scholarly journals Airborne SAR Radiometric Calibration Based on Improved Sliding Window Integral Method

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 320
Author(s):  
Lu Li ◽  
Fengli Zhang ◽  
Yun Shao ◽  
Qiufang Wei ◽  
Qiqi Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Integral Method ◽  
Target Position ◽  
Sliding Window ◽  
Radiometric Calibration ◽  
Sar Images ◽  
Point Target ◽  
Airborne Sar ◽  
The Impact

To verify the performance of the high-resolution fully polarimetric synthetic aperture radar (SAR) sensor carried by the Xinzhou 60 remote-sensing aircraft, we used corner reflectors to calibrate the acquired data. The target mechanism in high-resolution SAR images is more complex than it is in low-resolution SAR images, the impact of the point target pointing error on the calibration results is more obvious, and the target echo signal of high-resolution images is more easily affected by speckle noise; thus, more accurate extraction of the point target position and the response energy is required. To solve this problem, this paper introduces image context information and proposes a method to precisely determine the integration region of the corner reflector using sliding windows based on the integral method. The validation indicates that the fully polarimetric SAR sensor on the Xinzhou 60 remote-sensing aircraft can accurately reflect the radiometric characteristics of the ground features and that the integral method can obtain more stable results than the peak method. The sliding window allows the position of the point target to be determined more accurately, and the response energy extracted from the image via the integral method is closer to the theoretical value, which means that the high-resolution SAR system can achieve a higher radiometric calibration accuracy. Additionally, cross-validation reveals that the airborne SAR images have similar quality levels to Sentinel-1A and Gaofen-3 images.

scholarly journals METHOD OF AIRBORNE SAR RADIATION CALIBRATION BASED ON POINT TARGET

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 123-128
Author(s):  
S. Yang ◽  
Z. Xu ◽  
C. Cheng
Keyword(s):  
High Precision ◽  
Integral Method ◽  
Calibration Method ◽  
Antenna Pattern ◽  
Sinc Function ◽  
Sar Images ◽  
Key Technology ◽  
Point Target ◽  
Calibration Accuracy ◽  
Airborne Sar

Abstract. Radiation calibration of airborne SAR images is the basis for realizing the quantitative processing of airborne SAR images. Radiation calibration based on point targets is a general and convenient method. However, high precision is still the goal of improving the current point target SAR radiation calibration. For the key technology of high-precision radiation calibration processing for airborne SAR images, this paper uses the integral method and the peak method to calculate the point target radiation response energy, By analysing the radiation characteristics of the SAR image and comparing the methods, the sinc function model is used to fit the corrected antenna pattern. Combined with the radar power equation to solve the calibration constant, the complete point target radiation calibration method and process are established, and the different methods in the key technology are compared and analysed. The results show that the calibration method combined with the energy calculation model of the integral method and the sinc function antenna pattern correction model can achieve higher relative and absolute calibration accuracy. The optimized method can meet and exceed the requirements for radiometric calibration accuracy for high-resolution airborne SAR applications.

scholarly journals A Novel Orthogonal Waveform Separation Scheme for Airborne MIMO-SAR Systems

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3580 ◽  
Author(s):  
Jie Wang ◽  
Ke-Hong Zhu ◽  
Li-Na Wang ◽  
Xing-Dong Liang ◽  
Long-Yong Chen
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Synthetic Aperture Radar ◽  
3D Imaging ◽  
Synthetic Aperture ◽  
Separation Scheme ◽  
Sar Images ◽  
Wide Swath ◽  
Aperture Radar

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

scholarly journals Efficient Patch-Wise Semantic Segmentation for Large-Scale Remote Sensing Images

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3232 ◽  
Author(s):  
Yan Liu ◽  
Qirui Ren ◽  
Jiahui Geng ◽  
Meng Ding ◽  
Jiangyun Li
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Large Scale ◽  
Semantic Segmentation ◽  
Remote Sensing Image ◽  
Training Data ◽  
Land Resources ◽  
Remote Sensing Images ◽  
Training Strategy ◽  
The Impact

