The visualization of the use of land on the basis of the dynamics of the pedestrian movement from the interval UAV imaging

Abstract. The identification and visualization of the real land use based on the dynamics of pedestrian movement was the issue discussed in the research. The observation of the pedestrian movement was made on the basis of interval imaging from the low flight level of oblique projection obtained from the single observation station. That led to the occurrence of blind spots, i.e. spots covered by trees and other objects, on imaging made from the drone, which made it difficult or impossible to observe the pedestrian movement on the parts of the research area.In the research the data on the Land and Building Register were used in order to analyze the cadastral and infrastructural construction of the research area. The photogrammetric record was made during the maximum density of the pedestrian movement on the research area of 7&thinsp;ha, located on the university campus.The objective of the research was to create cartographic visualizations depicting the real land use with the employment of different mapping methods, diagrams and other forms of graphic presentation of spatial data. The georeference of the imaging obtained was based on the ground control points and its verification was carried out with the use of independent ground control points. The process allowed one to obtain an orthophotomap of the research area with the precision up to 27&thinsp;cm in relation to the coordinates of the ground control points, specified by means of GNSS RTK technology. On the basis of the orthophotomap worked out the location of specific pedestrians was determined with the employment of coordinates. Considering the large scale of the research and its objective, it was necessary to present particular pedestrians, using area spatial objects. The transformation of point objects into area objects was possible thanks to suitable methodology and geomatic transformation.Furthermore, thanks to the imaging of the 10-second interval and the geomatic research method it was possible to aggregate area objects that represented pedestrians into the land use area. Identified areas of ‘wild’ land use, on which the pedestrian movement was observed outside the specified communication infrastructure, are particularly noteworthy. Moreover, the aggregation allowed one to solve the problem of blind spots. As a result of the conducted research, numerical statements concerning the area of land use based on the observation of pedestrian movement were obtained, and the acquired spatial data were presented on cartographic visualizations.

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Geospatial Analysis of Groundwater Potential Zones in Keffi, Nassarawa State, Nigeria

Journal of Geography Environment and Earth Science International ◽

10.9734/jgeesi/2019/v23i130161 ◽

2019 ◽

pp. 1-16

Author(s):

D. R. Abdullahi ◽

O. O. Oladosu ◽

S. A. Samson ◽

L. O. Abegunde ◽

T. A. Balogun ◽

...

Keyword(s):

Spatial Data ◽

Control Point ◽

Drainage Density ◽

Groundwater Potential ◽

Ground Control ◽

Control Points ◽

Groundwater Potential Zones ◽

Ground Control Points ◽

Potential Map ◽

Groundwater Potential Map

Aim: Employ the use of Remote Sensing and Geographic Information System (GIS) to analyze areas of groundwater potentials in Keffi LGA to meet the rate of water demand. Study Design: The study is designed to delineate and analyze the drainage characteristics, and map out the groundwater potential zones. Place and Duration of Study: The study is conducted in Keffi LGA of Nassarawa State, Nigeria in 2018. Methodology: Both spatial and non-spatial data were utilized for this research, including Ground Control Points, satellite imageries, and maps. The data generated consisting of the rainfall, NDVI, lineament, geology, slope, and relief were prepared into thematic layers and used for the generation of the drainage morphometric parameters and multi-criteria overlay analysis. Each of the layer used has inputs were ranked based on their relative importance in controlling groundwater potential, and divided into classes using the hydro-geological properties. The groundwater potential analysis reveals four distinct zones representing high, moderate, less and least groundwater potential zones. The delineated groundwater potential map was verified using the available Ground Control Point of boreholes across the study area. Results: The drainage of the study area falls in the 4th order, with the drainage density ranging from 0.2 to 1.6. From the groundwater potential map generated using the rainfall, lineament, geology, drainage density, slope, soil, and NDVI attributes, areas categorized having the moderate groundwater potentials cover about 89.1 km2, while the least cover 0.1 km2 of the study area. Validating the result with borehole locations across the location shows that the boreholes are dug based on the availability of water following the groundwater potentials, and; 59.8% of the settlement area falls within the moderate groundwater potential classes. Conclusion: The area has adequate capacity for water supply, and only those within the high groundwater potential classes can access groundwater throughout the year.

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Dem Local Accuracy Patterns in Land-Use/Land-Cover Classification

Open Geosciences ◽

10.1515/geo-2016-0052 ◽

2016 ◽

Vol 8 (1) ◽

Author(s):

Wassim Katerji ◽

Mercedes Farjas Abadia ◽

Maria del Carmen Morillo Balsera

Keyword(s):

Land Use ◽

Pilot Study ◽

Geostatistical Analysis ◽

Ground Control ◽

Control Points ◽

Land Use Land Cover ◽

Ground Control Points ◽

Input And Output ◽

Local Accuracy ◽

The World

AbstractGlobal and nation-wide DEM do not preserve the same height accuracy throughout the area of study. Instead of assuming a single RMSE value for the whole area, this study proposes a vario-model that divides the area into sub-regions depending on the land-use / landcover (LULC) classification, and assigns a local accuracy per each zone, as these areas share similar terrain formation and roughness, and tend to have similar DEM accuracies. A pilot study over Lebanon using the SRTM and ASTER DEMs, combined with a set of 1,105 randomly distributed ground control points (GCPs) showed that even though the inputDEMs have different spatial and temporal resolution, and were collected using difierent techniques, their accuracy varied similarly when changing over difierent LULC classes. Furthermore, validating the generated vario-models proved that they provide a closer representation of the accuracy to the validating GCPs than the conventional RMSE, by 94% and 86% for the SRTMand ASTER respectively. Geostatistical analysis of the input and output datasets showed that the results have a normal distribution, which support the generalization of the proven hypothesis, making this finding applicable to other input datasets anywhere around the world.

