What question did this study set out to answer?

To assess the feasibility and methodological challenges of using temporal variations in Normalized Difference Vegetation Index (NDVI) data to classify global land cover types.

November 1, 1994International Journal of Remote Sensing

NDVI-derived land cover classifications at a global scale

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To assess the feasibility and methodological challenges of using temporal variations in Normalized Difference Vegetation Index (NDVI) data to classify global land cover types.
Analyzed a coarse spatial resolution (one-by-one degree) satellite dataset of monthly NDVI values spanning the year 1987.
Implemented a supervised maximum likelihood classification algorithm to distinguish eleven broad global cover types based on vegetation phenological profiles.
Demonstrated that satellite-derived NDVI time series can capture distinct phenological patterns to delineate eleven global land cover classes.
Identified critical scaling challenges, including seasonal phase shifts across hemispheres, spectral blending of cover type gradients, and an absence of systematic global ground truth data.

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Implication

Methodological study demonstrates the feasibility of global land cover mapping using monthly NDVI time series, highlighting the need for finer spatial resolution and systematic validation.

Cite This Study

DeFries et al. (1994) studied this question.

synapsesocial.com/papers/69d985488988aeabbe685981 https://doi.org/10.1080/01431169408954345

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Implication

Methodological study demonstrates the feasibility of global land cover mapping using monthly NDVI time series, highlighting the need for finer spatial resolution and systematic validation.

NDVI-derived land cover classifications at a global scale

Key Points

Discussion

Implication

Cite This Study

NDVI-derived land cover classifications at a global scale

Key Points

Discussion

Implication

Cite This Study

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