scholarly journals Understanding Mn-nodule distribution and related deep-sea mining impacts using AUV-based hydroacoustic sensing and optical observations

2017 ◽  
Author(s):  
Anne Peukert ◽  
Timm Schoening ◽  
Evangelos Alevizos ◽  
Kevin Köser ◽  
Tom Kwasnitschka ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Deep Sea ◽  
Ground Truth ◽  
Optical Observations ◽  
Small Scale ◽  
Ground Truth Data ◽  
Mining Impacts ◽  
Multibeam Data ◽  
Quantitative Assessments

Abstract. In this study ship- and AUV-based multibeam data from the German Mn-nodule license area in the Clarion-Clipperton Zone (CCZ; eastern Pacific) are linked to ground truth data from optical imaging. Photographs obtained by an AUV enable semi-quantitative assessments of nodule coverage at a spatial resolution in the range of meters. Together with high resolution AUV bathymetry this revealed a correlation of small-scale terrain variations (

scholarly journals Comparison of Surface Characteristics of the Antarctic Ice Sheet with Satellite Observations (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 253
Author(s):  
N. Young ◽  
I. Goodwin
Keyword(s):  
Surface Topography ◽  
Accumulation Rate ◽  
Ice Sheet ◽  
Ground Truth ◽  
Surface Characteristics ◽  
Small Scale ◽  
Landsat Images ◽  
Ground Truth Data ◽  
Additional Information ◽  
Wilkes Land

Ground surveys of the ice sheet in Wilkes Land, Antarctica, have been made on oversnow traverses operating out of Casey. Data collected include surface elevation, accumulation rate, snow temperature, and physical characteristics of the snow cover. By the nature of the surveys, the data are mostly restricted to line profiles. In some regions, aerial surveys of surface topography have been made over a grid network. Satellite imagery and remote sensing are two means of extrapolating the results from measurements along lines to an areal presentation. They are also the only source of data over large areas of the continent. Landsat images in the visible and near infra-red wavelengths clearly depict many of the large- and small scale features of the surface. The intensity of the reflected radiation varies with the aspect and magnitude of the surface slope to reveal the surface topography. The multi-channel nature of the Landsat data is exploited to distinguish between different surface types through their different spectral signatures, e.g. bare ice, glaze, snow, etc. Additional information on surface type can be gained at a coarser scale from other satellite-borne sensors such as ESMR, SMMR, etc. Textural enhancement of the Landsat images reveals the surface micro-relief. Features in the enhanced images are compared to ground-truth data from the traverse surveys to produce a classification of surface types across the images and to determine the magnitude of the surface topography and micro-relief observed. The images can then be used to monitor changes over time.

scholarly journals Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

2020 ◽  
Vol 12 (23) ◽  
pp. 3958
Author(s):  
Parwati Sofan ◽  
David Bruce ◽  
Eriita Jones ◽  
M. Rokhis Khomarudin ◽  
Orbita Roswintiarti
Keyword(s):  
Spatial Resolution ◽  
Fire Detection ◽  
Ground Truth ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Ground Truth Data ◽  
Spectral Instrument ◽  
Tropical Peatland ◽  
Tropical Environments ◽  
Sentinel 2

This study establishes a new technique for peatland fire detection in tropical environments using Landsat-8 and Sentinel-2. The Tropical Peatland Combustion Algorithm (ToPeCAl) without longwave thermal infrared (TIR) (henceforth known as ToPeCAl-2) was tested on Landsat-8 Operational Land Imager (OLI) data and then applied to Sentinel-2 Multi Spectral Instrument (MSI) data. The research is aimed at establishing peatland fire information at higher spatial resolution and more frequent observation than from Landsat-8 data over Indonesia’s peatlands. ToPeCAl-2 applied to Sentinel-2 was assessed by comparing fires detected from the original ToPeCAl applied to Landsat-8 OLI/Thermal Infrared Sensor (TIRS) verified through comparison with ground truth data. An adjustment of ToPeCAl-2 was applied to minimise false positive errors by implementing pre-process masking for water and permanent bright objects and filtering ToPeCAl-2’s resultant detected fires by implementing contextual testing and cloud masking. Both ToPeCAl-2 with contextual test and ToPeCAl with cloud mask applied to Sentinel-2 provided high detection of unambiguous fire pixels (>95%) at 20 m spatial resolution. Smouldering pixels were less likely to be detected by ToPeCAl-2. The detected smouldering pixels from ToPeCAl-2 applied to Sentinel-2 with contextual testing and with cloud masking were only 35% and 56% correct, respectively; this needs further investigation and validation. These results demonstrate that even in the absence of TIR data, an adjusted ToPeCAl algorithm (ToPeCAl-2) can be applied to detect peatland fires at 20 m resolution with high accuracy especially for flaming. Overall, the implementation of ToPeCAl applied to cost-free and available Landsat-8 and Sentinel-2 data enables regular peatland fire monitoring in tropical environments at higher spatial resolution than other satellite-derived fire products.

