Skip to main content

2020 | OriginalPaper | Buchkapitel

Producing Mid-Season Nitrogen Application Maps for Arable Crops, by Combining Sentinel-2 Satellite Images and Agrometeorological Data in a Decision Support System for Farmers. The Case of NITREOS

verfasst von : Emmanuel Lekakis, Dimitra Perperidou, Stylianos Kotsopoulos, Polimachi Simeonidou

Erschienen in: Environmental Software Systems. Data Science in Action

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

NITREOS (Nitrogen Fertilization, Irrigation and Crop Growth Monitoring using Earth Observation Systems) is a farm management information system (FMIS) for organic and conventional agriculture which aims in enabling farmers to tackle crop abiotic stresses and control important growing parameters to ensure crop health and optimal yields. NITREOS employs a user friendly, web-based platform that integrates satellite remote sensing data, numerical weather predictions and agronomic models, and offers a suite of farm management advisory services to address the needs of smallholder farmers, agricultural cooperatives and agricultural consultants. This paper provides an analysis of different methodologies employed in the nitrogen fertilization service of NITREOS. The methods are based on the determination of the Nitrogen Fertilization Optimization Algorithm for cotton, maize and wheat crops. Available agro-meteorological data on two distinct agricultural regions were used for the calibration and validation of the recommended Nitrogen rates.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Fountas, S., Aggelopoulou, K., Gemtos, T.A.: Precision agriculture: crop management for improved productivity and reduced environmental impact or improved sustainability. In: Iakovou, E., Bochtis, D., Vlachos. D., Aidonis, D. (eds.) Supply Chain Management for Sustainable Food Networks, Wiley-Blackwell, Oxford (2016)CrossRef Fountas, S., Aggelopoulou, K., Gemtos, T.A.: Precision agriculture: crop management for improved productivity and reduced environmental impact or improved sustainability. In: Iakovou, E., Bochtis, D., Vlachos. D., Aidonis, D. (eds.) Supply Chain Management for Sustainable Food Networks, Wiley-Blackwell, Oxford (2016)CrossRef
2.
Zurück zum Zitat Bu, Η.: Yield and quality prediction using satellite passive imagery and ground-based active optical sensors in sugar beet, spring wheat, corn, and sunflower. Master thesis, Soil Science Department, North Dakota State University (2014) Bu, Η.: Yield and quality prediction using satellite passive imagery and ground-based active optical sensors in sugar beet, spring wheat, corn, and sunflower. Master thesis, Soil Science Department, North Dakota State University (2014)
3.
Zurück zum Zitat Havlin, J.L., Beaton, J.D., Tisdale, S.L., Nelson, W.L.: Soil Fertility and Fertilizers: An Introduction to Nutrient Management. Pearson Education Inc., Upper Saddle River (2005) Havlin, J.L., Beaton, J.D., Tisdale, S.L., Nelson, W.L.: Soil Fertility and Fertilizers: An Introduction to Nutrient Management. Pearson Education Inc., Upper Saddle River (2005)
4.
Zurück zum Zitat Bach, H., Migdall, S., Mauser, W., Angermair, W., Sephton, A.J., Martin-de-Mercado, G.: An integrative approach of using satellite-based information for precision farming: TalkingFields. In: Proceedings 61st International Astronautical Congress, Prague (2010) Bach, H., Migdall, S., Mauser, W., Angermair, W., Sephton, A.J., Martin-de-Mercado, G.: An integrative approach of using satellite-based information for precision farming: TalkingFields. In: Proceedings 61st International Astronautical Congress, Prague (2010)
5.
Zurück zum Zitat He, J., Wang, J., He, D., Dong, J., Wang, Y.: The design and implementation of an integrated optimal fertilization decision support system. Math. Comput. Model. 54, 3–4 (2011) He, J., Wang, J., He, D., Dong, J., Wang, Y.: The design and implementation of an integrated optimal fertilization decision support system. Math. Comput. Model. 54, 3–4 (2011)
6.
