Ittai Herrmann

SWIR-based spectral indices for assessing nitrogen content in potato fields

Nitrogen (N) is an essential element in plant growth and productivity, and N fertilizer is therefore of prime importance in cultivated crops. The amount and timing of N application has economic and environmental implications and is consequently considered to be an important issue in precision agriculture. Spectral indices derived from handheld, airborne and spaceborne spectrometers are used for assessing N content. The majority of these indices are based on indirect indicators, mostly chlorophyll content, which is proven to be physiologically linked to N content. The current research aimed to explore the performance of new N spectral indices dependent upon the shortwave infrared (SWIR) region (1200–2500 nm), and particularly the 1510 nm band because it is related directly to N content. Traditional nitrogen indices (NIs) and four proposed new SWIR-based indices were tested with canopy-level spectral data obtained during two growing seasons in potato experimental plots in the northwest Negev, Israel. Above-ground biomass samples were collected at the same location of the spectral sampling to provide in-situ N content data. The performance of all indices was evaluated by three methods: (1) correlations between the existing and proposed indices and N as well as correlations among the indices themselves; (2) the root mean square error prediction (RMSEP) of the N content; and (3) the indices relative sensitivity (S r) to the N content. The results reveal a firm advantage for the proposed SWIR-based indices in their ability to predict, and in their sensitivity to, N content. The best index is one that combines information from the 1510 and 660 nm bands but no significant differences were found among the new SWIR-based indices.

Field spectroscopy for weed detection in wheat and chickpea fields

Weed control is commonly performed by applying selective herbicides homogeneously over entire agricultural fields. However, applying herbicide only where needed could have economical and environmental benefits. The objective of this study was to apply remote sensing to the detection of grasses and broadleaf weeds among cereal and broadleaf crops. Spectral relative reflectance values at both leaf and canopy scales were obtained by field spectroscopy for four plant categories: wheat, chickpea, grass weeds, and broadleaf weeds. Total reflectance spectra of leaf tissues for botanical genera were successfully classified by general discriminant analysis (GDA). The total canopy spectral classification by GDA for specific narrow bands was 95 ± 4.19% for wheat and 94 ± 5.13% for chickpea. The total canopy spectral classification by GDA for future Vegetation and Environmental Monitoring on a New Micro-Satellite (VENμS) bands was 77 ± 8.09% for wheat and 88 ± 6.94% for chickpea, and for the operative satellite Advanced Land Imager (ALI) bands was 78 ± 7.97% for wheat and 82 ± 8.22% for chickpea. Within the critical period for weed control, an overall classification accuracy of 87 ± 5.57% was achieved for >5% vegetation coverage in a wheat field, thereby providing potential for implementation of herbicide applications. Qualitative models based on wheat, chickpea, grass weed, and broadleaf weed spectral properties have high-quality classification and prediction potential that can be used for site-specific weed management.

Spectral monitoring of two-spotted spider mite damage to pepper leaves

Two-spotted spider mites (TSSM; Tetranychus urticae Koch) cause significant damage to crops and yields, in the field as well as in greenhouses. By feeding, TSSM destroy chloroplast-containing cells; this damage can be spectrally detected in the reflectance of the visible and near-infrared regions. This study focuses on hyperspectral reflectance data of greenhouse pepper (Capsicum annuum) leaves, obtained by integrated sphere. The reflectance data were transformed into vegetation indices allowing early TSSM damage detection by separation between leaf damage levels. One-way analysis of variance of coupled damage levels was applied to each of the vegetation indices. We concluded that early identification of TSSM greenhouse pepper leaf damage can be obtained by multispectral means. Furthermore, the proposed methods may identify the damage on the upper side of the leaves although the TSSM feed on the underside of leaves.

Approximating the average daily surface albedo with respect to soil roughness and latitude

The present study explores the diurnal variations in blue-sky albedo (α) of soils under clear sky conditions with respect to surface roughness. Three roughness levels of ploughed and unploughed soil surfaces, developed from the same loessial material, were examined. The relation between α of the surfaces and the solar zenith angle, determined during the experiment, enabled us to predict the diurnal α variation of the surfaces throughout the year at a given latitude, between 75° S and 75° N. The optimal time (T O) for measuring the soil albedo by an instantaneous observation was considered as the best represented time for the daily averaged value within an error lower than ±2%. It was found that the T O, falling at different times depending on the soil surface roughness, limits the possibilities of data achievement by remote-sensing satellites along one of their sun-synchronous orbits.

