Skip to main content

2021 | OriginalPaper | Buchkapitel

Simulation of Phytomass Dynamics of Plant Communities Based on Artificial Neural Networks and NDVI

verfasst von : Vladimir Mikhailov, Marija Ponomarenko, Vladislav Sobolevsky

Erschienen in: Recent Advances in Environmental Science from the Euro-Mediterranean and Surrounding Regions (2nd Edition)

Verlag: Springer International Publishing

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

search-config
loading …

Abstract

The paper presents the model of interannual dynamics of the phytomass of plant communities, which was realized as an artificial neural network. The neural network was trained by the sequence of data based on NDVI indices and environmental climate factors. The plant communities of the tundra biome were taken as a specific modeling object (Kolguyev Island, Russia). The modeling results are presented and the influence of separate factors on the validity of the model is analyzed. The technique of solving the problem—modeling the phytomass dynamics of plant communities using ANN and NDVI—has quite a general character and can be employed for different natural climatic biomes.

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!

Literatur
1.
Zurück zum Zitat Walker, D., Epstein, H., Jia, G., Balser, A., Copass, C., Edwards, E., Gould, W., Hollings, J., Knudson, J., Maier, H., Moody, A., Raynolds, M.: Phytomass, LAI, and NDVI in northern Alaska: relationships to summer warmth, soil pH, plant functional types, and extrapolation to the circumpolar Arctic. J. Geophys. Res. 108(D2), 8169, 1–15 (2003) Walker, D., Epstein, H., Jia, G., Balser, A., Copass, C., Edwards, E., Gould, W., Hollings, J., Knudson, J., Maier, H., Moody, A., Raynolds, M.: Phytomass, LAI, and NDVI in northern Alaska: relationships to summer warmth, soil pH, plant functional types, and extrapolation to the circumpolar Arctic. J. Geophys. Res. 108(D2), 8169, 1–15 (2003)
2.
Zurück zum Zitat Karlsen, S., Anderson, H., van der Wal, R., Hansen, B.: A new NDVI measure that overcomes data sparsity in cloud-covered regions and predicts annual variation in ground-based estimates of high arctic plant productivity. Environ. Res. Lett. 13(2), 025011 (2018)CrossRef Karlsen, S., Anderson, H., van der Wal, R., Hansen, B.: A new NDVI measure that overcomes data sparsity in cloud-covered regions and predicts annual variation in ground-based estimates of high arctic plant productivity. Environ. Res. Lett. 13(2), 025011 (2018)CrossRef
3.
Zurück zum Zitat Raynolds, M., Walker, D., Epstein, H., Pinzon, J., Tucker, C.: A new estimate of tundra-biom phytomass from trans-Arctic field data and AVHRR NDVI. Remote Sens. Lett. 3(5), 403–411 (2012)CrossRef Raynolds, M., Walker, D., Epstein, H., Pinzon, J., Tucker, C.: A new estimate of tundra-biom phytomass from trans-Arctic field data and AVHRR NDVI. Remote Sens. Lett. 3(5), 403–411 (2012)CrossRef
4.
Zurück zum Zitat Pouliot, D., Latifovic, R., Pasher, J., Duffe, J.: Assessment of convolution neural networks for wetland mapping with Landsat in the central Canadian boreal forest region. Remote Sens. 11(7), 772 (2019) Pouliot, D., Latifovic, R., Pasher, J., Duffe, J.: Assessment of convolution neural networks for wetland mapping with Landsat in the central Canadian boreal forest region. Remote Sens. 11(7), 772 (2019)
5.
Zurück zum Zitat Chang, T., Rasmussen, B., Dickson, B., Zachmann, L.: Chimera: a multi-task recurrent convolutional neural network for forest classification and structural estimation. Remote Sens. 11(7), 768 (2019) Chang, T., Rasmussen, B., Dickson, B., Zachmann, L.: Chimera: a multi-task recurrent convolutional neural network for forest classification and structural estimation. Remote Sens. 11(7), 768 (2019)
6.
Zurück zum Zitat Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edn. Springer, 745 pp. (2013) Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edn. Springer, 745 pp. (2013)
Metadaten
Titel
Simulation of Phytomass Dynamics of Plant Communities Based on Artificial Neural Networks and NDVI
verfasst von
Vladimir Mikhailov
Marija Ponomarenko
Vladislav Sobolevsky
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-51210-1_211