CONFERENCE PROCEEDINGS
Advanced Search >
Home > Proceedings > Volume 4385 > Article
Translator Disclaimer
22 March 2001 Estimating grassland yields by projection pursuit regression (PPR) and RS, GIS, and GPS
Jianlong Li
Author Affiliations +
Proceedings Volume 4385, Sensor Fusion: Architectures, Algorithms, and Applications V; (2001) https://doi.org/10.1117/12.421114
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States
Abstract
Four grassland types, plain desert, saline steppe, hill desert steppe, and mountain meadow, were observed to study their production changes in space and time using traditional method, PPR and remote sensing techniques. PPR models established by observed forage yields and different environmental factors as well as satellite information in four grasslands, and their applications of estimating grassland yields were discussed in detail in this paper. The problems of non-linear, non-normalized distribution, and correlated relationships between multi- variables for statistical data were solved by PPR technology. Therefore, the precision and effects to estimate grassland yields were greatly improved versus those of traditional multi-variate linear statistical method. Because of organic combination of remote sensing data and environmental information, it could not only estimate grassland yields on large area, but also extend the results gained on small area to a large extent for monitoring grassland resources and forecasting yields in future using the established models. By use of eight factors observed in four types of grasslands, the comprehensive yield in four different types were simulated by PPR and RS, GIS, GPS technology from 1995 to 1996. Results indicate that the precision of the models in plain desert, saline steppe, hill desert steppe, and mountain meadow reached over 81.76%, 88.61%, 83.50% and 92.35% respectively. The objective of scientific estimating yields in different grassland types was realized by PPR and RS, GIS, GPS, technology.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Jianlong Li "Estimating grassland yields by projection pursuit regression (PPR) and RS, GIS, and GPS", Proc. SPIE 4385, Sensor Fusion: Architectures, Algorithms, and Applications V, (22 March 2001); https://doi.org/10.1117/12.421114
PROCEEDINGS
 8 PAGES
DOWNLOAD PDF SAVE TO MY LIBRARY
SHARE
GET CITATION
< Previous Article
|
Next Article >
Advertisement
Advertisement
KEYWORDS
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top