Efficient and accurate semantic segmentation is the key technique for automatic remote sensing image analysis. While there have been many segmentation methods based on traditional hand-craft feature extractors, it is still challenging to process high-resolution and large-scale remote sensing images. In this work, a novel patch-wise semantic segmentation method with a new training strategy based on fully convolutional networks is presented to segment common land resources. First, to handle the high-resolution image, the images are split as local patches and then a patch-wise network is built. Second, training data is preprocessed in several ways to meet the specific characteristics of remote sensing images, i.e., color imbalance, object rotation variations and lens distortion. Third, a multi-scale training strategy is developed to solve the severe scale variation problem. In addition, the impact of conditional random field (CRF) is studied to improve the precision. The proposed method was evaluated on a dataset collected from a capital city in West China with the Gaofen-2 satellite. The dataset contains ten common land resources (Grassland, Road, etc.). The experimental results show that the proposed algorithm achieves 54.96% in terms of mean intersection over union (MIoU) and outperforms other state-of-the-art methods in remote sensing image segmentation.

scholarly journals Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France)

2017 ◽  
Vol 21 (11) ◽  
pp. 5693-5708 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Tiphaine Tallec ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

scholarly journals Road Extraction from High-Resolution SAR Images via Automatic Local Detecting and Human-Guided Global Tracking

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Jianghua Cheng ◽  
Wenxia Ding ◽  
Xishu Ku ◽  
Jixiang Sun
Keyword(s):  
High Resolution ◽  
Sar Images ◽  
The Road ◽  
Global Tracking ◽  
On The Road ◽  
Airborne Sar ◽  
Fitting In ◽  
Searching Method ◽  
Local Detection ◽  
Local Road

Because of existence of various kinds of disturbances, layover effects, and shadowing, it is difficult to extract road from high-resolution SAR images. A new road center-point searching method is proposed by two alternant steps: local detection and global tracking. In local detection step, double window model is set, which consists of the outer fixed square window and the inner rotary rectangular one. The outer window is used to obtain the local road direction by using orientation histogram, based on the fact that the surrounding objects always range along with roads. The inner window rotates its orientation in accordance with the result of local road direction calculation and searches the center points of a road segment. In global tracking step, particle filter of variable-step is used to deal with the problem of tracking frequently broken by shelters along the roadside and obstacles on the road. Finally, the center-points are linked by quadratic curve fitting. In 1 m high-resolution airborne SAR image experiment, the results show that this method is effective.

scholarly journals Boundary-layer remote-sensing observations and modeling of foehn in the Dead Sea valley

2021 ◽  
Author(s):  
Dorita Rostkier-Edelstein ◽  
Pavel Kunin ◽  
Pinhas Alpert
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
High Resolution ◽  
Dead Sea ◽  
Climate Projections ◽  
Modeling Tools ◽  
Model Simulations ◽  
Single Location ◽  
The Dead ◽  
The Impact

<p>The atmospheric dynamics in the Dead Sea (DS) Valley has been studied for decades. However, the studies relied mostly on surface observations and simple coarse-model simulations, insufficient to elucidate the complex flow in the area.  I will present a first study using high resolution (temporal and spatial) and sophisticate both, measurements and modeling tools. We focused on afternoon hours during summer time, when the Mediterranean Sea (MS) breeze penetrates into the DS Valley and sudden changes of wind, temperature and humidity occur in the valley.</p><p>An intense observations period , including ground-based remote sensing and in-situ observations, took place during August and November 2014. The measurements were conducted as part of the Virtual Institute DEad SEa Research Venue (DESERVE) project using the KITcube profiling instruments (wind lidars, radiometer and soundings) along with surface Energy Balance Station. These observations enabled analysis of the vertical profile of the atmosphere at one single location at the foothills of Masada, about 1 km west of the DS shore.</p><p>High resolution (1.1 km grid size) model simulations were conducted using the WRF model. The simulations enabled analysis of the 3D flow at the DS Valley, information not provided by the observations at a single location. Sensitivity tests were run to determine the best model configuration for this study.</p><p>Our study shows that foehn develops in the lee side of the Judean Mountains and DS Valley in the afternoon hours when the MS breeze reaches the area. The characteristics of the MS breeze penetration into the valley and of the foehn (e.g. their depth) and the impact they have on the boundary layer flow in the DS Valley (e.g. the changes in temperature, humidity and wind) are conditioned to the daily synoptic and mesosocale conditions. In the synoptic scale, the depth of the seasonal trough at sea level and the height of inversion layers play a significant role in determining the breeze and foehn characteristics. In the mesoscale, the intensity of the DS breeze and the humidity brought by it determines the outcomes at the time of MS breeze penetration and foehn development. Dynamically, the foehn is associated with a hydraulic jump.</p><p>Hypothetical model simulations with modified terrain and with warmer MS surface temperature were conducted to reveal the relative contribution of each of these factors and of their synergism on the observed phenomena. The information provided by the factor separation study can be useful in future climate projections, when a warmer MS is expected.</p><p>The forecasting feasibility of foehn and the sudden changes in the DS valley 24 hours in advance using WRF is suggested following the present study. These forecasts can be most valuable for the region affected by pollution penetration from the metropolitan coastal zone.</p>

