Biomass estimation using LiDAR data

ABSTRACT: Forest ecosystems play a very important role in carbon cycle because they suppose one of thebiggest carbon reservoirs and sinks. Estimating the aboveground forest biomass is critical tounderstand the global carbon storage process. Different models to estimate aboveground biomassin the Pinus radiata specie in a specific region of Spain have been developed, using, exclusively,public and accessible data with low point density gathered periodically from Light Detection andRanging (LiDAR) flights. The point clouds data were processed to obtain metrics considered aspredictive variables and afterwards, the multiple regression technique has been applied togenerate the biomass estimation models. The best models explain 76% of its variability with astandard error of 0.26 ton/ha in logarithmic units. The methodology can be considered as highlyautomated and extensible to other territories with similar characteristics. Our results support theuse of this approach for more sustainable management of forest areas

Regional coastal cliff classification: application to the cantabrian coast, Spain

The retreat of coastal cliffs is a natural process that occurs due to the interaction of different forcings that can be marine and atmospheric, and conditioned by the lithological properties of the rock material. Several attempts have been done at different scales to quantify and rank the various parameters that influence erosion rates, most of them agreeing that cliff retreat is governed by the lithological properties of the cliffs. Although, due to the large number of parameters involved there is not a clear consensus. The present study aims to characterize the cliffs along the Cantabrian coast by using an unsupervised classification of their physical and lithological characteristics, and by analyzing their retreat behavior. The proposed methodology is scalable to larger coastal areas. The study found that Cantabrian coastal cliffs have a low mean retreat rate of 0.042 m/year, with a maximum retreat rate of up to 0.4 m/year in two locations. Nine distinct groups of cliff behavior have been found, with only two of them presenting high erosional records, which are controlled by lithological features. Cliffs with the highest erosion rates are composed of alternating lithologies and more erodible materials. The results suggest that the factors most influencing erosive retreat in cliffs are the type of lithology and the alternation of different lithologies

Prediction of Aboveground Biomass from Low-Density LiDAR Data: Validation over P. radiata Data from a Region North of Spain

ABSTRACT: Estimation of forestry aboveground biomass (AGB) by means of aerial Light Detection and Ranging (LiDAR) data uses high-density point sampling data obtained in dedicated flights, which are often too costly for available research budgets. In this paper we exploit already existing public low-density LiDAR data obtained for other purposes, such as cartography. The challenge is to show that such low-density data allows accurate biomass estimation. We demonstrate the approach on data available from plantations of Pinus radiata in the Arratia-Nervión region, located in Biscay province located in the North of Spain. We use public data gathered from the low-density (0.5 pulse/m2) LiDAR flight conducted by the Basque Government in 2012 for cartographic production. We propose a linear regression model based on explanatory variables obtained from the LiDAR point cloud data. We calibrate the model using field data from the Fourth National Forest Inventory (NFI4), including the selection of the optimal model variables. The results revealed that the best model depends on two variables extracted from LiDAR data: One directly related with tree height and a second parameter with the canopy density. The model explained 80% of its variability with a standard error of 0.25 ton/ha in logarithmic units. We validate the predictions against the biomass measurements provided by the government institutions, obtaining a difference of 8%. The proposed approach would allow the exploitation of the periodic available low-density LiDAR data, collected with territorial and cartographic purposes, for a more frequent and less expensive control of the forestry biomass.The work reported in this paper was partially supported by FEDER funds for the MINECO project TIN2017-85827-P, and project KK-2018/00071 of the Elkartek 2018 funding program of the Basque Government

Umbrales de lluvia para el desencadenamiento de inestabilidades de ladera en el norte de Portugal y de España: estado del arte

ES: Gran número de trabajos sobre umbrales de lluvia para el desencadenamiento de inestabilidades de ladera se ha desarrollado en áreas del norte de Portugal y España. Como resultado de una revisión, se han recopilado 103 umbrales. Más del 30% aún no han sido publicados. La comparación de cuatro umbrales regionales pone de manifiesto importantes diferencias ligadas al uso de múltiples metodologías para definir las condiciones críticas de lluvia.A great number of works focused on the calculation of empirical rainfall thresholds for the triggering of landslides have been developed in the northern areas of Portugal and Spain. Because of a review, 103 thresholds have been compiled. More than 30% of them have not yet been published. The comparison of four regional thresholds highlights relevant differences linked to the use of multiple methodologies to define the critical rainfall conditions

Propuesta Metodológica de Estimación de la Biomasa Aérea en la Comarca de Arratia-Nervión en el País Vasco a partir de datos lidar del PNOA

La determinación de la biomasa forestal es una cuestión de doble interés: económica y medioambiental. Convencionalmente, su estimación se ha efectuado por diversos procedimientos, siendo los más empleados los que se basan en muestreos estadísticos apoyados por costosos y lentos trabajos en campo, así como por el uso de distintos tipos de imágenes. El objetivo de esta investigación es desarrollar un modelo que permita estimar la biomasa aérea para una cierta especie en cualquier zona del territorio nacional en base al uso de datos LiDAR, cuya obtención en el PNOA está programada regularmente. De esta forma se podría conseguir la obtención del volumen indicado de forma significativamente menos costosa que en la actualidad, tanto temporal como económicamente. En particular, se ha seleccionado la especie Pinus Radiata D. Don en la comarca de Arratia-Nervión, situada en Bizkaia, usando de los datos del vuelo LiDAR realizado por Gobierno Vasco en 2012. En el proceso, se han utilizado los datos de campo del Inventario Forestal Nacional 4 como base para estimar la biomasa de contraste. Partiendo de las nubes de puntos LiDAR y tras su procesado, se han calculado diversas métricas provenientes de las mismas que se consideran como variables predictivas, entre ellas variables directamente relaciones con la altura y variables relacionadas con la densidad del dosel. Para la consecución del modelo, se ha aplicado la técnica de análisis estadístico de la regresión lineal múltiple. El resultado obtenido ha revelado que el mejor modelo depende de dos variables: un parámetro directamente relacionado con la altura LiDAR y otro con la densidad del dosel. El modelo consigue explicar el 76% de la variabilidad del mismo con un error estándar que asciende a 0.26 ton/ha en unidades logarítmicas

Experiencia del Uso de la Base Topográfica Armonizada (BTA) como Fuente de Contrastación de la Clasificación del vuelo LIDAR PNOA.

