scholarly journals Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10158
Author(s):  
Álvaro Cortés-Molino ◽  
Isabel Aulló-Maestro ◽  
Ismael Fernandez-Luque ◽  
Antonio Flores-Moya ◽  
José A. Carreira ◽  
...  
Keyword(s):  
Stand Structure ◽  
Secondary Growth ◽  
Canopy Structure ◽  
Airborne Lidar ◽  
Distribution Area ◽  
Lidar Data ◽  
Fire Simulation ◽  
Entire Area ◽  
Fuel Models ◽  
Abies Pinsapo

In this study we combine information from aerial LIDAR and hemispherical images taken in the field with ForeStereo—a forest inventory device—to assess the vulnerability and to design conservation strategies for endangered Mediterranean fir forests based on the mapping of fire risk and canopy structure spatial variability. We focused on the largest continuous remnant population of the endangered tree species Abies pinsapo Boiss. spanning 252 ha in Sierra de las Nieves National Park (South Andalusia, Spain). We established 49 sampling plots over the study area. Stand structure variables were derived from ForeStereo device, a proximal sensing technology for tree diameter, height and crown dimensions and stand crown cover and basal area retrieval from stereoscopic hemispherical images photogrammetry. With this information, we developed regression models with airborne LIDAR data (spatial resolution of 0.5 points∙m−2). Thereafter, six fuel models were fitted to the plots according to the UCO40 classification criteria, and then the entire area was classified using the Nearest Neighbor algorithm on Sentinel imagery (overall accuracy of 0.56 and a KIA-Kappa Coefficient of 0.46). FlamMap software was used for fire simulation scenarios based on fuel models, stand structure, and terrain data. Besides the fire simulation, we analyzed canopy structure to assess the status and vulnerability of this fir population. The assessment shows a secondary growth forest that has an increasing presence of fuel models with the potential for high fire spread rate fire and burn probability. Our methodological approach has the potential to be integrated as a support tool for the adaptive management and conservation of A. pinsapo across its whole distribution area (<4,000 ha), as well as for other endangered circum-Mediterranean fir forests, as A. numidica de Lannoy and A. pinsapo marocana Trab. in North Africa.

scholarly journals Estimation of crown and canopy cover from airborne lidar data

2010 ◽  
Vol 52 (1) ◽  
pp. 5-17 ◽  
Author(s):  
Mait Lang
Keyword(s):  
Norway Spruce ◽  
Scots Pine ◽  
Stand Structure ◽  
Canopy Cover ◽  
Airborne Lidar ◽  
Silver Birch ◽  
Lidar Data ◽  
Crown Cover ◽  
Pine Trees ◽  
Airborne Lidar Data

Metsa katvuse ja liituse hindamine lennukilt laserskanneriga Tests were carried out in mature Scots pine, Norway spruce and Silver birch stands at Järvselja, Estonia, to estimate canopy cover (K) and crown cover (L) from airborne lidar data. Independent estimates Kc and Lc for K and L were calculated from the Cajanus tube readings made on the ground at 1.3 m height. Lidar data based cover estimates depended on the inclusion of different order returns significantly. In all the stands first order return based estimate K1 was biased positively (3-10%) at the reference height of 1.3 m compared to ground measurements. All lidar based estimates decreased with increasing the reference height. Single return (Ky) and all return (Kk) based canopy cover estimates depended more on the sand structure compared to K1. The ratio of all return count to the first return count D behaved like crown cover estimate in all stands. However, in spruce stand D understimated Lc significantly. In the Scots pine stand K1(1.3) = 0.7431 was most similar canopy cover estimate relative to the ground estimate Kc = 0,7362 whereas Ky(1.3) and Kk(1.3) gave significant underestimates (>15%) of K. Caused by the simple structure of Scots pine stand - only one layer pine trees, the Cajanus tube based canopy cover (Kc), crown cover (Lc) and lidar data based canopy density D(1.3) values were rather similar. In the Norway spruce stand and in the Silver birch stand second layer and regeneration trees were present. In the Silver birch stand Kk(1.3) and Ky(1.3) estimated Kc rather well. In the Norway spruce stand Ky(1.3) and K1(1.3) were the best estimators of Kc whereas Kk(1.3) underestimated canopy cover. Lidar data were found to be usable for canopy cover and crown cover assessment but the selection of the estimator is not trivial and depends on the stand structure.

