Integration of a GIS Data Set with Aerial Photography Using GPS for Control Points on the Newlands Project in Nevada

2009 ◽  
pp. 66-66-9
Author(s):  
DT Hansen ◽  
M Sebhat
Keyword(s):  
Aerial Photography ◽  
Control Points ◽  
Data Set ◽  
Gis Data

scholarly journals Using kites for 3-D mapping of gullies at decimetre-resolution over several square kilometres: a case study on the Kamech catchment, Tunisia

2018 ◽  
Vol 18 (6) ◽  
pp. 1567-1582 ◽  
Author(s):  
Denis Feurer ◽  
Olivier Planchon ◽  
Mohamed Amine El Maaoui ◽  
Abir Ben Slimane ◽  
Mohamed Rached Boussema ◽  
...  
Keyword(s):  
High Resolution ◽  
Aerial Photography ◽  
Airborne Lidar ◽  
Data Set ◽  
Topographic Data ◽  
Independent Field ◽  
Wide Range ◽  
Laser Systems ◽  
High Level

Abstract. Monitoring agricultural areas threatened by soil erosion often requires decimetre topographic information over areas of several square kilometres. Airborne lidar and remotely piloted aircraft system (RPAS) imagery have the ability to provide repeated decimetre-resolution and -accuracy digital elevation models (DEMs) covering these extents, which is unrealistic with ground surveys. However, various factors hamper the dissemination of these technologies in a wide range of situations, including local regulations for RPAS and the cost for airborne laser systems and medium-format RPAS imagery. The goal of this study is to investigate the ability of low-tech kite aerial photography to obtain DEMs with decimetre resolution and accuracy that permit 3-D descriptions of active gullying in cultivated areas of several square kilometres. To this end, we developed and assessed a two-step workflow. First, we used both heuristic experimental approaches in field and numerical simulations to determine the conditions that make a photogrammetric flight possible and effective over several square kilometres with a kite and a consumer-grade camera. Second, we mapped and characterised the entire gully system of a test catchment in 3-D. We showed numerically and experimentally that using a thin and light line for the kite is key for a complete 3-D coverage over several square kilometres. We thus obtained a decimetre-resolution DEM covering 3.18 km2 with a mean error and standard deviation of the error of +7 and 22 cm respectively, hence achieving decimetre accuracy. With this data set, we showed that high-resolution topographic data permit both the detection and characterisation of an entire gully system with a high level of detail and an overall accuracy of 74 % compared to an independent field survey. Kite aerial photography with simple but appropriate equipment is hence an alternative tool that has been proven to be valuable for surveying gullies with sub-metric details in a square-kilometre-scale catchment. This case study suggests that access to high-resolution topographic data on these scales can be given to the community, which may help facilitate a better understanding of gullying processes within a broader spectrum of conditions.

scholarly journals Influence of Control Points Configuration on the Mobile Laser Scanning Accuracy

2021 ◽  
Vol 906 (1) ◽  
pp. 012091
Author(s):  
Petr Kalvoda ◽  
Jakub Nosek ◽  
Petra Kalvodova
Keyword(s):  
Reference Point ◽  
Point Cloud ◽  
Laser Scanning ◽  
Reference Data ◽  
Data Sets ◽  
Control Points ◽  
Mobile Mapping ◽  
Data Set ◽  
Accuracy Test ◽  
Data Subset

Abstract Mobile mapping systems (MMS) are becoming widely used in standard geodetic tasks more commonly in the last years. The paper is focused on the influence of control points (CPs) number and configuration on mobile laser scanning accuracy. The mobile laser scanning (MLS) data was acquired by MMS RIEGL VMX-450. The resulting point cloud was compared with two different reference data sets. The first reference data set consisted of a high-accuracy test point field (TPF) measured by a Trimble R8s GNSS system and a Trimble S8 HP total station. The second reference data set was a point cloud from terrestrial laser scanning (TLS) using two Faro Focus3D X 130 laser scanners. The coordinates of both reference data sets were determined with significantly higher accuracy than the coordinates of the tested MLS point cloud. The accuracy testing is based on coordinate differences between the reference data set and the tested MLS point cloud. There is a minimum number of 6–7 CPs in our scanned area (based on MLS trajectory length) to achieve the declared relative accuracy of trajectory positioning according to the RIEGL datasheet. We tested two types of ground control point (GCP) configurations for 7 GCPs, using TPF reference data. The first type is a trajectory-based CPs configuration, and the second is a geometry-based CPs configuration. The accuracy differences of the MLS point clouds with trajectory-based CPs configuration and geometry-based CPs configuration are not statistically significant. From a practical perspective, a geometry-based CPs configuration is more advantageous in the nonlinear type of urban area such as our one. The following analyzes are performed on geometry-based CPs configuration variants. We tested the influence of changing the location of two CPs from ground to roof. The effect of the vertical configuration of the CPs on the accuracy of the tested MLS point cloud has not been demonstrated. The effect of the number of control points on the accuracy of the MLS point cloud was also tested. In the overall statistics using TPF, the accuracy increases significantly with increasing the number of GCPs up to 6. This number corresponds to a requirement of the manufacturer. Although further increasing the number of CPs does not significantly increase the global accuracy, local accuracy improves with increasing the number of CPs up to 10 (average spacing 50 m) according to the comparison with the TLS reference point cloud. The accuracy test of the MLS point cloud was divided into the horizontal accuracy test on the façade data subset and the vertical accuracy test on the road data subset using the TLS reference point cloud. The results of this paper can help improve the efficiency and accuracy of the mobile mapping process in geodetic praxis.

