scholarly journals REMOTE SENSING DATA AS BASIS FOR THE MODELLING AND REASSEMBLY OF DISMANTLED HERITAGE STRUCTURES

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 1187-1194 ◽  
Author(s):  
S. Vincke ◽  
M. Bassier ◽  
R. de Lima Hernandez ◽  
I. Dejaeghere ◽  
K. Carbonez ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Relative Position ◽  
3D Model ◽  
Remote Sensing Data ◽  
Current Situation ◽  
Built Heritage ◽  
Digital Modelling ◽  
Position And Orientation ◽  
Remote Sensing Techniques ◽  
Over Time

<p><strong>Abstract.</strong> Remote sensing techniques are invaluable for the documentation and preservation of built heritage. The techniques facilitate fast documentation of highly complex heritage structures with improved accuracies. Furthermore they improve the degree of detail substantially. This is extremely useful for the restoration of collapsed elements or the reassembly of dismantled structures. These entities are often challenging to puzzle back together. Moreover, the differential settlements of the elements over time heavily influence the relative position and orientation of the remaining pieces, further complicating the reconstruction. Digital modelling solutions with a 3D model of the current situation as take-off, are desperately needed by the industry to tackle the present obstacles. In this work, a framework is proposed that facilitates a more accurate reassembly of dismantled heritage elements. It consists of three major phases starting with the accurate recording of the current situation as well as the preserved components. Subsequently, the new design is dititally modelled, reducing the necessary time for the reassembly of the structure, which is the last step in the rebuilding workflow. The presented framework allows for an efficient and comprehensible reconstruction of the structure. A key aspect in the approach is the detection of missing components and the estimation of their dimensions for the production of accurate replicas. The potential is showcased by means of two case studies on the reassembly of flying buttresses and rib vaults of the Saint-James church in Leuven, Belgium, which is currently undergoing major stabilisation works. The presented approach allows heritage experts to gain better oversight over their reassembly project and work more efficiently.</p>

scholarly journals Possibilities of milpa identification in Yucatan through remote sensing techniques and Sentinel-2 data

10.29007/hbs2 ◽  
2019 ◽  
Author(s):  
Juan Carlos Valdiviezo-Navarro ◽  
Adan Salazar-Garibay ◽  
Karla Juliana Rodríguez-Robayo ◽  
Lilián Juárez ◽  
María Elena Méndez-López ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Food Sovereignty ◽  
Region Of Interest ◽  
Remote Sensing Data ◽  
Support Vector ◽  
Multispectral Images ◽  
Crop Fields ◽  
Remote Sensing Techniques ◽  
Sentinel 2

Maya milpa is one of the most important agrifood systems in Mesoamerica, not only because its ancient origin but also due to lead an increase in landscape diversity and to be a relevant source of families food security and food sovereignty. Nowadays, satellite remote sensing data, as the multispectral images of Sentinel-2 platforms, permit us the monitor- ing of different kinds of structures such as water bodies, urban areas, and particularly agricultural fields. Through its multispectral signatures, mono-crop fields or homogeneous vegetation zones like corn fields, barley fields, or other ones, have been successfully detected by using classification techniques with multispectral images. However, Maya milpa is a complex field which is conformed by different kinds of vegetables species and fragments of natural vegetation that in conjunction cannot be considered as a mono-crop field. In this work, we show some preliminary studies on the availability of monitoring this complex system in a region of interest in Yucatan, through a support vector machine (SVM) approach.

