- Average SPC height for mixed forest is always the lowest within the three classes.
Gradual decrease in the mean SPC heights is caused by the leaf and needle drop and color change which starts in early September and continues until November. The change in the average retrieved tree heights between October 18 and November 9 acquisitions is small in comparison to the change from September to October which indicates the major leaf drop have occurred during from early September to mid- October. Deciduous trees (alder and birch in test site) are known to drop their leaves during autumn. Coniferous forest on the contrary is known to keep most of their needles during winter. However, it has been reported that Scots pine also drop or lose their needles periodically  or diseases can cause needle loss in Norway spruce . Also the accuracy of the CLC2006 land classification map is less than 70%, thus we expect confusion in forest type classification. As a consequence, gradual drop in coniferous forest statistics are also expected. For these reasons, it is expected that highest temporal drop in average SPC height would belong to the deciduous forest and lowest to the coniferous forest. Since mixed forest can be considered as the mix of coniferous and deciduous kinds, the drop in the SPC is expected to be between. That is exactly what is observed in our analysis of TanDEM-X/TerraSAR-X data. The small increase in the mean SPC heights from October 29 to November 9 can be related to the big temperature drop between those dates since other weather conditions are quite similar. During the October acquisition, the temperature recorded was 10 o C. During the November acquisition, the temperature recorded was -1 o C which decreased the dielectric constant of the forest, and as a consequence, reflection from canopy and the SPC heights were increased.
Despite Canada’s extensive wetlands and several wetland studies using optical and PolSAR imagery, the interferometric coherence of Canadian wetlands has not been thoroughly investigated to date. In particular, the analysis of coherence variation for wetland classes has been limited to a few studies carried out in the Everglades  and Louisiana wetlands , both in the United States. However, Canadian wetland classes are different than those found in the United States. Given the relatively similar wetland types across the country, the results of this research provide the first detailed investigation towards Canadian wetland mapping, as well as other wetlands worldwide with similar ecological features, from a new perspective based upon the synergetic use of intensity and phase observations. Other studies, which have compared the coherence behavior of different wetland classes, applied only L- and C-band SAR data obtained by JERS-1, RADARSAT-1, and ERS , . In addition to examining the capacity of ALOS-1 and RADARSAT-2 in terms of coherence maintenance, the results of our study contribute to the success of wetland monitoring using X-band data with improved temporal resolution, which is of great importance for herbaceous wetlands. The results also indicate the potential of coherence as an input feature for wetland classifications, which is another significant contribution of this research study. Further improvement in classification accuracy is expected upon the synergistic use of intensity, coherence, and polarimetric decomposition features. This is because different input features incorporate different characteristics of ground targets, which may play various roles (i.e., contribution) in the classification results.
and L-band backscatter is utilized. This time however, due to the very large areal extent, the classification procedure needs to be fully automated. This will be achieved by means of the implementation of multitemporal data. Multi-temporal metrics contain additional information such as the backscatter variability and allow for threshold based classification strategies. First results based on C-band were characterized a classification accuracy above 95% . Detection of forest cover changes, i.e. monitoring the dynamics of forest cover, requires images that not only present certain sensitivity of the observable to forest cover but are also characterized by a limited effect of environmental conditions on the observable. In this respect L-band data are most appealing. In  it was shown that clear-cut detection in European and Siberian forests is possible with HH-backscatter acquired by the JERS-1 SAR sensor. The JERS winter coherence was instead proved to be effective to detect clear-cuts under frozen conditions in Siberia . The polarimetric feature of ALOS PALSAR enables an improvement with respect to JERS because of the strong sensitivity of the cross-polarized backscatter to forest density . Clear-cut detection in Swedish forest with a simple thresholding algorithm was found to perform well, with a detection accuracy of about 90% .
