Normalized Difference Vegetation Index (NDVI)

"The normalized difference vegetation index (NDVI) is a standardized index allowing you to generate an image displaying greenness, also known as relative biomass. This index takes advantage of the contrast of characteristics between two bands from a multispectral raster dataset—the chlorophyll pigment absorption in the red band and the high reflectivity of plant material in the near-infrared (NIR) band.

The documented and default NDVI equation is as follows:

NDVI = (NIR - Red) / (NIR + Red)

    NIR = pixel values from the near-infrared band
    Red = pixel values from the red band

This index outputs values between -1.0 and 1.0." (ESRI, 2018)

Sources

"Indices gallery". ArcGIS Pro, ESRI. 2018. 
http://pro.arcgis.com/en/pro-app/help/data/imagery/indices-gallery.htm.
Accessed February 1, 2019.

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Digital Earth Africa: Agriculture and Food Security

Digital Earth Africa learning platform

This learning platform helps users understand the significance of Earth observations, explore Digital Earth Africa datasets through an interactive map, and get started on the basics of python coding for spatial analysis.

Digital Earth Africa makes Earth observation (EO) data readily available, delivering decision-ready products to the African continent. Data generated by Digital Earth Africa will provide valuable insights for better decision-making across many areas, including resource management, food security and urbanisation.

Space-based Solution

Collaborating actors (stakeholders, professionals, young professionals or Indigenous voices)
Suggested solution

Note: this description is work in progress developed by the collaborating entities in a workshop. If you would like to contribute reach out to office@space4water.org, or your trusted Space4Water point of contact.

1. Data collection

To collect historic and high-resolution up-to-date imagery over the area, UNOOSA contacted the Land and Information New Zealand Data Service, which provided both historic aerial imagery and LIDAR data sources.

Historic data for the relevant land patch can be accessed via the Retrolens New Zealand Service.

Up-to-date aerial photos of the area can be accessed here at the New Zealand Data Service. Tile 503 and 603 are the ones of interest.

Relevant Landsat data available from 1989. For the study area, Landsat 7 data is available from 2 July 1999, and Landsat 4 from 2 February 1989.

HydroSHEDS: The core data products of HydroSHEDS are a series of gridded datasets designed for use in hydro-environmental model development and custom GIS applications. Data layers include the original digital elevation model (DEM) that underpins HydroSHEDS, a hydrologically conditioned version of the DEM, the derived flow direction and flow accumulation grids, as well as land mask and sink grids. These data products form the digital foundation of the derived secondary data products. HydroSHEDS core data products are currently available for HydroSHEDS v1 only, which is mostly based on SRTM elevation data. HydroSHEDS v2, which is derived from TanDEM-X elevation data, is currently under development and is scheduled for release in 2022.

A digital elevation model (DEM) is available at 30m resolution by Copernicus is availble at the Terrascope website.

2. Vegetation identification

Using NDVI allows for identifying the type of vegetation but not the specific species. One can see whether the type of vegetation has changed from trees to grassland, but specific plants cannot be seen.

Retrolense provides aerial photographs taken from an airplane at which the relevant bands for NDVI calcluation (infrared and red) are missing.

We can examine vegetation cover over the last 30+ years using NDVI with Landsat data.

For future reference/documentation purposes, if the Maori community can conduct a community survey in which elders are asked for tree or animal species on the land for the past 40 to 50 years, it can be benficial. These could be used as ground data.

A study called Aerial photography for assessing vegetation change: a review of applications and the relevance of findings for Australian vegetation history by Fensham and Fairfax published in 2022 in the Australian Journal of Botany and on the CSIRO page is accessible here.

 

Links to Space4Water resources that are part of the solution
Keywords (for the solution)
Climate Zone (addressed by the solution)
Habitat (addressed by the solution)
Region/Country (the solution was designed for, if any)
Relevant SDGs