Extreme values in SIR epidemic models with two strains and cross-immunity

The paper explores the dynamics of extreme values in an SIR (susceptible → infectious → removed) epidemic model with two strains of a disease. The strains are assumed to be perfectly distinguishable, instantly diagnosed and each strain of the disease confers immunity against the second strain, thus showing total cross-immunity. The aim is to derive the joint probability distribution of the maximum number of individuals simultaneously infected during an outbreak and the time to reach such a maximum number for the first time. Specifically, this distribution is analyzed by distinguishing between a global outbreak and the local outbreaks, which are linked to the extinction of the disease and the extinction of particular strains of the disease, respectively. Based on the mass function of the maximum number of individuals simultaneously infected during the outbreak, we also present an iterative procedure for computing the final size of the epidemic. For illustrative purposes, the twostrain SIR-model with cross-immunity is applied to the study of the spread of antibiotic-sensitive and antibiotic-resistant bacterial strains within a hospital ward

Mapping eucalyptus species using worldview 3 and random forest

Recent advances in remote sensing technologies have allowed the development of new innovative methodologies to obtain geospatial information about Eucalyptus genus distribution. This is an important task for forest stakeholders due to the high presence of this genus in forest plantations worldwide. Therefore, the next step in research should focus on exploring remote sensing possibilities to discern between Eucalytpus species. It would be an important step forward in forest management since different Eucalyptus species present different characteristics and properties that imply different management plans and industrial usages. This study accomplish the classification of E. nitens and E. globulus, the most common Eucalyptus species in the Iberian Peninsula. Worldview-3 images and random forest are used in a forest area placed in Galicia (Northwest of Spain). The differentiation of Eucalyptus species resulted in a producer’s accuracy of 84% and a users’ accuracy of 70% for E. nitens, while for E. globulus accuracy metrics did not reach 70%. The most important bands in the classification were the coastal blue and the blue, followed by the red related ones. The resulting unequal accuracy metrics might be caused by an imbalanced presence of both species in the selected study area. Therefore, further studies might be developed in different locations

Automatic forest change detection through a bi-annual time series of satellite imagery: toward production of an integrated land cover map

Land cover mapping is fundamental for national and international agencies to monitor forest resources. However, monitoring forest disturbances by direct comparison of these maps poses several difficulties and challenges. As a result, different methodologies have been explored to detect forest disturbances. However, most of them cannot be fully integrated with land cover map production since they require additional input data, while others are not suitable for monitoring small land parcels. This study presents a methodology that fulfils the need to integrate land cover mapping with land cover change detection. Specifically, this methodology was designed to complement the Sentinel-2-based land cover mapping used in Galicia, northwest Spain, a region characterized by small land parceling. First, two previously obtained land cover maps from 2019 and 2020 were compared to identify all the pixels with potential land cover changes using QGIS. The behavior of spectral indexes in a time series were then analyzed to identify which of the previously identified pixels correspond to forest disturbances. This step was implemented in the software R. Using the Normalized Difference Vegetation Index (NDVI) to detect different land cover changes it was obtained an overall accuracy of 82%, considering the existence of varying phenologies, diverse topographic conditions, and areas with a high level of stand fragmentation. This study could help agencies that have already developed their own land cover maps to easily advance the integration of their maps with land cover change detection, since this technique can be applied with any land cover mapping methodology based on multitemporal analysis of satellite images, without the need for additional input data.Ministerio de Universidades | Ref. FPU19/02054Agencia Estatal de Investigación | Ref. PID2019-111581RB-I00Xunta de GaliciaUniversidade de Vigo/CISU

Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest

Advances in remote sensing technologies are generating new perspectives concerning the role of and methods used for National Forestry Inventories (NFIs). The increase in computation capabilities over the last several decades and the development of new statistical techniques have allowed for the automation of forest resource map generation through image analysis techniques and machine learning algorithms. The availability of large-scale data and the high temporal resolution that satellite platforms provide mean that it is possible to obtain updated information about forest resources at the stand level, thus increasing the quality of the spatial information. However, photointerpretation of satellite and aerial images is still the most common way that remote sensing information is used for NFIs or forest management purposes. This study describes a methodology that automatically maps the main forest covers in Galicia (Eucalyptus spp., conifers and broadleaves) using Worldview-2 and the random forest classifier. Furthermore, the method also evaluates the separate mapping of the three most abundant Pinus tree species in Galicia (Pinus pinaster, Pinus radiata and Pinus sylvestris). According to the results, Worldview-2 multispectral images allow for the efficient differentiation between the main forest classes that are present in Galicia with a very high degree of accuracy (91%) and ample spatial detail. Pinus species can also be efficiently differentiated (83%).Xunta de GaliciaAgencia Estatal de Investigación | Ref. PID2019-111581RB-I00Universidade de Vig

Challenges in automatic forest change reporting through land cover mapping

Up-to-date knowledge about changes in forest resources and their spatial distribution is essential for sustainable forest management. Therefore, monitoring of forest evolution is increasingly demanded by national and international agencies to design forestry policies and to track their progress. Annually updated land cover maps based on open access satellite imagery may serve as a primary tool for monitoring forest surface evolution over time. Spatially detailed information about forest change might be obtained by comparing land cover maps over time. This study aims to better understand the processes underlying pixels whose land cover changes from 1 year’s map to the next and to understand why errors occur. In this study, two annual land cover maps were produced using Sentinel-2 images and afterwards they were compared. The comparison was performed in terms of total surface occupied in each map by each of the classes (net comparison) and in terms of spatial agreement, comparing the results pixel to pixel. The study was performed for the entire region of Galicia (in the Northwest of Spain) for the years 2019 and 2020. Land cover maps obtained had overall accuracies of 82 and 85 per cent. Differences in the total surface of change were encountered when performing the net comparison and spatial agreement comparison. The detailed analysis performed in this study helps to better understand the processes underlying the maps’ discrepancies revealing the processes leading to wrongly identified forest changes. Future studies could aim to integrate this knowledge into the monitoring system to improve the ultimate usability of land cover maps to retrieve information about forest changes.Ministerio de Universidades | Ref. FPU19/02054Agencia Estatal de Investigación | Ref. PID2019-111581RB-I00Universidade de Vigo/CISUGXunta de Galici