In recent years, several techniques have increased the potential of satellite data for the mapping and monitoring of landslides [ 22 – 24 ]. The launches of new generations of optical (e.g., Geoeye-1, WorldView-2, Pleiades 1A and 1B, SPOT5, 6 and 7, Formosat-2 and Kompsat-2, Sentinel-2) and radar (e.g., TerraSAR-X, COSMO-SkyMed, Sentinel-1) satellites with short repeat-pass cycles and high spatial resolutions resulted in better capabilities to acquire data over wide areas shortly after major landslide triggering events [ 25 – 28 ] and to monitor them at regular intervals [ 29 , 30 ]. In particular, radar interferometry is today frequently applied to landslide detection and monitoring of ground-deformations and landslide processes [ 31 – 38 ]. Multi-temporal Interferometry (MTI) techniques use large stacks composed of many Synthetic Aperture Radar (SAR) images (i.e., >20) acquired with the same geometry and exploit the redundant information of phase difference, thus removing much inherent noise (in particular reducing the atmospheric contribution called Atmospheric Phase Screen (APS)) for a better accuracy of the phase difference due to the ground displacement [ 39 ]. MTI techniques can be grouped in two main classes: Persistent Scatterers (PS) [ 39 ] or Small BAseline Subsets (SBAS) [ 40 ] to deliver displacements along the Line Of Sight (LOS) direction with accuracy in the order of a few millimeters per year [ 41 ]. Whilst building or infrastructure is taken as PS in urban areas [ 42 ], artificial Corner Reflectors (CRs) were installed to investigate areas characterized by low interferometric coherence or when a point wise analysis is foreseen [ 43 – 49 ]. Notti et al. [ 50 ] demonstrated the potential of X-band SAR data using TerraSAR-X for landslide mapping and monitoring but a few natural PS were found in mountainous areas. Barboux et al. [ 51 ] used the same band, combining PS-MTI and SBAS techniques for mapping slow movements in the Alps comparing these results to Real Time Kinematic GPS surveys. Barboux et al. [ 52 ] was also limited to precisely detect points moving with velocities below 3.5 cm/year in the LOS by PS-MTI technique.
for bare surfaces (HH and VV arrive in phase because are generated at the same point in the scene), and it would be equal to 1/3 is the scene were formed by an ideal random volume only. The temporal evolutions of this feature (black curves in Figure 4) show a narrow excursion for most crops, with all the values in the interval between 0.6 and 0.75. This can be interpreted as a balanced response from both soil and vegetation volume, which is expected for these data: the steep incidence angle (22.7 degrees) favours the soil contribution, whereas the acquisition frequency (Xband) provides a significant backscatter from the aboveground volume even from short crops. The crops with most noticeable changes in the correlation between channels are rice, at all dates, and wheat, sugar beet, and tomato at some specific dates. The radar response of rice at Xband, including its polarimetric features and its evolution along the growing season, has been described in previous studies, e.g., . Rice shows a very particular behaviour due to a unique characteristic of its cultivation: the soil is flooded (or saturated by water in the worst case) all along the growing season. Therefore, the response from the ground is dominated by the double-bounce scattering mechanism, and there is no influence of soil roughness or moisture.
boreal forest stem volume than has been reported in the studies mentioned before. However, when having only one or very few acquisitions, spatial variations in forest floor conditions - in terms of soil moisture, snow cover, litter depth - generally cause responses in backscatter in the range of or even larger than the intensity contrast between forest canopy and forest floor, strongly interfering the forest biophysical information (Rignot et al., 1994; Pulliainen et al., 1994, 1996, 1999; Wang et al., 1995; Hallikainen et al., 1998; Drezet & Quegan, 2006). A multitemporal consistency analysis, i.e. when correlating the standwise intensity measurements for different images, revealed a rather inconsistent behavior of ERS intensity measured over boreal forest with a mostly low correlation between standwise intensity measurements for even short repeat intervals (Askne et al., 2003). This observation stressed that effects like soil moisture variations have a large impact on C-band measurements over forest, interfering the forest biophysical information. In general, those environmental conditions can be considered the optimal acquisition conditions where soil moisture variations are minimized, for instance when the soils are frozen or very dry (Harrel et al., 1995, 1997; Pulliainen et al., 1996; Kurvonen et al., 1999). The advantage of multitemporal retrieval algorithms is that they are able to average out the variability in intensity related to the forest floor conditions.
