Spectroscopic Determination of Aboveground Biomass in Grasslands Using Spectral Transformations, Support Vector Machine and Partial Least Squares Regression

[EN] Aboveground biomass (AGB) is one of the strategic biophysical variables of interest in vegetation studies. The main objective of this study was to evaluate the Support Vector Machine (SVM) and Partial Least Squares Regression (PLSR) for estimating the AGB of grasslands from field spectrometer data and to find out which data pre-processing approach was the most suitable. The most accurate model to predict the total AGB involved PLSR and the Maximum Band Depth index derived from the continuum removed reflectance in the absorption features between 916–1,120 nm and 1,079–1,297 nm (R2 = 0.939, RMSE = 7.120 g/m2). Regarding the green fraction of the AGB, the Area Over the Minimum index derived from the continuum removed spectra provided the most accurate model overall (R2 = 0.939, RMSE = 3.172 g/m2). Identifying the appropriate absorption features was proved to be crucial to improve the performance of PLSR to estimate the total and green aboveground biomass, by using the indices derived from those spectral regions. Ordinary Least Square Regression could be used as a surrogate for the PLSR approach with the Area Over the Minimum index as the independent variable, although the resulting model would not be as accurate.SIThis research has been partially funded by the Junta de Castilla y Leó

A Deep Learning Model for Automatic Plastic Mapping Using Unmanned Aerial Vehicle (UAV) Data

[EN] Although plastic pollution is one of the most noteworthy environmental issues nowadays, there is still a knowledge gap in terms of monitoring the spatial distribution of plastics, which is needed to prevent its negative effects and to plan mitigation actions. Unmanned Aerial Vehicles (UAVs) can provide suitable data for mapping floating plastic, but most of the methods require visual interpretation and manual labeling. The main goals of this paper are to determine the suitability of deep learning algorithms for automatic floating plastic extraction from UAV orthophotos, testing the possibility of differentiating plastic types, and exploring the relationship between spatial resolution and detectable plastic size, in order to define a methodology for UAV surveys to map floating plastic. Two study areas and three datasets were used to train and validate the models. An end-to-end semantic segmentation algorithm based on U-Net architecture using the ResUNet50 provided the highest accuracy to map different plastic materials (F1-score: Oriented Polystyrene (OPS): 0.86; Nylon: 0.88; Polyethylene terephthalate (PET): 0.92; plastic (in general): 0.78), showing its ability to identify plastic types. The classification accuracy decreased with the decrease in spatial resolution, performing best on 4 mm resolution images for all kinds of plastic. The model provided reliable estimates of the area and volume of the plastics, which is crucial information for a cleaning campaign.S

Long-Term Monitoring of Inland Water Quality Parameters Using Landsat Time-Series and Back-Propagated ANN: Assessment and Usability in a Real-Case Scenario

[EN] Water scarcity and quality deterioration, driven by rapid population growth, urbanization, and intensive industrial and agricultural activities, emphasize the urgency for effective water management. This study aims to develop a model to comprehensively monitor various water quality parameters (WQP) and evaluate the feasibility of implementing this model in real-world scenarios, addressing the limitations of conventional in-situ sampling. Thus, a comprehensive model for monitoring WQP was developed using a 38-year dataset of Landsat imagery and in-situ data from the Water Information System of Europe (WISE), employing Back-Propagated Artificial Neural Networks (ANN). Correlation analyses revealed strong associations between remote sensing data and various WQPs, including Total Suspended Solids (TSS), chlorophyll-a (chl-a), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP). Optimal band combinations for each parameter were identified, enhancing the accuracy of the WQP estimation. The ANN-based model exhibited very high accuracy, particularly for chl-a and TSS (R2 > 0.90, NRMSE < 0.79%), surpassing previous studies. The independent validation showcased accurate classification for TSS and TN, while DO estimation faced challenges during high variation periods, highlighting the complexity of DO dynamics. The usability of the developed model was successfully tested in a real-case scenario, proving to be an operational tool for water management. Future research avenues include exploring additional data sources for improved model accuracy, potentially enhancing predictions and expanding the model’s utility in diverse environmental contexts.S

