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Spectroradiometry as a tool for phenological characterization of agricultural crop stands


Kneubühler, Mathias (2001). Spectroradiometry as a tool for phenological characterization of agricultural crop stands. In: Wissenschaftlich-Technische Jahrestagung der DGPF, Konstanz, 4 September 2001 - 7 September 2001, 379-388.

Abstract

From the early days of remote sensing until today, there has been a wide range of applications of remote sensing data for agricultural management. Improvements in spatial,
spectral and temporal resolution of available data products together with precision agriculture have meant an increase in the availability of services and products that help to manage agricultural operation more efficiently and profitably. Imagebased remote sensing offers the potential to provide spatially and temporally distributed information for agricultural management. Remote sensing information can improve the capacity and accuracy of decision support systems (DSS) and agronomic models by providing accurate input information or as a means of within-season calibration or validation. Crop phenology is an important variable required by precision crop management systems (PCMS) in support of time-critical crop management (TCCM). Estimates of crop development, which are used for nutrient deficiencies detection, crop yield prediction or timing of forthcoming harvest are important in agricultural planning and policy making.
While the collection of information on the status of biophysical and biochemical characteristics of a crop canopy, that can be correlated to its phenology, is time consuming and limited to punctual measurements, remote sensing allows large and continuous radiometric measurements. Parameters retrievable by a remote sensing system must have an impact on the spectral signal of vegetation canopies. Biophysical parameters are easier to determine because they affect broader spectral regions, whereas biochemical concentrations are more difficult to assess since their spectral features are small and therefore only detectable by hyperspectral sensors.
In this paper, a methodology to track the main development stages of two cereals relevant for agricultural purposes and precision farming needs, based on hyperspectral data, is presented. An investigation of the suitability of four key parameters to track a crop stand’s vitality and an error assessment are performed. Leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), water content and chlorophyll content are defined as the main parameters reflecting vitality and therefore alter with the plants’ phenological stage.

From the early days of remote sensing until today, there has been a wide range of applications of remote sensing data for agricultural management. Improvements in spatial,
spectral and temporal resolution of available data products together with precision agriculture have meant an increase in the availability of services and products that help to manage agricultural operation more efficiently and profitably. Imagebased remote sensing offers the potential to provide spatially and temporally distributed information for agricultural management. Remote sensing information can improve the capacity and accuracy of decision support systems (DSS) and agronomic models by providing accurate input information or as a means of within-season calibration or validation. Crop phenology is an important variable required by precision crop management systems (PCMS) in support of time-critical crop management (TCCM). Estimates of crop development, which are used for nutrient deficiencies detection, crop yield prediction or timing of forthcoming harvest are important in agricultural planning and policy making.
While the collection of information on the status of biophysical and biochemical characteristics of a crop canopy, that can be correlated to its phenology, is time consuming and limited to punctual measurements, remote sensing allows large and continuous radiometric measurements. Parameters retrievable by a remote sensing system must have an impact on the spectral signal of vegetation canopies. Biophysical parameters are easier to determine because they affect broader spectral regions, whereas biochemical concentrations are more difficult to assess since their spectral features are small and therefore only detectable by hyperspectral sensors.
In this paper, a methodology to track the main development stages of two cereals relevant for agricultural purposes and precision farming needs, based on hyperspectral data, is presented. An investigation of the suitability of four key parameters to track a crop stand’s vitality and an error assessment are performed. Leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), water content and chlorophyll content are defined as the main parameters reflecting vitality and therefore alter with the plants’ phenological stage.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:7 September 2001
Deposited On:26 Aug 2014 16:07
Last Modified:05 Apr 2016 18:21
Publisher:Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation (DGPF) e.V.
Series Name:Publikationen der Deutschen Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation
Number:Bd. 10
ISSN:0942-2870
Additional Information:Deutscher Titel im Inhaltsverzeichnis des Tagungsbandes: Spektrometrie zur phänologischen Charakterisierung landwirtschaftlicher Flächen
Free access at:Official URL. An embargo period may apply.
Official URL:http://www.dgpf.de/src/pub/DGPF2001.pdf
Permanent URL: https://doi.org/10.5167/uzh-98418

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