ALBERT

Description: Presents corrections to the paper, "Estimation of forest biomass from two-level model inversion of single-pass InSAR data" (Soja, M.J., et al.,Trans. Geosci. Remote Sens., vol. 53, no. 9, pp. 5083???5099, Sep. 2015).

Description: The temporal variations (diurnal and annual) in arboreal $(varepsilon_mathrm{Tree})$ and bare soil $(varepsilon_mathrm{Soil})$ dielectric constants and their correlation with precipitation were examined for several trees in Japan. A significant (1 $sigma$ (standard deviation) and 2 $sigma$ ) $varepsilon_mathrm{Tree}$ increase is observed after rainfall at 89.8% and 90.5% probability. However, rainfall does not always induce significant $varepsilon_mathrm{Tree}$ increases. Rainfall of more than 5 mm/day can induce 1 $sigma$ $varepsilon_mathrm{Tree}$ Tree increase at a 59.6% probability. In order to examine whether the increase in $varepsilon_mathrm{Tree}$ affects the L-band $sigma^{0}$ variation in a forest, the four-year temporal variation of the L-band backscattering coefficient $(sigma^{0})$ was estimated from observations by the Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar. Observed maximum absolute deviations from the mean over the forest area were 1.0 and 1.2 dB for $sigma_{mathrm{HH}}^{0}$ and $sigma_mathrm{HV}^{0}$ , respectively, and 4.0 and 3.0 dB over open land. $sigma^{0}$ and rainfall correlations show that $varepsilon_mathrm{Tree}$ and $sigma_mathrm{Forest}^{0}$ are proportional to precipitation integrated over seven or eight days; $varepsilon_mathrm{Soil}$ and $sigma_mathrm{Open land}^{0}$ are proportional to precipitation integrated over three days. This finding indicates that $varepsilon_mathrm{Tree}$ variations influence $sigma_{mathrm{Forest areas}}^{0}$ . A stronger correlation between $sigma_mathrm{HV}^{0}$ and precipitation is observed in several sites with low $sigma_mathrm{HV}^{0}$ , where less biomass is expected, and several sites with high $sigma_mathrm{HV}^{0}$ , where more biomass is expected. A weaker correlation between $sigma_mathrm{HV}^{0}$ and precipitation is observed for several sites with high $sigma_mathrm{HV}^{0}$ . These differences may be explained by the different contributions of double bounce scattering and potential transpiration, which is a measure of the ability of the atmosphere to remove water from the surface th

Description: The spectral and radiometric quality of airborne imaging spectrometer data is affected by the anisotropic reflectance behavior of the imaged surface. Illumination and observation angle-dependent patterns of surface reflected radiation propagate into products, hinder quantitative assessment of biophysical/biochemical parameters, and decrease the comparability of data from multiple flight lines. The Ross–Li model, originally developed for multiangular observations, can be inverted to estimate and correct for surface anisotropy effects. This requires land cover be stratified into distinct types of scattering behavior. When the observations subsumed in these classes cover a range of view angles, a pseudo multiangular view on the surface can be employed to invert the Ross–Li model. A discrete land cover classification, however, bears the risk of inappropriate scattering correction resulting in spatial artifacts in the corrected data, predominantly in transition regions of two land cover types (e.g., soil and sparse vegetation with varying fractions). We invert the Ross–Li model on continuous land cover fraction layers. We decompose land cover in dominating structural types using linear spectral unmixing. Ross–Li kernel weights and formulations are estimated for each type independently; the correction is then applied pixel-wise according to the fractional distribution. The corrected Airborne Prism EXperiment imaging spectrometer data show significant reduction of anisotropic reflectance effects of up to 90% (average 60% to 75%, $p=0.05$ ), measured in the overlapping regions of adjacent flight lines. No spatial artifacts or spectral irregularities are observed after correction.

