&lt;title&gt;Use of remote sensing to determine plant health and productivity&lt;/title&gt;

Chong, Chuan Shing; Basart, J. P.; Nutter, Forrest W.; Tylka, Gregory L.; Guan, Jie

doi:10.1117/12.455133

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Gittelson et al (1996) found that substituting green band for red band in NDVI gives better estimation of green biomass because green band is more sensitive to the chlorophyll concentrations. Vegetative indices have been widely used to relate the reflectance of various major crops to ground leaf cover as related to in-season N fertilization requirements for corn (Ma et al 1996;Sripada et al 2005) and wheat (Mahey et al 1991;Stone et al 1996), early prediction of soybean yield (Ma et al 2001), crop nutrient deficiencies (Blackmer and Schepers 1996) and crop health (Hart and Myers 1968;Toler et al 1981;Chong et al 2002). Similarly Shawn and Kelley (2005) used color-infrared and NDVI images as a scouting tool for soybean crop anomalies such as IDC, herbicide damage, and patches of weeds.…”

Section: Introductionmentioning

confidence: 99%

Remote sensing of soybean canopy as a tool to map high pH, calcareous soils at field scale

Rogovska

Blackmer

2008

Precision Agric

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Soybean (Glycine max Merr.) is extensively grown in areas of the US Corn Belt where soils often range from relatively acid (pH \ 6) to alkaline, calcareous. Iron availability decreases with increase in pH, consequently, soybean can suffer from iron deficiency chlorosis on high pH, calcareous areas of the field. The extent of those areas sometimes can be significant, but they often occur in complex and discontinuous patterns. The objective of the research was to explore how remote sensing of soybean canopies and GIS technologies could be used to map and quantitatively describe the extent of high pH, calcareous soils at field scale. Aerial images that consisted of visible red, green, blue, and near infrared bands were used to calculate green normalized difference vegetative index (GNDVI) and to guide plant and soil sampling at 10 fields during 2003 and 2004 growing seasons. Ten to 18 sampling areas were selected on each field to include a wide range in GNDVI values. Soil samples were analyzed for pH and calcium carbonate equivalent (CCE). Plant samples were used to estimate grain yields. Soil pH and CCE were significantly correlated with GNDVI values in eight and seven sites, respectively. A previously developed alkalinity stress index (ASI), which combines pH and CCE in one value, was significantly related to GNDVI at all 10 sites. Remote sensing of soybean canopy was shown to be a promising tool that can be used to quantitatively describe distribution of alkaline soils at field scale.

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Section: Introductionmentioning

confidence: 99%

Remote sensing of soybean canopy as a tool to map high pH, calcareous soils at field scale

Rogovska

Blackmer

2008

Precision Agric

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“…Plant analyses are mainly focused on the chlorophyll content [25] or substances contained in plants [91] and, consequently, the condition of plants [24,27]. Research on the growth and development of vegetation can be carried out in both strictly controlled laboratory conditions [29,79,92,93] and using satellite techniques [42,44,46,[49][50][51]56,59,61,62,[64][65][66]68,71,[75][76][77][78]80,88, or other means of transporting remote sensing devices (UAV, airships, airplanes) [43,47,54,55,65,84,[108][109][110]118,[140][141][142][143][144][145][146][147][148]…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

2022

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Analyses of climate change based on point observations indicate an extension of the plant growing season, which may have an impact on plant production and functioning of natural ecosystems. Analyses involving remote sensing methods, which have added more detail to results obtained in the traditional way, have been carried out only since the 1980s. The paper presents the results of a bibliometric analysis of papers related to the growing season published from 2000–2021 included in the Web of Science database. Through filtering, 285 publications were selected and subjected to statistical processing and analysis of their content. This resulted in the identification of author teams that mostly focused their research on vegetation growth and in the selection of the most common keywords describing the beginning, end, and duration of the growing season. It was found that most studies on the growing season were reported from Asia, Europe, and North America (i.e., 32%, 28%, and 28%, respectively). The analyzed articles show the advantage of satellite data over low-altitude and ground-based data in providing information on plant vegetation. Over three quarters of the analyzed publications focused on natural plant communities. In the case of crops, wheat and rice were the most frequently studied plants (i.e., they were analyzed in over 30% and over 20% of publications, respectively).

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Application of remote sensing to plant health and productivity determination

Chong

Basart

et al. 2002

SPIE Proceedings

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It has been found that a close relationship exists between the spectral reflectance and the health as well as the productivity of soybean canopies. Basing on this property, a remote sensing method was used to assess the plant productivity and health, which was able to cover a large area simultaneously. In this project, aerial images and reflectance measurements were obtained from two soybean fields located in Story Country, Iowa during summer 2000 and 2001. Aerial image were taken on both infrared band and color band. An eight-band radiometer was used to obtain the reflectance reading at ground level, which ranged from 460-nm to 810-nm.A study on aerial-radiometer data relation for two continuous years was carried out. The reflectance measurement from radiometer served as ground truth. Also, the calibration procedure for aerial image was applied. Because the atmospheric distortion became more pronounced when the aerial image was taken at higher altitude. Scattering and absorption will affect the image intensity which indirectly affect our analysis. The red, green and blue ground cloths were put beside the fields when the aerial image was taken. They are used as references to evaluate color distortion in the red, blue and green bands respectively.

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<title>Use of remote sensing to determine plant health and productivity</title>

Cited by 4 publications

References 8 publications

Remote sensing of soybean canopy as a tool to map high pH, calcareous soils at field scale

Remote sensing of soybean canopy as a tool to map high pH, calcareous soils at field scale

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

Application of remote sensing to plant health and productivity determination

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