scholarly journals Conflation and Integration of Archived Geologic Maps and Associated Uncertainties

2016 ◽  
Vol 8 (1) ◽  
pp. 28
Author(s):  
Tom Shoberg
Keyword(s):  
Confidence Interval ◽  
Test Area ◽  
Geological Survey ◽  
Data Set ◽  
Gis Data ◽  
Geologic Maps ◽  
Data Set Integration ◽  
The U.S

Old, archived geologic maps are often available with little or no associated metadata.  This creates special problems in terms of extracting their data to use with a modern database.  This research focuses on some problems and uncertainties associated with conflating older geologic maps in regions where modern geologic maps are, as yet, non-existent as well as vertically integrating the conflated maps with layers of modern GIS data (in this case, The National Map of the U.S. Geological Survey).   Ste. Genevieve County, Missouri was chosen as the test area.  It is covered by six archived geologic maps constructed in the years between 1928 and 1994. Conflating these maps results in a map that is internally consistent with these six maps, is digitally integrated with hydrography, elevation and orthoimagery data, and has a 95% confidence interval useful for further data set integration.

The relation between block size and building shape

2017 ◽  
Vol 46 (1) ◽  
pp. 103-121
Author(s):  
Masahiro Taima ◽  
Yasushi Asami ◽  
Kimihiro Hino
Keyword(s):  
Three Dimensional ◽  
Block Size ◽  
Area Ratio ◽  
Quantitative Relation ◽  
Maximum Volume ◽  
Data Set ◽  
Floor Area ◽  
Floor Area Ratio ◽  
Building Shape ◽  
Gis Data

Block restructuring has been strongly emphasized in Japan for renovating cities. However, little is known about the relation between block size and building shape. Moreover, the shape of buildings designed on a block after restructuring is unclear. In this study, the relation between block size and building shape is analyzed quantitatively, and a three-dimensional building shape is estimated by a model using an urban planning GIS data set of Tokyo. Results show the quantitative relation between block size and building shape, and the building shape image on the blocks. Higher buildings and buildings with a basement tend to be built in larger blocks, leading to efficient use of the maximum volume permitted in the block. In addition, the region composed by larger blocks can be spacious, because the range of building setback will be long in larger blocks. Designation of a high floor area ratio may induce integration and enlargement of blocks. Blocks are less likely to be partitioned in zones when a high floor area ratio is designated.

scholarly journals The New Approach to Camera Calibration – GCPs or TLS Data?

2016 ◽  
Vol XLI-B3 ◽  
pp. 75-82
Author(s):  
J. Markiewicz ◽  
P. Podlasiak ◽  
M. Kowalczyk ◽  
D. Zawieska
Keyword(s):  
Camera Calibration ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Automatic Identification ◽  
Test Field ◽  
Control Points ◽  
Data Set ◽  
Laser Measurements ◽  
Close Range ◽  
Processed Products

Camera calibration is one of the basic photogrammetric tasks responsible for the quality of processed products. The majority of calibration is performed with a specially designed test field or during the self-calibration process. The research presented in this paper aims to answer the question of whether it is necessary to use control points designed in the standard way for determination of camera interior orientation parameters. Data from close-range laser scanning can be used as an alternative. The experiments shown in this work demonstrate the potential of laser measurements, since the number of points that may be involved in the calculation is much larger than that of commonly used ground control points. The problem which still exists is the correct and automatic identification of object details in the image, taken with a tested camera, as well as in the data set registered with the laser scanner.

