Dataset describing riparian vegetation trends of selected areas in Baja California Sur, Mexico from 2016-2024

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Authors: Britt W. Smith, Laura M. Norman
Cited by: 0

Abstract

This dataset includes raster images of trends in normalized difference vegetation index (NDVI) derived from Sentinel-2 imagery for riparian vegetation within the Los Planes watershed of Baja California Sur, Mexico. A model was first trained to identify riparian vegetation using cloud-masked Sentinel-2 imagery from 2016-2024 and stream delineations derived from a 10m Japanese Aerospace Exploration Agency (JAXA) digital surface model. 30 riparian and 30 non-riparian point locations were used to train the random forest classifier. With each image classified, we took the average number of riparian classifications for each pixel across the time series. Pixels that passed a 60% threshold of being classified as riparian vegetation were considered riparian vegetation. The NDVI for each riparian vegetation pixel was calculated across the time series. Two different trend measurements, Sen's slope and a harmonic regression, were used to identify the NDVI trend for each riparian vegetation pixel.

Fields of Study & Subjects

Remote Sensing in Agriculture Remote-Sensing Image Classification Hydrology and Sediment Transport Processes

Publication details

Journal / source
USGS DOI Tool Production Environment
Publication date
12 February 2026
Language
EN
Document type
Dataset