Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review.

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture.

A montane species treeline is defined by both temperature and drought effects on growth season length.

Montane treelines are defined by a threshold low temperature. However, what are the dynamics when the snow-free summer growth season coincides with a 6-month seasonal drought? We tested this fundamental question by measuring tree growth and leaf activity across elevations in Mt Hermon (2814 m; in Israel and Syria), where oak trees (Quercus look and Quercus boissieri) form an observed treeline at 1900 m. While in theory, individuals can be established at higher elevations (minimum daily temperature >6.

Continuous seasonal monitoring of nitrogen and water content in lettuce using a dual phenomics system.

The collection and analysis of large amounts of information on a plant-by-plant basis contributes to the development of precision fertigation and may be achieved by combining remote-sensing technology with high-throughput phenotyping methods. Here, lettuce plants (Lactuca sativa) were grown under optimal and suboptimal nitrogen and irrigation treatments from seedlings to harvest. A Plantarray system was used to calculate and log weights, daily transpiration, and momentary transpiration rates throughout the experiment.

Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting.

Potassium is a macro element in plants that is typically supplied to crops in excess throughout the season to avoid a deficit leading to reduced crop yield. Transpiration rate is a momentary physiological attribute that is indicative of soil water content, the plant's water requirements, and abiotic stress factors. In this study, two systems were combined to create a hyperspectral-physiological plant database for classification of potassium treatments (low, medium, and high) and estimation of momentary transpiration rate from hyperspectral images.

Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry.

Waste sorting is key to the process of waste recycling. Exact identification of plastic resin and wood products using Near Infrared (NIR, 1-1.7µm) sensing is currently in use.

Diurnal emissivity dynamics in bare versus biocrusted sand dunes.

Land surface emissivity (LSE) in the thermal infrared depends mainly on the ground cover and on changes in soil moisture. The LSE is a critical variable that affects the prediction accuracy of geophysical models requiring land surface temperature as an input, highlighting the need for an accurate derivation of LSE. The primary aim of this study was to test the hypothesis that diurnal changes in emissivity, as detected from space, are larger for areas mostly covered by biocrusts (composed mainly of cyanobacteria) than for bare sand areas.

Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm.

Land surface temperature (LST) is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS). This paper presents an adjustment of the split window algorithm (SWA) for TIRS that uses atmospheric transmittance and land surface emissivity (LSE) as inputs.