the two classes will be included [ 13 ]. Further, Quegan et al. note a relationship between forest stand
age and backscatter: the attenuation of the soil contribution increases with growing age, resulting in a reduction of the overall backscatter. Following the initial decrease in backscatter for a growing forest, there is a slower increase leading up to the eventual saturation at the biomass limit. Because denser forest exposes less of the soil, the backscatter is less dependent on soil moisture and roughness and hence was found to exhibit less temporalvariability than sparser vegetation or bare soil. Other stable land cover includes grassland and urban areas, but these are stable at lower and higher backscatter values, respectively. As most non-forest areas exhibit greatly varying backscatter values over the year, they occasionally look similar to forest. For these reasons, the authors propose temporal backscatter stability as the most promising feature for forestmapping using C-band SAR data. Quegan et al. identified two types of land cover that would yield classification errors: non-forest areas of low backscatter variability (e.g., built-up areas or grassland), and forest areas of high backscatter variability. The classification accuracies for three test sites in the UK (11 images), Finland (15 images), and Poland (two images) were 90.7%, 94.1%, and 77.4%, respectively. The authors conclude that temporal backscatter stability is in fact the best predictor for forest cover derived from C-band SAR for forest of
irreversible damages of sensitive environments, such as permanent extinction of plants and animal habitats or accelerated soil erosion [ 1 ].
In this scenario, the up-to-date assessment and monitoring of the forest resource state is a task of crucial importance and, for this purpose, spaceborne remote sensing represents a unique solution for providing consistent, timely, and high-resolution data from the regional up to the global scale. In the last few decades, the majority of global forest classification products have been generated from optical remote sensing systems operating in the visible and near-infrared frequency range. Among these, it is worth highlighting the global forest tree cover map produced in 2013 from Landsat data at a spatial resolution of 30 m [ 2 ]. Given their day-light independence and their capability to penetrate through clouds, synthetic aperture radar sensors are now becoming operational systems for mapping forests coverage at a global scale. For example, global forest/non-forest classification maps have been provided by the L-band SAR sensor ALOS PALSAR at a posting of 25 m [ 3 ], and, more recently, by the TanDEM-X mission (Xband) at a resolution of 50 m [ 4 ].
stand is used together with the site index (yield class) and age, to estimate the height change as a function of age, cf. [ 15 , 16 ]. Balzter et al. [ 17 ] used SEASAT and JERS-1 L-bandradar backscatter and compared with the expected tree growth from general yield class models. However, reduced sensitivity of biomass to backscatter saturation is a severe limitation. The use of single-pass interferometric SAR, InSAR, has opened up the possibility to determine phase height. The latter is here defined as the height relative the DTM of a mean phase-scattering point within the forest canopy, and hence, related to the forest height and determined from the phase difference in the backscattered signals to the two satellites cf. [ 10 ]. Phase height is not expected to saturate with increasing biomass. Solberg et al. [ 18 , 19 ] used TanDEM-X together with C-band phase height from SRTM to determine height change and biomass change from 2000 to 2011. Recently, a paper concerning change detection of a tropical forest was published by Treuhaft et al. [ 20 ] based on 32 TanDEM-X scenes over a 3.2 year period. The strength of single-pass InSAR is the possibility to determine phase height accurately, due to the elimination of the temporal decorrelation associated with repeat pass InSAR [ 21 ].
The key objectives for the NeXtRAD December 2016 measurement campaign were to gather multiband (L and X) dual polarized (at X-band) sea clutter data recorded over a series of azimuth angles and ranges, with respect to the wind and wave direction. The system was deployed on the roof of the South African Institute for Maritime Technology (IMT) building in Simon‘s Town. From this site, there was a clear 180 ◦ of view over False Bay which enabled us to obtain data across a wide range of geometries. The scenario was a littoral environment and is not necessarily representative of an open sea, but this data will still be useful for the sea clutter research community.
