March 2021

D-CAT offers a wide range of imagery-derived vegetation indices that are used in various applications, including agriculture monitoring, offering food producers and farmers invaluable insights to help them sustainably manage their crops and soil.

Vegetation indices are measures of vegetation activity based on changes in spectral reflectance of the vegetation which can be accurately measured by optical sensors on satellites. These changes are known to correspond to factors of importance to crop and pasture production, and so a wide range of vegetation indices have been developed for agriculture applications. All provide relative measures, typically on a scale of -1 to 1, which can be plotted to show variations over time or mapped to show variations across land areas. 

The applicability of vegetation indices can be general, but also specific to species, vegetation types and local conditions. However, all can provide important information to enhance area-scale and field assessment of different vegetation and agronomic measures. An example of the generic use of a vegetation index is leaf area index (LAI) as a measure of canopy abundance / biomass for any vegetation, whereas the same index can also be utilised with viticulture knowledge to help predict fruit abundance or with agronomic expertise to inform final application before canopy closure.

Hence, vegetation indices provide invaluable decision aids to producers on the farm as well as providing insights for land and business owners who may be remote from sites. Evaluation of vegetation, including tree crops, to inform and aid agricultural decisions can be conducted using the spatial and temporal variation of such indices. In addition, the use of vegetation indices means that issues can be alerted before they are visible by eye, health assessments can be made efficiently, and benchmarking completed quickly and easily. 

D-CAT offers a wide variety of vegetation indices which are proven and ready to use worldwide. Whether for agricultural production applications, or as part of your sustainability plan, they have a part to play and real value to add. 

As an example of how vegetation indices can provide very wide area monitoring for macro-scale analysis of vegetation trends, and not just farm-level intelligence, the animation below is given. An area of 100km by 100km is shown over Argentina through its 2019/2020 growing season, and the increase in vegetation abundance is clear from sowing towards harvest (light greens through to dark greens). Very few brown regions are visible as the area is an agricultural region with very little non-vegetative areas over the time period chosen.

Argentina


The graph below shows the amount of abundance in this area during the 2019/2020 growing season.


The full set of this example data is available for free on AWS Data Exchange (ADX). D-CAT offers a service, fulfilled through ADX that can supply this data for any area or region.

Benefits

By using this service clients:

Example Applications

Agriculture

From determining when best to harvest, to detecting plant stress early. Monitoring crops with remote imagery gives farmers incredible insights into how to best manage their crops.

Forest fire monitoring

Vegetation indices are very useful for quantifying the extent of damage done by forest wildfires. This can help determine which locations have experienced the most severe damage which can save valuable time and improve the recovery process. They also offer an excellent method of monitoring the recovery of the vegetation and wider environment.

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