scholarly journals THE STUDY OF THE “CETUS” UNMANNED AERIAL VEHICLE FOR TOPOGRAPHIC AERIAL SURVEYING

2021 ◽  
Vol 47 (2) ◽  
pp. 96-103
Author(s):  
Volodymyr Hlotov ◽  
Alla Hunina ◽  
Ihor Kolb ◽  
Vadim Kolesnichenko ◽  
Ihor Trevoho
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Large Scale ◽  
Aerial Survey ◽  
Control Points ◽  
Gps Survey ◽  
Aerial Surveys ◽  
Spatial Coordinates ◽  
Aerial Vehicle ◽  
And Control

The work aims to analyze and study the possibilities of using “Cetus” unmanned aerial vehicle (UAV) for performing topographic aerial surveys. The authors developed and tested aircraft-type UAV for topographic aerial photography. The studies were conducted on a specialized landfill, at which there is an appropriate number of situational points whose coordinates are determined with high accuracy. These points were used as both reference and control points. The obtained UAV aerial survey materials were subjected to a phototriangulation process to determine the orientation elements and to analyze, first and foremost, the angular orientation elements. The surveying was carried out on a mountainous territory, where the spatial coordinates of 37 situational points were determined by the method of ground-based GPS survey with an average accuracy of up to 0.05 m. These points were used as reference and control points. Aerial photography was performed in such a way that the scale of the images was as uniform as possible. The design solutions implemented in the Cetus UAV provide all the possibilities to perform aerial surveys of territories in strict compliance with the projected flight parameters. UAV equipment provides the necessary real-time correction of the position of the aerial camera. At the same time the optimum straightness of routes, stability of scales and mutual overlapping of pictures is reached. Regarding the accuracy of obtaining the spatial coordinates of the points of terrain objects, using “Cetus” UAV surveys, plans can even be made on a scale of even 1: 1000. As a result of the creation of the UAV “Cetus”, it became possible to perform the topographic aerial survey of the territories and to create large-scale orthophotos that fully meet the instructions. As a result of testing the “Cetus” UAV, it can be used in production processes when drawing up topographic plans for a large-scale series: 1: 1000 – 1: 5000, which will significantly save the cost of performing topographic work.

Redwood National and State Parks: Geologic resources inventory report

2021 ◽  
Author(s):  
Katie KellerLynn
Keyword(s):  
Time Scale ◽  
Cultural Resources ◽  
State Parks ◽  
Geologic History ◽  
Data Set ◽  
Geologic Time ◽  
Needed Information ◽  
Gis Data ◽  
Geologic Time Scale ◽  
Geologic Map

Comprehensive park management to fulfill the NPS mission requires an accurate inventory of the geologic features of a park unit, but Comprehensive park management to fulfill the NPS mission requires an accurate inventory of the geologic features of a park unit, but park managers may not have the needed information, geologic expertise, or means to complete such an undertaking; therefore, the Geologic Resources Inventory (GRI) provides information and resources to help park managers make decisions for visitor safety, planning and protection of infrastructure, and preservation of natural and cultural resources. Information in the GRI report may also be useful for interpretation. park managers may not have the needed information, geologic expertise, or means to complete such an undertaking; therefore, the Geologic Resources Inventory (GRI) provides information and resources to help park managers make decisions for visitor safety, planning and protection of infrastructure, and preservation of natural and cultural resources. Information in the GRI report may also be useful for interpretation. This report synthesizes discussions from a scoping meeting for Redwood National and State Parks (referred to as the “parks” throughout this report) held in 2004 and a follow-up conference call in 2019. Two GRI–compiled GIS data sets of the geology and geohazards of the parks are the principal deliverables of the GRI. The GRI GIS data are available on the GRI publications website http://go.nps.gov/gripubs and through the NPS Integrated Resource Management Applications (IRMA) portal https://irma.nps.gov/App/Portal/Home. Enter “GRI” as the search text and select a park from the unit list. Writing of this report was based on those data and the interpretations of the source map authors (see “GRI Products” and “Acknowledgements”). A geologic map poster illustrates the geology GRI GIS data set and serves as a primary figure for this GRI report. No poster was prepared for the geohazards GRI GIS data set. Additionally, figure 7 of this report illustrates the locations of the major geologic features in the parks. Unlike the poster, which is divided into a northern and southern portion to show detail while accommodating the parks’ length, figure 7 is a single-page, simplified map. The features labeled on figure 7 are discussed in the “Geologic History, Features, and Processes” chapter. To provide a context of geologic time, this report includes a geologic time scale (see "Geologic History, Features, and Processes"). The parks’ geologic story encompasses 200 million years, starting in the Jurassic Period. Following geologic practice, the time scale is set up like a stratigraphic column, with the oldest units at the bottom and the youngest units at the top. Organized in this manner, the geologic time scale table shows the relative ages of the rock units that underlie the parks and the unconsolidated deposits that lie at the surface. Reading the “Geologic Event” column in the table, from bottom to top, will provide a chronologic order of the parks’ geologic history. The time scale includes only the map units within the parks that also appear on the geologic map poster; that is, map units of the geohazards data are not included. Geology is a complex science with many specialized terms. This report provides definitions of geologic terms at first mention, typically in parentheses following the term. Geologic units in the GRI GIS data are referenced in this report using map unit symbols; for example, map unit KJfrc stands for the Cretaceous (K) and Jurassic (J) Franciscan Complex (f), Redwood Creek schist (rc), which underlies a portion of the Redwood Creek watershed (see “GRI Products”).