Investigation of Highway Stormwater Management Pond Capacity for Flood Detention and Water Quality Treatment Retention via Remote Sensing Data and Conventional Topographic Survey

2020 ◽  
Vol 2674 (7) ◽  
pp. 514-527
Author(s):  
Houng Li
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Stormwater Management ◽  
Retention Volume ◽  
Remote Sensing Data ◽  
Stormwater Ponds ◽  
Topographic Survey ◽  
Storage Volume ◽  
Lidar Dem ◽  
Over Time

Stormwater management ponds are common best management practice (BMP) and green infrastructure (GI) for flood attenuation and water quality treatment in highway projects. Originally designed to provide storage volume for flood detention, stormwater ponds today often employ additional retention volume at pond bottom in a hope to improve water quality via sedimentation and other pollutant-removal mechanisms. It is commonly assumed that sediment accumulation and topographic variations (such as erosion, channelization, and in-pond plant growth and decay) over time often decrease the capacity of stormwater ponds. However, differences between design capacities and field capacities over time have never been verified and quantitatively analyzed before. This study presents such analysis using conventional topographic survey techniques and remote sensing data (topographic light detection and ranging digital elevation model [LIDAR DEM]) for 10 highway stormwater ponds along Interstate Highway-95 (I-95) systems in Baltimore City, Cecil County, and Harford County, Maryland, United States, with facility service life ranging from 14 to 26 years (1990–2015). Data derived from LIDAR DEM were compared with those from topographic survey; the LIDAR DEM data appear to be effective in measuring flood detention capacities and identifying silted ponds, but not in estimating the remaining retention volume for water quality treatment. Data from topographic survey indicate that the total volume in the ponds was relatively unchanged compared with the design, with increases in some instances. The increase typically occurred at the pond’s upper stages. Nonetheless, the water quality treatment capacity at pond bottom (wet pool volume) was drastically less (up to 100% of the design). As current maintenance practice of stormwater ponds relies heavily on visual inspection, the storage volume variations are often overlooked. As such, the findings prompt uncertainty on the long-term effectiveness of watershed implementation plan and models in the Chesapeake Bay watersheds, as many of them depend on wet pool volume design in BMP and GI.

scholarly journals Review of Satellite Interferometry for Landslide Detection in Italy

2020 ◽  
Vol 12 (8) ◽  
pp. 1351 ◽  
Author(s):  
Lorenzo Solari ◽  
Matteo Del Soldato ◽  
Federico Raspini ◽  
Anna Barra ◽  
Silvia Bianchini ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Management Strategies ◽  
Back Analysis ◽  
Remote Sensing Data ◽  
Economic Losses ◽  
Interferometric Synthetic Aperture Radar ◽  
Monitoring Tools ◽  
Average Production ◽  
Landslide Mapping ◽  
Remote Sensing Techniques

Landslides recurrently impact the Italian territory, producing huge economic losses and casualties. Because of this, there is a large demand for monitoring tools to support landslide management strategies. Among the variety of remote sensing techniques, Interferometric Synthetic Aperture Radar (InSAR) has become one of the most widely applied for landslide studies. This work reviews a variety of InSAR-related applications for landslide studies in Italy. More than 250 papers were analyzed in this review. The first application dates back to 1999. The average production of InSAR-related papers for landslide studies is around 12 per year, with a peak of 37 papers in 2015. Almost 70% of the papers are written by authors in academia. InSAR is used (i) for landslide back analysis (3% of the papers); (ii) for landslide characterization (40% of the papers); (iii) as input for landslide models (7% of the papers); (iv) to update landslide inventories (15% of the papers); (v) for landslide mapping (32% of the papers), and (vi) for monitoring (3% of the papers). Sixty-eight percent of the authors validated the satellite results with ground information or other remote sensing data. Although well-known limitations exist, this bibliographic overview confirms that InSAR is a consolidated tool for many landslide-related applications.

scholarly journals Accomplishments of the MUSICA project to provide accurate, long-term, global and high-resolution observations of tropospheric {H<sub>2</sub>O,<i>δ</i>D} pairs – a review

2016 ◽  
Vol 9 (7) ◽  
pp. 2845-2875 ◽  
Author(s):  
Matthias Schneider ◽  
Andreas Wiegele ◽  
Sabine Barthlott ◽  
Yenny González ◽  
Emanuel Christner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Measurement Techniques ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Horizontal Resolution ◽  
Atmospheric Composition ◽  
Remote Sensing Techniques ◽  
Middle Infrared

