A5042071637- Remote Sensing and LiDAR Applications
- Forest ecology and management
- Forest Ecology and Biodiversity Studies
- Remote Sensing in Agriculture
- 3D Surveying and Cultural Heritage
- Fire effects on ecosystems
- Soil erosion and sediment transport
- Advanced Optical Sensing Technologies
- Species Distribution and Climate Change
- Plant Water Relations and Carbon Dynamics
- Leaf Properties and Growth Measurement
- Forest Management and Policy
- Smart Agriculture and AI
Universitat Politècnica de València
2016-2024
Valencian International University
2024
Full-waveform LiDAR (FWF) offers a promising advantage over other technologies to represent the vertical canopy structure of secondary successions in Amazon region, as waveform encapsulates properties all elements intercepting emitted beam. In this study, we investigated modifications Amazonian across vegetation gradient from early advanced stages regrowth. The analysis was performed two distinct climatic regions (Drier and Wetter), designated using Maximum Cumulative Water Deficit (MCWD)....
Modelling fire behaviour in forest fires is based on meteorological, topographical, and vegetation data, including species’ type. To accurately parameterise these models, an inventory of the area analysis with maximum spatial temporal resolution required. This study investigated use UAV-based digital aerial photogrammetry (UAV-DAP) point clouds to classify tree shrub species Mediterranean forests, this information key for correct generation wildfire models. In July 2020, two test sites...
Abstract Global mapping of forest height is an extremely important task for estimating habitat quality and modeling biodiversity. Recently, three global canopy maps have been released, the map (GFCH), high‐resolution model Earth (HRCH), tree (GMTCH). Here, we assessed their accuracy usability biodiversity modeling. We examined by comparing them with reference models derived from airborne laser scanning (ALS). Our results show considerable differences between evaluated maps. The root mean...
Mapping forest structure variables provides important information for the estimation of biomass, carbon stocks, pasture suitability or wildfire risk prevention and control. The optimization prediction models these requires an adequate stratification landscape in order to create specific each structural type strata. This paper aims propose validate use object-oriented classification methodology based on low-density LiDAR data (0.5 m−2) available at national level, WorldView-2 Sentinel-2...
<p>Los métodos de regresión se utilizan ampliamente en el ámbito forestal para la predicción y cartografiado las variables estructura combustibilidad. En este artículo evalúan diferentes modelos (lineal, no lineal, árboles ensemble). Como independientes utilizaron métricas extraídas datos LiDAR full-waveform, mientras que los valores dependientes generaron a partir basados campo obtenidos 78 parcelas 16 m radio. Se llevaron cabo transformaciones e con selección atributos evaluar su...
Abstract. Crop classification based on satellite and aerial imagery is a recurrent application in remote sensing. It has been used as input for creating updating agricultural inventories, yield prediction land management. In the context of Common Agricultural Policy (CAP), farmers get subsidies crop area cultivated. The correspondence between declared actual needs to be monitored every year, parcels must properly maintained, without signs abandonment. this work, Sentinel- 2 time series...
Abstract Filtering approaches on Global Ecosystem Dynamics Investigation (GEDI) data differ considerably across existing studies and it is yet unclear which method the most effective. We conducted an in‐depth analysis of GEDI's vertical accuracy in mapping terrain canopy heights three study sites temperate forests grasslands Spain, California, New Zealand. started with unfiltered (2,081,108 footprints) describe a workflow for filtering using Level 2A parameters geolocation error mitigation....
In recent decades, the feasibility of using terrestrial laser scanning (TLS) in forest inventories was investigated as a replacement for time-consuming traditional field measurements. However, optimal acquisition point clouds requires definition minimum density, well sensor positions within plot. This paper analyzes effect (i) number and distribution scans, (ii) density on estimation seven parameters: above-ground biomass, basal area, canopy base height, dominant stocking quadratic mean...
Abstract. Remote sensing and photogrammetry techniques have demonstrated to be an important tool for the characterization of forest ecosystems. Nonetheless, use these requires accurate digital terrain model (DTM) height normalization procedure, which is a key step prior any further analyses. In this manuscript, we assess extraction DTM different (airborne laser scanning: ALS, terrestrial TLS, aerial in unmanned vehicle: UAV-DAP), processing tools with algorithms (FUSION/LDV© LAStools©),...
