yasser maghsoudi

Monitoring the earth and its biosphere is an essential task in any scale to achieve a sustainable development. Therefore, forests, as an invaluable natural resource, have an important role to control the climate changes and the carbon cycle. For this reason, biomass and consequently forest height have been known as the key information for monitoring the forest and its underlying surface. Several studies, it has been shown that Synthetic Aperture RADAR (SAR) imaging systems can greatly help to this purpose. In this framework, a novel technique called Polarimetric SAR Interferometry (PolInSAR) is an appropriate and an available tool for forest height estimation, due to its sensitivity to location and vertical distribution of the forest structural components. Based on this, from a view point, the methods employed in this field can be divided into two categories: a) based on Random Volume over Ground (RVoG) inversion model, and b) based on model-based decomposition techniques of PolInSAR data. In this study, in order to improve the forest height estimation, a novel method based on the combination of two mentioned categories has been proposed. The performance and the efficiency of the proposed method were demonstrated by two datasets simulated from the PolSARProSim software in L and P bands. So that, in L band, it obtained 0.69 m, 1.84 m and 3.38 m improvements for height estimation in Digital Elevation Model (DEM) differencing, coherence amplitude and combined (phase and coherence) methods, respectively. As well, in P band, in it obtained 1.53 m and 2.74 m improvements especially in DEM differencing and coherence amplitude methods, respectively.

 Estimation of forest Carbon stocks plays an important role in assessing the quantity of carbon exchange between the forest ecosystem and the atmosphere. Direct methods of measuring carbon stock are not economically efficient. Optical remote sensing methodsalso have limited capability in predicting forest biomass, because the spectral response of optical images is related to the interaction between solar radiation and canopy, especially in mature forests. These obstacles limit the efficiency of optical sensors for forest biomass estimation. Recently, airborne data has received a great deal of scientific and operational attention for estimation of forest features. LiDAR data also faces challengessuch as limited efficiency in large areas, high costs and large data volumes. In contrast to the optical and LiDAR systems, SAR systems have some advantages, such as the possibility of data collection in any weather condition, penetration through clouds and canopy, and easy access. The potential of SAR images with quad polarization for the estimation of Iranian Hyrcanian forests biomass will be investigated. The main purpose of this study was to investigate the efficiency of ALOS-2 /PALSAR-2 backscattering coefficients andpolarimetric features in leaf-on and Leaf-off crown conditions, evaluate the linear regression model and select the most appropriate variables for biomass estimation.  

The study area is located in a part of forests of Mazandaran province. The region forms a part of the deciduous broadleaf temperate plain forests. The forestsunder study was classified into 4 major types: (1) Forest reserve, (2) Natural forest, (3) Degraded forest and (4) Mixed species forest plantations. 115 circular sample plots (each including 0.1 hectares)were collected from the 4 different sites with various forest structures and biomasses. In each sample, tree species and diameter at breast height (DBH) of all trees with DBH > 7.5 cm were recorded. Allometric equations were used to convert tree diameter to biomass. The present study is based on polarimetric L-band PALSAR-2 data collected in spring and winter. Backscattering matrix was generated using the PALSAR data which consists of amplitude and phase information. Speckle noise filtering was performed using the Refined Lee adaptive filter. Following the filtering, all polarimetric features were extracted. After converting the SAR products to NRCS, geometric correction and georeferencingwere performed and the average backscattering coefficient (sigma naught value)was extracted for each sample plot by overlaying the AOI layers on corresponding SAR images. Finally, the relationship between forest biomass and backscattering intensity was investigated. 