Description: Most spaceborne sensors have a tradeoff between high spatial and high temporal resolutions. This tradeoff limits the use of remote sensing data in various applications that require images in both the high spatial and high temporal resolutions. In this paper, we propose a novel technique to create a fine spatial and high temporal resolution images at a ground-based data processing system. Resourcesat-2 is one of the Indian Space Research Organization missions, and it carries the Linear Imaging Self-Scanning sensors (LISS III and LISS IV) and an Advanced Wide-Field Sensor (AWiFS) onboard. The spatial resolution of LISS III is 23.5 m, and that of AWiFS is 56 m. The temporal resolution of LISS III is 24 days, and that of AWiFS is five days. The proposed method creates a synthetic LISS-III image at 23.5-m spatial and five-day temporal resolutions. It is based on the subpixel relationship between a single AWiFS–LISS-III image pair, which is acquired before or after the prediction date. In temporal data composition, spurious spatial discontinuities are inevitable for land-cover type changes. These discontinuities were identified with temporal edge primitives and were smoothed with a spatial-profile-averaging method. A synthetic LISS-III image for time $t_{k}$ is predicted from an AWiFS image at time $t_{k}$ and a single AWiFS–LISS-III image pair at time $t_{0}$ , where $t_{0}ne t_{k}$ . Experimental results demonstrated that the proposed method is superior in terms of the computational efficiency and prediction accuracy with the other existing methods.

Description: Glacier avalanches are natural hazards that could damage infrastructures and threaten lives in high-altitude mountainous terrains. On April 7, 2012, a massive ice avalanche struck a Pakistani base at Gayari sector, Saltoro Valley, and buried/killed 148 soldiers and civilians. Keeping in view the catastrophe, a study was designed with the objectives to: 1) model and simulate the Gayari sector glacier avalanche incident in terms of height, extent, velocity, pressure, and momentum; 2) generate hazard risk assessment of possible other glacier avalanches in the Saltoro Valley through modeling and simulation; and 3) suitability analysis of current camp sites and recommendation of new safe camps sites locations in the Saltoro valley. To simulate the Gayari sector glacier event and other Glacier possible avalanches, a physical process-based rapid mass movements (RAMMS) was used. The RAMMS has two main components, i.e., Voellmy–Salm (VS) model and random kinetic energy, which deals with variables such as avalanche height and the mean avalanche velocity during the course of simulation. The suitability analysis of current camp sites were achieved using weighted overlay analysis with different constraints in ArcGIS Spatial Analyst. The RAMMS model simulation of the Gayari avalanche event predicted a maximum velocity of 74 ms -1 , generating a pressure of 5074 kPa and attaining a height of 45 m, whereas the predicted debris volume on the ground was 3.8145 million m 3 . A good agreement was found between actual debris height and extent, as compared with the RAMMS model output. The RAMMS model simulated all the potential tributary glacier avalanches of Saltoro valley very well. The weighted overlay analyses in ArcGIS Spatial Analyst revealed that the existing camp sites are safe and were not threatened by the glacier avalanche hazard. However, it was recommended that the Gayari camp should not be constructed at the same location and should be relocated- to the proposed safe camp sites identified in this research study. The proposed methodology developed in the current study could be applied in the Siachen conflict zone for avalanche hazard/risk analysis of all the camp sites located in the valley.

Description: Object-oriented remote sensing image classification is becoming more and more popular because it can integrate spatial information from neighboring regions of different shapes and sizes into the classification procedure to improve the mapping accuracy. However, object identification itself is difficult and challenging. Superpixels, which are groups of spatially connected similar pixels, have the scale between the pixel level and the object level and can be generated from oversegmentation. In this paper, we establish a new classification framework using a superpixel-based graphical model. Superpixels instead of pixels are applied as the basic unit to the graphical model to capture the contextual information and the spatial dependence between the superpixels. The advantage of this treatment is that it makes the classification less sensitive to noise and segmentation scale. The contribution of this paper is the application of a graphical model to remote sensing image semantic segmentation. It is threefold. 1) Gradient fusion is applied to multispectral images before the watershed segmentation algorithm is used for superpixel generation. 2) A probabilistic fusion method is designed to derive node potential in the superpixel-based graphical model to address the problem of insufficient training samples at the superpixel level. 3) A boundary penalty between the superpixels is introduced in the edge potential evaluation. Experiments on three real data sets were conducted. The results show that the proposed method performs better than the related state-of-the-art methods tested.

