<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>An important factor threatening global security is climate change and its impact on changing rainfall patterns and seasonal temperature variability. For this reason, farmers and crop scientists are striving to detect plant stress as soon as possible and introduce preventive measures so that key decisions in maintaining plant health are made in a timely way. Currently, multispectral images acquired from UAVs (Unmanned Aerial Vehicles) make it possible to provide objective and reliable information related to the state of agro-ecosystems, the dynamics of changes occurring on them and the monitoring of natural resources in a rapid and non-contact method. In the present study, the suitability of low-altitude multispectral imaging for proper stress detection in plants was assessed. The botanical garden in Kielce, a site with a high biodiversity of plant specimens, was chosen as the testing ground. In this study, four spectral indexes maps were analysed in the form of: NDVI (Normalized Difference Vegetation Index), NDRE (Normalized Difference Red-Edge Index), GNDVI (Green Normalized Difference Vegetation Index) and the less frequently used PSRI (Plant Senescence Reflectance Index) for the assessment of plant health. PSRI values > 0.50 clearly identified areas of high stress, in contrast to the other spectral indices analysed in this study. The study confirmed the suitability of the PSRI for conducting monitoring activities in areas with varying crop characteristics in an efficient and rapid approach.</p>
</abstract>

An important factor threatening global security is climate change and its impact on changing rainfall patterns and seasonal temperature variability. For this reason, farmers and crop scientists are striving to detect plant stress as soon as possible and introduce preventive measures so that key decisions in maintaining plant health are made in a timely way. Currently, multispectral images acquired from UAVs (Unmanned Aerial Vehicles) make it possible to provide objective and reliable information related to the state of agro-ecosystems, the dynamics of changes occurring on them and the monitoring of natural resources in a rapid and non-contact method. In the present study, the suitability of low-altitude multispectral imaging for proper stress detection in plants was assessed. The botanical garden in Kielce, a site with a high biodiversity of plant specimens, was chosen as the testing ground. In this study, four spectral indexes maps were analysed in the form of: NDVI (Normalized Difference Vegetation Index), NDRE (Normalized Difference Red-Edge Index), GNDVI (Green Normalized Difference Vegetation Index) and the less frequently used PSRI (Plant Senescence Reflectance Index) for the assessment of plant health. PSRI values > 0.50 clearly identified areas of high stress, in contrast to the other spectral indices analysed in this study. The study confirmed the suitability of the PSRI for conducting monitoring activities in areas with varying crop characteristics in an efficient and rapid approach.

Assessment of the Suitability of Spectral Indices for Detecting Areas of Increased Stress among Plants – A Case Study of the Botanical Garden in Kielce

Structure and Environment

This work is licensed under the Creative Commons Attribution 3.0 Public License.

An important factor threatening global security is climate change and its impact on changing rainfall patterns and seasonal temperature variability. For this...

Assessment of the Suitability of Spectral Indices for Detecting Areas of Increased Stress among Plants – A Case Study of the Botanical Garden in Kielce

Publicado en línea: 02 feb 2024

Páginas: 253 - 268

DOI: https://doi.org/10.30540/sae-2023-022

Palabras clave
Remote Sensing (RS), botanical garden, crop monitoring, stress detection, Plant Senescence Reflectance Index (PSRI), Unmanned Aerial Vehicle (UAV), Precision Agriculture (PA)

© 2023 Szymon Sylwester Sobura, published by Sciendo

This work is licensed under the Creative Commons Attribution 3.0 Public License.

Assessment of the Suitability of Spectral Indices for Detecting Areas of Increased Stress among Plants – A Case Study of the Botanical Garden in Kielce

Publicado en línea: 02 feb 2024

Páginas: 253 - 268

DOI: https://doi.org/10.30540/sae-2023-022

Palabras claveRemote Sensing (RS), botanical garden, crop monitoring, stress detection, Plant Senescence Reflectance Index (PSRI), Unmanned Aerial Vehicle (UAV), Precision Agriculture (PA)

© 2023 Szymon Sylwester Sobura, published by Sciendo

This work is licensed under the Creative Commons Attribution 3.0 Public License.

Palabras clave
Remote Sensing (RS), botanical garden, crop monitoring, stress detection, Plant Senescence Reflectance Index (PSRI), Unmanned Aerial Vehicle (UAV), Precision Agriculture (PA)