On grass yield remote sensing estimation models of China's northern farming-pastoral ecotone

Advances in Intelligent and Soft Computing

Volumn 141 AISC, Issue , 2012, Pages 281-291

  Yang, Xiuchun ^a   Xu, Bin ^a   Jin, Yunxiang ^a   Li, Jinya ^a   Zhu, Xiaohua ^b  

^a INSTITUTE OF PLANT PROTECTION   (China)

^b INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

Author keywords

China's northern farming pastoral ecotone; Grass yield; Model; Monitoring; Remote sensing

Indexed keywords

BP NEURAL NETWORK MODEL; BP NEURAL NETWORKS; CHINA'S NORTHERN FARMING-PASTORAL ECOTONE; ESTIMATION MODELS; GRASS YIELD; NON-LINEAR MODEL; SAMPLE DATA; VEGETATION INDEX; YIELD CONDITIONS; YIELD ESTIMATION;

MODELS; MONITORING; NASA; NEURAL NETWORKS; NONLINEAR SYSTEMS; REMOTE SENSING; VEGETATION;

ESTIMATION;

EID: 84860650702     PISSN: 18675662     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-27957-7_35     Document Type: Conference Paper

References (23)

1. Deering, D.W.: Rangeland reflectance characteristics measured by aircraft and spacecraft sensors. Ph.D. Dissertation, Texas A&M University, College Station, TX. 338 (1978)
2. Gao, J.: Quantification of grassland properties: how it can benefit from geoinformatic technologies? International Journal of Remote Sensing 27, 1351-1365 (2006)
3. Hornik, K.M., Stinchcombe, M., White, H.: Multilayer feed forward networks are universal approximators. Neural Networks 2, 359-366 (1989)
4. Huang, J., Wang, X., Hu, X.: Studies on grass yield monitoring models for different natural grassland types using remote sensing data in Northern Xinjiang. Grassland of China 21, 7-11, 18 (1999)
5. Huang, J., Wang, X., Wang, R., et al.: Relation analysis between the production of natural grassland and satellite vegetation indices. Research of Agricultural Modernization 21, 33-36 (2000)
6. Huang, J., Wang, X., Wang, R., et al.: A study on monitoring and predicting models of grass yield in natural grassland using remote sensing data and meteorological data. Journal of Remote Sensing 5, 71-76 (2001)
7. Huete, A.R.: A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment 25, 295-309 (1988)
8. Jiang, D., Yang, X., Clinton, N., et al.: An artificial neural network model for estimating crop yields using remotely sensed information. International Journal of Remote Sensing 25, 1723-1732 (2004)
9. Kanemasu, E.T., Demetriades-Shah, T.H., Su, H., et al.: Estimating grassland biomass using remotely sensed data. In: Steven, M.D., Clark, J.A. (eds.) Applications of Remote Sensing in Agriculture, pp. 185-199. Butterworth-Heinemanm, London (1990)
10. Li, J., Jiang, P.: The Study on the Remote Sensing Technology in Estimating and Forecasting Grassland Field Applications. Journal of Wuhan Technical University of Surveying and Mapping 23, 153-157 (1998)
11. Li, X., Yeh, A.G.O.: Cellular automata for simulating complex land use systems using neural networks. Geographical Research 24, 19-27 (2005)
12. Liu, H.Q., Huete, A.R.: A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Trans. Geosci. Remote Sensing 33, 457-465 (1995)
13. Niu, Z.C., Ni, S.X.: Study on Models for Monitoring of Grassland Biomass around Qinghai Lake Assisted by Remote Sensing. Acta Geographica Sinica 58, 395-702 (2003)
14. Piao, S.L., Fang, J.Y., He, J.S., Xiao, Y.: Spatial distribution of grassland biomass in China. Acta Phytoecologica Sinica 28, 491-498 (2004)
15. Purevdorj, T., Tateishi, R., Ishiyama, T., et al.: Relationship between percent vegetation cover and vegetation indices. International Journal of Remote Sensing 19, 3519-3535 (1998)
16. Qi, J.A.: Modified soil adjusted vegetation index. Remote Sensing of Environment 25, 295-309 (1988)
17. Rasmussen, M.S.: Developing simple, operational, consistent NDVI-vegetation models by apply environmental and climatic information: Part I. Assessment of net primary production. International Journal of Remote Sensing 19, 97-117 (1998)
18. Ren, J.Z.: Scientific research methods of the grass industry, pp. 201-203. China Agriculture Press, Beijing (1998)
19. Rondeaux, G., Steven, M., Baret, F.: Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment 55, 95-107 (1996)
20. Roy, P.S., Jonna, S., Pant, D.N.: Evaluation of grasslands and spectral reflectance relationship to its biomass in Kanha National Park (M P), India. Geocarto International 6, 39-45 (1991)
21. Simpson, G.: Crop yield prediction using a CMAC neural network. In: Proceedings of the Society of Photo-Optical Instrumentation Engineers, vol. 2315, pp. 160-171 (1994)
22. Wang, Z., Liu, C., Zhao, B., et al.: ANPP estimate from MODIS-EVI for the grassland region of Xilingol, China. Journal of Lanzhou University (Natural Science Edition) 41, 10-16 (2005)
23. Xu, B., Xin, X.P., Qin, Z.H., et al.: Development of spatial GIS databases for monitoring on dynamic state of grassland productivity and animal loading balance in northern China. In: Proceeding of the 12th International Conference on Geoinformatics 2004, pp. 585-592. University of Gavle Press, Sweeden (2004)