XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/6: Agriculture, Ecosystems and Bio-Diversity]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: NDVI FROM ACTIVE OPTICAL SENSORS AS A MEASURE OF CANOPY COVER AND BIOMASS E. M. Perry, G. J. Fitzgerald, N. Poole, S. Craig, A. Whitlock

Document type:: Multivolume work

Structure type:: Chapter

(IX-B8, 2012 l - a program for ta, Computers and flood-watch from n Space Research, e E.T., Possingham uacy in dynamic ion of vegetation Pantanal wetland. rrent and potential cisions on drought view. Agricultural R., 2011. Imagens ) Pantanal em áreas ogas: resultados de Sensoriamento 559-3566. MBRASIL. Folha plos, vegetaçäo uso Janeiro. pp. 448. ybrid approach to ver transition from from the Bolivian ment, 115, pp. 353- 2007. Analysis of ex data for crop 1s. Remote Sensing (TS 2010/52614-4) for o CAPES for the iro de Almeida to International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia NDVI FROM ACTIVE OPTICAL SENSORS AS A MEASURE OF CANOPY COVER AND BIOMASS E.M. Perry", G.J. Fitzgerald", N. Poole’, S. Craig, A. Whitlock ? Department Primary Industries, Future Farming Systems Research, 110 Natimuk Rd. Horsham VIC 3401 Australia - (eileen.perry, glenn.fitzgerald) 9 dpi.vic.gov.au ? Foundation for Arable Research, Lincoln 7640 NZ - poolen@far.org.nz ¢ Birchip Cropping Group, Birchip VIC 3483 Australia - simon@bcg.org.au 4 Precision.agriculture.com.au - Andrew @precisionagriculture.com.au KEY WORDS: Agriculture, Farming, Vegetation, Sensor, Spatial, Real-time ABSTRACT: Commercially available proximal sensors are being used in precision agriculture to provide non-destructive, real-time spatial information on ‘green biomass’ that may be of interest to the remote sensing community. The sensors are described as biomass sensors, but questions remain on which canopy characteristics can be best estimated by the sensor measurements. In this study Normalized Difference Vegetation Index (NDVI) measurements from active optical sensors were examined across multiple datasets, representing different active optical sensors, different years, and different sites for wheat and barley. The NDVI values were compared with spatially and temporally coincident measurements of fractional green cover and above ground biomass, expressed as dry matter in kg ha’. Direct comparison of NDVI measurements from the different sensors for the same plots over a range of canopy cover demonstrates differences for plot means of NDVI. Canopy fractional green cover values were well described by NDVI using a linear model. Using all of the datasets, the linear regression of fractional green cover on NDVI yielded an r? of 0.71 and a standard error of 0.12. NDVI measured by the sensors did not explain as much of the variance in dry matter as for fractional cover. Dry matter was related to NDVI using a non-linear model. For all sensors, sites and dates with green biomass, the model was fitted with r^ value of 0.27, and standard error of 2133 kg ha‘, The relationship between NDVI and dry matter was nearly linear at levels of biomass less than 1000 kg ha''. Results for these datasets indicate that the active optical sensors may be a useful surrogate for fractional cover, but not for above ground biomass. 1. INTRODUCTION Commercially available proximal sensors are being used in precision agriculture to provide non-destructive, real-time spatial information on ‘green biomass’. These active optical sensors utilise built-in light sources, pulsed to differentiate the artificial signal from sunlight. This gives these sensors a tremendous advantage over passive optical sensors (such as ground-based spectrometers) in that they can be used under any sky conditions, or even in complete darkness. The sensors are described as biomass sensors, but questions remain on what canopy characteristics the sensors best relate to. There is a relevance to the remote sensing community in that these sensors could potentially provide ground truth on fractional ground cover and/or plant biomass. In this study Normalized Difference Vegetation Index (NDVI; Rouse et al. 1973) measurements from active optical sensors were examined across multiple datasets, representing different active optical sensors, different years, and different sites for wheat and barley grown under rainfed conditions. 2. METHODS Several sites and sensor combinations were used for this study: *Small plot agronomic trials near Horsham Vic (36° 44° S latitude, 142° 06’ E longitude) on various cultivars of wheat (Triticum aestivum L) for the years 2007, 2008, and 2010. Two sensor models were used, the Crop Circle ACS-210 and Crop Circle ACS-470 (Holland Scientific Inc, Lincoln NE, USA). : Corresponding author. Large plot agronomic trials near Lubeck VIC (36° 46’ 42” S latitude, 142? 30' 33" W longitude) on wheat (Triticum aestivum L cv. Derrimut) for 2009 and 2010. Two sensor models were used, the Greenseeker handheld (NTech Industries, Ukiah CA, USA) and Crop Circle ACS-470 (Holland Scientific Inc, Lincoln NE, USA). ePaddock scale agronomy trials on eight paddocks near Inverleigh VIC (144? 2" 17" W, 38? 9' 0" S) on wheat (Triticum aestivum L cv. Derrimut) and barley (H. vulgare L. cv. Gairdner) during 2009 and 2010. A Crop Circle ACS-470 was used to measure NDVI. Sensor measurements were made throughout the growing season for the Lubeck and Inverleigh trials, and until anthesis (flowering) for the Horsham trials. Sensor measurements were made with the sensor head situated 1 to 1.5 m above the canopy, with the sensor field of view spanning across rows. The NDVI values were either computed from the red and near infrared bands (Holland Scientific sensors) or output directly from the sensor (Greenseeker). Estimates of fractional green cover were made using colour photographs following methods described in Li el al. 2010 for each of the sensor data acquisitions. Above ground biomass (dry matter in kg ha!) was determined by biomass cuttings for the plots and paddock scale sample locations at key crop growth stages that corresponded with sensor acquisitions. Regression and non linear model fitting were performed using GenStat (Payne et al. 2009).

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