Determination of the cultivated area and plant density of sugar beet fields using satellite data | ||
| چغندرقند | ||
| Article 8, Volume 30, Issue 2, March 2015, Pages 222-207 PDF (1022.56 K) | ||
| Document Type: Scientific - Research | ||
| DOI: 10.22092/jsb.2015.6956 | ||
| Authors | ||
| F. Forughimanesh* 1; M. Abdollahian2 | ||
| 1Master expert of Sugar Company Ghazvin, Iran | ||
| 2Associate Professor of Sugar Beet Seed Institute (SBSI), Iran | ||
| Abstract | ||
| The purpose of this study was to determine the plant density of sugar beet fields in Qazvin region using satellite images and remote sensing techniques. The plant density can be used to estimate the pre-harvest sugar beet yield and as a result the proper management of agricultural and industrial processes involved in sugar production. Satellite data can be used to remove the cost and time of conventional field methods. In this study, using satellite imagery of TM and GeoEye, the plant density of sugar beet fields in a part of Qazvin region was estimated in 2011. Results derived from the assessment of accuracy of operations and comparison of the maps obtained from remote sensing data with ground samples showed that using satellite data, the plant density of sugar beet can be estimated with relative certainty. The calculation of the overall data showed that the accuracy of maps outputs was 91.7% with Kappai coefficient of 0.84. In addition, remote sensing data can illustrate the density variation in different parts of the field. | ||
| Keywords | ||
| Optimal Cropping Pattern; Remote sensing techniques; sugar beet; Water | ||
|
Supplementary Files
|
||
| References | ||
|
Alavipanah S. Application of remote sensing in earth sciences. Tehran University Publication, 2003; pp. 63. (in Persian)
Alizadeh H. Introducing in GIS. SAMT Publication, 2002; pp. 217. (in Persian)
Anonymous. Sugar beet production. Iranian Syndicate of sugar industry. 2011. (in Persian) http://www.isfs.ir.
Arnon I. Crop production in dry regions. Jahad-e-Daneshgahi Publication. 1996; pp 127. (in Persian)
Asadi-Rashed H, Mirbagheri V, Abkar A. Estimation of Qazvin plain water yield of leaf area index produced using IRS satellite imagery. Geomantic Conference. National Cartographic Organization in Iran. 2008. (in Persian)
Ebrahimian H. Effect of nitrogen and plant density on sugar beet technological value. Sugar beet Seed Institute. Publication. 1992; P 81. (in Persian)
Gavin A, John C, Taylor J. Calibration methodology for mapping within-field crop variability using remote sensing. Biosystems Engineering. 2003; 84 (4), 409–423.
Jensen J. Introductory Digital Image Processing, Prentice- Hall, USA. 1996; pp. 117.
Johnson L, Roczen F, Youkhana D, Nemani R, Bosch D. Mapping vineyard leaf area with multispectral satellite imagery. Computers and Electronics in Agriculture. 2003; 38: 33-44.
Khodabandeh N. Industrial plants. Tehran University Publication; 1993. pp. 454. (in Persian)
Liang S. Quantitative Remote Sensing of Land Surface. 2004. John Wiley & Sons, Canada. p 92-99.
Mastali R. Estimation and evolution of maize plant density per unit area with using of satellite image in NDVI method (MSc thesis). Azad University of Tehran; 2007. (in Persian, abstract in English)
Minghas Z, Hendley P. Corn and Soybean yield indicators using remotely sensed vegetation indictor. University of California, Davis. 2002; p. 95-116.
Richards J, Jia X. Remote Sensing Digital Image Analysis, 4th Edition. Springer publication, Berlin, 2006; P. 32-41
Sawasawa H. Crop yield Estimation. Integrating RS, GPS and Management Factors, ITC Thesis. 2003.
Zobeiri M, Majd A. Introduction to Mapping Invasive in Natural Science. Tehran UniversityPublication, 2002; pp. 137. (in Persian) | ||
|
Statistics Article View: 3,235 PDF Download: 1,595 |
||
Journal management system. designed by sinaweb