Szacowanie plonów roślin uprawnych na podstawie naziemnych pomiarów spektralnych

• Autorzy: Piekarczyk J.

Warianty tytułu

EN

Estimating crop yields on the basis of ground hyperspectral measurements

• Języki publikacji: PL

Abstrakty

EN

The objective of the study was to compare the variability of hyperspectral characteristics of winter oilseed rape and winter spelt in the early growing season and to determine the usefulness of vegetation indices obtained during the ground-based hyperspectral measurements to predict the yield of these crops. Field hyperspectral measurements were taken from the experimental plots of three varieties of winter oilseed rape and four winter spelt varieties during the fi rst part of the growing season. The oilseed rape plots were sown at four dates in the autumn and the spelt plots were fertilized in six schemes. Vegetation indices were calculated on the basis of the reflectance factors of the visible and near-infrared bands and their logarithmic and first derivative transformations. Then, relationships between the vegetation indices and oilseed rape and spelt yields were analyzed. Among the unprocessed indices the highest R2 values (0.86) were obtained for the relationship between the winter rape yield and NDVI550-775 recorded at the beginning of the fl owering stage. The transformation of the spectral data improved the relationship between the NDVI675-775, NDVI820-980, SRWI870-1260 and yield up to 0.86. The winter spelt yield was most strongly correlated with NDVI550-775 (R2=0.80) at the stem elongation stage and the transformation of the spectral data did not improve the relationship.

Słowa kluczowe

PL

teledetekcja; naziemne pomiary hiperspektralne; rzepak ozimy; orkisz ozimy; wskaźniki roślinne; plon

EN

remote sensing; ground hyperspectral measurements; winter oilseed rape; winter spelt; vegetation indices; yield

• Wydawca: Polskie Towarzystwo Geograficzne, Oddział Teledetekcji i Geoinformatyki
• Czasopismo: Teledetekcja Środowiska
• Rocznik: 2011
• Tom: T. 46
• Strony: 23--28
• Opis fizyczny: Bibliogr. 14 poz., rys., tab., wykr.

Twórcy

autor

Piekarczyk J.

• Uniwersytet im. Adama Mickiewicza w Poznaniu, Instytut Geografii Fizycznej i Kształtowania Środowiska Przyrodniczego w Poznaniu

Bibliografia

• 1. Behrens T., Muller J., Diepenbrock W., 2006, Utilization of canopy reflectance to predict properties of oilseed rape (Brassica napus L.) and barley (Hordeum vulgare L.) during ontogenesis. European, Journal of Agronomy, 25, 345–355.
• 2. Broge N.H., Leblanc E., 2000, Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment, 76, 156-172.
• 3. Doraiswamy P.C., Moulin S., Cook P.W., Stern A., 2003, Crop yield assessment from remote sensing. Photogrammetric Engineering and Remote Sensing, 69, 665−674.
• 4. Funk C., Budde M.E., 2009, Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe. Remote Sensing of Environment, 113, 115−125.
• 5. Huang Z., Turner B.J., Durya S.J., Wallis I.R., Foley W.J., 2004, Estimating foliage nitrogen concentration from HYMAP data using continuum removal analysis. Remote Sensing of Environment, 93, 18–29.
• 6. Justice C.O., Becker-Reshef I., 2007, Report from the workshop on developing a strategy for global agricultural monitoring in the framework of Group on Earth Observations (GEO). s 1−67.
• 7. Manjunath K.R., Potdar M.B., Purohit N.L., 2002, Large area operational wheat yield model development and validation based on spectral and meteorological data. International Journal of Remote Sensing, 23, 3023−3038.
• 8. Maselli F., Rembold F., 2001, Analysis of GAC NDVI data for cropland identification and yield forecasting in Mediterranean African countries. Photogrammetric Engineering and Remote Sensing, 67, 593−602.
• 9. Mika J., Kerenyi J., Rimoczi-Paal A., Merza A., Szinell C., Csiszar I., 2002, On correlation of maize and wheat yield with NDVI: Example of Hungary (1985–1998). Advances in Space Research, 30, 2399−2404.
• 10. Moriondo M., Maselli F., Bindi M., 2007, A simple model of regional wheat yield based on NDVI data. European Journal of Agronomy, 26, 266−274.
• 11. Prasad A.K., Chai L., Singh R.P., Kafatos M., 2006, Crop yield estimation model for Iowa using remote sensing and surface parameters. International Journal of Applied Earth Observation and Geoinformation, 8, 26−33.
• 12. Rojas O., 2007, Operational maize yield model development and validation based on remote sensing and agro-meteorological data in Kenya. International Journal of Remote Sensing, 28, 3775−3793.
• 13. Salazar L., Kogan F., Roytman L., 2007, Use of remote sensing data for estimation of winter wheat yield in the United States. International Journal of Remote Sensing, 28, 3795−3811.
• 14. Wall L., Larocque D., Leger P.M., 2007, The early explanatory power of NDVI in crop yield modeling. International Journal of Remote Sensing, 29, 2211−2225.