Využití družicové SAR interferometrie pro identifikaci a mapování sesuvů ve městě Sánchez, Dominikánské republice

The landscapes we see today are the result of constant changes during millions of years. Mass movement is one of the principal geomorphology process responsible for these changes and occurs in different scales around the world, causing disaster in populated areas. Sánchez is a municipality located in Samaná province, Dominican Republic, where continuous motion had created an atmosphere of uncertainness among the inhabitants, that observed day after day the deterioration of infrastructures, loss of agricultural capability and potential life-threatening situations. Slope instability has been increased by anthropogenic activity and triggers factors as: elimination of forest for coconut plantation, lack of proper wasted drainage and drinking water supply system, growth of community, change of construction material, meteorological phenomena and seismic events. This investigation aims to identify slope movement and map it, using SENTINEL-1 satellite SAR interferometry (InSAR). By applying multi-temporal techniques to a series of SENTINEL-1 scenes, it is possible to recognize a continuous surface deformation in the area. The results will help authorities to develop short and long-term risk management plans.Zeměpisy, které dnes vidíme, jsou výsledkem neustálých změn v průběhu několika miliónů let. Masový pohyb je jedním z hlavních geomorfologických procesů zodpovědných za tyto změny a probíhá v různých měřítkách po celém světě a způsobuje katastrofu v osídlených oblastech. Sánchez je obec ležící v provincii Samaná, Dominikánská republika, kde neustálý pohyb vytvářel atmosféru nejistoty mezi obyvateli, která každodenně pozorovala zhoršování infrastruktury, ztrátu zemědělské kapacity a potenciální život ohrožující situace. Nestabilita svahu byla zvýšena antropogenní aktivitou a spouští faktory jako: odstranění lesů pro kokosové plantáže, nedostatek správného odpadního kanalizace a zásobování pitnou vodou, růst obce, změna stavebního materiálu, meteorologické jevy a seismické události. Cílem tohoto šetření je identifikovat pohyb svahu a mapovat ho pomocí SARINEL-1 satelitní SAR interferometrie (InSAR). Aplikací multičasových technik na řadu scén SENTINEL-1 je možné rozpoznat kontinuální povrchovou deformaci v oblasti. Výsledky pomohou orgánům vypracovat krátkodobé a dlouhodobé plány řízení rizik.548 - Katedra geoinformatikyvýborn

Tracking hidden crisis in India's capital from space: implications of unsustainable groundwater use.

Funder: Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum - GFZNational Capital Region (NCR, Delhi) in India is one of the fastest-growing metropolitan cities which is facing a severe water crisis due to increasing water demand. The over-extraction of groundwater, particularly from its unconsolidated alluvial deposits makes the region prone to subsidence. In this study, we investigated the effects of plummeting groundwater levels on land surface elevations in Delhi NCR using Sentinel-1 datasets acquired during the years 2014-2020. Our analysis reveals two distinct subsidence features in the study area with rates exceeding 11 cm/year in Kapashera-an urban village near IGI airport Delhi, and 3 cm/year in Faridabad throughout the study period. The subsidence in these two areas are accelerating and follows the depleting groundwater trend. The third region, Dwarka shows a shift from subsidence to uplift during the years which can be attributed to the strict government policies to regulate groundwater use and incentivizing rainwater harvesting. Further analysis using a classified risk map based on hazard risk and vulnerability approach highlights an approximate area of 100 square kilometers to be subjected to the highest risk level of ground movement, demanding urgent attention. The findings of this study are highly relevant for government agencies to formulate new policies against the over-exploitation of groundwater and to facilitate a sustainable and resilient groundwater management system in Delhi NCR

Radar Interferometry for Monitoring Crustal Deformation. Geodetic Applications in Greece

The chapatti and breadmaking quality of nine (eight Indian and one Australian) wheat (Triticum aestivum L.) cultivars was compared. The extension of a chapatti strip measured with a Kieffer dough extensibility rig correlated with chapatti scores for overall quality (r = 0.84), pliability (r = 0.91), hand feel (r = 0.72), chapatti eating quality (r = 0.68), and taste (r = 0.80). Overall chapatti quality also correlated with the resistance to extension of a chapatti strip (r = 0.68) when tested for uniaxial extension with a texture analyzer. The texture analyzer provided objectivity in the scoring of chapatti quality. The high-molecular-weight glutenin subunit protein composition assessed by sodium dodecyl sulfate polyacrylamide gel electrophoresis did not correlate with the overall chapatti score. A negative correlation was found between chapatti and bread scores (r = 0.77). The different requirements for chapatti and bread quality complicate the breeding of new wheat varieties and the exchange of germplasm between regions producing wheat for chapatti and those supplying bread producers

Advances on the investigation of landslides by space-borne synthetic aperture radar interferometry

Landslides are destructive geohazards to people and infrastructure, resulting in hundreds of deaths and billions of dollars of damage every year. Therefore, mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks. In this paper, the main outcomes relevant to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon-5 initiative cooperation project ID 59,339 “Earth observation for seismic hazard assessment and landslide early warning system” are reported. The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks, detect potential landslides in wide regions, and demonstrate EO-based landslide early warning system over selected landslides. This work only focuses on the landslide hazard content of the project, and thus, in order to achieve these objectives, the following tasks were developed up to now: a) a procedure for phase unwrapping errors and tropospheric delay correction; b) an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements; c) the application of polarimetric SAR interferometry (PolInSAR) to increase the number and quality of monitoring points in landslide-prone areas; d) the semiautomatic mapping and preliminary classification of active displacement areas on wide regions; e) the modeling and identification of landslides in order to identify triggering factors or predict future displacements; and f) the application of an InSAR-based landslide early warning system on a selected site. The achieved results, which mainly focus on specific sensitive regions, provide essential assets for planning present and future scientific activities devoted to identifying, mapping, characterizing, monitoring and predicting landslides, as well as for the implementation of early warning systems.This work was supported by the ESA-MOST China DRAGON-5 project with ref. 59339, by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI), and the European Funds for Regional Development under grant [grant number PID2020-117303GB-C22], by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital in the framework of the project CIAICO/2021/335, by the Natural Science Foundation of China [grant numbers 41874005 and 41929001], the Fundamental Research Funds for the Central University [grant numbers 300102269712 and 300102269303], and China Geological Survey Project [grant numbers DD20190637 and DD20190647]. Xiaojie Liu and Liuru Hu have been funded by Chinese Scholarship Council Grants Ref. [grant number 202006560031] and [grant number 202004180062], respectively