Caracterización del interfaz forestal/urbano empleando LiDAR como herramienta para la estimación del riesgo de daños por incendios forestales

[EN] Galicia is a region in NW Spain which is usually affected by a high number of forest fires, and it should meet the current regulations regarding the distance between forests and buildings. This paper aims to identify and characterize woodlands and classify buildings according to their fire risk, for a 36 km2 area in Forcarei (Pontevedra, Spain). We used LiDAR data to generate three spatial models (DTM: Digital Terrain Model, DSM: Digital Surface Model and nDSM: Normalized Digital Surface Model) and two statistics to characterize the forest stands (density of dominant trees per hectare and their average height). The identification of forested areas was performed using an object-based classification method using the intensity image, the height model and an orthophotograph of the area, and a kappa coefficient of 0.82 was obtained in the validation. The woodlands were reclassified according to the magnitude of a possible fire, based on the density and the average height of the woodlands. The forest stands were mapped according to the magnitude of a possible fire and it was found that 1.18 km2 would be susceptible to a low magnitude fire, 3.75 km2 to a medium magnitude fire and 2.25 km2 to a fire of a high magnitude. Afterwards, it was determined whether the buildings in the area complied with the legislation relating to minimum distance from the forested areas (30 meters). For those that did not meet this distance, the risk of damage in case of a wildfire was calculated. The result was that 43.01% of buildings in the area complied with the regulations, 9.95% were located in a very low risk area, 25.74% in a low risk location, 12.37% in a medium risk area and 8.93% were in a high or very high risk area.S

Advantages and shortcomings of migrating cartography from ArcViewTM to ArcGisTM. Conclusions and practical recommendations

P. 1-11En este artículo se exponen de un modo práctico las ventajas e inconvenientes de la migración de la cartografía de ArcViewTM 3.x a ArcGISTM 8.x y se incluyen recomendaciones y sugerencias basadas en la experiencia práctica de los autores, para hacer esta tarea más sencilla. Los usuarios SIG se encontrarán con un nuevo sistema y nuevos conceptos, más allá de un simple cambio de versión. Diseñar un nuevo SIG en lugar de adaptar el existente puede ser incluso la solución más sencilla, puesto que tratar de mantener la misma apariencia en la cartografía puede convertirse en una tarea tediosa. La migración ha sido considerada por los autores como una oportunidad para revisar la estructura del SIG existente. El experto en SIG debe informar al responsable de la toma de decisiones de las ventajas e inconvenientes del nuevo sistema de modo que se satisfagan todos los requerimientos y emerjan otros nuevosS

Estimación de biomasa en herbáceas a partir de datos hiperespectrales, regresión PLS y la transformación continuum removal

[ES] El objetivo del estudio fue comparar los resultados de dos métodos para la estimación de la biomasa aérea a partir de datos de espectroradiometría de campo: (i) regresión por mínimos cuadrados parciales (Partial Least Squa-res Regression, PLSR) y (ii) regresión lineal utilizando los índices Profundidad del Mínimo (Maximum Band Depth, MBD) y Área Sobre el Mínimo (Area Over the Minimum, AOM) como descriptores. En ambos casos se llevó a cabo una previa transformación de los espectros mediante Continuum Removal (CR). Como los resultados empleando PLS (R2=0,920, RMSE=3,622 g/m2) fueron muy similares a los obtenidos con los índices (para AOM: R2=0,915, RMSE=3,615 g/m2), recomendamos los índices derivados del CR puesto que su interpretación es más sencilla que la del PLSRS

Assessment of low-cost GPS receiver accuracy and precision in forest environments

P. 159-167Selecting the apppropriate receiver is an issue when a major portion of global positioning system (GPS) data collection is below forest canopies. This study compares four low-cost GPS receivers, in order to determine the most suitable receiver for position assessment under differnt forest canopy covers, in terms of ease of use, accuracy, and relability. A total of 33 positional assessments were gathered per receiver, plot, and method, in 18 forest location.S