The resultsvary regarding to the forest type, the range of biomass and forest canopy cover percentage.Forest type and biomass range as well as canopy cover percentage affect the scattering mechanism and correlations between biomass and SAR backscattering coefficient. Canopy cover percentageofthe 1stand 4thsites were over 90% and consequently, the sensitivity of HV backscatter value to biomass was higher than HH and VV. In the 2nd and especially 3rd sites, the correlation between HH backscattervalueand AGB was better than its correlation with HV backscatter. This is mainly because of the canopy structure in these sites which is not complete and the fact that the sensitivity of HH backscatter value to biomass is higher than HV. Results indicate in the 1st and 4th sites, the correlation between volume scatter component of decomposition methods with AGB was better than its correlation with double-bounce scatter component. In contrast, the double-bounce decomposition componentsexhibited the best results in the 2nd and 3rd sites. These findings are in agreement with the results obtained from the T3 matrix components. The least correlation value was observed between Freeman decomposition components and AGB. The volume scatter component of Cloude and also double-bounce component of Freeman did not provide suitable results. Results also indicate higher efficiency of images collected in spring as compared to those collected in winter.Linear regression results show that in the best possible situation, RMSE of the first forest habitat was 34.68 t/ha, and 30.09, 27.07 and 23.69 t/ha were estimated for the 2nd, 3rd, and 4th forest habitats, respectively. Therefore, it seems that classification of forests is necessary before biomass estimation.  

The potential of PALSAR-2 data for Hyrcanian forest biomass estimation was assessed in this study. We demonstrated that L-band data are sensitive to the above-ground biomass (AGB) of Hyrcanianforestsand can be used to provide accurate estimates of biomass. Findings confirmed that decomposition methods are more efficient than backscattering coefficients for biomass mapping.

The spectral Direct Normal Irradiance (SDNI) is a basic radiometric quantity from which many other quantities can be derived. It provides not only information about the spectral and distribution of the direct solar radiation reaching a particular location. Accurate knowledge about the spectral direct irradiance shall enable us to gain new scientific results in the: determination of cloud effects, calculation of power yield of solar cells for electricity providers, derivation of aerosol distributions and their impact on the radiation field, determining the UV spectral irradiance for medical applications and in the improvement of our understanding of the radiative transfer in a changing climate. Nevertheless, at present, DNI measurements are not available in many instances. Therefore, the main objectives of this project are the setup, characterization, the calibration, the validation and the application of an operational measurement for the (SDNI) at the Institute of Meteorology and Climatology (IMUK) at the Leibniz University Hannover. With sampling times of less than one second even rapid changes of the SDNI can be recorded with a spectral resolution of about 1 nm in the wavelength range from 300 -800 nm (from UV to NIR). For this purpose three different tracking units were used to precisely track the sun location in the sky and finally based on the measurements and tracking strategy best instrument was selected. Finally the best tracking unit was used and the set-up was tested in the institute of Meteorology and climathology of Hannover (Longitude 52.37◦, Latitude 9.73◦). The comparison between the integrated value of the measurements and Pyranometer observations on the same platform, and during a complete day presented in this paper. It is worth to mention that the technique for setting up such a measurement station is very important as a basis for remote sensing research focused on the solar energy and meteorology applications.

A number of regions around the world have suffered severe subsidence due to groundwater withdrawal. Mashhad as one of the largest municipalities in Iran has suffered subsidence due to deep groundwater overextraction. Land subsidence in this area can be destructive for urban infrastructures and can create serious environmental issues and structural damages. So, the aim of this research is to precisely determine the uninterrupted vertical subsidence in Mashhad by Permanent Scatterer InSAR technique and also to assess the previous reports on the study area. We complement previous works using more accurate data and procedure in an urban area. Furthermore, we considered geotechnical properties which was not focused in the previous studies. For this purpose, 69 descending and ascending C-band radar images, provided by relatively high-resolution Sentinel-1A satellite, were used to estimate the deformation-trend of the interest area. The method was applied to the images spanning October, 2014, and February, 2017 investigating land subsidence. The assessment procedure demonstrated a high-rate of subsidence in northwest of Mashhad with the significant deformation of 140 mm/year. The outputs were validated using in-situ measurements data and hydraulic head variations respecting piezometric data from groundwater wells. Subsequently, the geotechnical properties of the chosen area were considered to interpret the results. It was illustrated that the land subsidence in the case study is brutally continuous and there is no decrease on the deformation rate.

