L-band SAR co-polarized phase difference modeling for corn fields

This research aims at modeling the microwave backscatter of corn fields by coupling an incoherent, interaction-based scattering model with a semi-empirical bulk vegetation dielectric model. The scattering model is fitted to co-polarized phase difference measurements over several corn fields imaged with fully polarimetric synthetic aperture radar (SAR) images with incidence angles ranging from 20° to 60°. The dataset comprised two field campaigns, one over Canada with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR, 1.258 GHz) and the other one over Argentina with Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) (ALOS-2/PALSAR-2, 1.236 GHz), totaling 60 data measurements over 28 grown corn fields at peak biomass with stalk gravimetric moisture larger than 0.8 g/g. Co-polarized phase differences were computed using a maximum likelihood estimation technique from each field’s measured speckled sample histograms. After minimizing the difference between the model and data measurements for varying incidence angles by a nonlinear least-squares fitting, well agreement was found with a root mean squared error of 24.3° for co-polarized phase difference measurements in the range of -170.3° to -19.13°. Model parameterization by stalk gravimetric moisture instead of its complex dielectric constant is also addressed. Further validation was undertaken for the UAVSAR dataset on earlier corn stages, where overall sensitivity to stalk height, stalk gravimetric moisture, and stalk area density agreed with ground data, with the sensitivity to stalk diameter being the weakest. This study provides a new perspective on the use of co-polarized phase differences in retrieving corn stalk features through inverse modeling techniques from space.This research was partially funded by the Argentinean National Scientific and Technical Research Council (CONICET, project PICT 2015 N◦3689), by the Spanish Ministry of Science and Innovation (project CICYT RTI2018-099008-B-C21/AEI/10.13039/501100011033 “Sensing with pioneering opportunistic techniques”) and by the grant to “CommSensLab-UPC” Excellence Research Unit Maria de Maeztu (MINECO grant).Peer ReviewedPostprint (published version

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Tracking data highlight the importance of human-induced mortality for large migratory birds at a flyway scale

Human-induced direct mortality affects huge numbers of birds each year, threatening hundreds of species worldwide. Tracking technologies can be an important tool to investigate temporal and spatial patterns of bird mortality as well as their drivers. We compiled 1704 mortality records from tracking studies across the African-Eurasian flyway for 45 species, including raptors, storks, and cranes, covering the period from 2003 to 2021. Our results show a higher frequency of human-induced causes of mortality than natural causes across taxonomic groups, geographical areas, and age classes. Moreover, we found that the frequency of human-induced mortality remained stable over the study period. From the human-induced mortality events with a known cause (n = 637), three main causes were identified: electrocution (40.5 %), illegal killing (21.7 %), and poisoning (16.3 %). Additionally, combined energy infrastructure-related mortality (i.e., electrocution, power line collision, and wind-farm collision) represented 49 % of all human-induced mortality events. Using a random forest model, the main predictors of human-induced mortality were found to be taxonomic group, geographic location (latitude and longitude), and human footprint index value at the location of mortality. Despite conservation efforts, human drivers of bird mortality in the African-Eurasian flyway do not appear to have declined over the last 15 years for the studied group of species. Results suggest that stronger conservation actions to address these threats across the flyway can reduce their impacts on species. In particular, projected future development of energy infrastructure is a representative example where application of planning, operation, and mitigation measures can enhance bird conservation

L-Band SAR Co-Polarized Phase Difference Modeling for Corn Fields

This research aims at modeling the microwave backscatter of corn fields by coupling an incoherent, interaction-based scattering model with a semi-empirical bulk vegetation dielectric model. The scattering model is fitted to co-polarized phase difference measurements over several corn fields imaged with fully polarimetric synthetic aperture radar (SAR) images with incidence angles ranging from 20° to 60°. The dataset comprised two field campaigns, one over Canada with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR, 1.258 GHz) and the other one over Argentina with Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) (ALOS-2/PALSAR-2, 1.236 GHz), totaling 60 data measurements over 28 grown corn fields at peak biomass with stalk gravimetric moisture larger than 0.8 g/g. Co-polarized phase differences were computed using a maximum likelihood estimation technique from each field’s measured speckled sample histograms. After minimizing the difference between the model and data measurements for varying incidence angles by a nonlinear least-squares fitting, well agreement was found with a root mean squared error of 24.3° for co-polarized phase difference measurements in the range of −170.3° to −19.13°. Model parameterization by stalk gravimetric moisture instead of its complex dielectric constant is also addressed. Further validation was undertaken for the UAVSAR dataset on earlier corn stages, where overall sensitivity to stalk height, stalk gravimetric moisture, and stalk area density agreed with ground data, with the sensitivity to stalk diameter being the weakest. This study provides a new perspective on the use of co-polarized phase differences in retrieving corn stalk features through inverse modeling techniques from space

Parameterization and optimization of inversion models for soil moisture retrieval from Synthetic Aperture Radar (SAR) data

