ALOS PALSAR双极化数据水稻制图

以江苏省海安县为研究区,使用2008年获取的日本ALOS卫星PALSAR双极化模式数据,分析水稻在L波段SAR图像上的后向散射特征,并提出相应的水稻制图方法。水稻在L波段上表现出了和C波段相同的时相变化特征。HH极化后向散射依赖于水稻植株的空间分布结构,某些机械插秧区域的布拉格共振现象引起水稻后向散射严重增强,给利用PALSAR数据水稻制图带来了困难。而HV极化不存在布拉格共振现象。在考虑布拉格共振影响的条件下,提出了联合PALSAR双极化模式HH和HV极化数据、基于时相变化特征进行水稻制图的方法,获得了88.4%的制图精度。     

Surface roughness signatures of summer arctic snow-covered sea ice in X-band dual-polarimetric SAR

ABSTRACT

Surface roughness of sea ice is primary information for understanding sea ice dynamics and air–ice–ocean interactions. Synthetic aperture radar (SAR) is a powerful tool for investigating sea ice surface roughness owing to the high sensitivity of its signal to surface structures. In this study, we explored the surface roughness signatures of the summer Arctic snow-covered first-year sea ice in X-band dual-polarimetric SAR in terms of the root mean square (RMS) height. Two ice campaigns were conducted for the first-year sea ice with dry snow cover in the marginal ice zone of the Chukchi Sea in August 2017 and August 2018, from which high-resolution (4 cm) digital surface models (DSMs) of the sea ice were derived with the help of a terrestrial laser scanner to obtain the in situ RMS height. X-band dual-polarimetric (HH and VV) SAR data (3 m spatial resolution) were obtained for the 2017 campaign, at a high incidence angle (49.5°) of TerraSAR-X, and for the 2018 campaign, at a mid-incidence angle (36.1°) of TanDEM-X 1–2 days after the acquisition of the DSMs. The sea ice drifted during the time between the SAR and DSM acquisitions. As it is difficult to directly co-register the DSM to SAR owing to the difference in spatial resolution, the two datasets were geometrically matched using unmanned aerial vehicle (4 cm resolution) and helicopter-borne (30 cm resolution) photographs acquired as part of the ice campaigns. A total of five dual-polarimetric SAR features―backscattering coefficients at HH and VV polarizations, co-polarization ratio, co-polarization phase difference, and co-polarization correlation coefficient ―were computed from the dual-polarimetric SAR data and compared to the RMS height of the sea ice, which showed macroscale surface roughness. All the SAR features obtained at the high incidence angle were statistically weakly correlated with the RMS height of the sea ice, possibly influenced by the low backscattering close to the noise level that is attributed to the high incidence angle. The SAR features at the mid-incidence angle showed a statistically significant correlation with the RMS height of the sea ice, with Spearman’s correlation coefficient being higher than 0.7, except for the co-polarization ratio. Among the intensity-based and polarimetry-based SAR features, HH-polarized backscattering and co-polarization phase difference were analyzed to be the most sensitive to the macroscale RMS height of the sea ice. Our results show that the X-band dual-polarimetric SAR at mid-incidence angle exhibits potential for estimation of the macroscale surface roughness of the first-year sea ice with dry snow cover in summer.     

Concurrent use of active and passive microwave remote sensing data for monitoring of rice crop

Estimation of crop area, growth and phenological information is very important for monitoring of agricultural crops. However, judicious combination of spatial and temporal data from different spectral regions is necessary to meet the requirement. This study highlights the use of active microwave QuikSCAT Ku-band scatterometer and Special Sensor Microwave/Imager (SSM/I) passive microwave radiometer data to derive information on important phenological phases of rice crop. The wetness index, a weekly composite product derived using brightness temperatures from 19, 37 and 85 GHz channels of SSM/I, was used to identify the puddling period. Ku-band scatterometer data provided the signal of transplanted rice seedlings since they acts as scatterers and increases the backscattering. Dual peak nature of temporal backscatter curve around the heading stage of rice crop was observed in Ku-band. The decrease of backscatter after first peak was associated with the threshold value of 60% crop canopy cover. The symmetric (Gaussian) and asymmetric (lognormal) curve fits were attempted to derive the date of initiation of the heading phase. The temporal signature from each of these sensors was found to complement each other in crop growth monitoring. Image showing pixel-wise timings of heading stage revealed the differences exists in various parts of the study area.     