Monitoring and assessment of the biosphere are two essential tasks at any scale. Based on this, forests play an important role in controlling the climate and the global carbon cycle. For this reason, biomass and consequently forest height are known as the key information for forest monitoring. In the recent decade, several studies have shown that the Synthetic Aperture RADAR (SAR) imaging systems in Compact Polarimetry (CP) mode can overcome the disadvantages of Full Polarimetric (FP) SAR imaging systems and provide a good performance in various remote sensing applications such as monitoring and managing the important natural resources like forests. In this regard, a novel technique named Polarimetric Interferometry SAR (PolInSAR) has been further considered as a powerful tool for forest height estimation. 

In this research, the performance of the Compact PolInSAR (C-PolInSAR) data in Dual Circular Polarization (DCP) mode has been investigated in order to retrieve the forest height. For this reason, the common methods which are used for forest height estimation including Digital Elevation Model (DEM) differential method, coherence amplitude inversion, and phase & coherence inversion methods were applied and implemented on these data. In all of the aforementioned methods, LL+RR and LR polarizations were considered as the selected channels for estimating the volumetric and ground coherences, respectively. Then, the estimated coherences were considered as the input parameters for all of the mentioned methods. 

To evaluate the performance and the efficiency of C-PolInSAR data in DCP mode, the results obtained from these data were compared with those obtained from Full PolInSAR (F-PolInSAR) data. The results obtained in this study in two datasets simulated from PolSARProSim software in both L and P bands showed that the C-PolInSAR data in DCP mode yielded a similar result compared to the F-PolInSAR data for forest height estimation (when the HH+VV polarization is adopted as the ground backscattering), because, in this case the LL+RR and the LR polarizations are equal to the HV and the HH+VV polarizations, respectively, particularly, the C-PolInSAR data in DCP mode yielded 0.78 m and 0.55 m improvements for forest height estimation in L and P bands, respectively. In addition, all of the employed methods provided better and closer results compared to the real forest height (i.e. 18 m) in L band compared to P band, because the electromagnetic (EM) waves have a more penetration into the canopy in L band compared to P band. Thus, the attenuation of these waves is low and consequently the height estimation is more accurate. Without considering the used bands, the DEM method provided the lowest precision compared to other methods, because the HV (or LL+RR) phase center can lie anywhere between half the tree height and top of the canopy. The exact location of this phase depends on two vegetation parameters which are the wave mean attenuation and the vertical canopy structure variations. In this case, the trees have very thin canopies, and consequently, the attenuation is small, but the phase center is high due to the structure. In other words, when the canopy extends over the entire forest height, then the phase center can be at half the true height for low density (low attenuation), through to the top of the canopy for dense vegetation (high attenuation). This ambiguity is inherent in single baseline methods, and in order to overcome this, model-based correction methods need to be employed. It was also observed that the coherence amplitude method is among the weak algorithms due to ignoring the phase and its sensitivity to the attenuation and structural variations but it can be used as a backup solution when other approaches fail. Finally, the phase and the coherence inversion method had better results than two aforementioned methods for the forest height estimation. In this method, selecting the factor ‘’ is very important and it should be selected in a way to be strong towards the attenuation changes. In this study,  0.4 was adopted to maintain the height error variations.

As the final result, the C-PolInSAR data can be an efficient strategy due to its performance, when the full polarimetric imaging systems are either limited or not available. Moreover, utilizing these data in long wavelengths (e.g. P band) is more appropriate due to the effect of the Faraday rotation on the transmitted polarization.

Persistent Scatterer Interferometry (PSI) is a technique for detection and analysis of a network of coherent pixels referred to as the Permanent/Persistent scatterer (PS) which have high phase strength over long time periods. This technique has been widely used by the scientific community to measure the displacement related to thesubsidence/uplift, landslide, tectonic, and volcanoes. As the density and quality of PS pixels are important factors in PSI algorithms, the concept of polarimetric optimization in the PSI algorithms was proposed to improve the number of PS pixels. The recent launch of radar sensors operating with a polarimetric configuration can help improvingthePS-InSAR analysisby increasing the PS density. Therefore, the combination of thepolarimetric and interferometric techniques helpsimprove the PSI techniques, especially in non-urban areas which suffer from lack of the PS density. In this study, we investigated how the contribution of the S1A and TSX data in the PSI analysis could lead to the improvement of the results of the PSInSAR algorithm. Indeed, the main objective of this paper is to illustrate the capability of each dataset for improving the polarimetric optimization results.
 

