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Inventario y cartografía de variables del bosque con datos derivados de LiDAR: comparación de métodos.
- Source :
-
Madera y Bosques . otono2015, Vol. 21 Issue 3, p111-128. 18p. - Publication Year :
- 2015
-
Abstract
- The most common method to estimate forest variables to a large or small scale is the forest inventory based on field sampling. Currently, remote sensing techniques offer a range of possibilities in forest resources estimation; this is the case of LiDAR (Light Detection And Ranging) that allows the characterization forest structure in three-dimensions. We analyzed the relationship between LiDAR and field data to estimate forest variables such as: basal area (AB), total biomass (BT), crown cover (COB) and timber volume (VOL) through four methods: 1) multiple linear regression, 2) non-linear regression, 3) ratio estimators and 4) traditional forest inventory (stratified sampling). Total estimates derived from the ratio estimator were within the 95% confidence interval calculated by traditional inventory for AB, BT and VOL; this estimator showed the closest values and precision to those obtained by traditional forest inventory. In general, estimates through non-linear models were the most optimistic compared to the traditional forest inventory. Our results indicated a good relationship (R2 > 0.50) between LiDAR metrics and field data, particularly the percentiles of height and rates of return on a defined height. From the linear models fit we generated maps for each of the forest variables analyzed. [ABSTRACT FROM AUTHOR]
- Subjects :
- *FOREST mapping
*FORESTRY research
*BIOMASS
*FOREST biomass
*FOREST surveys
Subjects
Details
- Language :
- Spanish
- ISSN :
- 14050471
- Volume :
- 21
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Madera y Bosques
- Publication Type :
- Academic Journal
- Accession number :
- 111952391