Detailed Investigation of Spectral Vegetation Indices for Fine Field-Scale Phenotyping

Abstract

Spectral vegetation indices (VIs) are a well-known and widely used method for crop state estimation. These technologies have great importance for plant state monitoring, especially for agriculture. The main aim is to assess the performance level of the selected VIs calculated from space-borne multispectral imagery and point-based field spectroscopy in application to crop state estimation. The results obtained indicate that space-borne VIs react on phenology. This feature makes it an appropriate data source for monitoring crop development, crop water needs and yield prediction. Field spectrometer VIs were sensitive for estimating pigment concentration and photosynthesis rate. Yet, a hypersensitivity of field spectral measures might lead to a very high variability of the calculated values. The results obtained in the second part of the presented study were reported on crop state estimated by 17 VIs known as sensitive to plant drought. An alternative approach for identification early stress by VIs proposed in this study is Principal Component Analysis (PCA). The results show that PCA has identified the degree of similarity of the different states and together with reference stress states from the control plot clearly estimated stress in the actual irrigated field, which was hard to detect by VIs values only.

Comparing Remote Sensing and In Situ Analyses on assessing the Phenology of Test Wheat Plants as Means for Optimizing Data Collection in Precision Agriculture

“…One of the strengths of this research is the frequency of measurement, which is better than the current study. However, Polivova (2021) pointed out that the optical sensor vegetation indices are highly variable compared to the vegetation indices of multispectral images. Bareth et al (2016) also compare uncalibrated multispectral images vegetation index with the NDVI from the optical spectrometer.…”

Analysis of declining trends in sugarcane yield at Wonji-Shoa Sugar Estate, Central Ethiopia

“…Increasing crop productivity is a key objective of the United Nations’ 2030 Agenda for Sustainable Development (Jhariya et al, 2019; Polivova & Brook, 2021). Previous research has shown that a 0.6–1.0% increase in crop productivity can reduce the proportion of households living in extreme poverty by 0.6–1.2% (Liliane & Charles, 2020; Thirtle et al, 2001).…”

A simplified approach to satellite-based monitoring system of sugarcane plantation to manage yield decline at Wonji-Shoa Sugar Estate, central Ethiopia

“…In this regard, satellite-based crop monitoring offers the best opportunity since it enables plantation personnel to safely, effectively, and efficiently monitor crop health [ 21 ] and thus facilitates early intervention and management of potential problems before they spread widely [ 22 ]. As stated by Polivova and Brook [ 23 ], crop stresses detected in advance permit rapid adjustments in cropping system calendars and thus prevent yield penalties that may occur.…”