scholarly journals ORIENTED VEHICLE DETECTION IN HIGH-RESOLUTION REMOTE SENSING IMAGES BASED ON FEATURE AMPLIFICATION AND CATEGORY BALANCE BY OVERSAMPLING DATA AUGMENTATION

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 153-159
Author(s):  
N. Mo ◽  
L. Yan
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Vehicle Detection ◽  
Training Dataset ◽  
Remote Sensing Images ◽  
Feature Maps ◽  
Fine Grained ◽  
Bounding Boxes ◽  
The Impact ◽  
Oriented Bounding Boxes

Abstract. Vehicles usually lack detailed information and are difficult to be trained on the high-resolution remote sensing images because of small size. In addition, vehicles contain multiple fine-grained categories that are slightly different, randomly located and oriented. Therefore, it is difficult to locate and identify these fine categories of vehicles. Considering the above problems in high-resolution remote sensing images, this paper proposes an oriented vehicle detection approach. First of all, we propose an oversampling and stitching method to augment the training dataset by increasing the frequency of objects with fewer training samples in order to balance the number of objects in each fine-grained vehicle category. Then considering the effect of the pooling operations on representing small objects, we propose to improve the resolution of feature maps so that detailed information hidden in feature maps can be enriched and they can better distinguish the fine-grained vehicle categories. Finally, we design a joint training loss function for horizontal and oriented bounding boxes with center loss, to decrease the impact of small between-class diversity on vehicle detection. Experimental verification is performed on the VEDAI dataset consisting of 9 fine-grained vehicle categories so as to evaluate the proposed framework. The experimental results show that the proposed framework performs better than most of competitive approaches in terms of a mean average precision of 60.7% and 60.4% in detecting horizontal and oriented bounding boxes respectively.

scholarly journals Effects of multi-temporal high-resolution remote sensing products on simulated hydrometeorological variables in a cultivated area (southwestern France)

2017 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Aurore Brut ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Annual Precipitation ◽  
Surface Model ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes often include a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes as simulated by land surface and distributed hydrological models. Sentinel-2 mission satellite remote sensing products allow for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy flux via the ISBA-SURFEX land surface model. The study area is a 24 km by 24 km agricultural zone in southwestern France. An initial reference simulation was conducted from 2006–2010 using the ECOCLIMAP-II database. This global numerical land ecosystem database was created at a 1 km resolution and includes an ecosystem classification with a consistent set of land surface parameters required for the model, such as the Leaf Area Index (LAI) and albedo measures. The LAI of ECOCLIMAP is climatologic and derived from a 2000–2005 analysis of MODIS satellite products. This low resolution induces that several vegetation covers can be mixed in a model cell. The climatic construction of LAI dynamics also suggests that there is no interannual variability in the vegetation cycle. A second simulation was performed by forcing the same model with annual land cover maps and monthly LAI values derived from a series of 105 8 m-resolution Formosat-2 images for the same period. Both simulations were conducted at the parcel scale, i.e., a computation unit covers an area of connected pixels of the same vegetation type (a crop field, forest patch, etc.). To evaluate our simulations, we used in situ measurements of evapotranspiration and latent and sensible heat flux from two eddy covariance stations in the study area. Our results show that the use of Formosat-2 high-resolution products significantly improves simulated evapotranspiration results with respect to ECOCLIMAP-II, especially when a surface is covered with summer crops (the correlation coefficient with monthly measurements is increased by roughly 0.3 and the root mean square error is decreased by roughly 31 %). This finding is attributable to a better description of LAI evolution processes reflected by Formosat-2 data, which further modify soil water content and drainage levels of deep soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels from Formosat-2 data in comparison to reference values. In smaller proportions, runoff is also increased by roughly 1 % of annual precipitation when using Formosat-2 data. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

Sign in / Sign up

Export Citation Format

Share Document