Zurück zum Zitat Söderström, M, Stadig, H, Martinsson, J, Piikki, K, Stenberg, M.: CropSAT – a public satellite-based decision support system for variable-rate nitrogen fertilization in Scandinavia. In: Proceedings of the 13th International Conference on Precision Agriculture. Monticello, IL, USA, p. 8. International Society of Precision Agriculture (2016) Söderström, M, Stadig, H, Martinsson, J, Piikki, K, Stenberg, M.: CropSAT – a public satellite-based decision support system for variable-rate nitrogen fertilization in Scandinavia. In: Proceedings of the 13th International Conference on Precision Agriculture. Monticello, IL, USA, p. 8. International Society of Precision Agriculture (2016)
7.
Zurück zum Zitat Raun, W.R., et al.: In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J. 93, 131–138 (2001)CrossRef Raun, W.R., et al.: In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J. 93, 131–138 (2001)CrossRef
8.
Zurück zum Zitat Raun, W.R., et al.: Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agron. J. 94, 815–820 (2002)CrossRef Raun, W.R., et al.: Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agron. J. 94, 815–820 (2002)CrossRef
9.
Zurück zum Zitat Lukina, E.V., Freeman, K.W., Wynn, K.J., Thomason, W.E., Mullen, R.W., Klatt, A.R., et al.: Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. J. Plant Nutr. 24, 885–898 (2001)CrossRef Lukina, E.V., Freeman, K.W., Wynn, K.J., Thomason, W.E., Mullen, R.W., Klatt, A.R., et al.: Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. J. Plant Nutr. 24, 885–898 (2001)CrossRef
11.
Zurück zum Zitat Raun, W.R., et al.: Optical sensor-based algorithm for crop nitrogen fertilization. Commun. Soil Sci. Plant Anal. 36, 2759–2781 (2005)CrossRef Raun, W.R., et al.: Optical sensor-based algorithm for crop nitrogen fertilization. Commun. Soil Sci. Plant Anal. 36, 2759–2781 (2005)CrossRef
12.
Zurück zum Zitat Barger, G.L.: Total growing degree days. Wkly Weather Crop Bull. 56, 10 (1969) Barger, G.L.: Total growing degree days. Wkly Weather Crop Bull. 56, 10 (1969)
13.
Zurück zum Zitat Johnson, G.V., Raun, W.R.: Nitrogen response index as a guide to fertilizer management. J. Plant Nutr. 26, 249–262 (2003)CrossRef Johnson, G.V., Raun, W.R.: Nitrogen response index as a guide to fertilizer management. J. Plant Nutr. 26, 249–262 (2003)CrossRef
14.
Zurück zum Zitat Mullen, R.W., Freeman, K.W., Raun, W.R., Johnson, G.V., Stone, M.L., Solie, J.B.: Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agron. J. 95, 347–351 (2003)CrossRef Mullen, R.W., Freeman, K.W., Raun, W.R., Johnson, G.V., Stone, M.L., Solie, J.B.: Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agron. J. 95, 347–351 (2003)CrossRef
15.
Zurück zum Zitat Teal, R.K., et al.: In-season prediction of corn grain yield potential using normalized difference vegetation index. Agron. J. 98, 1488–1494 (2006)CrossRef Teal, R.K., et al.: In-season prediction of corn grain yield potential using normalized difference vegetation index. Agron. J. 98, 1488–1494 (2006)CrossRef
16.
Zurück zum Zitat Morris, K.B., et al.: Mid-season recovery from nitrogen stress in winter wheat. J. Plant Nutr. 29, 727–745 (2006)CrossRef Morris, K.B., et al.: Mid-season recovery from nitrogen stress in winter wheat. J. Plant Nutr. 29, 727–745 (2006)CrossRef
17.
