Mathematical modelling for forest growing stock using remote sensing - construction and validation


Citation

Benchalli S.S., . and Prajapati R.C., . Mathematical modelling for forest growing stock using remote sensing - construction and validation. pp. 177-189. ISSN 0302-2935

Abstract

In this paper the authors have attempted to combine aerial photographic and satellite data to form mathematical models for predicting forest biomass in the field. The result shows that the models so formed provide useful basis to assess the forest biomass quickly with reduced human interpretation and field work and thus enable the detection of changes in the biomass a less cumbersome process in near real time monitoring. The accuracy with which the models predict the biomass is quite satisfactory in terms of standard deviation and root mean square error. The models suggested have been found to be statistically significant.


Download File

Full text available from:

Abstract

In this paper the authors have attempted to combine aerial photographic and satellite data to form mathematical models for predicting forest biomass in the field. The result shows that the models so formed provide useful basis to assess the forest biomass quickly with reduced human interpretation and field work and thus enable the detection of changes in the biomass a less cumbersome process in near real time monitoring. The accuracy with which the models predict the biomass is quite satisfactory in terms of standard deviation and root mean square error. The models suggested have been found to be statistically significant.

Additional Metadata

[error in script]
Item Type: Article
Additional Information: Summary (En)
AGROVOC Term: FORESTS
AGROVOC Term: BIOMASS
AGROVOC Term: MODELS
AGROVOC Term: AERIAL SURVEYING
AGROVOC Term: PHOTOGRAPHY
AGROVOC Term: SATELLITES
AGROVOC Term: MONITORING
AGROVOC Term: CONSTRUCTION BOSQUES
AGROVOC Term: BIOMASA
AGROVOC Term: MODELOS
Depositing User: Ms. Norfaezah Khomsan
Last Modified: 24 Apr 2025 05:52
URI: http://webagris.upm.edu.my/id/eprint/17625

Actions (login required)

View Item View Item