scholarly journals Patch dynamics and the development of structural and spatial heterogeneity in Pacific Northwest forests

2011 ◽  
Vol 41 (12) ◽  
pp. 2276-2291 ◽  
Author(s):  
Van R. Kane ◽  
Rolf F. Gersonde ◽  
James A. Lutz ◽  
Robert J. McGaughey ◽  
Jonathan D. Bakker ◽  
...  
Keyword(s):  
Pacific Northwest ◽  
Stand Structure ◽  
Spatial Scales ◽  
Canopy Structure ◽  
Patch Dynamics ◽  
Spatial Arrangement ◽  
Airborne Lidar ◽  
Small Scale ◽  
Individual Site ◽  
Time Required

Over time, chronic small-scale disturbances within forests should create distinct stand structures and spatial patterns. We tested this hypothesis by measuring the structure and spatial arrangement of gaps and canopy patches. We used airborne LiDAR data from 100 sites (cumulative 11.2 km2) in the Pacific Northwest, USA, across a 643 year chronosequence to measure canopy structure, patch and gap diversity, and scales of variance. We used airborne LiDAR’s ability to identify strata in canopy surface height to distinguish patch spatial structures as homogeneous canopy structure, matrix–patch structures, or patch mosaics. We identified six distinct stand structure classes that were associated with the canopy closure, competitive exclusion, maturation, and three patch mosaics stages of late seral forest development. Structural variance peaked in all classes at the tree-to-tree and tree-to-gap scales (10–15 m), but many sites maintained high variance at scales >30 m and up to 200 m, emphasizing the high patch-to-patch heterogeneity. The time required to develop complex patch and gap structures was highly variable and was likely linked to individual site circumstances. The high variance at larger scales appears to be an emergent property that is not a simple propagation of processes observed at smaller spatial scales.

Tropical Forest Canopy Structure and Change Assessment Using Landsat, GEDI, and Airborne Lidar Data

2021 ◽  
Author(s):  
Peter Potapov ◽  
Xinyuan Li ◽  
Andres Hernandez-Serna ◽  
Svetlana Turubanova ◽  
Alexandra Tyukavina ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Canopy ◽  
Canopy Structure ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Change Assessment ◽  
Airborne Lidar Data ◽  
Tropical Forest Canopy

Estimating canopy structure and biomass in bamboo forests using airborne LiDAR data

2019 ◽  
Vol 148 ◽  
pp. 114-129 ◽  
Author(s):  
Lin Cao ◽  
Nicholas C. Coops ◽  
Yuan Sun ◽  
Honghua Ruan ◽  
Guibin Wang ◽  
...  
Keyword(s):  
Canopy Structure ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Airborne Lidar Data

Reconstruction of the disturbance history of a temperate coniferous forest through stand-level analysis of airborne LiDAR data

2019 ◽  
Author(s):  
Nuria Sanchez-Lopez ◽  
Luigi Boschetti ◽  
Andrew T Hudak
Keyword(s):  
Forest Canopy ◽  
Stand Structure ◽  
Explanatory Power ◽  
Coniferous Forest ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Disturbance History ◽  
History Of ◽  
Level Analysis

Abstract Spatially explicit information about stand-level Time Since the last stand-replacing Disturbance (TSD) is fundamental for modelling many forest ecosystem processes, but most of the current satellite remote sensing mapping approaches are based on change detection and time series analysis, and can detect only disturbances that have occurred since the start of the optical satellite data record. The spatial legacy of stand-replacing disturbances can however persist on the landscape for several decades to centuries, in the form of distinct horizontal and vertical stand structure features. We propose a new approach to reconstruct the long-term disturbance history of a forest, estimating TSD through stand-level analysis of LiDAR data, which are highly sensitive to the three-dimensional forest canopy structure. The study area is in the Nez Perce-Clearwater National Forest in north-central Idaho, where airborne LiDAR covering about 52,000 ha and ancillary TSD reference data for a period of more than 140 years were available. The root mean square difference (RSMD) between predicted and reference TSD was 17.5 years with a BIAS of 0.8 years; and on 72.8% of the stands the predicted TSD was less than 10 years apart from the reference TSD (78.2% of the stands when considering only disturbances occurred in the last 100 years). The results demonstrate that airborne LiDAR-derived data have enough explanatory power to reconstruct the long-term, stand-replacing disturbance history of temperate forested areas at regional scales.

Sign in / Sign up

Export Citation Format

Share Document