scholarly journals Understanding Mn-nodule distribution and evaluation of related deep-sea mining impacts using AUV-based hydroacoustic and optical data

2018 ◽  
Vol 15 (8) ◽  
pp. 2525-2549 ◽  
Author(s):  
Anne Peukert ◽  
Timm Schoening ◽  
Evangelos Alevizos ◽  
Kevin Köser ◽  
Tom Kwasnitschka ◽  
...  
Keyword(s):  
High Resolution ◽  
Optical Data ◽  
Water Current ◽  
Small Scale ◽  
Benthic Habitat ◽  
Ferromanganese Nodule ◽  
Mining Operations ◽  
Data Set ◽  
Ground Truth Data ◽  
The Impact

Abstract. In this study, ship- and autonomous underwater vehicle (AUV)-based multibeam data from the German ferromanganese-nodule (Mn-nodule) license area in the Clarion–Clipperton Zone (CCZ; eastern Pacific) are linked to ground-truth data from optical imaging. Photographs obtained by an AUV enable semi-quantitative assessments of nodule coverage at a spatial resolution in the range of meters. Together with high-resolution AUV bathymetry, this revealed a correlation of small-scale terrain variations (< 5 m horizontally, < 1 m vertically) with nodule coverage. In the presented data set, increased nodule coverage could be correlated with slopes > 1.8∘ and concave terrain. On a more regional scale, factors such as the geological setting (existence of horst and graben structures, sediment thickness, outcropping basement) and influence of bottom currents seem to play an essential role for the spatial variation of nodule coverage and the related hard substrate habitat. AUV imagery was also successfully employed to map the distribution of resettled sediment following a disturbance and sediment cloud generation during a sampling deployment of an epibenthic sledge. Data from before and after the “disturbance” allow a direct assessment of the impact. Automated image processing analyzed the nodule coverage at the seafloor, revealing nodule blanketing by resettling of suspended sediment within 16 h after the disturbance. The visually detectable impact was spatially limited to a maximum of 100 m distance from the disturbance track, downstream of the bottom water current. A correlation with high-resolution AUV bathymetry reveals that the blanketing pattern varies in extent by tens of meters, strictly following the bathymetry, even in areas of only slightly undulating seafloor (<1 m vertical change). These results highlight the importance of detailed terrain knowledge when engaging in resource assessment studies for nodule abundance estimates and defining mineable areas. At the same time, it shows the importance of high-resolution mapping for detailed benthic habitat studies that show a heterogeneity at scales of 10 to 100 m. Terrain knowledge is also needed to determine the scale of the impact by seafloor sediment blanketing during mining operations.

Combining in situ observations and high resolution VENμS data to monitor temperate deciduous shrub and tree phenology

2020 ◽  
Author(s):  
Alison Donnelly ◽  
Rong Yu
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Carbon Budget ◽  
Vegetation Index ◽  
Return Time ◽  
Small Scale ◽  
Spatial Coverage ◽  
Temperate Deciduous

&lt;p&gt;Direct in situ phenological observations of co-located trees and shrubs help characterize the phenological profile of ecosystems, such as, temperate deciduous forests. Accurate determination of the start and end of the growing season is necessary to define the active carbon uptake period for use in reliable carbon budget calculations. However, due to the resource intensive nature of recording in situ phenology the spatial coverage of sampling is often limited. In recent decades, the use of freely available satellite-derived phenology products to monitor &amp;#8216;green-up&amp;#8217; at the landscape scale have become commonplace. Although these data sets are widely available they either have (i) high temporal resolution but low spatial resolution, such as, MODIS (daily return time; 250m) or (ii) low temporal resolution but high spatial resolution, such as, Landsat (16-day return time; 30m). However, the recently (2017) launched VEN&amp;#956;S (Vegetation and Environment monitoring on a New Micro-Satellite) satellite combines both high temporal (two-day return time) and spatial (5-10m) resolution at a local scale thus providing an opportunity for small scale comparison of a range of phenometrics. The next challenge is to determine what in situ phenophase corresponds to the satellite-derived phenology. Our study site is a temperate deciduous woodlot on the campus of the University of Wisconsin-Milwaukee, USA, where we monitored in situ phenology on a range of (5) native (N) and (3) non-native invasive (NNI) shrub species, and (6) tree species for a 3-year period (2017-2019) to determine the timing and duration of key spring (bud-open, leaf-out, full-leaf unfolded) and autumn (leaf color, leaf fall) phenophases. The monitoring campaign coincided with the 2-day return time of VEN&amp;#956;S to enable direct comparison with the satellite data. The shrubs leafed out before the trees and the NNIs, in particular, remained green well into the autumn season when the trees were leafless. The next step will be to determine what exact in situ phenophses correspond to NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived start, peak and end of season from MODIS and VEN&amp;#956;S data. In addition, we will determine if VEN&amp;#956;S can detect differences in phenological profile between N and NNI shrubs at seasonal extremes. We anticipate that the high resolution VEN&amp;#956;S data will increase the accuracy of phenological determination which could help improve carbon budget determination and inform forest management and conservation plans.&lt;/p&gt;