scholarly journals A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region

2013 ◽  
Vol 5 (2) ◽  
pp. 393-402 ◽  
Author(s):  
G. Hugelius ◽  
J. G. Bockheim ◽  
P. Camill ◽  
B. Elberling ◽  
G. Grosse ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Mineral Soil ◽  
Geographical Information ◽  
Gis Mapping ◽  
Permafrost Region ◽  
Data Sets ◽  
Depth Range ◽  
Data Set ◽  
Spatial Coverage ◽  
Gis Data

Abstract. High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 106 km2). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m−2) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/. The NCSCDv2 data set has a digital object identifier (doi:10.5879/ECDS/00000002).

Background to the four stages of emergency management: The role of enterprise GIS

2018 ◽  
Vol 16 (4) ◽  
pp. 229
Author(s):  
F. Peirce Eichelberger
Keyword(s):  
Emergency Management ◽  
Information Needs ◽  
Ad Hoc ◽  
Full Range ◽  
Data Sets ◽  
Data Set ◽  
Gasoline Station ◽  
Emergency Manager ◽  
Gis Data ◽  
Data Requirements

Few examples of enterprise geographic information systems (GISs) implementation are as important and illustrative as the use of GIS to support the four stages of emergency management (EM). The full range of data required to support the four stages of EM are much greater, then any one department can be responsible for by itself. Only with an enterprise-wide GIS perspective can the full range of required data elements be made available to the emergency manager. Most critically, to keep these data sets accurate and up to date, the emergency manager must rely on other agencies and functions to keep all the data current. Without other assistance, the data requirements for the EM team will be quickly overwhelming. Waugh and Hy describe emergency events as either intentional (terrorism) or unintentional (weather/earthquake). The focus of this analysis is primarily on unintentional events, yet examples show that the four stages of EM are applicable with either type of event. Enterprise GIS has not been discussed much lately, but it is absolutely critical to solving the information needs of the contemporary emergency manager. Enterprise GIS means that many of the key data sets needed to support the four stages of EM are readily available, in a consistent manner and are always up to date. An enterprise perspective also means that GIS data are compatible with surrounding areas and GIS products are consistent with local, state, and federal information needs/requirements. The “common operating picture” we hear so much about in today’s EM world. Most importantly, an enterprise GIS perspective means that all data and systems work together or can “talk” to each other. Easily sharing data by address or by parcel means that the information/knowledge content can grow quickly and ad-hoc data requirements or events can be handled quickly and reliably. GIS is no longer a system or even just an architecture—it literally is a way of thinking. It is so exciting to implement GIS capabilities only to see that they can be used in ways not originally intended or described. This is analogous to the EM problem of having data/maps collected for the last emergency and not the current one! This means that the GIS staff get involved and more fully understand the in-depth system requirements of each application/data set. By putting these requirements together, in an enterprise-wide perspective, we can begin to see how a school inventory needed for drug free zones (for the district attorney’s office) is also useful as a possible shelter/feeding/inoculation site inventory for EM. A cell tower inventory for address assignments (for E-911/CAD) may also prove useful to the assessment professionals who see income potentials in silos, flag poles and steeples, often on tax-exempt properties like churches or municipal water tanks. A gasoline station inventory from Health’s Weights and Measures is immediately applicable to EM’s requirements for a better understanding of possible gasoline rationing actions/scenarios. Another way of looking at enterprise GIS and its support of EM would be to always think about the other stages of EM as this particular data/map or application is being collected, designed, or implemented. Perhaps just including another data element or two could support other later (or earlier) stages of EM? The GIS data can provide the continuity that EM needs to handle an incident through the four stages.

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