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.
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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
| 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 |
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