Visualisation of blooming in an Amazonian tree species and canola crops
Normalized Difference Yellowness Index (NDYI)
A guest blog post by Mario Alberto Guzmán Soza
Foreword by Sentinel Hub
This post is part of a series of guest blog posts written by authors talking about their entries to the Sentinel Hub Custom Script Contest. The author is one of the winners of our special edition of the Contest — Climate Change — which ran from May to September 2022. The award for the second best custom script went to Mario Alberto Guzmán Soza. His script is available on our Custom Script Repository.
“The clearest way into the Universe is through a forest wilderness” — John Muir, (1938)
The main motivation for this script was to characterize the flowering of the species Schizolobium parahyba in the evergreen forest within the Noel Kempff Mercado National Park, one of the largest and best conserved protected areas in the department of Santa Cruz, Bolivia (Fig. 1). This event is not unknown to those who have visited the site during the flowering season, both in overflights and on the ground, however, its characterization through remote sensing is still pending. On the other hand, the phenology of canola (Brassica napus L.) in the northern hemisphere mainly, has been better studied through satellite images at different resolutions [2]-[4], both in its vegetative and reproductive stage (flowering), for the latter has been developed the normalized difference yellowness index (NDYI), which is better able to measure the productivity of crops in Bloom than with other more extended indexes, such as NDVI, taking advantage of the difference in reflectivity in the blue and green bands of the yellow petals of their flowers [2]. As for the spectral signature of Schizolobium parahyba, it is very similar to that of canola crops in bloom, which was an advantage when applying it locally. Despite its usefulness, this index does not appear in most lists of vegetation indices usually used in remote sensing.
Some important facts about Schizolobium parahyba (Fig. 2), this species is distributed in a large part of the South American and Bolivian Amazon, it blooms annually with the arrival of winter, usually coinciding with the dry season or the time of least rainfall, from May to July. This species is deciduous, loses its leaves at the time of flowering, can reach a height of 40 m, also has a large crown, and yellow inflorescences which are very prominent in the flowering season [1]. These characteristics make it easy to detect in images from optical satellites such as Sentinel-2, even when the trees are scattered. Another aspect to highlight is that climatic variations can alter the arrival of the flowering season of Schizolobium parahyba, this can be considered an indicator of climate change easily detectable with multispectral images of medium resolution in the Amazonian forest.
Canola crops are widespread in Canada and China, and are economically important as a source of edible oil and biofuel feedstock. Based on studies in these countries, several spectral indices were proposed to measure crop productivity at peak flowering [3]-[4], one of which is the NDYI. This index facilitates the discrimination of the flowering peak of both canola crops and Schizolobium parahyba trees in bloom, taking advantage of the contrast between the blue and green bands (bands B02 and B03 of the MSI sensor of the Sentinel-2 satellite) by applying the formula ((Blue — Green) / (Blue + Green)), this scheme is applied in many other indices to discriminate or highlight different attributes on the ground. The reflectance of canola in flowering stage as well as of other objects on the ground are shown in (Fig. 3), Schizolobium parahyba shows a very similar spectral behaviour. The script with this index was applied to Sentinel-2 L1C images (Top-of-atmosphere reflectance), although lacking atmospheric correction, they present fewer artifacts than Sentinel-2 L2B images, which reduces false positives. However, when applying the script before and after flowering in both canola crops and Schizolobium parahyba trees, discrimination becomes more difficult as the contrast between the blue and green bands decreases.
An example of the application of the script is shown in Fig. 4, using as background a true-color composite of a Sentinel-2 L1C image dated June 16, 2022, during the flowering season of Schizolobium parahyba, the image corresponds to an area of the Noel Kempff Mercado National Park in Santa Cruz, Bolivia. The NDYI is applied on the blue and green bands and values less than 0.02 are represented, so that a large part of the individual Schizolobium parahyba trees in flower can be visualised. Another example of the application of the script, extracted from reference [4], shows similar results (Fig. 5), discriminating canola crops in the flowering stage in an important production region in China.
The main idea in developing this script was to show a subtle yet appealing natural phenomenon in one of the most pristine regions of Bolivia by applying knowledge from remote sensing studies in regions of the world dominated by extensive canola cultivation. To achieve this, the tools and data offered by Sentinel Hub and EO Browser, as well as the resources and guides for their use, were of great worth, as the platform made it possible to analyse images from all over the world and from different dates in a quick and intuitive way. In addition, the basic information on the NDYI index and the species Schizolobium parahyba (known locally as Serebó) obtained from the references was an important source of knowledge without which this script would not have been possible.
REFERENCES
[1] Justiniano, M. J., Pariona, W., Fredericksen, T. S., & Nash, D. (2001). Ecología y silvicultura de especies menos conocidas: Serebó o Sombrerillo Schizolobium parahyba (Vell.) SF Blake Caesalpiniaceae (№634.973749 E19). Proyecto de Manejo Forestal Sostenible, Santa Cruz (Bolivia). https://pdf.usaid.gov/pdf_docs/Pnacw358.pdf
[2] Sulik, J. J. & Long, D. S. (2016). Spectral considerations for modeling yield of canola. Remote Sensing of Environment, 184, 161–174. https://doi:10.1016/j.rse.2016.06.016
[3] Tian, H. Chen, T. Li, Q. Mei, Q.Wang, S. Yang, M.Wang, Y. Qin, Y. A Novel Spectral Index for Automatic Canola Mapping by Using Sentinel-2 Imagery. Remote Sens. 2022, 14, 1113. https://doi.org/10.3390/rs14051113
[4] Zang, Y.; Chen, X.; Chen, J.; Tian, Y.; Shi, Y.; Cao, X.; Cui, X. Remote Sensing Index for Mapping Canola Flowers Using MODIS Data. Remote Sens. (2020.) 12, 3912. https://doi.org/10.3390/rs12233912
The Sentinel Hub team would like to thank Mario Alberto for his participation in the Sentinel Hub Custom Script Contest.
We recommend the Sentinel Hub Educational page and the Custom Scripts webinar to learn more about satellite imagery and custom scripts. You can also visit a dedicated topic in the Sentinel Hub Forum for more information. We’d also like to invite you to take a look at the other entries submitted to the Sentinel Hub Custom Script Contests, which can be found here.
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