Fusion of Sentinel and PlanetScope images for high resolution soil moisture mapping: Algorithm and preliminary validation

2020 ◽  
Author(s):  
Mateo Gašparović ◽  
Sudhir Kumar Singh
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Spatial Resolution ◽  
Land Degradation ◽  
New Technologies ◽  
Critical Role ◽  
Soil Parameters ◽  
Area Index ◽  
Ground Truth Data ◽  
Sentinel 2

&lt;p&gt;High resolution remote sensing images plays a critical role in detection and monitoring of land degradation and development. Monitoring the soil parameters represents great importance for sustainable development and agriculture, as well as smart food production. The space segment component of the Copernicus programme (e.g., Sentinel-1, Sentinel-2 etc.) enables continuously monitoring of Earth&amp;#8217;s surface at 10-m spatial resolution. New technologies, development, and minimization of sensors led to the development of micro-satellites (e.g., PlanetScope). These satellites allow us to monitor the Earth's surface daily in 3-m spatial resolution. The developed algorithm for soil moisture mapping is based on the fusion of Sentinel-2 and PlanetScope images. This allows a soil moisture mapping in high spatial resolution. Soil moisture was estimated based on the Leaf Area Index (LAI) and Enhanced Vegetation Index (EVI) using modified water cloud model. Ground-truth data were collected from 15 stations of the International Soil Moisture Network across the globe and used for mapping and validation of soil moisture. The developed algorithm provides a new knowledge that can be widely applied in various research for the detection and monitoring of land degradation and development.&lt;/p&gt;

Damage Detection Using High-Resolution SAR Imagery in the 2009 L'Aquila, Italy, Earthquake

2013 ◽  
Vol 29 (4) ◽  
pp. 1521-1535 ◽  
Author(s):  
Pralhad Uprety ◽  
Fumio Yamazaki ◽  
Fabio Dell'Acqua
Keyword(s):  
High Resolution ◽  
Damage Detection ◽  
Correlation Coefficient ◽  
Ground Truth ◽  
Threshold Value ◽  
Building Damage ◽  
Urban Setting ◽  
Ground Truth Data ◽  
Emergency Situations ◽  
Sar Imagery

Satellite remote sensing is being used to monitor disaster-affected areas for post-disaster reconnaissance and recovery. One of the special features of Synthetic Aperture Radar (SAR) is that it can operate day and night and penetrate the cloud cover because of which it is being widely used in emergency situations. Building damage detection for the 6 April 2009 L'Aquila, Italy, earthquake was conducted using high-resolution TerraSAR-X images obtained before and after the event. The correlation coefficient and the difference of backscatter coefficients of the pre- and post-event images were calculated in a similar way as Matsuoka and Yamazaki (2004) . The threshold value of the correlation coefficient was suggested and used in detecting building damage. The results were compared with ground truth data and a post-event optical image. Based on the study, building damage could be observed in an urban setting of L'Aquila with overall accuracy of 89.8% and Kappa coefficient of 0.45.

scholarly journals POST-FIRE FORESTRY RECOVERY MONITORING USING HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLES

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 301-305 ◽  
Author(s):  
L. Pádua ◽  
T. Adão ◽  
N. Guimarães ◽  
A. Sousa ◽  
E. Peres ◽  
...  
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Tree Height ◽  
Ground Truth ◽  
Cost Effective ◽  
Forest Disturbances ◽  
Ground Truth Data ◽  
High Resolution Data ◽  
Aerial Vehicles ◽  
Fire Scenarios

