Assessment of airborne LIDAR for snowpack depth modeling
Fuente:
Redalyc
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Artículo científico |
| Lingua: | en |
| Pubblicazione: |
Sociedad Geológica Mexicana, A.C.
2011
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1876468397119635456 |
|---|---|
| author | Ignacio Moreno Baños |
| author_facet | Ignacio Moreno Baños |
| contents | Assessment of airborne LIDAR for snowpack depth modeling Ignacio Moreno Baños Antoni Ruiz García Jordi Marturià i Alavedra Pere Oller i Figueras Jordi Piña Iglesias Pere Martínez i Figueras Julià Talaya López Ciencias de la Tierra GIS LIDAR Pyrenees Snowpack depth stepwise regression tree The Institut Geològic de Catalunya (IGC) and the Institut Cartogràfic de Catalunya (ICC) have begun a joint project to model snowpack depth distribution in the Núria valley (a 38 km² basin located in the Eastern Pyrenees) in order to evaluate water reserves in mountain watersheds . The evaluation was based on a remote sensing airborne LIDAR survey and validated with field-work calculations. Previous studies have applied geostatistical techniques to extrapolate sparse point data obtained from costly field-work campaigns. Despite being a recently developed technique, LIDAR has become a useful method in snow sciences as it produces dense point data and covers wide areas. The new methodology presented here combines LIDAR data with field-work, the use of geographical information systems (GIS) and the stepwise regression tree (SRT), as an extrapolation technique. These methods have allowed us to map snowpack depth distribution in high spatial resolution. Extrapolation was necessary because raw LIDAR data was only obtained from part of the study area in order to minimise costs. Promising results show high correlation between LIDAR data and field data, validating the use of airborne laser altimetry to estimate snow depth. Moreover, differences of total snow volume calculated from modeled snowpack distribution and total volume from LIDAR data differ by only 1 %. 2011 artículo científico 1405-3322 https://www.redalyc.org/articulo.oa?id=94319372009 en http://www.redalyc.org/revista.oa?id=943 Boletín de la Sociedad Geológica Mexicana application/pdf Sociedad Geológica Mexicana, A.C. Boletín de la Sociedad Geológica Mexicana (México) Num.1 Vol.63 |
| format | Artículo científico |
| id | redalyc_94319372009 |
| institution | Redalyc |
| language | en |
| publishDate | 2011 |
| publisher | Sociedad Geológica Mexicana, A.C. |
| spellingShingle | Assessment of airborne LIDAR for snowpack depth modeling Ignacio Moreno Baños Ciencias de la Tierra GIS LIDAR Pyrenees Snowpack depth stepwise regression tree Assessment of airborne LIDAR for snowpack depth modeling Ignacio Moreno Baños Antoni Ruiz García Jordi Marturià i Alavedra Pere Oller i Figueras Jordi Piña Iglesias Pere Martínez i Figueras Julià Talaya López Ciencias de la Tierra GIS LIDAR Pyrenees Snowpack depth stepwise regression tree The Institut Geològic de Catalunya (IGC) and the Institut Cartogràfic de Catalunya (ICC) have begun a joint project to model snowpack depth distribution in the Núria valley (a 38 km² basin located in the Eastern Pyrenees) in order to evaluate water reserves in mountain watersheds . The evaluation was based on a remote sensing airborne LIDAR survey and validated with field-work calculations. Previous studies have applied geostatistical techniques to extrapolate sparse point data obtained from costly field-work campaigns. Despite being a recently developed technique, LIDAR has become a useful method in snow sciences as it produces dense point data and covers wide areas. The new methodology presented here combines LIDAR data with field-work, the use of geographical information systems (GIS) and the stepwise regression tree (SRT), as an extrapolation technique. These methods have allowed us to map snowpack depth distribution in high spatial resolution. Extrapolation was necessary because raw LIDAR data was only obtained from part of the study area in order to minimise costs. Promising results show high correlation between LIDAR data and field data, validating the use of airborne laser altimetry to estimate snow depth. Moreover, differences of total snow volume calculated from modeled snowpack distribution and total volume from LIDAR data differ by only 1 %. 2011 artículo científico 1405-3322 https://www.redalyc.org/articulo.oa?id=94319372009 en http://www.redalyc.org/revista.oa?id=943 Boletín de la Sociedad Geológica Mexicana application/pdf Sociedad Geológica Mexicana, A.C. Boletín de la Sociedad Geológica Mexicana (México) Num.1 Vol.63 |
| title | Assessment of airborne LIDAR for snowpack depth modeling |
| topic | Ciencias de la Tierra GIS LIDAR Pyrenees Snowpack depth stepwise regression tree |
| url | https://www.redalyc.org/articulo.oa?id=94319372009 |