2.1  The proposed method was tested using a dataset of 40 dual-pol SAR data (VV/VH) acquired by Sentinel1-A between February 2017 and May 2018 and 20 dual-pol SAR data (HH/VV) acquired by TerraSAR-X betweenJuly 2013 and April 2014.
 
 2.2 Polarimetric SAR Interferometry
 
The general principle of polarimetric SAR interferometry was proposed by (Cloude & Papathanassiou, 1997) for the first time. The scattering matrix S represents the polarimetric information associated with each pixel of the image.  Considering the monostatic configuration, the scattering matrix S is defined as follows:
(1)
Where and are co-polar channels, is the cross polar channel. This matrix can be represented with the target scattering vector  as:
(2)
Where, is the transposed operator. The Pauli vector for the dual-pol data (HH/VV) of the TerraSAR-X sensor, is written as :
(3)
Similarly,the Pauli vectorfor the dual-pol data (VV/VH) of theSentinel1-A sensorcan be expressed as:
(4)
In order to generate scattering coefficient μ, projecting the scatteringvector  on the projection vectorwould be sufficient:
(5)
Where is thelinear combination of the elements of matrix S, i is the correspondent of the 2 images, and * represents the conjugate operator. The projection vectorfor the dual-pol data isdefined as:
(6)
Where, and are two real parameters whose ranges are finite and known and are related to the geometrical and electromagnetic properties of the targets. In our research, the main purpose of the polarimetric optimization is to find theoptimum projection vector, in a 2-dimensional search space,  and
 
2.3 Amplitude Dispersion Index Optimization
 
Substituting (5) into (7), the ADIfor the polarimetric case () can be expressed as follows: 
(7)
(8)
According to (6), the polarimetric optimization problem isreduced to finding a suitable  and  in a finite and known range,so that (8) is minimized.

The results showed that the proposed method improved the performance of the PSInSAR algorithm in two terms of phase quality and density of  the PS pixels. Compared with the VV channel, , the number of PSC and PS pixels increased about 2 and 1.7 times In S1A data, using the ESPO method while, compared with the normal channels like HH and VV, the number of PSC and PS pixels in ESPO method increased about 3.5 and 3 times in TSX data.Based on  these results, the optimization methods are more effective in improving the quality of the PSC densitythan in increasing the number of PS pixels. This is mainly because the employed optimization is based on minimizing ADI criterion which is used in the PSC selection. Moreover, ESPO method has been more successful for TSX data compared to the S1A data. This result is due to the higher capability of the TSX data in creating more diverse scattering mechanisms and hence identifying more optimum scattering mechanism compared to S1A data. We also investigated the effect of polarimetric optimization in increasing the PS density in urban and non-urban areas. The experimental results showed that the method succeeded to significantly increase the final set of PS pixels in both urban and nonurban areas.
    

The results show that the optimization methods have been more successful in the improvement of PS density for  the TSX data compared to the S1A data. This result is due to the higher capability of the TSX data in creating more diverse scattering mechanisms compared to the S1A data. In summary, thanks to the polarimetric data, it is possible to exploit a larger number of pixels compared with the single polarization case.

During the past decades, Tehran has suffered from subsidence crisis. Prolonged droughts and excessive exploitation of groundwater for agricultural and industrial purposes have reduced the level of aquifers and reduced the density of the subsurface soil layers. This study focuses on monitoring the displacement of the ground in west of Tehran which is affected by subsidence of Shahriyar and Tehran plains. A time series of 30 Sentinel-1 images were processed by radar interferometry technic based on the persistent scatterers in two years. Average annual displacement map was prepared for the region of study. The result of study indicates 15 centimeters of displacement in southern part of the study area where it ends to Shahriyar and Tehran plains. However, displacement is not limited to plain and non-urban areas. It has also scattered through industrial and urban areas. In industrial and residential areas, cumulative displacement of 9 to 13 centimeter was recorded in two years especially in Fath Highway which experiences more than 4 centimeters of displacement each year. Relative evaluation of results was made based on the data gathered from underpass 35. Considering the small difference in the estimates obtained from orbits 28 and 35, these areas had little Horizontal displacement. Displacement vector was high in vertical movement. Vertical displacement was computed for ascending and descending orbits in the second study region and verified by data from a GPS station.