An Overview of the Regional Experiments for Land-atmosphere Exchanges 2012 (REFLEX 2012) Campaign

The REFLEX 2012 campaign was initiated as part of a training course on the organization of an airborne campaign to support advancement of the understanding of land-atmosphere interaction processes. This article describes the campaign, its objectives and observations, remote as well as in situ. The observations took place at the experimental Las Tiesas farm in an agricultural area in the south of Spain. During the period of ten days, measurements were made to capture the main processes controlling the local and regional land-atmosphere exchanges. Apart from multi-temporal, multi-directional and multi-spatial space-borne and airborne observations, measurements of the local meteorology, energy fluxes, soil temperature profiles, soil moisture profiles, surface temperature, canopy structure as well as leaf-level measurements were carried out. Additional thermo-dynamical monitoring took place at selected sites. After presenting the different types of measurements, some examples are given to illustrate the potential of the observations made.

Soil surface illumination at micro-relief scale and soil BRDF data collected by a hyperspectral camera

The results of the paper draw attention to the fact that the hyperspectral image of soil surface at micro-relief scale may display variation in the soil spectral shape due to illumination conditions of the surface. The image of an extremely rough cultivated soil surface, very deeply ploughed, was obtained by a hyperspectral camera, in the range of 0.4–1.0 μm with 0.67–0.74 nm spectral resolution. It was found that the soil reflectance spectra of the studied surface, illuminated by the direct sunbeams, are clearly convex with distinct absorption features. Furthermore, the soil normalized reflectance spectra were used to distinguish the subtlety of the analysed shaded soil spectra shape. They show that depressions caused by the absorption features of O2 and H2O, contained in the atmosphere above directly illuminated soil fragments, transform into peaks, if the same soil is deeply shaded.

Hyperspectral Technologies for Assessing Seed Germination and Trifloxysulfuron-methyl Response in Amaranthus palmeri (Palmer Amaranth)

Weed infestations in agricultural systems constitute a serious challenge to agricultural sustainability and food security worldwide. Amaranthus palmeri S. Watson (Palmer amaranth) is one of the most noxious weeds causing significant yield reductions in various crops. The ability to estimate seed viability and herbicide susceptibility is a key factor in the development of a long-term management strategy, particularly since the misuse of herbicides is driving the evolution of herbicide response in various weed species. The limitations of most herbicide response studies are that they are conducted retrospectively and that they use in vitro destructive methods. Development of a non-destructive method for the prediction of herbicide response could vastly improve the efficacy of herbicide applications and potentially delay the evolution of herbicide resistance. Here, we propose a toolbox based on hyperspectral technologies and data analyses aimed to predict A. palmeri seed germination and response to the herbicide trifloxysulfuron-methyl. Complementary measurement of leaf physiological parameters, namely, photosynthetic rate, stomatal conductence and photosystem II efficiency, was performed to support the spectral analysis. Plant response to the herbicide was compared to image analysis estimates using mean gray value and area fraction variables. Hyperspectral reflectance profiles were used to determine seed germination and to classify herbicide response through examination of plant leaves. Using hyperspectral data, we have successfully distinguished between germinating and non-germinating seeds, hyperspectral classification of seeds showed accuracy of 81.9 and 76.4%, respectively. Sensitive and resistant plants were identified with high degrees of accuracy (88.5 and 90.9%, respectively) from leaf hyperspectral reflectance profiles acquired prior to herbicide application. A correlation between leaf physiological parameters and herbicide response (sensitivity/resistance) was also demonstrated. We demonstrated that hyperspectral reflectance analyses can provide reliable information about seed germination and levels of susceptibility in A. palmeri. The use of reflectance-based analyses can help to better understand the invasiveness of A. palmeri, and thus facilitate the development of targeted control methods. It also has enormous potential for impacting environmental management in that it can be used to prevent ineffective herbicide applications. It also has potential for use in mapping tempo-spatial population dynamics in agro-ecological landscapes.