the timing of vegetation and animal pheno-phases such as germination, flowering, hibernation, and bird migration. Satellite observations provide continuous spatial and temporal coverage enabling scientists to assess and model seasonal dynamics and phenological variability of landscapes across large areas [6,7,8,9,10,11,12,13,14,15,16]. Time series of NDVI data derived from visible red and near-infrared bands [17] have been used to calculate phenological metrics [12,13,15,18]
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