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The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b1-1079-2016 ◽

2016 ◽

Vol XLI-B1 ◽

pp. 1079-1084 ◽

Cited By ~ 3

Author(s):

M. L. Yeh ◽

Y. T. Chou ◽

L. S. Yang

Keyword(s):

Land Use ◽

Unmanned Aerial Vehicle ◽

Three Dimensional ◽

High Mobility ◽

Urban Land Use ◽

Ground Control ◽

Surface Model ◽

Control Points ◽

Ground Control Points ◽

Aerial Vehicle

The efficiency and high mobility of Unmanned Aerial Vehicle (UAV) made them essential to aerial photography assisted survey and mapping. Especially for urban land use and land cover, that they often changes, and need UAVs to obtain new terrain data and the new changes of land use. This study aims to collect image data and three dimensional ground control points in Taichung city area with Unmanned Aerial Vehicle (UAV), general camera and Real-Time Kinematic with positioning accuracy down to centimetre. The study area is an ecological park that has a low topography which support the city as a detention basin. A digital surface model was also built with Agisoft PhotoScan, and there will also be a high resolution orthophotos. There will be two conditions for this study, with or without ground control points and both were discussed and compared for the accuracy level of each of the digital surface models. According to check point deviation estimate, the model without ground control points has an average two-dimension error up to 40 centimeter, altitude error within one meter. The GCP-free RTK-airborne approach produces centimeter-level accuracy with excellent to low risk to the UAS operators. As in the case of the model with ground control points, the accuracy of x, y, z coordinates has gone up 54.62%, 49.07%, and 87.74%, and the accuracy of altitude has improved the most.

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Analysis of the impacts on the quality of UAV photogrammetric products

Geodetski vestnik ◽

10.15292/geodetski-vestnik.2020.04.489-507 ◽

2020 ◽

Vol 64 (04) ◽

pp. 489-507

Author(s):

Mojca Kosmatin Fras ◽

Urška Drešček ◽

Anka Lisec ◽

Dejan Grigillo

Keyword(s):

Data Acquisition ◽

Unmanned Aerial Vehicles ◽

Spatial Data ◽

Point Clouds ◽

Ground Control ◽

Control Points ◽

Positional Accuracy ◽

Ground Control Points ◽

Aerial Vehicles

Unmanned aerial vehicles, equipped with various sensors and devices, are increasingly used to acquire geospatial data in geodesy, geoinformatics, and environmental studies. In this context, a new research and professional field has been developed – UAV photogrammetry – dealing with photogrammetry data acquisition and data processing, acquired by unmanned aerial vehicles. In this study, we analyse the selected factors that impact the quality of data provided using UAV photogrammetry, with the focus on positional accuracy; they are discussed in three groups: (a) factors related to the camera properties and the quality of images; (b) factors related to the mission planning and execution; and (c) factors related to the indirect georeferencing of images using ground control points. These selected factors are analysed based on the detailed review of relevant scientific publications. Additionally, the influence of the number of ground control points and their spatial distribution on point clouds' positional accuracy has been investigated for the case study. As the conclusion, key findings and recommendations for UAV photogrammetric projects are given; we have highlighted the importance of suitable lighting and weather conditions when performing UAV missions for spatial data acquisition, quality equipment, appropriate parameters of UAV data acquisition, and a sufficient number of ground control points, which should be determined with the appropriate positional accuracy and their correct distribution in the field.

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A New Method for Positional Accuracy Analysis in Georeferenced Satellite Images without Independent Ground Control Points

Remote Sensing ◽

10.3390/rs12244132 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4132

Author(s):

Miguel Sánchez ◽

Aurora Cuartero ◽

Manuel Barrena ◽

Antonio Plaza

Keyword(s):

Spatial Data ◽

Traditional Method ◽

Satellite Images ◽

New Method ◽

Ground Control ◽

Landsat 8 ◽

Control Points ◽

Positional Accuracy ◽

National Geographic ◽

Ground Control Points

This paper introduces a new method to analyze the positional accuracy of georeferenced satellite images without the use of ground control points. Compared to the traditional method used to carry out this kind of analysis, our approach provides a semiautomatic way to obtain a larger number of control points that satisfy the requirements of current standards regarding the size of the set of sample points, the positional accuracy of such points, the distance between points, and the distribution of points in the sample. Our methodology exploits high quality orthoimages, such as those provided by the Aerial Orthography National Plan (PNOA)—developed by the Spanish National Geographic Institute—and has been tested on spatial data from Landsat 8. Our method works under the current international standard (ASPRS 2014) and exhibits similar performance than other well-known methods to analyze the positional accuracy of georeferenced images based on the use of independent ground control points. More specifically, the positional accuracy achieved for a Landsat 8 dataset evaluated by the traditional method is 5.22 ± 1.95 m, and when evaluated with the proposed method, it exhibits a typical accuracy of 5.76 ± 0.50 m. Our experimental results confirm that the method is equally effective and less expensive than other available methods to analyze the positional accuracy of satellite images.

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