Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle

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Francisco Agüera Vega, Fernando Carvajal Ramírez, Patricio J. Martínez Carricondo

2017

Measurement 98: 221-227

http://dx.doi.org/10.1016/j.measurement.2016.12.002

ABSTRACT

Digital Surface Models and orthoimages at high spatial and temporal resolution and accuracy is of increasing importance for many applications. From several years ago photogrammetry-UAV is being used to produce these topographic products. The aim of this study is to analyse the influence of the number of Ground Control Points used for georeferencing on Digital Surface Model and orthoimage accuracies obtained with UAV-photogrammetry. In this purpose, 160 images were taken on a 17.64 ha surface at 120 m altitude above ground level, and five replications of photogrammetric projects taking into account 4, 5, 6, 7, 8, 9, 10, 15, and 20 GCPs were made. Root Mean Square Error (RMSE) was used as accuracy measurement.
Optimal results for RMSEX, RMSEY and RMSEXY mean ± standard deviation values were reached for 15 GCPs: 3.3 ± 0.346, 3.2 ± 0.441, 4.6 ± 0.340 and 4.5 ± 0.169 cm respectively. Similar conclusions was derived for vertical accuracy: lower RMSEZ mean ± standard deviation values were reached for 15 and 20 GCPs: 5.8 ± 1.21 cm and 4.7 ± 0.860 cm respectively.
In view of these results maps at 1:150 scale and contour interval of 15 cm can be obtained from
UAV-photogrammetry.

Effects of image orientation and ground control points distribution on unmanned aerial vehicle photogrammetry projects on a road cut slope

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Fernando Carvajal Ramírez, Francisco Agüera Vega, and Patricio J. Martínez Carricondo

2016

Journal of Applied of Remote Sensing, 034004

http://dx.doi.org/10.1117/1.JRS.10.034004

ABSTRACT

The morphology of road cut slopes, such as length and high slopes, is one of the most prevalent causes of landslides and terrain stability troubles. Digital elevation models (DEMs) and orthoimages are used for land management purposes. Two flights with different orientations with respect to the target surface were planned, and four photogrammetric projects were carried out during these flights to study the image orientation effects. Orthogonal images oriented to the cut slope with only sidelaps were compared to the classical vertical orientation, with sidelapping, endlapping, and both types of overlapping simultaneously. DEM and orthoimages obtained from the orthogonal project showed smaller errors than those obtained from the other three photo- grammetric projects, with the first one being much easier to manage. One additional flight and six photogrammetric projects were used to establish an objective criterion to locate the three ground control points for georeferencing and rectification DEMs and orthoimages. All possible sources of errors were evaluated in the DEMs and orthoimages.

Accuracy of Digital Surface Models and Orthophotos Derived from Unmanned Aerial Vehicle Photogrammetry

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Francisco Agüera Vega, Fernando Carvajal Ramírez, Patricio J. Martínez Carricondo

2016

Journal of Surveying Engineering, 04016025

http://dx.doi.org/10.1061/(ASCE)SU.1943-5428.0000206

ABSTRACT

This paper explores the influence of flight altitude, terrain morphology, and the number of ground control points (GCPs) on digital surface model (DSM) and orthoimage accuracies obtained with unmanned aerial vehicle (UAV) photogrammetry. For this study, 60 photogrammetric projects were carried out considering five terrain morphologies, four flight altitudes (i.e., 50, 80, 100, and 120 m), and three different numbers of GCPs (i.e., 3, 5, and 10). The UAV was a rotatory wing platform with eight motors, and the sensor was a nonmetric mirrorless reflex camera. The root-mean-square error (RMSE) was used to assess the accuracy of the DSM (Z component) and orthophotos (X, Y, and XY components RMSEX, RMSEY, and RMSEXY, respectively). The results show that RMSEX, RMSEY, and RMSEXY were not influenced by flight altitude or terrain morphology. For horizontal accuracy, differences between terrain morphologies were observed only when 5 or 10 GCPs were used, which were the best accuracies for the flattest morphologies. Nevertheless, the number of GCPs influenced the horizontal accuracy; as the number of GCPs increased, the accuracy improved. Vertical accuracy was not influenced by terrain morphology, but both flight altitude and the number of GCPs had significant influences on RMSEZ; as the number of GCPs increased, the accuracy improved. Regarding flight altitude, vertical accuracy decreased as flight altitude increased. The most accurate combination of flight altitude and number of GCPs was 50 m and 10 GCPs, respectively, which yielded RMSEX, RMSEY, RMSEXY, and RMSEZ values equal to 0.038, 0.035, 0.053, and 0.049 m, respectively.
In view of these results, the map scale according to the legacy American Society for Photogrammetry and Remote Sensing map standard of 1990 will be approximately 1:150, and an equivalent contour interval of 0.150 m is sufficient for most civil engineering projects.