Zurück zum Zitat Inman, D., Khosla, R., Reich, R.M., Westfall, D.G.: Active remote sensing and grain yield in irrigated maize. Precis. Agric. 8, 241–252 (2007)CrossRef Inman, D., Khosla, R., Reich, R.M., Westfall, D.G.: Active remote sensing and grain yield in irrigated maize. Precis. Agric. 8, 241–252 (2007)CrossRef
18.
Zurück zum Zitat Ortiz-Monasterio, J.I., Raun, W.R.: Reduced nitrogen and improved farm income for irrigated spring wheat in the Yaqui Valley, Mexico, using sensor based nitrogen management. J. Agric. Sci. 145, 1–8 (2007)CrossRef Ortiz-Monasterio, J.I., Raun, W.R.: Reduced nitrogen and improved farm income for irrigated spring wheat in the Yaqui Valley, Mexico, using sensor based nitrogen management. J. Agric. Sci. 145, 1–8 (2007)CrossRef
19.
Zurück zum Zitat Li, F., Miao, Y., Zhang, F., Cui, Z., Li, R., Chen, X., et al.: In-season optical sensing improves nitrogen-use efficiency for winter wheat. Soil Sci. Soc. Am. J. 73, 1566–1574 (2009)CrossRef Li, F., Miao, Y., Zhang, F., Cui, Z., Li, R., Chen, X., et al.: In-season optical sensing improves nitrogen-use efficiency for winter wheat. Soil Sci. Soc. Am. J. 73, 1566–1574 (2009)CrossRef
20.
Zurück zum Zitat Tubaña, B.S., et al.: Adjusting midseason nitrogen rate using a sensor-based optimization algorithm to increase use efficiency in corn. J. Plant Nutr. 31, 1393–1419 (2008)CrossRef Tubaña, B.S., et al.: Adjusting midseason nitrogen rate using a sensor-based optimization algorithm to increase use efficiency in corn. J. Plant Nutr. 31, 1393–1419 (2008)CrossRef
21.
Zurück zum Zitat Roberts, D., Brorsen, B., Taylor, R., Solie, J., Raun, W.: Replicability of nitrogen recommendations from ramped calibration strips in winter wheat. Precis. Agric. 12, 653–665 (2011)CrossRef Roberts, D., Brorsen, B., Taylor, R., Solie, J., Raun, W.: Replicability of nitrogen recommendations from ramped calibration strips in winter wheat. Precis. Agric. 12, 653–665 (2011)CrossRef
22.
Zurück zum Zitat Singh, B., Sharma, R., Jaspreet, K., Jat, M.L., Martin, K.L., Yadvinder, S., et al.: Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agron. Sustain. Dev. 31, 589–603 (2011)CrossRef Singh, B., Sharma, R., Jaspreet, K., Jat, M.L., Martin, K.L., Yadvinder, S., et al.: Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agron. Sustain. Dev. 31, 589–603 (2011)CrossRef
23.
Zurück zum Zitat Tubaña, B., Viator, S., Teboh, J., Lofton, J., Kanke, Y.: Feasibility of using remote sensing technology in N management in sugarcane production. Int. Sugar J. 113, 747 (2011) Tubaña, B., Viator, S., Teboh, J., Lofton, J., Kanke, Y.: Feasibility of using remote sensing technology in N management in sugarcane production. Int. Sugar J. 113, 747 (2011)
24.
Zurück zum Zitat Lofton, J., Tubaña, B.S., Kanke, Y., Teboh, J., Viator, H., Dalen, M.: Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index. Sensors 12, 7529–7547 (2012)CrossRef Lofton, J., Tubaña, B.S., Kanke, Y., Teboh, J., Viator, H., Dalen, M.: Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index. Sensors 12, 7529–7547 (2012)CrossRef
25.