With 6.8 percent oil reservoirs, Zagros is one of the most prolific oil sedimentary basins. The greater part of its hydrocarbon reservoirs are concentrated in anticlinal traps, which they are also the subsets of the structural traps. In addition to rich and vast hydrocarbon reservoirs, Zagros have been also considered well in terms of it's the Neotectonic activities. Studies of Neotectonic activities as an important factor in the control of landforms in tectonic regions, Apart from its social and economic interest, studies of active tectonics follow a multi disciplinary approach, integrating data from structural geology, geomorphology, stratigraphy, geochronology, seismology, and geodesy.The unrelenting competition between tectonic processes that tend to build topography and surface processes that tend to tear them down represents the core of tectonic geomorphology.Since so Most effective morphometric indices have been related to erosional and depositional processes associated with fluvial systems.Rivers are highly sensitive to subtle landscape fluctuations induced by tectonic activity and can assist in differentiating active segments of geologic structures. Because Drainage basins represent dynamic systems that may retain records of formation and progression since most tectono-geomorphic processes occur within its confines. Therefore, Morphometric analyses of river networks, drainage basins and relief using geomorphic indices, as well as geostatistical analyses of topographical data, have become useful tools for investigating landform evolution. In recent studies related to morphotectonics, a mixture of geomorphologic and morphometric analyses of landforms and topographic analyses are utilized to obtain active tectonics and they have been tested in different tectonically active areas and provide insight about particular areas that are subject to active tectonic deformation.Therefore, since so many of geomorphologic effects are highly susceptible to tectonic movements and their changes are happening at the same time, we should be looking for forms and shapes that have retained these changes over the years. With regard to the abovementioned matter and using geomorphologic indices, the current study attempts to consider Neotectonic activities and its impact on the positioning of the oil fields in the Jarahi and Zohre sub-basins.
In order to achieve the goals of this research, documentary information,1:50000-1:25000 topographic maps and 1:100000-1:250000 geological map, a digital elevation model (DEM) related to SRTM topographic data and landsat 8 satellite images have been the important research tools. For the analysis of Neotectonic activities in the case study area, have been used such geomorphologic indices as Stream Length-Gradient index, River Sinuosity, Relief Amplitude, Hypsometric Integral, Basin Shape Factor and Drainage Basin Asymmetry Factor Index.Arc GIS software was used to digitize the topographic maps and drawing of river networks for calculating these indices.
Results of the calculation of geomorphologic indices: The SL values in the study area range from 0 to 573, The S values in the study area range from `1.1 to 2.46, The RA values in the study area range from 31 to 3254, The HI values in the study area range from 0.04 to 0.56, TheB_Svalues in the study area range from 0.19 to 2.49 and The |AF–50| values in the study area range from -28.83 to 32.59. The classification used in this paper for each geomorphic index is calculated from El Hamdouni's method.According to Relative Tectonic Activity (lat) index, three class high active(1.6 ≤ LAT The obtained quantitative values from the results of the geomorphic indices in the 38 sub – basin led to divide the studied basin into three tectonic areas with low, medium, and high tectonic activity. It was also shown that the Neotectonic activity level in different parts of the basin is not the same and the forces act with greater intensity in the eastern half. This activity caused to more oil fields of Jarahi – Zohre basin, i.e. 61.6 percent located in the region with the lowest Neotectonic activity. In fact, being in the lowest Neotectonic Class acted as the factor to emerge the oil traps and to maintain the hydrocarbons. On the other hand, in the areas with the highest Class of Neotectonic, there was virtually no oil field. The results indicated that Neotectonic has important role in the running or migration of oil traps and the extent of tectonic is necessary to create small fractures to oil running and finally oil production. In fact, it can be attributed to Neotectonic both destructive and inhibiting role in addition to constructive and transferring hydrocarbons.