Estimating the Evaporation from Irrigation Reservoirs of Greenhouses Using Satellite Imagery

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Fernando Carvajal Ramírez, Francisco Agüera Vega, and Julián Sánchez-Hermosilla López

2016

Environ. Prog. Sustainable Energy, 35: 1750–1757

http://dx.doi.org/10.1002/ep.12419

ABSTRACT

The agricultural system in south-eastern Spain is based on intensive horticulture in greenhouses. Public and private organizations have spent substantial resources on optimizing irrigation, due to the scant annual precipitation (close to 250 mm). In order to preserve natural water resources, avoiding overexploitation and salinization aquifers, the water loss has to be minimized. Farmers save water in irrigation reservoirs, which are open to the atmosphere most of the time. In this work, the loss to evaporation from open water reservoirs was estimated in a typical agricultural greenhouse area in Almeria province, south-eastern Spain. The data source was both a high-resolution satellite image, and a set of climatic data from the Agro-climatic Information Network of Andalusia (AINA) and from a Class-A pan evaporimeter. The image was used for detecting and delineating open water bodies applying a supervised classification algorithm based on an artificial neural network. The climatic data were used to estimate the distribution of monthly evaporation. It was concluded that irrigation water reservoirs can evaporate 3.76% of the input water used for crops. If all of the water bodies were covered with shade materials and if the precipitation intercepted by the roofs of greenhouses were saved in the irrigation water reservoirs, 49.87% of water annually consumed by greenhouse crops could be saved.

Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop

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Francisco Agüera Vega, Fernando Carvajal Ramírez, Mónica Pérez Saiz, Francisco Orgaz Rosúa

2015

Biosystems engineering 132: 19-2 7

http://dx.doi.org/10.1016/j.biosystemseng.2015.01.008

ABSTRACT

The objective of this study is to determine the capability of an unmanned aerial vehicle system carrying a multispectral sensor to acquire multitemporal images during the growing season of a sunflower crop. Measurements were made at different times of the day
and with different resolutions to estimate the normalised difference vegetation index (NDVI) and study its relationship with several indices related to crop status with the aim of generating useful information for application to precision agriculture techniques. NDVI
was calculated from images acquired on four different dates during the cropping season.
On two of these dates, two images were acquired to determine how the time of day when the images were taken influences NDVI value. To study the influence of image resolution on NDVI, the original images were resampled to 30 x 30 and 100 x 100 cm pixel sizes. The
results showed that the linear regressions between NDVI and grain yield, aerial biomass and nitrogen content in the biomass were significant at the 99% confidence level, except during very early growth stages, whereas the time of day when the images were acquired,
the classification process, and image resolution had no effect on the results. The methodology provides information that is related to crop yield from the very early stages of growth and its spatial variability within the crop field to be harvested, which can subsequently
be used to prescribe the most appropriate management strategy on a site-specific basis.

Water balance in artificial on-farm agricultural water reservoirs for the irrigation of intensive greenhouse crops

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Fernando Carvajal Ramírez, Francisco Agüera Vega, Julián Sánchez-Hermosilla López.

2014

Agricultural Water Management 131: 146– 155

http://dx.doi.org/10.1016/j.measurement.2016.12.002

ABSTRACT

The intensive-cropping system used in southeastern Spain is one of the most productive of the European Union. It is based on the efficient use of irrigation water using localised irrigation systems with water obtained mostly from small artificial on-farm agricultural water reservoirs (AWRs) that meet the evapotranspiration demands of the intensive greenhouse crops.

Several public and private initiatives have attempted to optimise the distribution of the water from wells and desalinating plants to avoid losses in the delivery network. However, the AWR water loss to evaporation could be dramatically reduced with the use of plastic shade materials. In addition, simple water-collection devices for capturing rainwater from the greenhouse roofs, which are currently used in more than half of the greenhouses of the study zone, recirculate water to the irrigation AWRs, significantly improving the water balance of the system.

The present work provides a monthly balance of the water deficit that could be overcome in an AWR over an irrigation season considering the rainwater directly received by the AWR, the losses due to direct evaporation from the AWR, and the water demand that must be met to provide sufficient irrigation. These water balances were compared with those that would occur if the AWR had been covered with shading material to reduce direct evaporation and if the rainwater from the greenhouse roofs had been collected in the AWR. When applying both of these management approaches, the annual water deficit decreased by 53.02%

Relationship between atmospheric corrections and training-site strategy with respect to accuracy of greenhouse detection process from very high resolution imagery

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Fernando Carvajal Ramírez, Francisco Agüera, Fernando J. Aguilar, Manuel A. Aguilar

2010

International Journal of Remote Sensing, 31: 2977 — 2994

http://dx.doi.org/10.1080/01431160902946580

ABSTRACT

Frequently, satellite images that are acquired to extract a target surface are atmospherically corrected prior to the detection process. Thus, the unification of measure units is achieved, and atmospheric effects are removed from various imagery sources or taken at different dates. In this paper, four increasing levels of atmospheric corrections are applied (Top-Of-Atmosphere transformation: TOA; Apparent Reflectance Model: ARM; Flat Areas Model: FAM; Non-Flat Areas Model: NFAM). Then, the classification process is carried out using two strategies of training-site definitions (statistically purified and crude training sites) and two satellite imagery sources (QuickBird and Ikonos). Three-way Analysis of Variance (ANOVA) tests and Fisher’s least-significant difference tests are included in quality classification assessment, based on four accuracy indexes. Two images from both remote sensors are orthorectified, and then it is checked that all selected atmospheric correction levels have significantly different influences on the statistics of both orthoimages. Taking into account the conditions established in this work, it is concluded that a lower atmospheric correction level would be preferred because it does not present significantly worse results than other levels considered. Training sites would not be statistically purified, and QuickBird or Ikonos would be chosen, depending on the aspect of the greenhouse detection accuracy preferred.

