Landsat NDVI timeseries data for nTabamhlophe fire exclusion site 2000 - 2023
Description
Manuscript Title: Through to bush and back to grass in 84yrs: the effect of reintroducing fire and grazing after 56years of exclusion at nTabamhlophe (White Mountain) Research Station ------------------------------------------------------------ The data was developed to examine the hypothesis that the fire exclusion plot at nTabamhlophe continued to progress towards characteristics of a pure grassy landscape after the year 2000. The goal was to show a downward trajectory in NDVI, indicating a shift from values typical of a wooded landscape—rich in trees and woody vegetation—to values more representative of grassland. Data diction --------------------- Year: This column represents the year when the data was recorded. It contains integer values (e.g., 2000). Month_Number: This column corresponds to the numerical representation of the month (1 for January, 2 for February, and so on). It also contains integer values. Month_Name: Here, the column contains the full name of the month (e.g., “February” or “March”). The data type for this column is typically a string (text). Day: This column represents the day of the month when the NDVI (Normalized Difference Vegetation Index) measurement was taken. It contains integer values (e.g., 18). NDVI: The NDVI is a vegetation index that quantifies the greenness or health of vegetation. It ranges from -1 to 1, with higher values indicating healthier vegetation. The data type for this column is typically a floating-point number (decimal).
Files
Steps to reproduce
In the GEE Code Editor, the region of interest (ROI) was delineated using a square shape overlaying the fence line of the nTabamhlophe Long-term Fire Exclusion Plot. Landsat images were loaded and filtered to exclude those with cloud coverage exceeding 5% of the ROI. The satellite imagery was then confined to the specified date range. NDVI was calculated using the formula (NIR - RED) / (NIR + RED). This calculation was used to reduce the image collection to mean NDVI values for the plot, with two images per month corresponding to the 15-day overpass interval. The resulting NDVI values were exported to Google Drive as a CSV file. The downloaded CSV file was subsequently opened in Excel for further analysis of the NDVI data.