River morphological changes detection from drone and radar satellite data

2020 ◽  
Author(s):  
Giulia Marchetti ◽  
Francesco Asaro ◽  
Simone Bizzi ◽  
Stefano Mariani ◽  
Barbara Lastoria ◽  
...  
Keyword(s):  
Satellite Data ◽  
Large Scale ◽  
Morphological Changes ◽  
Atmospheric Condition ◽  
Radar Data ◽  
Radar Signal ◽  
Catchment Scale ◽  
Natural Risk ◽  
Sediment Size ◽  
Radar Satellite

<p>The identification and quantification of morphological changes occurring in the river channel over time are essential to understand rivers behaviour, assess sediment budgets, evaluate effectiveness of river management strategies and support the production of natural risk map. Recently, river science has made a breakthrough thanks to emerging remote sensing technologies and today we can rely on an unparalleled amount of data, at spatial and temporal resolution not available in the past. This has opened new perspectives for river monitoring and fluvial survey practices, allowing to cover areas up to the catchment scale and get information almost in continuum. This research aims to investigate the potential of radar satellite data collected from Sentinel 1 mission to infer information about rivers morphodynamics processes (such as erosion and deposition), that may occur on medium-large river (e.g., active channel width > 50 m) after a flood that caused significant morphological adjustments. Drone and satellite data were collected in September 2017 and September 2018 on a selected site along the Po river, in northern Italy, characterized by a large exposed sediment bar. In March 2018 a flood caused an avulsion and a new secondary channel was opened. We used the sequential drone acquisitions to generate a Dem of Difference, that revealed geomorphic changes of the monitored sediment bar up to 2 m erosion and 1.5 m deposition. We then exploited the radar data of Sentinel 1 and conducted a seasonal analysis using both the coherence data between image pairs and the backscattered radar signal, by investigating the variability of the radar signals through the year and the correspondent condition of the bar. Results show that there is a significant correlation between morphological changes occurred in the site and the associated values of both the amplitude and the coherence of the radar data pre and post the event that caused the morphological changes measured. Further studies are needed to better discriminate the different contributions to changes in amplitude and coherence driven by soil water content, vegetation, sediment size, atmospheric condition for the various time windows analysed. Despite that, these initial evidences are encouraging and new applications to other sites and flood events are planned because these results prove the sensitiveness of the radar signal to geomorphic events. Even simply the ability to detect where channel morphological processes are occurring and their expected intensity through Sentinel 1 data would allow to prioritize more detailed field campaigns by, for instance, UAV technology providing a notable advance compared to the current ability to monitor river morphological changes on large scale.</p>

Global quantification of InSAR sensitivity for landslide deformation tracking

2021 ◽  
Author(s):  
Adriaan van Natijne ◽  
Roderik Lindenbergh ◽  
Thom Bogaard
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Radar Data ◽  
Google Earth ◽  
Project Planning ◽  
Deformation Monitoring ◽  
Radar Signal ◽  
Sensitivity Index ◽  
Potential Indicator ◽  
Landslide Deformation

<p>Landslides are lurking hazards, that often remains unnoticed. Fortunately, unstable slopes frequently show precursory deformation preceding more destructive accelerations. Thanks to satellite remote sensing, regional deformation monitoring is now available in near real-time.</p><p>Deformation time series are required for both training and validation of models for landslide nowcasting and forecasting. Various studies have shown that satellite Interferometric Synthetic Aperture Radar (InSAR) is capable of delivering the desired deformation time series. Although satellite radar data, such as from the Copernicus Sentinel-1 program, is freely available, application is not (yet) straightforward: InSAR processing is complex, computational intensive and requires specialist knowledge. Moreover, assessment of the potential of the technique on specific slopes requires experience.</p><p>Therefore, we present two concepts to a-priori assess the potential of InSAR landslide deformation tracking. First, the sensitivity index, available globally, indicates the minimum visibility of deformation in the radar signal on any slope. Second, the detection potential indicator, provided as Google Earth Engine application, performs a preliminary analysis of the Sentinel-1 data available at any specific location. Our analysis shows that on 89% of the world's slopes deformation is likely to be detectable with InSAR.</p><p>The detection potential indicator is a valuable tool in the project planning phase, while exploring the site specific possibilities for InSAR deformation monitoring. Furthermore, the sensitivity index provides overview of the slopes where large scale, machine learning driven, landslide nowcasting and forecasting are likely to succeed. We will present an analysis of the global sensitivity index, as well as demonstrate how to apply our detection potential application on a case study.</p>

scholarly journals Validasi Sebaran Kapal Penangkap Ikan Tradisional Menggunakan Data Penginderaan Jauh Dan GPS Tracker

2017 ◽  
Vol 4 (1) ◽  
pp. 14
Author(s):  
Komang Iwan Suniada
Keyword(s):  
Satellite Data ◽  
Radar Data ◽  
Fishing Vessel ◽  
Ground Station ◽  
Iuu Fishing ◽  
Accuracy Test ◽  
Fishing Vessels ◽  
Position Data ◽  
Radar Satellite ◽  
Traditional Fishing