Geometric accuracy assessment of the orthorectification process from very high resolution satellite imagery for Common Agricultural Policy purposes

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Manuel A. Aguilar, Francisco Agüera Vega, Fernando J. Aguilar, Fernando Carvajal Ramírez

2008

International Journal of Remote Sensing 29: 7181-7197

http://dx.doi.org/10.1080/01431160802238393

ABSTRACT

This study has, as its main aim, the assessment of different sensor models to achieve the best geometric accuracy in orthorectified imagery products obtained from IKONOS Geo Ortho Kit and QuickBird basic imagery. The final orthoimages are compared, both geometrically and visually, with the panchromatic orthophotos based on a photogrammetric flight with an approximate scale of 1 : 20 000, which are now used for the European Union Common Agricultural Policy in Andalusia (Spain). Two‐dimensional root mean square (RMS2d) errors in independent check points are used as accuracy indicators. The ancillary data were generated by high accuracy methods: (1) check and ground control points (GCPs) were measured with a differential global positioning system and (2) an accurate digital elevation model was used for image orthorectification. Two sensor models were used to correct the satellite data: (1) a three‐dimensional (3D) rational function refined by the user with zero‐ (RPC0) or first‐(RPC1) order polynomial adjustment and (2) the 3D Toutin physical model (CCRS). For the IKONOS image, the best results in the final orthoimages (RMS2d of about 1.15 m) were obtained when the RPC0 model was used. Neither a large number of GCPs (more than nine), nor a better distribution of them, improved the results obtained with the RPC0. For the QuickBird image, the CCRS model generated the best results (RMS2d of about 1.04 m), although it was sensitive to the number and distribution of the GCPs used in its computation.

Developing digital cartography in rural planning applications

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Fernando J. Aguilar, Fernando Carvajal Ramírez, Manuel A. Aguilar, Francisco Agüera Vega

2007

Computers and Electronics in Agriculture 55 : 89–106

http://dx.doi.org/10.1016/j.compag.2006.12.008

ABSTRACT

The main objective of the present study is to develop an efficient methodology at a reasonable cost, that will allow the use of the latest technological developments in the areas of image analysis and geographical information systems (GIS) for the generation, compilation, operation and updating of digital cartography on a large scale in rural environments. The various possibilities offered by the current analytic cartography allow the utilization of this spatially geo-referenced database to obtain quantitative and qualitative information of great interest for the study of planning, land organization and sustainable rural development.

The methodological proposal to achieve this objective consists of three well differentiated phases: the generation of digital cartography from 1:5000 scale colour aerial photographs, the compilation of cartographic information obtained in an open architecture GIS, and, finally, the periodical updating of the GIS cartographic database by means of digital treatment and geometrical modelling of high resolution satellite imagery.

The methodology described above is being developed and applied in a specially interesting rural milieu, like “El Campo de Níjar”, located in the province of Almería (Spain) on the border with the nature reserve “Parque Natural de Cabo de Gata”.

Minimising the Earthwork Cost in the Construction of Irrigation Offstream Reservoirs

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Francisco Agüera Vega, Fernando J. Aguilar, Manuel A. Aguilar, Fernando Carvajal Ramírez

2007

Water Resources Management 21: 375–397

http://dx.doi.org/10.1007/s11269-006-9021-7

ABSTRACT

In the majority of agricultural areas it is necessary to construct irrigation offstream reservoirs to store the required amount of water to be available at any time. In this type of projects, the earthwork can represent up to 80% of the total budget, therefore, one of the criteria in their design is minimising this cost. Due to the fact that the minimising process is carried out by the trial and error method, calculating the cost in different locations and devoting a great deal of time and effort to these calculations, finding the definite location for the lowest earthwork cost is very complicated and difficult to achieve. In this study a computer application which carries out this process is presented. Once the geometry of the offstream reservoir has been defined, as well as that of the land where it will be located and the cut and fill surfaces slopes, a boundary can be fixed within which it will be constructed, and the computer application will perform automatically the calculation of the cost of the earthwork in a series of locations. The different locations within the defined limit are obtained by moving the offstream reservoir along West-East and South-North directions, changing the crown elevation, and even making it rotate with regard to a vertical axis. The range of values for these movements and the increase in variation as they go from one to the next will determine the number of places where the cost of the earthwork will be calculated. The cost function incorporated to the programme allows to take into account the types of materials that will be excavated and the disposition of the soil layers. In the first place, a series of algorithms are detailed which have been developed to do the calculations, then the computer application is described which integrates these algorithms, and finally an application of the programme is explained in which the minimum cost is sought for an offstream reservoir with a capacity of 100000 m3.