Crop phenology based on MODIS satellite imagery as an indicator of plant available water content

Proceedings - 20th International Congress on Modelling and Simulation, MODSIM 2013

Volumn , Issue , 2013, Pages 1896-1902

  Araya, Sofanit ^a   Ostendorf, Bertram ^a   Lyle, Gregory ^a   Lewis, Megan ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Digital Soil Mapping (DSM); Remote sensing; Satellite imagery; Spatio temporal

Indexed keywords

BIOLOGY; CLIMATE CHANGE; CROPS; DECISION MAKING; FORESTRY; IMAGE ENHANCEMENT; OPERATIONS RESEARCH; PRODUCTIVITY; RADIOMETERS; RAIN; REMOTE SENSING; SOIL SURVEYS; SOILS;

AGRICULTURAL PRODUCTIVITY; AVAILABLE WATER CONTENTS; CROP GROWTH AND YIELDS; DIGITAL SOIL MAPPINGS; MEDITERRANEAN ENVIRONMENT; PLANT AVAILABLE WATER CAPACITY OF SOIL (PAWC); SPATIAL AND TEMPORAL VARIABILITY; SPATIO TEMPORAL;

SATELLITE IMAGERY;

EID: 85018988028     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. Angus, J. and M. Moncur. 1977. Water stress and phenology in wheat. Australian Journal of Agricultural Research 28:177-181.
2. Asseng, S., J. T. Ritchie, A. J. M. Smucker, and M. J. Robertson. 1998. Root growth and water uptake during water deficit and recovering in wheat. Plant and Soil 201:265-273.
3. Brisson, N. and M. L. Casals. 2005. Leaf dynamics and crop water status throughout the growing cycle of durum wheat crops grown in two contrasted water budget conditions. Agronomy for Sustainable Development 25:151-158.
4. DeFries, R., M. Hansen, and J. Townshend. 1995. Global discrimination of land cover types from metrics derived from AVHRR pathfinder data. Remote Sensing of Environment 54:209-222.
5. Eyre Peninsula Agricultural Research Foundation, E., 2011, Eyre Peninsula Agricultural Research Foundation, Available online at http://www.minnipaagriculturalcentre.com.au/publication-list.html, Accessed at [Jan 14, 2013, 2013]
6. Eyre Peninsula Farming Systems. 2009. Eyre Peninsula Farming Systems 2009 Summary
7. FAO, IIASA, ISRIC, ISSCAS, and JRC. 2009. Harmonized World Soil Database (version1.1). FAO, Rome, Italy and IIASA, Laxenburg, Austria.
8. Henderson, B. L., E. N. Bui, C. J. Moran, and D. A. P. Simon. 2005. Australia-wide predictions of soil properties using decision trees. Geoderma 124:383-398.
9. Hill, M. J. and G. E. Donald. 2003. Estimating spatio-temporal patterns of agricultural productivity in fragmented landscapes using AVHRR NDVI time series. Remote Sensing of Environment 84:367-384.
10. Jiang, P., N. R. Kitchen, S. H. Anderson, E. J. Sadler, and K. A. Sudduth. 2008. Estimating Plant-Available Water Using the Simple Inverse Yield Model for Claypan Landscapes.
11. Kouadio, L., G. Duveiller, B. Djaby, M. El Jarroudi, P. Defourny, and B. Tychon. 2012. Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data. International Journal of Applied Earth Observation and Geoinformation 18:111-118.
12. Lloyd, D. 1990. A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery. Remote Sensing 11:2269-2279.
13. McDonald, G. K. 2006. Effects of soil properties on variation in growth, grain yield and nutrient concentration of wheat and barley. Australian Journal of Experimental Agriculture 46:93-106.
14. McMaster, G. and W. Wilhelm. 2003. Phenological responses of wheat and barley to water and temperature: improving simulation models. The Journal of Agricultural Science 141:129-147.
15. McMASTER, G. S. 2005. Phytomers, phyllochrons, phenology and temperate cereal development. The Journal of Agricultural Science 143:137-150.
16. McMaster, G. S. and J. C. Ascough, II. 2011. Crop management to cope with global change: a systems perspective aided by information technologies. Pages 172-190 CABI Climate Change Series, Volume 2. CABI, Wallingford.
17. McMaster, G. S., J. W. White, A. Weiss, P. S. Baenziger, W. Wilhelm, J. Porter, and P. D. Jamieson. 2008. Simulating crop phenological responses to water deficits. Response of crops to limited water: understanding and modeling water stress effects on plant growth processes 1:277.
18. Morgan, C., J. Norman, R. Wolkowski, B. Lowery, G. Morgan, R. Schuler, P. Robert, R. Rust, and W. Larson. 2000. Two approaches to mapping plant available water: EM-38 measurements and inverse yield modeling. Pages 1-13. American Society of Agronomy.
19. Mullins, J. 1981. Estimation of the plant available water capacity of a soil profile. Soil Research 19:197-207.
20. Oliver, Y., M. Wong, R. Robertson, and K. Wittwer. 2006. PAWC determines spatial variability in grain yield and nitrogen requirement by interacting with rainfall on northern WA sandplain. Pages 10-14.
21. Ostendorf, B. 2011. Overview: Spatial information and indicators for sustainable management of natural resources. Ecological Indicators 11:97-102.
22. Reed, B. C., J. F. Brown, D. VanderZee, T. R. Loveland, J. W. Merchant, and D. O. Ohlen. 1994. Measuring Phenological Variability from Satellite Imagery. Journal of Vegetation Science 5:703-714.
23. Robertson, M. and F. Giunta. 1994. Responses of spring wheat exposed to pre-anthesis water stress. Australian Journal of Agricultural Research 45:19-35.
24. Rodrigues, A., A. R. S. Marcal, and M. Cunha. 2011. PhenoSat: A tool for vegetation temporal analysis from satellite image data. Pages 45-48 in Analysis of Multi-temporal Remote Sensing Images (Multi-Temp), 2011 6th International Workshop on the.
25. Solano, R., K. Didan, A. Jacobson, and A. Huete. 2010. MODIS Vegetation Index User's Guide (MOD13 Series).
26. Sun, H., A. Xu, H. Lin, L. Zhang, and Y. Mei. 2012. Winter wheat mapping using temporal signatures of MODIS vegetation index data. International Journal of Remote Sensing 33:5026-5042.
27. Wardlow, B. D. and S. L. Egbert. 2008. Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains. Remote Sensing of Environment 112:1096-1116.
28. Wardlow, B. D., S. L. Egbert, and J. H. Kastens. 2007. Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains. Remote Sensing of Environment 108:290-310.
29. Wong, M. and S. Asseng. 2006a. Determining the Causes of Spatial and Temporal Variability of Wheat Yields at Sub-field Scale Using a New Method of Upscaling a Crop Model. Plant and Soil 283:203-215.
30. Wong, M., Y. Oliver, M. Robertson, and K. Wittwer. 2006b. Technologies to estimate plant available soil water storage capacities at high spatial resolution. Pages 10-14 in 13th Australian Agronomy Conference, Perth, West Australia.
31. Zhang, X., M. A. Friedl, C. B. Schaaf, A. H. Strahler, J. C. F. Hodges, F. Gao, B. C. Reed, and A. Huete. 2003. Monitoring vegetation phenology using MODIS. Remote Sensing of Environment 84:471-475.