<p><strong>Abstract.</strong> In recent years unmanned aerial vehicles (UAVs) have been used in several applications and research studies related to environmental monitoring. The works performed have demonstrated the suitability of UAVs to be employed in different scenarios, taking advantage of its capacity to acquire high-resolution data from different sensing payloads, in a timely and flexible manner. In forestry ecosystems, UAVs can be used with accuracies comparable with traditional methods to retrieve different forest properties, to monitor forest disturbances and to support disaster monitoring in fire and post-fire scenarios. In this study an area recently affected by a wildfire was surveyed using two UAVs to acquire multi-spectral data and RGB imagery at different resolutions. By analysing the surveyed area, it was possible to detect trees, that were able to survive to the fire. By comparing the ground-truth data and the measurements estimated from the UAV-imagery, it was found a positive correlation between burned height and a high correlation for tree height. The mean NDVI value was extracted used to create a three classes map. Higher NDVI values were mostly located in trees that survived that were not/barely affected by the fire. The results achieved by this study reiterate the effectiveness of UAVs to be used as a timely, efficient and cost-effective data acquisition tool, helping for forestry management planning and for monitoring forest rehabilitation in post-fire scenarios.</p>

scholarly journals High-resolution topography of the Antarctic Peninsula combining the TanDEM-X DEM and Reference Elevation Model of Antarctica (REMA) mosaic

2021 ◽  
Vol 15 (9) ◽  
pp. 4421-4443
Author(s):  
Yuting Dong ◽  
Ji Zhao ◽  
Dana Floricioiu ◽  
Lukas Krieger ◽  
Thomas Fritz ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Antarctic Peninsula ◽  
Data Consistency ◽  
Optical Data ◽  
Small Scale ◽  
Potential Contribution ◽  
Polar Regions ◽  
Elevation Model ◽  
The Antarctic

Abstract. The Antarctic Peninsula (AP) is one of the widely studied polar regions because of its sensitivity to climate change and potential contribution of its glaciers to global sea level rise. Precise digital elevation models (DEMs) at a high spatial resolution are much demanded for investigating the complex glacier system of the AP at fine scales. However, the two most recent circum-Antarctic DEMs, the 12 m TanDEM-X DEM (TDM DEM) from bistatic interferometric synthetic aperture radar (InSAR) data acquired between 2013 and 2014 and the Reference Elevation Model of Antarctica mosaic (REMA mosaic) at an 8 m spatial resolution derived from optical data acquired between 2011 and 2017 have specific individual limitations in this area. The TDM DEM has the advantage of good data consistency and few data voids (approx. 0.85 %), but there exist residual systematic elevation errors such as phase-unwrapping errors in the non-edited DEM version. The REMA mosaic has high absolute vertical accuracy, but on the AP it suffers from extended areas with data voids (approx. 8 %). To generate a consistent, gapless and high-resolution topography product of the AP, we fill the data voids in the TDM DEM with newly processed TDM raw DEM data acquired in austral winters of 2013 and 2014 and detect and correct the residual systematic elevation errors (i.e., elevation biases) in the TDM DEM with the support of the accurately calibrated REMA mosaic. Instead of a pixelwise replacement with REMA mosaic elevations, these provide reference values to correct the TDM elevation biases over entire regions detected through a path propagation algorithm. The procedure is applied iteratively to gradually correct the errors in the TDM DEM from a large to small scale. The proposed method maintains the characteristics of an InSAR-generated DEM and is minimally influenced by temporal or penetration differences between the TDM DEM and REMA mosaic. The performance of the correction is evaluated with laser altimetry data from Operation IceBridge and ICESat-2 missions. The overall root mean square error (RMSE) of the corrected TDM DEM has been reduced from more than 30 m to about 10 m which together with the improved absolute elevation accuracy indicates comparable values to the REMA mosaic. The generated high-resolution DEM depicts the up-to-date topography of the AP in detail and can be widely used for interferometric applications as well as for glaciological studies on individual glaciers or at regional scales.

Long-Range Geo-Monitoring Using Image Assisted Total Stations

2014 ◽  
Vol 8 (3) ◽  
Author(s):  
Andreas Wagner ◽  
Ben Huber ◽  
Wolfgang Wiedemann ◽  
Gerhard Paar
Keyword(s):  
High Resolution ◽  
Long Range ◽  
Ground Truth ◽  
Monitoring Methods ◽  
Ground Truth Data ◽  
Areal Coverage ◽  
Achievable Accuracy ◽  
The Eu

AbstractImage Assisted Total Stations (IATS) unify geodetic precision of total stations with areal coverage of images. The concept of using two IATS devices for high-resolution, long-range stereo survey of georisk areas has been investigated in the EU-FP7 project DE-MONTES (www.de-montes.eu). The paper presents the used methodology and compares the main features with other terrestrial geodetic geo-monitoring methods. The theoretically achievable accuracy of the measurement systemis derived and verified by ground truth data of a distant clay pit slope and simulated deformations. It is shown that the stereo IATS concept is able to obtain higher precision in the determination of 3D deformations than other systems of comparable sensor establishment effort.

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