Zurück zum Zitat Arnall, D.B.: Analysis of the coefficient of variation of remote sensor readings in winter wheat, and development of a sensor based mid-season n recommendation for cotton. Ph.D. thesis, Oklahoma State University. Department of Plant and Soil Sciences (2008) Arnall, D.B.: Analysis of the coefficient of variation of remote sensor readings in winter wheat, and development of a sensor based mid-season n recommendation for cotton. Ph.D. thesis, Oklahoma State University. Department of Plant and Soil Sciences (2008)
27.
Zurück zum Zitat Arnall, D.B., Joy, M., Abit, M., Taylor, R.K., Raun, W.R.: Development of an NDVI-based nitrogen rate calculator for cotton. Crop Sci. 56, 3263–3271 (2016)CrossRef Arnall, D.B., Joy, M., Abit, M., Taylor, R.K., Raun, W.R.: Development of an NDVI-based nitrogen rate calculator for cotton. Crop Sci. 56, 3263–3271 (2016)CrossRef
28.
Zurück zum Zitat Raper, T.B., Varco, J.J., Hubbard, K.J.: Canopy-based normalized difference vegetation index sensors for monitoring cotton nitrogen status. Agron. J. 105, 1345–1354 (2013)CrossRef Raper, T.B., Varco, J.J., Hubbard, K.J.: Canopy-based normalized difference vegetation index sensors for monitoring cotton nitrogen status. Agron. J. 105, 1345–1354 (2013)CrossRef
29.
Zurück zum Zitat Boquet, D.J., Breitenbeck, G.A.: Nitrogen rate effect on partitioning of nitrogen and dry matter by cotton. Crop Sci. 40, 1685–1693 (2000)CrossRef Boquet, D.J., Breitenbeck, G.A.: Nitrogen rate effect on partitioning of nitrogen and dry matter by cotton. Crop Sci. 40, 1685–1693 (2000)CrossRef
30.
Zurück zum Zitat Khalilian, A., Henderson, W., Han, Y., Wiatrak, P.J.: Improving nitrogen use efficiency in cotton through optical sensing. In: Proceedings of the Beltwide Cotton Conferences, National Cotton Council of America, Memphis (2008) Khalilian, A., Henderson, W., Han, Y., Wiatrak, P.J.: Improving nitrogen use efficiency in cotton through optical sensing. In: Proceedings of the Beltwide Cotton Conferences, National Cotton Council of America, Memphis (2008)
31.
Zurück zum Zitat Miller, E.C., Bushong, J.T., Raun, W.R., Abit, M.J.M., Arnall, D.B.: Predicting early season nitrogen rates of corn using indicator crops. Agron. J. 109, 2863–2870 (2017)CrossRef Miller, E.C., Bushong, J.T., Raun, W.R., Abit, M.J.M., Arnall, D.B.: Predicting early season nitrogen rates of corn using indicator crops. Agron. J. 109, 2863–2870 (2017)CrossRef
32.
Zurück zum Zitat Dhital, S., Raun, W.R.: Variability in optimum nitrogen rates for maize. Agron. J. 108, 2165–2173 (2016)CrossRef Dhital, S., Raun, W.R.: Variability in optimum nitrogen rates for maize. Agron. J. 108, 2165–2173 (2016)CrossRef
33.
Zurück zum Zitat Butchee, K.S., May, J., Arnall, B.: Sensor based nitrogen management reduced nitrogen and maintained yield. Crop Manag. 10 (2011)CrossRef Butchee, K.S., May, J., Arnall, B.: Sensor based nitrogen management reduced nitrogen and maintained yield. Crop Manag. 10 (2011)CrossRef
Metadaten
Titel
Producing Mid-Season Nitrogen Application Maps for Arable Crops, by Combining Sentinel-2 Satellite Images and Agrometeorological Data in a Decision Support System for Farmers. The Case of NITREOS
verfasst von
Emmanuel Lekakis
Dimitra Perperidou
Stylianos Kotsopoulos
Polimachi Simeonidou
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-39815-6_10