Assessing post-storm forest dynamics in the pyrenees using high-resolution LIDAR data and aerial photographs

Blázquez-Casado, Ángela; Martín-Alcón, Santiago; Just, Ariadna; Cabré, Mariló; Coll, Lluís

doi:10.1007/s11629-014-3327-3

Cited by 3 publications

(1 citation statement)

References 51 publications

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“…El uso combinado de los datos procedentes de sensores remotos, como son los datos LiDAR y las imágenes de satélite, se ha convertido en un medio asequible y riguroso para la caracterización espacial y temporal de los ecosistemas forestales, dado que permiten la provisión de información espacial y temporalmente continua (Blázquez-Casado et al 2015). La adquisición de estos datos procedentes de sensores remotos no sustituye la necesidad de obtener datos de campo sólidos, pero disminuye notablemente su volumen (Stereńczak et al 2018).…”

Section: Integración De Imágenes De Satélite Y Datos Lidar Como Herraunclassified

Aplicación de imágenes de satélites y datos LiDAR en la modelización de recursos forestales

Casado¹

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Section: Integración De Imágenes De Satélite Y Datos Lidar Como Herraunclassified

Aplicación de imágenes de satélites y datos LiDAR en la modelización de recursos forestales

Casado¹

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Developing kNN forest data imputation for Catalonia

Pukkala,

Aquilué,

Just

et al. 2024

J. For. Res.

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The combined use of LiDAR (Light Detection And Ranging) scanning and field inventories can provide spatially continuous wall-to-wall information on forest characteristics. This information can be used in many ways in forest mapping, scenario analyses, and forest management planning. This study aimed to find the optimal way to obtain continuous forest data for Catalonia when using kNN imputation (kNN stands for “k nearest neighbors”). In this method, data are imputed to a certain location from k field-measured sample plots, which are the most similar to the location in terms of LiDAR metrics and topographic variables. Weighted multidimensional Euclidean distance was used as the similarity measure. The study tested two different methods to optimize the distance measure. The first method optimized, in the first step, the set of LiDAR and topographic variables used in the measure, as well as the transformations of these variables. The weights of the selected variables were optimized in the second step. The other method optimized the variable set as well as their transformations and weights in one single step. The two-step method that first finds the variables and their transformations and subsequently optimizes their weights resulted in the best imputation results. In the study area, the use of three to five nearest neighbors was recommended. Altitude and latitude turned out to be the most important variables when assessing the similarity of two locations of Catalan forests in the context of kNN data imputation. The optimal distance measure always included both LiDAR metrics and topographic variables. The study showed that the optimal similarity measure may be different for different regions. Therefore, it was suggested that kNN data imputation should always be started with the optimization of the measure that is used to select the k nearest neighbors.

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Space–time modeling of changes in the abundance and distribution of tree species

Moreno-Fernández

Hernández

Sánchez-González

et al. 2016

Forest Ecology and Management

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Assessing post-storm forest dynamics in the pyrenees using high-resolution LIDAR data and aerial photographs

Abstract: have shape Pyrenean s purpose w obtained fr comparison from airbor of past nat distribution forest stru regeneratio (T3), uneve and T6). Al and severit structures b recent time areas that h the study pe medium le presented whereas th markedly a

Cited by 3 publications

References 51 publications

Aplicación de imágenes de satélites y datos LiDAR en la modelización de recursos forestales

Aplicación de imágenes de satélites y datos LiDAR en la modelización de recursos forestales

Developing kNN forest data imputation for Catalonia

Space–time modeling of changes in the abundance and distribution of tree species

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