Zobrazeno 1 - 10
of 38
pro vyhledávání: '"María Teresa Lamelas"'
Publikováno v:
Remote Sensing, Vol 16, Iss 18, p 3536 (2024)
In this study, we evaluated the capability of an unmanned aerial vehicle with a LiDAR sensor (UAV-LiDAR) to classify and map fuel types based on the Prometheus classification in Mediterranean environments. UAV data were collected across 73 forest plo
Externí odkaz:
https://doaj.org/article/68f7466506494334936fd1b4fa1cffe0
Publikováno v:
Fire, Vol 7, Iss 2, p 59 (2024)
The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow for the und
Externí odkaz:
https://doaj.org/article/f5ad7b77741048969d3f07b43d93dc4e
Autor:
María Teresa Lamelas, Darío Domingo
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4589 (2023)
Forest ecosystems cover 31% of the world [...]
Externí odkaz:
https://doaj.org/article/a958da6e87644bdeaf023b12051e8541
Autor:
Raúl Hoffrén, María Teresa Lamelas, Juan de la Riva, Darío Domingo, Antonio Luis Montealegre, Alberto García-Martín, Sergio Revilla
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 116, Iss , Pp 103175- (2023)
Identification of forest fuels is a key step for forest fire prevention since they provide valuable information of fire behavior. This study assesses NASA’s Global Ecosystem Dynamics Investigation (GEDI) system to classify fuel types in Mediterrane
Externí odkaz:
https://doaj.org/article/b2f6ce56f28b4711af4ff8d0a51d6ecc
Autor:
Darío Domingo, Antonio Luis Montealegre, María Teresa Lamelas, Alberto García-Martín, Juan de la Riva, Francisco Rodríguez, Rafael Alonso
Publikováno v:
GIScience & Remote Sensing, Vol 56, Iss 8, Pp 1210-1232 (2019)
The estimation of forest residual biomass is of interest to assess the availability of green energy resources. This study relates the Pinus halepensis Miller forest residual biomass (FRB), estimated in 192 field plots, to several independent variable
Externí odkaz:
https://doaj.org/article/f285449b896249279f0f11e5171d8aaf
Autor:
Antonio Luis Montealegre-Gracia, María Teresa Lamelas-Gracia, Alberto García-Martín, Juan de la Riva-Fernández, Francisco Escribano-Bernal
Publikováno v:
GIScience & Remote Sensing, Vol 54, Iss 5, Pp 721-740 (2017)
The aim of study is to map the carbon dioxide (CO2) emission of the aboveground tree biomass (AGB) in case of a fire event. The suitability of low point density, discrete, multiple-return, Airborne Laser Scanning (ALS) data and the influence of sever
Externí odkaz:
https://doaj.org/article/223db1806b3b4d9586bdaf3e0e3f3f09
Autor:
Darío Domingo, María Teresa Lamelas-Gracia, Antonio Luis Montealegre-Gracia, Juan de la Riva-Fernández
Publikováno v:
European Journal of Remote Sensing, Vol 50, Iss 1, Pp 384-396 (2017)
The knowledge of the forest biomass reduction produced by a wildfire can assist in the estimation of greenhouse gases to the atmosphere. This study focuses on the estimation of biomass losses and CO2 emissions by combustion of Aleppo pine forest in a
Externí odkaz:
https://doaj.org/article/1351a6b7af7d4f7d88c8b624dc6485b3
Autor:
Sergio Revilla, María Teresa Lamelas, Darío Domingo, Juan de la Riva, Raquel Montorio, Antonio Luis Montealegre, Alberto García-Martín
Publikováno v:
Remote Sensing, Vol 13, Iss 3, p 342 (2021)
Fuel type is one of the key factors for analyzing the potential of fire ignition and propagation in agricultural and forest environments. The increase of three-dimensional datasets provided by active sensors, such as LiDAR (Light Detection and Rangin
Externí odkaz:
https://doaj.org/article/7615e7d75c964255b5ad0851612a3f6a
Autor:
Darío Domingo, Juan de la Riva, María Teresa Lamelas, Alberto García-Martín, Paloma Ibarra, Maite Echeverría, Raúl Hoffrén
Publikováno v:
Remote Sensing, Vol 12, Iss 21, p 3660 (2020)
Mediterranean forests are recurrently affected by fire. The recurrence of fire in such environments and the number and severity of previous fire events are directly related to fire risk. Fuel type classification is crucial for estimating ignition and
Externí odkaz:
https://doaj.org/article/6dea7a4c0058464b916981870cb9c4e8
Publikováno v:
Remote Sensing, Vol 7, Iss 7, Pp 8631-8654 (2015)
Airborne Laser Scanning (ALS) is capable of estimating a variety of forest parameters using different metrics extracted from the normalized heights of the point cloud using a Digital Elevation Model (DEM). In this study, six interpolation routines we
Externí odkaz:
https://doaj.org/article/0347c1c02b5743a08a3c7eef1bf09056