NDVIanalyses

NDVIanalyses refers to the use of the Normalized Difference Vegetation Index (NDVI) in quantitative assessments of vegetation condition, biomass, land-cover change, and related ecological or agricultural phenomena. NDVI is calculated from satellite or airborne sensor reflectances in the near-infrared and red bands using the formula (NIR − Red) / (NIR + Red), producing values typically between −1 and +1 that indicate vegetation vigor and density.

Common applications include crop monitoring, drought assessment, phenology tracking, land-use classification, and carbon stock estimation. Analysts use single-date NDVI maps to assess spatial variability and time-series NDVI to detect seasonal cycles, trends, and abrupt changes such as deforestation or regrowth. NDVI-based products support decision-making in precision agriculture, natural resource management, and climate impact studies.

NDVIanalyses usually require preprocessing steps such as atmospheric correction, geometric alignment, cloud and shadow masking, and sensor calibration to ensure comparability across dates and platforms. Popular data sources include Landsat, Sentinel-2, MODIS, and high-resolution commercial imagery. Common tools and environments for conducting NDVI analyses are GIS software, Google Earth Engine, and programming libraries for Python and R.

Limitations include sensitivity to soil background, saturation in very dense canopies, atmospheric effects, and variability between sensors and viewing geometries. Complementary indices (for example EVI) and field validation are often used to address these shortcomings and improve interpretation.