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PA—Precision Agriculture: Remote-Sensing and Mapping of Weeds in Crops

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TLDR
This paper summarizes the work completed to date to investigate the use of airborne remote-sensing for weed mapping in crops, and discusses application of the technology in precision weed management practices.
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This article is published in Journal of Agricultural Engineering Research.The article was published on 2001-02-01. It has received 726 citations till now. The article focuses on the topics: Precision agriculture & Weed.

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Citations
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Laplacian Eigenmaps for dimensionality reduction and data representation

TL;DR: In this article, the authors proposed a geometrically motivated algorithm for representing high-dimensional data, based on the correspondence between the graph Laplacian, the Laplace Beltrami operator on the manifold and the connections to the heat equation.
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On digital soil mapping

TL;DR: The generic framework, which the authors call the scorpanSSPFe (soil spatial prediction function with spatially autocorrelated errors) method, is particularly relevant for those places where soil resource information is limited.
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Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties

TL;DR: In this article, partial least squares regression (PLSR) was used to construct calibration models which were independently validated for the prediction of various soil properties from the soil spectra, including soil pHCa,p H w, lime requirement (LR), organic carbon (OC), clay, silt, sand, cation exchange capacity, exchangeable calcium (Ca), exchangeable aluminium (Al), nitrate-nitrogen (NO3-N), available phosphorus (PCol), exchangeability potassium (K) and electrical conductivity (EC).
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The application of small unmanned aerial systems for precision agriculture: a review

TL;DR: To provide a reliable end product to farmers, advances in platform design, production, standardization of image georeferencing and mosaicing, and information extraction workflow are required and the farmer should involve in the process of field design, image acquisition, image interpretation and analysis.
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Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps

TL;DR: A variety of spectral indices now exist for various precision agriculture applications, rather than a focus on only normalised difference vegetation indices as discussed by the authors, and the spectral bandwidth has decreased dramatically with the advent of hyperspectral remote sensing, allowing improved analysis of specific compounds, molecular interactions, crop stress, and crop biophysical or biochemical characteristics.
References
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Journal ArticleDOI

Color Indices for Weed Identification Under Various Soil, Residue, and Lighting Conditions

TL;DR: In this article, color slide images of weeds among various soils and residues were digitized and analyzed for red, green, and blue (RGB) color content, and several indices of chromatic coordinates were studied, tested, and were successful in identifying weeds.
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Opportunities and limitations for image-based remote sensing in precision crop management

TL;DR: It is found that both aircraft- and satellite-based re-trote sensing could provide valuable information for PCM applications, and future work should be focused on assimilating remotely sensed information into existing decision support systems (DSS), and conducting economic and technical analysis of remote sensing applications with season-long pilot projects.
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Implementing precision agriculture in the 21st century.

TL;DR: In this paper, the authors describe the need for further technology development in the area of sensing and mapping systems to provide spatially related data on crop, soil, and environmental factors.
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How unique are spectral signatures

TL;DR: In this paper, the authors show that sufficiently high spectral resolution, of order 0.01 μm, would not be sufficient to discriminate virtually any soils, vegetation types, and rocks, but this is not necessarily the case.
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A review of spectral properties of plants and their potential use for crop/weed discrimination in row-crops

Reyer Zwiggelaar
- 01 May 1998 - 
TL;DR: The use of spectral information for the discrimination of crops and weeds is reviewed, discussing research results covering most of this century, and a range of experiments covering different spectral regions are reviewed and the usefulness of the resulting spectral information is discussed.
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