Abstract. In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

scholarly journals MEASUREMENTS FROM A FAST-MOVING AIR-CUSHION PLATFORM

1986 ◽  
Vol 1 (20) ◽  
pp. 27 ◽  
Author(s):  
P. Kerchkaert ◽  
A. Grobben ◽  
P. De Candt
Keyword(s):  
Remote Sensing ◽  
Fast Moving ◽  
Remote Sensing Data ◽  
Measuring Method ◽  
Coastal Morphology ◽  
Nearshore Area ◽  
Comprehensive Survey ◽  
Air Cushion ◽  
Aerial Remote Sensing ◽  
Remote Sensing Techniques

In 1976 the Belgian Government decided to enlarge the harbour of Zeebrugge and to execute an artificial beach renourishment on the beaches at Knokke-Heist. A comprehensive survey program along the 24 km coastline was conceived using remote sensing techniques. This enabled correct momentary recordings of the beach areas, the production of differential charts and calculations of dune and beach volumes. However, the observations of the nearshore and offshore areas from ordinary survey vessels take too long so that no accurate momentary recordings of the seabottom topography can be achieved. On these grounds, in 1983, the Belgian Authorities have instructed the Eurosense Belfotop Company to develop an effective measuring method based on the use of a hovercraft. This hovercraft platform, named "BEASAC" and designed for hydrographic surveys, is now used for monitoring the coastal morphology and the dredging activities in the access channels to the major Belgian seaports. On the basis of the "Beasac"-soundings of the nearshore area and the aerial remote sensing data of the beach, charts and differential charts of the combined beach and nearshore area are produced. The results of this technique are very promising and will be incorporated in the further survey programs ordered by the Belgian Authorities as a substitute for the classic bathymetric vessel soundings.

scholarly journals Spatial synchrony in vegetation response

2019 ◽  
Author(s):  
Haim Weissman ◽  
Yaron Michael ◽  
Nadav M. Shnerb
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Time Lag ◽  
Remote Sensing Data ◽  
Structured Populations ◽  
Terrestrial Vegetation ◽  
Spatial Synchrony ◽  
Spatially Structured Populations ◽  
Power Law Function ◽  
Over Time

Spatial synchrony is ubiquitous in nature, and its decrease with the distance is an important feature that affects the viability of spatially structured populations. Here we present an empirical study of spatial synchrony in terrestrial vegetation using large scale remote sensing data. The decrease of synchrony with distance, as expressed by the correlation in rate of abundance change at a given time lag, is characterized using a power-law function with stretched-exponential cutoff. The range of these correlations appears to decrease when precipitation increases and to increase over time. The relevance of these results to the viability of populations is discussed.

scholarly journals RELATIONSHIP OF SPECTRAL REFLECTANCE AND NDVI TO SOME SOIL PROPERTIES OF BRICKS FACTORIES SOILS IN NAHRAWAN AREA,BAGHDAD IRAQ

2019 ◽  
Vol 50 (3) ◽  
Author(s):  
R. K. Abdullatiff
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Spectral Reflectivity ◽  
Tigris River ◽  
The Difference ◽  
Remote Sensing Techniques ◽  
The One ◽  
Relationship Of

A study was conducted to investigate the effect of the brick industry on the environmental system of these project soils of the brick factories in Alnahrawan district. Remote sensing techniques was used to study the relationship between the spectral reflectivity and the vegetative index on the one hand and some surface soil characters of the project and to determine the variation in vegetation cover for the same area and for two different periods.Ten sites were selected to study spectral reflectivity under similar geomorphological conditions near the brickworks project in the Anahrawan district with an area of 10,000 hectares. Soil samples were taken from the surface and at a depth of 0-30 cm. Some chemical and physical characters of research soil were analyzed in the soil department laboratories, college of Agriculture, Baghdad University.Several satellite images taken from the satellite Land sat (ETM) 2013 and another from same satellite in 1990 T.M to determining the change between the two periods. After obtaining remote sensing data (reflectivity and vegetation index).the correlation analysis was carried out between these data. It was observed that the soil salinity values were decreased due to the drainage that the area was confined between the Tigris River and the Diyala tributary which leads to good natural drainage.The attached tables indicate that thedigital numbers of the soil sampling sites in 2013 are highly significant correlated, While some of the characters did not show the use of this region industrially. After calculating the difference between the two images to determine the change. A 100% change was observed and the vegetation cover was sharply reduced between the two images. as well as the extension of the land of empty land, although these lands are still suitable for agriculture.

