Maximum Depression Storage and Surface Drainage Network in Uneven Agricultural Landforms

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Fernando Carvajal Ramírez; Manuel A. Aguilar; Francisco Agüera Vega; Fernando J. Aguilar; Juan Vicente Giráldez Cervera

2006

Biosystems Engineering 95: 281–293

http://dx.doi.org/10.1016/j.biosystemseng.2006.06.003

ABSTRACT

The volume and spatial distribution of the water available for cultivated plant roots largely depends on the soil surface relief. In traditional irrigation systems, soil micro-relief plays an important part in distributing the surface drainage produced by rainfall or irrigation. In this paper, an algorithm is proposed for estimating the water distribution network on a soil surface. It has been applied to plots of around 3 m2, and the digital elevation model (DEM) has been obtained in three surface morphologies.

With each of these DEMs, a flow directions map was calculated, a hydrodynamic classification was made, vortices were detected and eliminated, a drainage network was traced, and surface flow accumulation, maximum depression storage (MDS) and the soil surface roughness index were calculated. All of these processes were carried out using a programme specifically designed for this study, called REDES©. The method designed makes it possible to establish the influence of soil morphology on surface drainage by means of a complete characterisation of the soil and its visual comparison with soil morphologies. With respect to the drainage network, the maximum convergence level appeared in gully morphology, with 306 flow paths in the rill pixel located in the lower position. Convergence levels in the others two morphologies, tilled soil and non-tilled soil, are similar and close to half of the convergence of gully morphology. The biggest contributing basin was in gully morphology, about 1440 cm2, followed by non-tilled soil, with 470 cm2, and by tilled soil, with 260 cm2.

A study of the relationship between the DEM resolution and precision to estimate the MDS is included. When the pixel size became 24 times larger than the ‘true model’, the standard deviation of unitary vectors (SDUV) increased between 2 and 9%. Introducing this relationship, a simple predictive model to find out the estimation error of the MDS has been adjusted. The input variables used were soil roughness and DEM resolution.

Geometric accuracy of Ikonos Geo Panchromatic orthoimage products

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

2006

Revue Française de Photogrammétrie et de Telédétection. ISPRS Commission Technique I, Symposium, nº 184: 5-10

http://www.scopus.com/inward/record.url?eid=2-s2.0-33748913533&partnerID=MN8TOARS

ABSTRACT

The new very high space resolution satellite images, such as QuickBird and IKONOS, open new possibilities in cartographic applications. This work has as its main aim the assessment of different sensor models for achieving the best geometric accuracy in orthorectified imagery products obtained from IKONOS Geo Ortho Kit Imagery. Two dimensional Root Mean Square Error (RMSE2D) is computed and utilized as accuracy indicator. The ancillary data were generated by high accuracy methods: (1) Check (ICPs) and control points (GCPs) were measured with a differential global positioning system (DGPS) and, (2) a digital elevation model (DEM) with grid spacing of 5 m derived from digitized contour lines with an interval of 10 m and extracted from the 1:10,000 Andalusia Topographic Maps series (RMSEz<1.75 m), was used for image orthorectification process. Four sensor models were used to correct the satellite data: (1) First order 3D rational functions without vendor image support data (RFM1), (2) 3D rational functions refined by the user with zero order polynomial adjustment (RPC0), (3) 3D rational functions refined by the user with first order polynomial adjustment (RPC1), and (4) the 3D Toutin physical model (CCRS). The number of control points per orthorectified imagery (9 and 18 GCPs) and their distribution (random and stratified random sampling) were studied as well. The best results, both in the phase of sensor orientation (RMSEO about 0.59 m) as in the final orthoimages (RMSEORTHO about 1.25 m), were obtained when the model RPC0 was used. Neither a large number of GCPs (more than nine) nor a better distribution (stratified random sampling) improved the results obtained from RPC0.

An integrated model to estimate the accuray of digital orthoimages from high resolution satellite imagery

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

2005

Revue Française de Photogrammétrie et de Telédétection. ISPRS Commission Technique I, Symposium, nº 184: 11-16

http://www.scopus.com/inward/record.url?eid=2-s2.0-34848928190&partnerID=MN8TOARS

