Browsing by Author "Ionut Sandric"

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Exploring the potential of SCAT-SAR SWI for soil moisture retrievals at selected COSMOS-UK sites
(Taylor and Francis Ltd., 2021) Owen D. Howells; George P. Petropoulos; Prashant K. Srivastava; Dimitrios Triantakonstantis; Ionut Sandric
The need for information on soil moisture at large scale to facilitate a sustainable intensification of agricultural land and to ensure food security due to increasing populations cannot be overstated. Remote sensing provides a platform for potential national coverage of soil moisture monitoring. This study explores the potential for using a Synthetic-Aperture-Radar Soil Water Index (SCAT-SAR SWI) product as a method of accurately monitoring soil moisture across the UK by comparing its output with the COSMOS-UK cosmic-ray soil moisture observation network. Using the daily data from these stations, SWI data from SCAT-SAR were compared during 2015 for the UK. Five COSMOS-UK network sites were selected across the UK for assessment, and the respected SCAT-SAR SWI pixels were extracted for their soil moisture values. Statistical test that were computed allowed quantifying the correlation between the truth data of the TDT soil moisture sensors and the COSMOS and SCAT-SAR soil moisture product. It was found that the SCAT-SAR product consistently underestimated the soil moisture with elevation affecting the level of agreement. The COSMOS network slightly overestimated soil moisture but was found, at least in this study, noticeably more accurate than the SCAT-SAR. The RMSD of the SCAT-SAR product was noticeably higher at sites with the highest elevation. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
Using PlanetScope imagery and GEOBIA to map urban green spaces
(Elsevier, 2023) Evangelos A. Dosiadis; George P. Petropoulos; Ana-Maria Popa; Ionut Sandric; Antigoni Faka; Diana Andrea Onose; Prashant K. Srivastava
Urban green spaces (UGSs) are vital natural infrastructure that improves environmental and social outcomes, public health, and maintaining ecological diversity. Therefore the present chapter provides the comprehensive layout of UGSs and explores the potential of PlanetScope high spatial resolution imagery for mapping UGSs utilizing the geographic object-based image analysis (GEOBIA) classification approach. As a case study the region of Athens, Greece, has been used for which PlanetScope imagery was acquired for the year 2020 (June). The uncertainty matrix and picture photointerpretation were used to evaluate the UGSs retrievals. Furthermore, UGSs from the Urban Atlas global operational product were used to evaluate UGSs predictions made by the investigated technique. The study demonstrated the effectiveness of GEOBIA combining with PlanetScope imagery for effective planning and management of UGSs to make cities livable and sustainable. © 2024 Elsevier Ltd. All rights reserved.