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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.
Water Resources Management 01/2007; 21(2):375-397. · 2.05 Impact Factor
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International Journal of Geographical Information Science. 01/2006; 20:169-192.
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ABSTRACT: Generating maps of small areas using conventional aerial photography is of great interest for small engineering firms. The main problem is the high cost of the sophisticated digital photogrammetric workstations usually employed. In this paper, a low-cost close range photogrammetric software package is used to measure the three-dimensional coordinates of points on the land surface from a photogrammetric flight at a scale of approximately 1:5000. Furthermore, the influence of the type of scanner used to digitise photographs (consumer-grade or photogrammetric scanner), the resolution of the digital images and the number of control points required are examined. The root mean square errors obtained at the check points, using a low-cost close range software package, scanning aerial images with a photogrammetric scanner and 24 ground control points, were around 116 mm for X and Y coordinates, and 191 mm for Z. These levels of accuracy allow the generation of planimetric maps at a scale of 1:1500 and topographic maps with a contour interval of around 1 m. When the images were scanned with a consumer-grade scanner, the root mean square errors were around 150 mm for X and Y, and 271 mm for Z.RésuméProduire des cartes sur des petites surfaces en utilisant des photographies aériennes conventionnelles est d'un grand intérêt pour les petites sociétés d'ingénierie. Le problème principal est le coût élevé des stations de travail utilisées pour la photogrammétrie numérique. Dans cet article, on montre l'utilisation d'un logiciel de photogrammétrie à bas prix pour la mesure de points 3D à partir d'un vol à l’échelle approximative du 1:5000. De plus, nous étudions l'influence du type de scanner utilisé pour numériser les images (scanner de bureau ou scanner photogrammétrique), la résolution des images scannées et le nombre de points d'appui nécessaires. Les erreurs RMS obtenues sur les points de contrôle avec un logiciel photogrammétrique à bas prix, un scanner photogrammétrique et 24 points d'appui, sont d'environ 116 mm en XY et 191 mm en Z. Un tel niveau de précision permet la production de plans à l’échelle du 1:5000 et de cartes topographiques avec une équidistance des courbes de niveau d'environ 1 m. Avec un scanner de bureau, l'erreur RMS devient d'environ 150 mm en XY et 271 mm en Z.ZusammenfassungFür Ingenieurbüros ist die Möglichkeit der Kartierung kleiner Gebiete mittels traditioneller Luftbildphotogrammetrie von großem Interesse. Allerdings stehen dem die hohen Kosten für leistungsfähige digitale photogrammetrische Arbeitsstationen gegenüber. Als Alternative wird hier ein kostengünstiges photogrammetrisches Softwarepaket für Nahbereichsanwendungen für die dreidimensionale Auswertung eines photogrammetrischen Luftbildblockes mit Bildmaßstab 1:5000 eingesetzt. Neben der Anwendbarkeit werden die Einflüsse des Scanners (Desktop- oder photogrammetrischer Scanner), der Auflösung der digitalen Bilder und der Anzahl der notwendigen Passpunkte untersucht. Die mittleren quadratischen Fehler an den Kontrollpunkten lagen bei der Anwendung eines photogrammetrischen Scanners und 24 Passpunkten bei ungefähr 116 mm für X und Y Koordinaten, und bei 191 mm für Z. Damit können Grundrisse im Maßstab 1:1500 und topographische Karten mit einem Höhenlinienintervall von ca. 1 m hergestellt werden. Im Vergleich dazu lagen bei Verwendung eines Desktopscanners die mittleren quadratischen Fehler bei ca. 150 mm für X und Y, und 271 mm für Z.ResumenLa posibilidad de generar planos de superficies pequeñas utilizando fotografía aérea convencional es de gran interés para pequeños gabinetes de ingeniería. El principal problema es el alto coste económico de las sofisticadas estaciones fotogramétricas digitales con las que usualmente se realizan. En este artículo, se utiliza un programa de fotogrametría de objeto cercano y bajo coste para obtener las coordenadas tridimensionales de puntos sobre la superficie del terreno, a partir de un vuelo aéreo a una escala aproximada de 1:5000. Además, se estudia la influencia del tipo de escáner empleado en la digitalización de los fotogramas (escáner de oficina o escáner fotogramétrico), la resolución de las imágenes digitales y el número de puntos de control requeridos. El error medio cuadrático obtenido en los puntos de comprobación, cuando usamos el programa de fotogrametría de objeto cercano y bajo coste, un escáner fotogramétrico y 24 puntos de control, estuvo en torno a los 116 mm en X e Y, y 191 mm para la coordenada Z. Estos niveles de exactitud permiten la generación de planos planimétricos a escala 1:1500 y topográficos con una equidistancia entre curvas de nivel de exactitud de 1 m. Cuando empleamos un escáner de oficina para la digitalización de las imágenes, el error medio cuadrático fue de unos 150 mm en X e Y, y 271 mm en Z.
The Photogrammetric Record 11/2005; 20(112):335 - 350. · 1.10 Impact Factor
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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”.
Computers and Electronics in Agriculture.
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ABSTRACT: The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the optimum texture parameter depended on the main objective of the image classification. If the main classification goal is to minimize the number of pixels wrongly classified, the mean texture parameter should be used, whereas if the main classification goal is to minimize the unclassified pixels the angular second moment texture parameter should be used. On the whole, both QuickBird and IKONOS images offered promising results in classifying plastic greenhouses.
ISPRS Journal of Photogrammetry and Remote Sensing.