Utilization of radar satellite data to monitoring vessels distribution in regard to combating IUU fishing is a newly developed in Indonesia. Ship detection using radar satellite data performed with high accuracy which is about 79% to the size of the boats between 24-81 meters (averaging 45 meters).  However, information about accuracy of the radar satellites to detect small traditional fishing vessel are not yet widely available, and making this study is very important to conducted.    The research was conducted at the west part of Belitung Island waters using RADARSAT-2 satellite data to detect vessels distribution which was acquired by radar ground station Perancak at October 25, 2016 and also using vessel position data which is acquired by using GPS tracker.  There are 10 traditional fishing vessel was used as a sample, in accordance with the availability of GPS tracker.  All vessels are made from wood with the size between 11 to 15 meter and using ‘bubu’ as a primary fishing gear to catch fish.  Accuracy test was done using overlay analysis between vessel distribution information resulted from radar image analysis with the vessel position data coming from the GPS Tracker.  Result showed that the accuracy of radar data on extended high incidence beam mode to detect the distribution of traditional fishing vessels with small size (11-15 meters) is about 30% and over estimate measuring between 7.5 to 8 meters.

scholarly journals Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

2011 ◽  
Vol 15 (4) ◽  
pp. 1117-1129 ◽  
Author(s):  
R. Fieuzal ◽  
B. Duchemin ◽  
L. Jarlan ◽  
M. Zribi ◽  
F. Baup ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Satellite Data ◽  
Agricultural Practices ◽  
Grain Filling ◽  
Absolute Error ◽  
Radar Signal ◽  
Soil Conditions ◽  
Envisat Asar ◽  
Radar Satellite

Abstract. The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (Envisat/ASAR and Formosat-2). Time series of images were collected over the Yaqui irrigated area (Mexico) throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data indicates that the sensitivity of the radar signal to vegetation is masked by the variability of soil conditions. On-going irrigated areas can be detected all over the wheat growing season. The empirical algorithm developed for the retrieval of topsoil moisture from Envisat/ASAR images takes advantage of the Formosat-2 instrument capabilities to monitor the seasonality of wheat canopies. This monitoring is performed using dense time series of images acquired by Formosat-2 to set up the SAFY vegetation model. Topsoil moisture estimates are not reliable at the timing of plant emergence and during plant senescence. Estimates are accurate from tillering to grain filling stages with an absolute error about 9% (0.09 m3 m−3, 35% in relative value). This result is attractive since topsoil moisture is estimated at a high spatial resolution (i.e. over subfields of about 5 ha) for a large range of biomass water content (from 5 and 65 t ha−1 independently from the viewing angle of ASAR acquisition (incidence angles IS1 to IS6).

scholarly journals Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

2010 ◽  
Vol 7 (4) ◽  
pp. 6207-6242
Author(s):  
R. Fieuzal ◽  
B. Duchemin ◽  
L. Jarlan ◽  
M. Zribi ◽  
F. Baup ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Satellite Data ◽  
Agricultural Practices ◽  
Grain Filling ◽  
Absolute Error ◽  
Radar Signal ◽  
Soil Conditions ◽  
Envisat Asar ◽  
Radar Satellite ◽  
Irrigated Wheat

Abstract. The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (ENVISAT/ASAR and FORMOSAT-2). Time series of images were collected over the Yaqui irrigated area (Mexico) throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data indicates that the sensitivity of the radar signal to vegetation is masked by the variability of soil conditions. On-going irrigated areas can be detected all over the wheat growing season. The empirical algorithm developed for the retrieval of topsoil moisture from ENVISAT/ASAR images takes advantage of the unique capabilities of the FORMOSAT-2 instrument to monitor the seasonality of wheat canopies. Topsoil moisture estimates are scattered at the timing of plant emergence and during plant senescence. Estimates are much more accurate from tillering to grain filling stages with an absolute error about 9% (0.09 m3 m−3, 35% in relative value). This result is attractive since topsoil moisture is estimated at a high spatial resolution (i.e. over subfields of about 5 ha) for a large range of biomass water content (from 5 and 65 t ha−1) independently from the viewing angle of ASAR acquisition (incidence angles IS1 to IS6).

scholarly journals The MJO in a Coarse-Resolution GCM with a Stochastic Multicloud Parameterization

2015 ◽  
Vol 72 (1) ◽  
pp. 55-74 ◽  
Author(s):  
Qiang Deng ◽  
Boualem Khouider ◽  
Andrew J. Majda
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Deterministic Model ◽  
Weather Prediction ◽  
General Circulation Models ◽  
Radar Data ◽  
Equation Model ◽  
Death Process ◽  
Relevant Parameter ◽  
Convective Systems