En este documento se presentan las conclusiones obtenidas en cuanto al uso de la Base Topográfica Armonizada (BTA) de la Comunidad Autónoma del País Vasco (CAPV) con el fin de entrenar y verificar una metodología de minería de datos para clasificar nubes de puntos capturadas en un vuelo LiDAR. Junto a esta información, se han utilizado las bandas Rojo (R), Verde (G), Azul (B) e Infrarrojo Cercano (NIR) procedentes de las ortografías del vuelo fotogramétrico. Ambos vuelos capturados dentro del marco del Plan Nacional de Ortofotografía Aérea (PNOA) del año 2008. Señalar que si bien la Base Topográfica Armonizada (BTA) ha permitido validar la metodología planteada para la clasificación de puntos LiDAR con fines cartográficos en zonas de diversas tipologías considerando el punto como unidad de trabajo, para el entrenamiento y la verificación de los resultados sería conveniente disponer de otra base de contrastación más acorde con la precisión de las nubes de puntos y las categorías a discrimina

Evaluación y análisis del riesgo de inundación del Río Besaya a su paso por Los Corrales de Buelna, Cantabria

En este estudio se plantea una metodología para analizar el riesgo de inundación a partir de la generación de series de precipitación sintéticas distribuidas por toda la cuenca y técnicas geoestadísticas, tomando como datos de partida series de precipitación real existentes. Realizada la reconstrucción de las series temporales sintéticas, se realizan simulaciones del comportamiento hidrológico de la cuenca. De las series de caudal obtenidas, se seleccionan aquellos eventos más significativos para realizar una simulación hidráulica y computar sus calados y velocidades de inundación. El resto de eventos se resuelven mediante técnicas híbridas de reducción de escala y métodos de minería de datos. Para calcular la inundación producida para un determinado período de retorno, la estadística de extremos se lleva a cabo sobre el calado y la velocidad de la inundación, no sobre la precipitación. La metodología propuesta muestrea de forma más exhaustiva el espacio de posibilidades, proporcionando mapas de riesgo de inundación que responden de manera más fidedigna a la información histórica

Rainfall and weather conditions inducing intense landslide activity in northern Spain (Deba, Guipúzcoa)

The Deba area is intensely affected by frequent shallow landslides triggered by rainfall. This contribution explores the role of rainfall in landslide activity during a quite long time span (60 years), from a large network of rainfall gauges and a complete inventory of landslides. Out of 1,180 landslides inventoried, more than 50% occurred simultaneously in 6 known dates, corresponding to 6 episodes triggering multiple landslides; 3,241 rainfall episodes have been automatically recognized and characterized in terms of rainfall amount and duration, providing a representative dataset that covers a wide range of movement types and behaviors. Relationship between rainfall episodes driving multiple movements simultaneously has not been explored in depth so far in northern Spain. The analysis provides different results. The extraordinary character of the triggering rainfall has been assessed and empirical rainfall thresholds (total amount, and mean intensity), producing multiple landslides, has been found and compared with others described in literature. Also, the meteorological conditions associated to those extreme events have been recognized: multiple landslide occurrences are triggered by extreme convective rainfall: intense, short and with limited horizontal extent, as well as a marked summer-autumn seasonality. This weather pattern is more characteristic of Mediterranean areas than of mild marine west-coast climates. The definition of the conditions of the multiple landslide occurrence events, qualitative and quantitative, makes it possible to better understand the behaviour of slopes, which is essential for better predictability of landslide occurrence.This work was supported by the research projects: ESPERIDES (CGL2013-46425-P, MINECO, Spain) and “Influencia del cambio climático y de la actividad humana en los procesos y riesgos geomorfológicos” (29.P052.64004, UC)

Quantitative and qualitative analysis on the integration of geographic information systems and building information modeling for the generation and management of 3D models

3D virtual management is a topic of growing interest. The AEC industry is undergoing a real revolution because of the technological changes that are taking place. Synchronized 3D visualization is one of the tools being deployed at an accelerated pace. This, together with collaborative work, contributes to optimal management for all stakeholders. The integration of geographic information systems and building information modeling and heritage BIM is one of the most innovative concepts; it enables the generation of collaborative, fluid systems. The objective of this research is to identify the most significant technological developments and potential applications of the aforementioned integration. For this purpose, after a bibliographic consultation (26,245 sources), two analyses are carried out (from the screening of 179 sources), one quantitative (bibliometric) and the other qualitative (focused on five key concepts). The results show that regarding the integration of GIS with BIM and HBIM, the highest concentration of contributions is in engineering with 30.66%, followed by computer science with 21.01%. The country with the highest number of citations is China with 717, followed by Australia and the USA with 549 and 513, respectively, but relativizing the number of citations based on various indices (human development index, gross national income per capita, and population-tertiary education level), Hong Kong (18.04), Australia (10.64), and Egypt (10.16) would take the top positions, respectively. Regarding universities, the entity that has generated the most references is Delft University of Technology (the Netherlands) with 15 papers, followed by University College London (UK) with 13. Finally, the results show that GIS and BIM and HBIM provide virtual 3D models with multiple applications for buildings and infrastructures