 Asst. Leсt. Basim Khalaf Jarulla, Asst. Leсt. Izz Kadhum Abboud and Asst. Leсt. Wail Ibrahim Khali “Dual band miсrostrip antenna with slit load design for wireless loсal area network appliсation” Al-Qadisiya Journal For Engineering Sсienсes, Vol. 5, No. 4, 347-353, Year 2012.  P. N. Mishra “Planar Reсtangular Miсrostrip Antenna for
Abstract. This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a clima- tological dataset using a high spatial (120 m) and temporal (16 s) resolution X-bandradar. This makes it a study of the potential for high-resolution rainfall measurements with non- polarimetric X-bandradar over flat terrain. An appropriate radar reflectivity – rain rate relation is derived from mea- surements of raindrop size distributions and compared with radar – rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyz- ing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward atten- uation correction algorithms have been studied. Five indi- vidual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-bandradar and the effectiveness of the presented correction methods. X-bandradar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical opera- tional C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-bandradar is considered to be suitable for
Abstract. At short wavelengths, especially C-, X-, and K- band, weather radar signals are attenuated by the precipita- tion along their paths. This constitutes a major source of error for radar rainfall estimation, in particular for intense precipitation. A recently developed stochastic simulator of range profiles of raindrop size distributions (DSD) provides a controlled experiment framework to investigate the accuracy and robustness of attenuation correction algorithms. The work presented here focuses on the quantification of the in- fluence of uncertainties concerning radar calibration, the pa- rameterization of power law relations between the integral variables (radar reflectivity Z and specific attenuation k), and total path integrated attenuation (PIA) estimates at X-band. The analysis concerns single frequency, incoherent and non- polarimetric radar systems. Two attenuation correction algo- rithms, based on a forward and a backward implementation respectively, are studied. From DSD range profiles, the cor- responding profiles of integral radar variables are derived. Using a Monte Carlo approach, the accuracy and robustness of the two algorithms are quantified for the different sources of error previously mentioned. This framework of realistic DSD variability provides a robust way to confirm that, under realistic assumptions concerning the PIA estimation uncer- tainty, the forward algorithm outperforms the backward al- gorithm for PIA values below 10 dB.
One of the most critical aspects of the RF board design is the integration of the MMICs. Bare dies are used in order to reduce the integration area. It is worth noticing that the high number of input/output ports of the Ka-band chips does not allow the use of flip chip integration techniques as the density of the traces is not compliant with a standard PCB process. For this reason, it was necessary to employ a wire bonding technique. Furthermore, in order to reduce the length of the bonds (i.e. their parasitic inductance) laser cavities were carved into the upper layers of the stack-up (from L1 to L3) to accommodate the MMICs as shown in Fig. 3. Bondwires have a diameter of 25 µm and an average length of 0.65 mm. The simulated parasitic inductance is about 500pH. Considering the limited available space around the chips on layer L1 (see Fig. 5), the bondwire inductance has been compensated inside the chip in the input matching network for each LNA. The pad frame of the
Abstract. The aim of this work is to analyse the advantages and disadvantages of using the new X-band SAR data acquired by TerraSAR-X sensors for landslides mapping. This dataset has been processed using a Persistent Scatterer Interferometry technique over the Upper Tena Valley (Central Pyrenees, Spain). In the first section, the geological and geomorphological setting of the study area is introduced, focusing on the description of the landslide inventory. Then the Stable Point Network technique is briefly described, followed by the assessment of the performance of the X-band SAR dataset. In this context, we present first a model to predict the distribution of Persistent Scatterers based on the slope geometry and the land use information, which has then been validated with X-band data results. On a second stage, we have assessed the performance of X-band dataset to detect and monitor mapped landslides. Finally some illustrative case studies are shown demonstrating the potential of using X-band SAR data not only for landslide mapping but also to detect and monitor deformations affecting human infrastructures.
As already mentioned, there are a multitude of different possible parametrisations of the drop size distribution available, which determine the values of a and b in the ex- ponential rainfall-reflectivity relationship (Eq. 2.6). The wide range of available values describe differing precipitation processes, from tropical warm rain events which contain larger numbers of smaller drops (Fujiwara, 1967) to intense convective systems where the distribution has a much greater median diameter (Joss et al., 1970). Even within these classically defined precipitation types there is a great variation in the values presented with this variability all inherent within one possible radar scan which leads to uncertainty in the ’best’ value to use for a given observation (Atlas et al., 1999; Uijlenhoet et al., 2003). Figure 2.1 shows just a small subset of the available parametrisations and high- lights the possible variation in retrieved rainfall depending on the DSD parametrisation chosen, for example just using the four distributions shown a reflectivity measurement of 40 dBZ could equate to a rainfall intensity of between 8 and 20 mm hr −1 depending on the type of rainfall being observed. In order to deal with DSD variations, pre-classification of echoes is required to allow the application of an appropriate parametrisation, particu- larly in the USA where the radar network covers an extensive geographical area with wide variations in atmospheric conditions. For single polarisation radar this is achieved using the intensity of the reflectivity measurements, generally in combination with their three dimensional structure(Rosenfeld et al., 1995; Steiner et al., 1995; Anagnostou, 2004; Qi et al., 2013), with results showing improved rainfall estimation provided the classification can be achieved with a high level of accuracy.