scholarly journals From small-scale forest structure to Amazon-wide carbon estimates

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Edna Rödig ◽  
Nikolai Knapp ◽  
Rico Fischer ◽  
Friedrich J. Bohn ◽  
Ralph Dubayah ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Biomass ◽  
3D Structure ◽  
Basal Area ◽  
Remote Sensing Data ◽  
Small Scale ◽  
Frequency Distributions ◽  
Forest Attributes ◽  
Detailed Interpretation ◽  
Remote Sensing Techniques

Abstract Tropical forests play an important role in the global carbon cycle. High-resolution remote sensing techniques, e.g., spaceborne lidar, can measure complex tropical forest structures, but it remains a challenge how to interpret such information for the assessment of forest biomass and productivity. Here, we develop an approach to estimate basal area, aboveground biomass and productivity within Amazonia by matching 770,000 GLAS lidar (ICESat) profiles with forest simulations considering spatial heterogeneous environmental and ecological conditions. This allows for deriving frequency distributions of key forest attributes for the entire Amazon. This detailed interpretation of remote sensing data improves estimates of forest attributes by 20–43% as compared to (conventional) estimates using mean canopy height. The inclusion of forest modeling has a high potential to close a missing link between remote sensing measurements and the 3D structure of forests, and may thereby improve continent-wide estimates of biomass and productivity.

The creation of information models of roads on the basis of research with the use of global systems and remote sensing techniques

2021 ◽  
pp. 102-107
Author(s):  
A.A. NERETIN ◽  
◽  
I.I. POZNIAK ◽  
Keyword(s):  
Remote Sensing ◽  
3D Model ◽  
Information Model ◽  
Information Modeling ◽  
Digital Model ◽  
The Road ◽  
Information Models ◽  
Remote Sensing Techniques ◽  
Transfer Of Information ◽  
Global Systems

Information modeling allows you to move to the end-to-end transfer of information from surveys to designers, then to builders, and then to operational services. The information 3D model begins to be formed at the stage of research in the form of an information digital model, then a project information model of the road is created on its basis

Effect of Locust Invasion and Mitigation Using Remote Sensing Techniques: A Case Study of North Sindh Pakistan

2022 ◽  
Vol 88 (1) ◽  
pp. 47-53
Author(s):  
Muhammad Nasar Ahmad ◽  
Zhenfeng Shao ◽  
Orhan Altan
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Landsat 8 ◽  
Abrupt Decrease ◽  
Computing Platform ◽  
Remote Sensing Techniques ◽  
Processing Techniques

This study comprises the identification of the locust outbreak that happened in February 2020. It is not possible to conduct ground-based surveys to monitor such huge disasters in a timely and adequate manner. Therefore, we used a combination of automatic and manual remote sensing data processing techniques to find out the aftereffects of locust attack effectively. We processed MODIS -normalized difference vegetation index (NDVI ) manually on ENVI and Landsat 8 NDVI using the Google Earth Engine (GEE ) cloud computing platform. We found from the results that, (a) NDVI computation on GEE is more effective, prompt, and reliable compared with the results of manual NDVI computations; (b) there is a high effect of locust disasters in the northern part of Sindh, Thul, Ghari Khairo, Garhi Yaseen, Jacobabad, and Ubauro, which are more vulnerable; and (c) NDVI value suddenly decreased to 0.68 from 0.92 in 2020 using Landsat NDVI and from 0.81 to 0.65 using MODIS satellite imagery. Results clearly indicate an abrupt decrease in vegetation in 2020 due to a locust disaster. That is a big threat to crop yield and food production because it provides a major portion of food chain and gross domestic product for Sindh, Pakistan.

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