Multispectral remote sensing for site-specific nitrogen fertilizer management

Abstract

-The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R 2 =0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

Analysis of Vegetation Indices to Determine Nitrogen Application and Yield Prediction in Maize (Zea mays L.) from a Standard UAV Service

“…This does not increase grain yield but, instead, wastes fertilizer, increases costs, and can cause nitrate pollution [8]. This problem has led farmers, scientist and politicians to explore how to improve N efficiency, reduce N inputs and prevent water and soil pollution associated with maize production [9][10][11].…”

“…In recent years, the use of chlorophyll meters (CM), which measure leaf chlorophyll content to estimate N nutrition status, has increased among researchers and farmers [10,11]. Hawkings et al [12] found that the adjusted R 2 of the relationship between CM readings and the nitrogen rate difference (ND) for the economic optimum nitrogen rate (EONR) was 0.76 for a maize-maize rotation.…”

“…This map of maize N content also related well to the real maize N content obtained using traditional destructive measurement techniques (R 2 = 0.70). In this respect, multispectral satellite images, such as Aster and QuickBird, and manned-flight airborne images have been used to assess irrigated maize N status at V12 (12 leaves with visible leaf collars) and later stages of crop growth, as well as to determine field variability for in-season N management in order to complement ground-based measurements [9,10,17]. In fact, most previous studies have shown that both real and false colour images acquired between growth stages V7 and VT could be used to predict N deficiencies and N requirements in maize [18].…”

“…Despite the apparent advantages offered by remote sensing from satellites and manned aircraft, the cost of obtaining high-resolution multispectral images for relatively small areas is considered an important drawback [10,21]. At present, this can be overcome by using unmanned aerial vehicles (UAV), mounted with multispectral cameras.…”

Influence of leaf chemistry on dietary choice and habitat quality of koala (Phascolarctos cinereus) populations in southwest Queensland

“…No studies mapping DigN with satellite remote sensing were found during a literature search, but a wide range of studies have used satellite-derived data (from WorldView-2, SPOT, Hyperion, Aster and IKONOS) to map N in crops and trees (Reyniers and Vrindts 2006, Bagheri et al 2013, Boegh et al 2013, Adjorlolo et al 2014, Zandler et al 2015. These studies tested the correlation between N and the potential spectral indices, which spectral transformation of two or more spectral bands contain absorption features of N (e.g.…”