ABSTRACT

In this work, a theoretical-empirical model has been developed for the modelling of the local geometric accuracy of digital orthoimages from panchromatic QuickBird Very High Resolution Satellite Imagery (VHRSI). The empirical component integrates the error of sensor orientation and its propagation to the orthoimage generation process. The theoretical component, mainly a geometrical study from QuickBird Image Metadata File, seeks to model the propagation of DEM error throughout the orthorectificacion process in addition to the previous errors of the bundle adjustment. For the goal of model developing and calibration, a panchromatic QuickBird Basic Imagery was acquired on 19 December 2004, registering a mean collected GSD of 0.62 m, off-nadir view angle of 8.4º and an azimuth and elevation angle of the satellite with respect to the centre of the image of 123.3º and 80.9º respectively. The QuickBird image employed covered an area of 17 x 18 Km over the district of Níjar, located at the North-East of Almería city, Spain. It was centred on the UTM coordinates European Datum ED50 (easting and northing) of 577,848 and 4,087,277 m. The Toutin’s 3D physical model was the selected method to compute the bundle adjustment and so to carry out the sensor orientation using PCI Geomatica OrthoEngine software v. 9.1.7. On this score, 3D coordinates of 124 ground points were measured by means of high precision differential GPS techniques. From the whole set of ground points, a sub-set of 45 ones uniformly distributed was selected for the sensor orientation (GCPs), whereas the remaining 79 were used as independent check points (ICPs) to assess the performance of the developed model regarding to the average error of the final orthoimages. Inasmuch to the results, the empirical component, which takes into account the effect of pointing error and number and accuracy of GCPs on sensor orientation, presented an acceptable fitting to the experimental data, with a regression coefficient R2 = 0.932. The theoretical component also offered good results, observing like the proposed model reproduces with reasonable accuracy the statistical behaviour of the 2D orthoimage errors measured at the 79 ground points checked. The findings obtained in this work could be used as a guide for the selection of appropriate operational parameters in projects related to digital cartography production and updating from QuickBird imagery.

Effects of Terrain Morphology, Sampling Density, and Interpolation Methods on Grid DEM Accuracy

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

2005

Photogrammetric Engineering & Remote Sensing 71: 805–816

ABSTRACT

This paper explores the effects of terrain morphology, sampling density, and interpolation methods for scattered sample data on the accuracy of interpolated heights in grid Digital Elevation Models (DEM). Sampled data were collected with a 2 by 2 meters sampling interval from seven different
morphologies, applying digital photogrammetric methods to large scale aerial stereo imagery (1:5000). The experimental design was outlined using a factorial scheme, and an analysis of variance was carried out. This analysis yielded the following main conclusions: DEM accuracy (RMSE) is affected significantly by the variables studied in this paper according to “morphology > sampling density > interpolation” method. Multiquadric Radial Basis Function (RBF) was rated as the best interpolation method, although Multilog RBF performed similarly for most morphologies. The rest of RBF interpolants tested (Natural Cubic Splines, Inverse Multiquadric, and Thin Plate Splines) showed numerical instability working with low smoothing factors. Inverse Distance Weighted interpolant performed worse than RBF Multiquadric or RBF Multilog. In addition, it is found that the relationship between the RMSE and the sampling density N is adjusted to a decreasing potential function that may be expressed as RMSE/Sdz = 0.1906(N/M)exp(-0.5684) (R2 = 0.8578), being Sdz the standard deviation of the heights of the M check points used for accuracy estimation, and N the number of sampling points used for creating the DEM.
The results obtained in this study allow us to observe the possibility of establishing empirical relationships between the RMSE expected in the interpolation of a Grid DEM and
such variables as terrain ruggedness, sampling density, and the interpolation method, among others that could be added. Therefore, it would be possible to establish a priori the optimum grid size required to generate or storage a DEM of a particular accuracy, with the economy in computing time and file size that this would signify for the digital flow of the mapping information.

The Evaluation of Close-range Photogrammetry for the Modelling of Mouldboard Plough Surfaces

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

2005

Biosystems Engineering 90: 397–407

http://dx.doi.org/10.1016/j.biosystemseng.2004.11.006

ABSTRACT

The geometric heterogeneity existing in mouldboard ploughs hinders its inclusion in models in which the redistribution of soil particles is predicted, or the force exerted on the working component is measured. In this study, both the mathematical surface (second-, third- and fourth-order polynomials, both splines and Bezier) and the number of control points required for its adjustment (100, 49, 25, 20, 16), are examined to produce optimal modelling of the mouldboard plough geometry. The three-dimensional coordinates of 193 points on the surface of a plough are measured with great accuracy (root mean square 0·66 mm), using low-cost close-range photogrammetry. The results obtained indicate that the surface of a mouldboard plough can be shaped with an accuracy of approximately 1·30 mm, with the adjustment of a cubic polynomial surface to just 25 control points randomly distributed over the surface of the plough.