Description: We introduce a practical and accurate model, referred to as “GO4,” to describe near-nadir microwave scattering from the sea surface, and at the same time, we address the issue of the filtered mean square slope (mss) conventionally used in the geometrical optics model. GO4 is a simple correction of this last model, taking into account the diffraction correction induced by the rough surface through what we call an effective mean square curvature (msc). We evaluate the effective msc as a function of the surface wavenumber spectrum and the radar frequency and show that GO4 reaches the same accuracy as the physical optics model in a wide range of incidence and frequency bands with the sole knowledge of the mss and msc parameters. The key point is that the mss entering in GO4 is not the filtered but the total slope. We provide estimation of the effective msc on the basis of classical sea spectrum models. We also evaluate the effective msc from near-nadir satellite data in various bands and show that it is consistent with model predictions. Non-Gaussian effects are discussed and shown to be incorporated in the effective msc. We give some applications of the method, namely, the estimation of the total sea surface mss and the recalibration of relative radar cross sections.

Description: This paper evaluates the radiometric accuracy of observations from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership and Sondeur Atmospherique du Profil d' Humidité Intropicale par Radiométrie (SAPHIR) onboard Megha-Tropiques through intercalibration and validation versus in situ radiosonde and Global Positioning System Radio Occultation (GPS-RO) observations. SAPHIR and ATMS water vapor channels operate at slightly different frequencies. We calculated the bias due to radiometric errors as the difference between the observed and simulated differences between the two instruments. This difference, which is often referred to as double difference, ranges between 0.3 and 0.7 K, which shows good consistency between the instruments. We used a radiative transfer model to simulate the satellite brightness temperatures (Tbs) using radiosonde and GPS-RO profiles and then compared simulated and observed Tbs. The difference between radiosonde and ATMS Tbs for the middle and upper tropospheric temperature sounding channels was less than 0.5 K at most stations, but the difference between radiosonde and ATMS/SAPHIR Tbs for water vapor channels was between 0.5 and 2.0 K. The larger bias for the water vapor channels is mainly due to several errors in radiosonde humidity observations. The mean differences between the ATMS observations and the Tbs simulated using GPS-RO profiles were 0.2, 0.3, 0.4, 0.2, and −0.2 K for channels 10–14, respectively; and the uncertainty increases from 0.02 K for channel 10 to 0.07 K for channel 14.

Description: This paper presents a completely automatic processing chain for orthorectification of optical pushbroom sensors. The procedure is robust and works without manual intervention from raw satellite image to orthoimage. It is modularly divided in four main steps: metadata extraction, automatic ground control point (GCP) extraction, geometric modeling, and orthorectification. The GCP extraction step uses georeferenced vector roads as a reference and produces a file with a list of points and their accuracy estimation. The physical geometric model is based on collinearity equations and works with sensor-corrected (level 1) optical satellite images. It models the sensor position and attitude with second-order piecewise polynomials depending on the acquisition time. The exterior orientation parameters are estimated in a least squares adjustment, employing random sample consensus and robust estimation algorithms for the removal of erroneous points and fine-tuning of the results. The images are finally orthorectified using a digital elevation model and positioned in a national coordinate system. The usability of the method is presented by testing three RapidEye images of regions with different terrain configurations. Several tests were carried out to verify the efficiency of the procedure and to make it more robust. Using the geometric model, subpixel accuracy on independent check points was achieved, and positional accuracy of orthoimages was around one pixel. The proposed procedure is general and can be easily adapted to various sensors.

Description: This paper presents a new ground moving target imaging (GMTIm) algorithm for airborne synthetic aperture radar (SAR) based on a novel time-frequency representation (TFR), Lv's distribution (LVD). We first analyze generic moving target signatures for a multichannel SAR and then derive the analytical spectrum of a point target moving at a constant velocity by a polar format algorithm for SAR image formation. SAR motion deviation from a predetermined flight track is considered to facilitate airborne SAR applications. LVD, as a recently developed TFR for the analysis of multicomponent linear-frequency-modulated signal, is adopted to represent the target kinematic spectrum in the Doppler centroid frequency and chirp rate domain. As a result, the proposed SAR-GMTIm algorithm is capable of imaging multiple moving targets even when they are located at the same range resolution cell. Some practical issues such as imaging maneuvering targets and small/weak targets are discussed to enhance the applicability of the proposed algorithm. Simulation results with isotropic point moving targets are presented to validate the effectiveness and superiority of the proposed algorithm. Raw data collected by an airborne multichannel SAR are also used to verify the performance improvement made by the proposed algorithm.