Remote Sens.2013, 5(12), 6691-6716; doi:10.3390/rs5126691 (doi registration under processing) - published online 4 December 2013 Show/Hide Abstract
Abstract: This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.
Remote Sens.2013, 5(12), 6667-6690; doi:10.3390/rs5126667 (doi registration under processing) - published online 4 December 2013 Show/Hide Abstract
Abstract: A synthetic aperture radar (SAR) system requires external absolute calibration so that radiometric measurements can be exploited in numerous scientific and commercial applications. Besides estimating a calibration factor, metrological standards also demand the derivation of a respective calibration uncertainty. This uncertainty is currently not systematically determined. Here for the first time it is proposed to use hierarchical modeling and Bayesian statistics as a consistent method for handling and analyzing the hierarchical data typically acquired during external calibration campaigns. Through the use of Markov chain Monte Carlo simulations, a joint posterior probability can be conveniently derived from measurement data despite the necessary grouping of data samples. The applicability of the method is demonstrated through a case study: The radar reflectivity of DLR’s new C-band Kalibri transponder is derived through a series of RADARSAT-2 acquisitions and a comparison with reference point targets (corner reflectors). The systematic derivation of calibration uncertainties is seen as an important step toward traceable radiometric calibration of synthetic aperture radars.
Remote Sens.2013, 5(12), 6647-6666; doi:10.3390/rs5126647 (doi registration under processing) - published online 4 December 2013 Show/Hide Abstract
Abstract: Remote sensing can provide good alternatives for traditional in situ water status measurements in orchard crops, such as stem water potential (Ψstem). However, the heterogeneity of these cropping systems causes significant differences with regards to remote sensing products within one orchard and between orchards. In this study, robust spectral indicators of Ψstem were sought after, independent of sensor viewing geometry, orchard architecture and management. To this end, Ψstem was monitored throughout three consecutive growing seasons in (deficit) irrigated and rainfed pear orchards and related to spectral observations of leaves, canopies and WorldView-2 imagery. On a leaf and canopy level, high correlations were observed between the shortwave infrared reflectance and in situ measured Ψstem. Additionally, for canopy measurements, visible and near-infrared wavelengths (R530/R600, R530/R700 and R720/R800) showed significant correlations. Therefore, the Red-edge Normalized Difference Vegetation Index (ReNDVI) was applied on fully sunlit satellite imagery and found strongly related with Ψstem (R2 = 0.47; RMSE = 0.36 MPa), undoubtedly showing the potential of WorldView-2 to monitor water stress in pear orchards. The relationship between ReNDVI and Ψstem was independent of management, irrigation setup, phenology and environmental conditions. In addition, results showed that this relation was also independent of off-nadir viewing angle and almost independent of viewing geometry, as the correlation decreased after the inclusion of fully shaded scenes. With further research focusing on issues related to viewing geometry and shadows, high spatial water status monitoring with space borne remote sensing is achievable.
Remote Sens.2013, 5(12), 6611-6646; doi:10.3390/rs5126611 - published online 3 December 2013 Show/Hide Abstract
Abstract: Indoor localization and mapping is an important problem with many applications such as emergency response, architectural modeling, and historical preservation. In this paper, we develop an automatic, off-line pipeline for metrically accurate, GPS-denied, indoor 3D mobile mapping using a human-mounted backpack system consisting of a variety of sensors. There are three novel contributions in our proposed mapping approach. First, we present an algorithm which automatically detects loop closure constraints from an occupancy grid map. In doing so, we ensure that constraints are detected only in locations that are well conditioned for scan matching. Secondly, we address the problem of scan matching with poor initial condition by presenting an outlier-resistant, genetic scan matching algorithm that accurately matches scans despite a poor initial condition. Third, we present two metrics based on the amount and complexity of overlapping geometry in order to vet the estimated loop closure constraints. By doing so, we automatically prevent erroneous loop closures from degrading the accuracy of the reconstructed trajectory. The proposed algorithms are experimentally verified using both controlled and real-world data. The end-to-end system performance is evaluated using 100 surveyed control points in an office environment and obtains a mean accuracy of 10 cm. Experimental results are also shown on three additional datasets from real world environments including a 1500 meter trajectory in a warehouse sized retail shopping center.
Remote Sens.2013, 5(12), 6587-6610; doi:10.3390/rs5126587 - published online 3 December 2013 Show/Hide Abstract
Abstract: Monitoring Yellowstone National Park’s hydrothermal systems and establishing hydrothermal baselines are the main goals of an ongoing collaborative effort between Yellowstone National Park’s Geology program and Utah State University’s Remote Sensing Services Laboratory. During the first years of this research effort, improvements were made in image acquisition, processing and calibration. In 2007, a broad-band, forward looking infrared (FLIR) camera (8–12 microns) provided reliable airborne images for a hydrothermal baseline of the Hot Spring Basin hydrothermal system. From 2008 to 2011, night-time, airborne thermal infrared image acquisitions during September yielded temperature maps that established the temporal variability of the hydrothermal system. A March 2012 airborne image acquisition provided an initial assessment of seasonal variability. The consistent, high-spatial resolution imagery (~1 m) demonstrates that the technique is robust and repeatable for generating corrected (atmosphere and emissivity) and calibrated temperature maps of the Hot Spring Basin hydrothermal system. Atmospheric conditions before and at flight-time determine the usefulness of the thermal infrared imagery for geohydrologic applications, such as hydrothermal monitoring. Although these ground-surface temperature maps are easily understood, quantification of radiative heat from the Hot Spring Basin hydrothermal system is an estimate of the system’s total energy output. Area is a key parameter for calculating the hydrothermal system’s heat output. Preliminary heat calculations suggest a radiative heat output of ~56 MW to 62 MW for the central Hot Spring Basin hydrothermal system. Challenges still remain in removing the latent solar component within the calibrated, atmospherically adjusted, and emissivity corrected night-time imagery.
Remote Sens.2013, 5(12), 6560-6586; doi:10.3390/rs5126560 - published online 3 December 2013 Show/Hide Abstract
Abstract: This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value for the detection of buried archaeological features using remote sensing techniques. The proposed transformations, re-projects the initial VNIR bands of the satellite image, into a new 3D coordinate system where the first component is the so called “crop mark”, the second component “vegetation” and the third component “soil”. For the purpose of this study, a large ground spectral signature database has been explored and analyzed separately for each different satellite image. The narrow band reflectance has been re-calculated using the Relative Spectral Response filters of each sensor, and then a PCA analysis was carried out. Subsequently, the first three PCA components were rotated in order to enhance the detection of crop marks. Finally, all proposed transformations have been successfully evaluated in different existing archaeological sites and some interesting crop marks have been exposed.