<p>LiDAR technology –airborne and terrestrial- is becoming more relevant in the development of forest inventories, which are crucial to better understand manage ecosystems. In this study, we assessed a classification species composition Mediterranean following C4.5 decision tree. Different data sets from airborne laser scanner full-waveform (ALS<sub>FW</sub>), discrete (ALS<sub>D</sub>) terrestrial (TLS) were combined as input for classification. Species divided...
Abstract. The management of riverine areas is fundamental due to their great environmental importance. fast changes that occur in these river mechanics and human pressure makes it necessary obtain data with high temporal spatial resolution. This study proposes a workflow map species using Unmanned Aerial Vehicle (UAV) imagery. Based on RGB point clouds, our work derived simple geometric spectral metrics classify an area the public hydraulic domain Palancia (Spain) five different classes:...
Recognizing the species composition of an ecosystem is essential for conservation and land management. This study presents software Class3Dp, a supervised classifier vegetation coloured point clouds. Class3Dp run through graphical user interface (GUI) that allows selection training samples from RGB or MS (multispectral) clouds their classification based on geometric, spectral neighbourhood features, along with different machine learning methods, obtaining cloud classified according to...
In the last decade, full-waveform airborne laser scanning (ALSFW) has proven to be a promising tool for forestry applications. Compared traditional discrete (ALSD), it is capable of registering complete signal going through different vertical layers vegetation, allowing better characterization forest structure. However, there lack ALSFW software tools taking greater advantage these data. Additionally, most existing do not include radiometric correction, which essential use data, since...
The aim of this study was to analyze the variation on accuracy and errors aboveground biomass (AGB) canopy base height (CBH) estimates when modifying lidar full-waveform (FW) pulse density, voxel size regression methods. We reduced randomly density from 9 1 pulses.m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> in steps 0.5 36 plots. Afterwards, eight FW metrics were computed for each (i.e. 0.25, m) plot. These used as explanatory...
Abstract. LiDAR full-waveform provides a better description of the physical and forest vertical structure properties than discrete since it registers full wave that interacts with canopy. In this paper, effect flight line side-lap is analysed on canopy fuel variables estimations. Differences are related to pulse density changes between stripe areas, varying point 2.65 m−2 33.77 in our study area. These differences modify metrics extracted from data therefore variable values estimated these...
LiDAR full-waveform provides a better description of the physical and forest vertical structure properties than discrete since it registers full wave that interacts with canopy. In this paper, effect flight line side-lap is analysed on canopy fuel variables estimations. Differences are related to pulse density changes between stripe areas, varying point 2.65&thinsp;m&lt;sup&gt;&minus;2&lt;/sup&gt; 33.77&thinsp;m&lt;sup&gt;&minus;2&lt;/sup&gt;...
Abstract A methodology for estimating forest structure and fuel variables from airborne LiDAR data is presented, based on the following steps: (1) pre-treatment to obtain digital terrain model canopy height model; (2) extraction of features or attributes each sampling plot; (3) generation prediction models at plot level; (4) its extension maps in larger areas. The was applied a study area 4,100 ha municipality Cuenca, where flight carried out with nominal density 4 points/m 2 . For models,...
Airborne full-waveform LiDAR (ALSFW) is able to register forest structure properties, essential for fire prevention, in more detail than airborne discrete (ALSD). However, few studies have analyzed ALSFW methodological parameters (i.e., voxel size and assignation value) due the complexity lack of processing tools. In this paper we analyze influence pulse density on metrics, as well characterization understory vegetation through ALSFW. Results show that metrics may be modelled differences...
<p class="Bodytext">This PhD thesis addresses the development of full-waveform airborne laser scanning (ALS<sub>FW</sub>) processing and analysis methods to characterize vertical forest structure, in particular understory vegetation. In this sense, influence several factors such as pulse density, voxel parameters (voxel size assignation value), scan angle at acquisition, radiometric correction regression is analyzed on extraction ALS<sub>FW</sub> metric values...