Resultados de búsqueda - "Synthetic-aperture radar"

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  1. Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen por Lapaz Olveira, Adrián, Castro Franco, Mauricio, Sainz Rozas, Hernan Rene, Carciochi, Walter, Balzarini, Mónica, Avila, Oscar, Ciampitti, Ignacio, Reussi Calvo, Nahuel Ignacio

    Publicado 2023
    “…Therefore, the aim of this study was to assess NNI predicted from optical and C-band Synthetic Aperture Radar (C-SAR) satellite data and available soil N (Nav) at different vegetative growth stages for corn crop. …”
    Enlace del recurso
    Enlace del recurso
    Enlace del recurso
    Artículo
  2. Synthetic Aperture Radar (SAR)-based paddy rice monitoring system: Development and application in key rice producing areas in Tropical Asia por Setiyono, T.D., Holecz, F., Khan, N.I., Barbieri, M., Quicho, E., Collivignarelli, F., Maunahan, A., Gatti, L., Romuga, G.C.

    Publicado 2017
    “…Reliable and regular rice information is essential part of many countries' national accounting process but the existing system may not be sufficient to meet the information demand in the context of food security and policy. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland paddy rice, especially in tropical region where pervasive cloud cover in the rainy seasons limits the use of optical imagery. …”
    Enlace del recurso
    Journal Article
  3. A decadal historical satellite data and rainfall trend analysis (2001–2016) for flood hazard mapping in Sri Lanka por Alahacoon, Niranga, Matheswaran, Karthikeyan, Pani, Peejush, Amarnath, Giriraj

    Publicado 2018
    “…This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE) gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR) and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. …”
    Enlace del recurso
    Journal Article
  4. Comparison of UAV and SAR performance for crop type classification using machine learning algorithms: a case study of humid forest ecology experimental research site of west Africa por Duke, O.P., Alabi, T.R., Neeti, N., Adewopo, Julius

    Publicado 2022
    “…A synergistic approach comprising a high-resolution multispectral UAV optical dataset and synthetic aperture radar (SAR) can help understand spectral features of target objects, especially with crop type identification. …”
    Enlace del recurso
    Journal Article
  5. Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data por Wessels, Konrad, Mathieu, Renaud, Knox, Nichola, Main, Russell, Naidoo, Laven, Steenkamp, Karen

    Publicado 2019
    “…The aim of study was to develop a system to map and monitor fractional woody cover (FWC) at national scales (50 m and 75 m resolution) using Synthetic Aperture Radar (SAR) satellite data (Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) global mosaics, 2009, 2010, 2015, 2016) and ancillary variables (mean annual precipitation—MAP, elevation), with machine learning models that were trained with diverse airborne Light Detection and Ranging (LiDAR) data sets (244,032 ha, 2008–2014). …”
    Enlace del recurso
    Journal Article
  6. Assessing the accuracy for area-based tree species classification using Sentinel-1 C-band SAR data por Udali, Alberto

    Publicado 2019
    “…The re-mote sensing data used were C-band Synthetic Aperture Radar (SAR) data from Sentinel-1. Dual polarization backscatter values were extracted for the period October 2017 - February 2019 and the area-based method was applied. …”
    H2
  7. Mapping of clear-cuts in Swedish forest using satellite images acquired by the radar sensor ALOS PALSAR por Krantz, Anders

    Publicado 2009
    “…An extensive dataset of images acquired by the Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) is investigated for clear-cut detection in boreal forests in northern Sweden (Lat. 64°14’ N, Long. 19°50’ E). …”
    H1
  8. Satellite based approach for rice yield monitoring and forecasting por Mathieu, Renaud, Murugesan, Deiveegan, Maunahan, Aileen, Quicho, Emma, Sataphaty, Sushree, Dossou-Yovo, Elliott Ronald, Salif, Doumba, Akpoffo, Marius, Gatti, Luca

    Publicado 2023
    “…Results from study sites in Sikasso and Segou regions suggest that incorporating remote sensing data, specifically Synthetic aperture radar (SAR), into a process-based crop model improves the spatial distribution of yield estimates. …”
    Enlace del recurso
    Informe técnico
  9. Framskrivning av ALS data med TanDEM-X por Wästlund, André

    Publicado 2016
    “…Satellitparet TanDEM-X och TerraSAR-X levererar InSAR (Interferometric synthetic aperture radar) data med möjlighet till beräkning av en tredje dimension och potential för goda skattningar, med hög temporal upplösning. …”
    Enlace del recurso
    Second cycle, A2E
  10. Analys av säsongsvariationer vid skattning av skogliga variabler med InSAR teknik por Sjödin, Edward

    Publicado 2016
    “…Interferometrisk Synthetic Aperture Radar (InSAR) är en radarteknik som satelliterna i TanDEM-X möjliggör. …”
    Enlace del recurso
    Second cycle, A2E
  11. Eco-hydrological characterization of inland wetlands in Africa using L-Band SAR por Rebelo, Lisa-Maria

    Publicado 2010
    “…Multi-temporal L-band Synthetic Aperture Radar (SAR) datasets are combined with Landsat Thematic Mapper and ASTER images, digital elevation models, and vegetation species data to provide information on wetland ecology and hydrology. …”
    Enlace del recurso
    Journal Article
  12. Training guide: advancing paddy mapping using open-source earth observation data and geospatial technologies por Jayamini, Kalpani, Alahacoon, Niranga, Amarnath, Giriraj

    Publicado 2025
    “…Targeted at technical officers, researchers, and analysts, the guide demonstrates how different platforms such as Google Earth Engine, Google Colab, QGIS, and Python can deliver reliable rice extent maps and seasonal monitoring using Sentinel-1 Synthetic Aperture Radar (SAR). The guide details the full workflow: creating and linking a GEE Cloud Project, authenticating service accounts in Colab, preprocessing time-series SAR data, extracting indices (e.g., mRVI), treating outliers, classifying start-peak-harvest stages, and performing validation and accuracy assessments with ground observations. …”
    Enlace del recurso
    Manual
  13. QGIS plugin for fine-scale hazard, exposure, vulnerability, and risk mapping por Jayamini, Kalpani, Alahacoon, Niranga, Amarnath, Giriraj

    Publicado 2025
    “…A key feature of the plugin is its use of multi-year Sentinel-1 Synthetic Aperture Radar (SAR) imagery to derive flood Hazard. …”
    Enlace del recurso
    Informe técnico
  14. Modelling the flood-risk extent using LISFLOOD-FP in a complex watershed: case study of Mundeni Aru River Basin, Sri Lanka por Amarnath, Giriraj, Umer, Yakob, Alahacoon, Niranga, Inada, Yoshiaki

    Publicado 2015
    “…Results from the flood inundation model were evaluated using Synthetic Aperture Radar (SAR) images to assess product accuracy. …”
    Enlace del recurso
    Journal Article
  15. Quality Control of CyGNSS Reflectivity for Robust Spatiotemporal Detection of Tropical Wetlands por Arai, Hironori, Zribi, Mehrez, Oyoshi, Kei, Dassas, Karin, Huc, Mireille, Sobue, Shinichi, Thuy Le Toan

    Publicado 2022
    “…The behaviors of the GNSS-R reflectivity and the Advanced Land Observing Satellite-2 Phased-Array type L-band Synthetic Aperture Radar-2 quadruple polarimetric scatter signals were compared and found to be nonlinearly correlated due to the influence of the incidence angle and the effective scattering area.…”
    Enlace del recurso
    Journal Article

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