Abstract The representation of the Madden–Julian oscillation (MJO) is still a challenge for numerical weather prediction and general circulation models (GCMs) because of the inadequate treatment of convection and the associated interactions across scales by the underlying cumulus parameterizations. One new promising direction is the use of the stochastic multicloud model (SMCM) that has been designed specifically to capture the missing variability due to unresolved processes of convection and their impact on the large-scale flow. The SMCM specifically models the area fractions of the three cloud types (congestus, deep, and stratiform) that characterize organized convective systems on all scales. The SMCM captures the stochastic behavior of these three cloud types via a judiciously constructed Markov birth–death process using a particle interacting lattice model. The SMCM has been successfully applied for convectively coupled waves in a simplified primitive equation model and validated against radar data of tropical precipitation. In this work, the authors use for the first time the SMCM in a GCM. The authors build on previous work of coupling the High-Order Methods Modeling Environment (HOMME) NCAR GCM to a simple multicloud model. The authors tested the new SMCM-HOMME model in the parameter regime considered previously and found that the stochastic model drastically improves the results of the deterministic model. Clear MJO-like structures with many realistic features from nature are reproduced by SMCM-HOMME in the physically relevant parameter regime including wave trains of MJOs that organize intermittently in time. Also one of the caveats of the deterministic simulation of requiring a doubling of the moisture background is not required anymore.

scholarly journals Is environmental legislation conserving tropical stream faunas? A large-scale assessment of local, riparian and catchment-scale influences on Amazonian fish

2017 ◽  
Vol 55 (3) ◽  
pp. 1312-1326 ◽  
Author(s):  
Cecília G. Leal ◽  
Jos Barlow ◽  
Toby A. Gardner ◽  
Robert M. Hughes ◽  
Rafael P. Leitão ◽  
...  
Keyword(s):  
Large Scale ◽  
Environmental Legislation ◽  
Tropical Stream ◽  
Catchment Scale ◽  
Large Scale Assessment ◽  
Amazonian Fish ◽  
Scale Assessment

scholarly journals Quantification of water purification in South African palmiet wetlands

2018 ◽  
Vol 78 (5) ◽  
pp. 1199-1207
Author(s):  
Alanna J. Rebelo ◽  
Willem-Jan Emsens ◽  
Karen J. Esler ◽  
Patrick Meire
Keyword(s):  
South African ◽  
Water Purification ◽  
Large Scale ◽  
Poor Quality ◽  
Quality Parameters ◽  
Catchment Scale ◽  
Valley Bottom ◽  
Major Cations ◽  
Dissolved Silicon ◽  
Wetland Processes

Abstract Despite the importance of water purification to society, it is one of the more difficult wetland ecosystem services to quantify. It remains an issue in ecosystem service assessments where rapid estimates are needed, and poor-quality indicators are overused. We attempted to quantify the water purification service of South African palmiet wetlands (valley-bottom peatlands highly threatened by agriculture). First, we used an instantaneous catchment-scale mass balance sampling approach, which compared the fate of various water quality parameters over degraded and pristine sections of palmiet wetlands. We found that pristine palmiet wetlands acted as a sink for water, major cations, anions, dissolved silicon and nutrients, though there was relatively high variation in these trends. There are important limitations to this catchment-scale approach, including the fact that at this large scale there are multiple mechanisms (internal wetland processes as well as external inputs) at work that are impossible to untangle with limited data. Therefore, secondly, we performed a small field-scale field survey of a wetland fragment to corroborate the catchment-scale results. There was a reasonable level of agreement between the results of the two techniques. We conclude that it appears possible to estimate the water purification function of these valley-bottom wetlands using this catchment-scale approach.

scholarly journals Assessing the large-scale impacts of environmental change using a coupled hydrology and soil erosion model

2018 ◽  
Vol 6 (3) ◽  
pp. 687-703 ◽  
Author(s):  
Joris P. C. Eekhout ◽  
Wilco Terink ◽  
Joris de Vente
Keyword(s):  
Soil Erosion ◽  
Environmental Change ◽  
Sediment Yield ◽  
Large Scale ◽  
Catchment Scale ◽  
Time Step ◽  
Vegetation Development ◽  
Erosion Model ◽  
Complete Representation ◽  
Large Catchment

Abstract. Assessing the impacts of environmental change on soil erosion and sediment yield at the large catchment scale remains one of the main challenges in soil erosion modelling studies. Here, we present a process-based soil erosion model, based on the integration of the Morgan–Morgan–Finney erosion model in a daily based hydrological model. The model overcomes many of the limitations of previous large-scale soil erosion models, as it includes a more complete representation of crucial processes like surface runoff generation, dynamic vegetation development, and sediment deposition, and runs at the catchment scale with a daily time step. This makes the model especially suited for the evaluation of the impacts of environmental change on soil erosion and sediment yield at regional scales and over decadal periods. The model was successfully applied in a large catchment in southeastern Spain. We demonstrate the model's capacity to perform impact assessments of environmental change scenarios, specifically simulating the scenario impacts of intra- and inter-annual variations in climate, land management, and vegetation development on soil erosion and sediment yield.

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