Mapping feasibility for wood supply: a high-resolution geospatial approach to enhance sustainable forest management in Galicia (NW Spain)

The forest value chain is key to the European transition to a climate-neutral economy. Sustainable forest management is essential for this task. To plan sustainable forest management, it is essential to track forest resources in relation to their feasibility for wood supply. This means considering the constraints that may limit the incorporation of these resources into the forest value chain. Maps adapted to specific regional constraints and to the characteristics of specific forests are essential for performing sustainable forest management at a local scale. This study presents a methodology for the integrated analysis of geospatial data focused on classifying the land and the forest resources of a region according to their feasibility for wood supply. It produces maps of the feasibility for wood supply in an area and of the existing forest resources at a 10 m spatial resolution. This was done by integrating information about the legal and technical constraints present in the area according to decision rules. The land was classified into three classes: favorable, intermediate or unfavorable. Additionally, updated forest-oriented land cover maps were produced to analyze the feasibility for wood supply of the forest resources present in the region. It was found that 42% of the Eucalyptus spp., 48% of the conifers and 30% of the broadleaves in the study area were located in favorable areas. These maps would help in the quest for more sustainable forest management in the region and aid in boosting the competitiveness of the regional forest value chain.Agencia Estatal de Investigación | Ref. PID2019-111581RB-I00Ministerio de Universidades | Ref. FPU19/02054Universidade de Vig

Automatic tree detection and attribute characterization using portable terrestrial lidar

Currently, the implementation of portable laser scanners (PLS) in forest inventories is being studied, since they allow for significantly reduced field-work time and costs when compared to the traditional inventory methods and other LiDAR systems. However, it has been shown that their operability and efficiency are dependent upon the species assessed, and therefore, there is a need for more research assessing different types of stands and species. Additionally, a few studies have been conducted in Eucalyptus stands, one of the tree genus that is most commonly planted around the world. In this study, a PLS system was tested in a Eucalyptus globulus stand to obtain different metrics of individual trees. An automatic methodology to obtain inventory data (individual tree positions, DBH, diameter at different heights, and height of individual trees) was developed using public domain software. The results were compared to results obtained with a static terrestrial laser scanner (TLS). The methodology was able to identify 100% of the trees present in the stand in both the PLS and TLS point clouds. For the PLS point cloud, the RMSE of the DBH obtained was 0.0716, and for the TLS point cloud, it was 0.176. The RMSE for height for the PLS point cloud was 3.415 m, while for the PLS point cloud, it was 10.712 m. This study demonstrates the applicability of PLS systems for the estimation of the metrics of individual trees in adult Eucalyptus globulus stands.Agencia Estatal de Investigación | Ref. PID2019-111581RB-I00Ministerio de Ciencia, Innovación y Universidades | Ref. FPU19/02054Universidade de Vigo/CISU

Forestry applications of ground-penetrating radar

Ground-penetrating radar (GPR) is a geophysical and close-range remote sensing technique based on the use of radar pulses to obtain cross-section images of underground features. This method is characterized by the transmission of an electromagnetic short length pulse (1-2 ns), presenting a centre frequency ranging from 10 MHz to 2.5 GHz. The principles of GPR operation are based on the ability of low frequency radar waves to penetrate into a non-conductive medium, usually subsoil, but also walls, concrete or wood. Those waves are detected after suffering a reflection in electromagnetic discontinuities of the propagation medium. Therefore, this is a suitable method to study changes in those physical properties, and also to characterize different mediums and the reflective targets providing information about their physical properties. The aim of this work is to describe and demonstrate different applications of GPR in forestry, showing the obtained results together with their interpretation. Firstly, in this paper, it is illustrated how GPR is able to map shallow bedrock, subsoil stratigraphy and also to estimate shallow watertable depth. Secondly, different tree trunks as well as dry timber are analyzed, evaluating the different radar data obtained in each particular case, and observing differences in their electromagnetic properties related to the GPR response. Finally, several measurements were taken in order to analyze the use of GPR to detect tree root systems using polarimetric techniques, being possible to detect medium and big size roots, together with groups of small roots. Key words: GPR, remote sensing, bedrock, watertable, trunk, root system.Postprint (published version

Metric potential of a 3D measurement system based on digital compact cameras

P. 4178-4194This paper presents an optical measuring system based on low cost, hogh resolution digital cameras. Once the cameras are synchronised, the portable and adjuntable system can be used to observe living beings, bodies in motion, or deformations of very different sizes. Each of the cameras has been modelled individually and studied with regard to the photogrammetric potential of the system. We have investigated the photogrammetric precision obtained from the crossing of rays, the repeatability of results, and the accuracy of the coordinates obtained. Systematic and random errors are identified in validity assessment of the definition of the precision of the system from crossing of rays or from marking residuals in images. The results have clearly demonstrated the capability of a low-cost multiple-camera system to measure with sub-millimetre precision.S

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