Dentro del Plan Espacial Nacional (PEN), la Comisión Nacional de Actividades Espaciales (CONAE) tiene previsto el lanzamiento de la misión satelital SAOCOM, un radar de apertura sintética (SAR) que opera en microondas (λ = 23cm) y cuyo principal objetivo es la estimación de humedad del suelo sobre Pampa Húmeda. El problema de la estimación de variables biogeofísicas a partir de imágenes SAR es un problema mal condicionado, donde con frecuencia existen muchas combinaciones de parámetros de la superficie que producen las mismas observaciones SAR. Por esta razón, existen diversas técnicas de inversión, las cuales deben tener en cuenta lo siguiente: 1. la dificultad en la parametrización de los modelos de dispersión que rigen la respuesta del blanco ante un onda electromagnética incidente sobre él, 2. las incertezas en la medición del radar proveniente de ruido de origen coherente (conocido como ruido speckle), 3. las incertezas provenientes de la ingeniería del sensor, 4. las incertezas provenientes de la variabilidad espacial de las variables del blanco, en particular de la humedad del suelo. En este trabajo de tesis se desarrolló un esquema de inversión bayesiano que toma en cuenta todos estos temas. Dicho esquema se evaluó con datos SAR y mediciones de campo provenientes de varias campa˜nas con sistemas aerotransportados y satelitales. El esquema bayesiano considera todas las dificultades encontradas en el desarrollo de un producto operativo de humedad del suelo y puede resultar en un algoritmo alternativo al desarrollado por CONAE para la misión satelital SAOCOM.Within the framework of the Argentinean Space Plan (PEN), the National Space Activities Commission (CONAE) plans to launch the SAOCOM mission, which involves a synthetic aperture radar (SAR) operating in the microwave region (λ = 23cm) and whose main goal is the estimation of soil moisture over the Pampas Plains. Estimation of biogeophysical variables through radar images is an ill-posed problem, where there are often many combinations of surface parameters that produce the same SAR observations. For this reason, there are various retrieval techniques, which should take into account 1. the difficulty of parameterizing the scattering models which govern the response of the target to an electromagnetic wave impinging on it, 2. uncertainties in the radar measurement due to speckle noise, 3. instrumental noise from the sensor, 4. uncertainties from the spatial variability of the target variables, in particular of soil moisture. In this thesis a Bayesian retrieval scheme was developed, which takes into account all these issues. This scheme is assessed with SAR data and field measurements from various campaigns involving airborne and satellite systems. Also, the Bayesian scheme considers all the difficulties encountered in the development of an operational soil moisture product and can lead to an alternative algorithm to that developed by CONAE for the SAOCOM mission.Fil:Barber, Matías Ernesto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Tracking data highlight the importance of human-induced mortality for large migratory birds at a flyway scale

Human-induced direct mortality affects huge numbers of birds each year, threatening hundreds of species worldwide. Tracking technologies can be an important tool to investigate temporal and spatial patterns of bird mortality as well as their drivers. We compiled 1704 mortality records from tracking studies across the African-Eurasian flyway for 45 species, including raptors, storks, and cranes, covering the period from 2003 to 2021. Our results show a higher frequency of human-induced causes of mortality than natural causes across taxonomic groups, geographical areas, and age classes. Moreover, we found that the frequency of human-induced mortality remained stable over the study period. From the human-induced mortality events with a known cause (n = 637), three main causes were identified: electrocution (40.5 %), illegal killing (21.7 %), and poisoning (16.3 %). Additionally, combined energy infrastructure-related mortality (i.e., electrocution, power line collision, and wind-farm collision) represented 49 % of all human-induced mortality events. Using a random forest model, the main predictors of human-induced mortality were found to be taxonomic group, geographic location (latitude and longitude), and human footprint index value at the location of mortality. Despite conservation efforts, human drivers of bird mortality in the African-Eurasian flyway do not appear to have declined over the last 15 years for the studied group of species. Results suggest that stronger conservation actions to address these threats across the flyway can reduce their impacts on species. In particular, projected future development of energy infrastructure is a representative example where application of planning, operation, and mitigation measures can enhance bird conservation.publishedVersio

Käytännön kosteikkosuunnittelu

Maatalouden vesiensuojelua edistetään monin tavoin. Ravinteita ja eroosioainesta sisältäviä valumavesiä pyritään puhdistamaan erilaisissa kosteikoissa. Tämä opas on kirjoitettu avuksi pienimuotoisten kosteikkojen perustamiseen. Oppaassa esitetään käytännönläheisesti kosteikon toteuttamisen eri vaiheet paikan valinnasta suunnitteluun ja rakentamiseen. Vuonna 2010 julkaistun painoksen tiedot on saatettu ajantasalle. Julkaisu on toteutettu osana Tehoa maatalouden vesiensuojeluun (TEHO) -hanketta ja päivitetty TEHO Plus -hankkeen toimesta. Oppaan toivotaan lisäävän kiinnostusta kosteikkojen suunnitteluun ja edelleen niiden rakentamiseen