The total number of events identified using the radar is significantly higher with respect to using the rain gauges, except for what concern mountains areas. It is more probable to identify an extreme event with the radar because it does not make a punctual measurement and usually extreme events have a small footprint. In fact, the rain gauges identify them only if they are localized and stationary over them. In the mountain area the effect of orography is very high for what concern the radar: all radar maps may present clutter echoes (the corresponding maps were rejected according to criteria described in paragraph 4.2) and the radar beam can be partially blocked. Moreover the mountain sub-area is more distant from the radar installations with respect to the other sub-areas and radar measurement cells are larger.
For this reason, in the framework of the FORALPS project, a small number of commercially available devices for the remote sensing of rainfall (newly developed by ENVISENS) have been installed and tested in some selected areas of the Alpine space. In particular a network of portable X-band RADARs has been set up in Alpine areas of the Aosta Valley, Piedmont, Carinthia and Friuli Venezia Giulia. One of the main characteristics of these RADARs is that of portability and low-cost. Another important feature is their vertical scanning strategy, which supplies essentially three beams of information: two horizontal, for direct ground rainfall measurement, and one vertical, for the estimate of the reflectivity profile aloft. The devices were tested in order to evaluate their possible use for the direct measurement of rain intensity, and for the provision of extra-information to already existing remote sensing devices, in order to improve their performances in orographically shielded areas.
The fact that birds have a wider spectrum of sensory capacities than humans (Kreithen, 1979; Beason and Semm, 1991) and are able to orient according to the static magnetic field of the earth (Wiltschko and Wiltschko, 1991, 1996) led to speculation about the potential disturbance of this orientation system by oscillating magnetic fields or by pulsed or continuous electromagnetic fields (Steiner and Bruderer, 1999). Short-term deviations of migratory birds in the neighbourhood of radar transmitters were often associated with the effects of these pulsed microwaves (Poor, 1946; Drost, 1949; Knorr, 1954; Hild, 1971). However, Busnel et al. (1956), trying to repeat Knorr’s (1954) observations, failed to find any reaction. Indoor experiments by Kramer (1951) showed no reactions of conditioned birds to the transmission of continuous waves at 520 MHz, while Kreithen and Davis (1995) were able to demonstrate physiological reactions of pigeons to pulsed signals of 1.25 and 2.45 GHz. Eastwood and Rider (1964) found no changes in the directions of migratory birds when aiming an additional strong radar beam at migrating birds observed using surveillance radar. In his comprehensive review of radar ornithology, Eastwood (1967) confirmed the view that radar has no recognizable influence on migrating birds. Wagner (1972), tracking released homing pigeons
Like all standard mobile Meteor 50/60DX radars, NX- Pol is transportable. The radar is constructed on a wheeled platform that is approved for towing on roads in the Eu- ropean Union by a 4 × 4 vehicle and can also be lifted by a crane. This trailer includes a generator to provide neces- sary power and the communications infrastructure to operate and monitor the radar remotely for up to 24 h. This mobil- ity makes NXPol a highly versatile tool for studying a di- verse array of atmospheric phenomenon across the globe. The main difference between NXPol and the standard mo- bile Meteor 50/60DX is that the NXPol has been fitted with a larger 2.4 m diameter antenna that produces a 0.98 ◦ half- power beam width. The NXPol is operated without a radome, which is beneficial for eliminating radome attenuation ef- fects, but extra care is required during transport, and long- distance shipping may need the antenna and external waveg- uides to be removed. The decision to fit NXPol with a larger antenna was made to support the ability to make higher reso- lution observations of convective clouds. In comparison, the standard mobile Meteor 50/60DX has a 1.8 m antenna that produces a 1.3 ◦ half-power beam width and is usually oper-