Radial growth and wood density reflect the impacts and susceptibility to defoliation by gypsy moth and climate in radiata pine

[EN] Drought stress causes a reduction in tree growth and forest productivity, which could be aggravated by climate warming and defoliation due to moth outbreaks. We investigate how European gypsy moth (Lymantria dispar dispar L., Lepidoptera: Erebidae) outbreak and related climate conditions affected growth and wood features in host and non-host tree species in north-western Spain. There, radiata pine (Pinus radiata D. Don) plantations and chestnut (Castanea sativa Mill.) stands were defoliated by the moth larvae, whereas Maritime pine (Pinus pinaster Ait.) was not defoliated. The gypsy moth outbreak peaked in 2012 and 2013, and it was preceded by very warm spring conditions in 2011 and a dry-warm 2011–2012 winter. Using dendrochronology we compared growth responses to climate and defoliation of host species (radiata pine, chestnut) with the non-host species (Maritime pine). We also analyzed wood density derived from X-ray densitometry in defoliated and non-defoliated trees of radiata pine. We aimed to: (i) disentangle the relative effects of defoliation and climate stress on radial growth, and (ii) characterize defoliated trees of radiata pine according to their wood features (ring-width, maximum and minimum density). Radial growth during the outbreak (2012–2013) decreased on average 74% in defoliated (>50% of leaf area removed) trees of radiata pine, 43% in defoliated trees of chestnut, and 4% in non-defoliated trees of Maritime pine. After applying a BACI (Before-After-Control-Impact) type analysis, we concluded that the difference in the pattern of radial growth before and during the defoliation event was more likely due to the differences in climate between these two periods. Radiata pines produced abundant latewood intra-annual density fluctuations in 2006 and 2009 in response to wet summer conditions, suggesting a high climatic responsiveness. Minimum wood density was lower in defoliated than in non-defoliated trees of radiata pine prior to the outbreak, but increased during the outbreak. The pre-outbreak difference in minimum wood density suggests that the trees most affected by the outbreak produced tracheids with wider lumen and were more susceptible to drought stress. Results of this study illustrate (i) that the pattern of radial growth alone may be not a good indicator for reconstructing past defoliation events and (ii) that wood variables are reliable indicators for assessing the susceptibility of radiata pine to defoliation by the gypsy mothSIFunding for this research was provided by the Local Government of Cubillos del Sil (Spain) through the contract Seguimiento y bases para la gestión de las masas forestales afectadas por defoliación de Lymantria dispar en el municipio de Cubillos del Sil

Vineyard area estimation using medium spatial resolution satellite imagery

P. 441-452The European Union requires member states to estimate their wine growing potential. For this porpose, most member states have developed or updated vineyard registers. The present study suggests locating vineyards using medium spatial resolution satellite imagery. The work was carried out using Landsat images that were validated for the Designation of Origin "Bierzo", León, SpainS

Geometric Stability and Lens Decentering in Compact Digital Cameras

P. 1553-1572A study on the geometric stability and decentering present in sensor-lens systems of six identical compact digital cameras has been conducted. With regard to geometrical stability, the variation of internal geometry parameters (principal distance, principal point position and distortion parameters) was considered. With regard to lens decentering, the amount of radial and tangential displacement resulting from decentering distortion was related with the precision of the camera and with the offset of the principal point from the geometric center of the sensor. The study was conducted with data obtained after 372 calibration processes (62 per camera). The tests were performed for each camera in three situations: during continuous use of the cameras, after camera power off/on and after the full extension and retraction of the zoom-lens. Additionally, 360 new calibrations were performed in order to study the variation of the internal geometry when the camera is rotated. The aim of this study was to relate the level of stability and decentering in a camera with the precision and quality that can be obtained. An additional goal was to provide practical recommendations about photogrammetric use of such cameras.S