NDVI – Ge-iSee Health Lab

Dataset Creator: Xin Liu
Email: liuxin_swpu@163.com
Affiliated Organization: &nbsp; Ge-iSEE Lab, University of Toronto, Ontario, Canada

16-Day Normalization Difference Vegetation Index (NDVI)

DATASET DESCRIPTION

The 16-day NDVI data over Ontario are available from 2005 to 2023. The data is provided in full-coverage gridded maps with a spatial resolution of 250 meters. These datasets are derived from the MODIS vegetation indices product, MYD13Q1, which are computed from atmospherically-corrected bi-directional surface reflectance that have been masked for water, clouds, heavy aerosols, and cloud shadows.

NDVI, which ranges from -1 to 1 represents the difference between near-infrared and red light reflected by vegetation. Values closer to 1 indicate healthy, dense vegetation, while values near 0 suggest sparse or no vegetation. Negative values typically represent non-vegetated surfaces such as water, snow, or bare soil. NDVI is crucial for understanding the health and productivity of ecosystems and for detecting trends and anomalies in plant growth. It also plays a significant role in climate change analysis. These data have a wide range of applications, including agricultural monitoring, land use planning, environmental health analysis, and disaster management.

Data citation: Kamel Didan – University of Arizona, Alfredo Huete – University of Technology Sydney and MODAPS SIPS – NASA. (2015). MYD13Q1 MODIS/Aqua Vegetation Indices 16-Day L3 Global 250m SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD13Q1.006