Exploitation of TerraSAR-X Data for Land use/Land Cover Analysis Using Object-Oriented Classification Approach in the African Sahel Area, Sudan

Recently, object-oriented classification techniques based on image segmentation approaches are being studied using high-resolution satellite images to extract various thematic information. In this study different types of land use/land cover (LULC) types were analysed by employing object-oriented classification approach to dual TerraSAR-X images (HH and HV polarisation) at African Sahel. For that purpose, multi-resolution segmentation (MRS) of the Definiens software was used for creating the image objects. Using the feature space optimisation (FSO) tool the attributes of the TerraSAR-X image were optimised in order to obtain the best separability among classes for the LULC mapping. The backscattering coefficients (BSC) for some classes were observed to be different for HH and HV polarisations. The best separation distance of the tested spectral, shape and textural features showed different variations among the discriminated LULC classes. An overall accuracy of 84 % with a kappa value 0.82 was resulted from the classification scheme, while accuracy differences among the classes were kept minimal. Finally, the results highlighted the importance of a combine use of TerraSAR-X data and object-oriented classification approaches as a useful source of information and technique for LULC analysis in the African Sahel drylands.     

Discrimination between Babul plantations and Mustard crop using Polarimetric C- and L- band data

Radar sensors can be used for large-scale vegetation mapping and monitoring using backscattering coefficients in different polarizations and wavelength bands. C-band space borne SAR is widely used for the classification of agricultural crops, but can only perform a limited discrimination of various tree species. This paper presents the results of discrimination between mustard crop and babul plantation (Prosopis sp.) using quad polarisation Radarsat 2 and ALOS PALSAR data. Study area is comprised of dense babul plantation along the canal, mustard crop on one side of the canal and Fallow land near to Ramgarh village of Jaisalmer district. Three bands of Radarsat (HH, HV and VV) acquired during peak mustard crop growth stage were integrated with four polarizations (HH, HV, VH and VV) of ALOS PALSAR acquired when crop cover was absent. Using only Radarsat data Jefferies-Matusita (JM) separability between mustard crop and babul plantation was found to be poor (710). Where as in the seven band combination the separability was observed to be high (1374). Among the different polarizations three layer combination, highest separability was observed using cross polarizations (HV and VH) of L-band with any one of the Radarsat Polarisation (HH/HV/VV). This combination of C- and L-band resulted in easy separation of mustard and babul plantation which was otherwise difficult using only Radarsat data.     

Using cosmo-skymed images to detect wet snow cover on the Kraków Ice Field,King George Island,Antarctica

This work analysed the spatio-temporal variation of snow cover on the Kraków Ice Field, located in the King George Island, Antarctica. High spatial resolution images of COSMO-SkyMed were used in this study. These X-band images are vertically and horizontally co-polarized and their intensity data were converted to amplitude (dB). The COSMO-SkyMed images were classified by a minimum distance algorithm and post-classified based on knowledge of adjacency relationships of snow zones. Hypsometric, slope, aspect and solar radiation maps to support the interpretation of backscatter patterns in the COSMO-SkyMed images. Three radar zones were classified in these images: percolation, slush and wet snow radar zone. Positive surface air temperatures and rainfall events, registered from a meteorological station, lead to increase in wet snow and slush zones. The COSMO-SkyMed images and minimum distance algorithm were adequate to discriminate the snow cover and to assess the supraglacial melting pattern during the ablation season in the study area.     

Assessing Performance of Tomo-SAR and Backscattering Coefficient for Hemi-Boreal Forest Aboveground Biomass Estimation

Tomo-SAR technique has been used for hemi-boreal forest height and further forest biomass estimation through allometric equation. Backscattering coefficient especially in longer wavelength (L- or P-band) is thought as a useful parameter for hemi-boreal forest biomass retrieval. The aim of this paper is to assess the performance of vertical backscattering power and backscattering coefficient for hemi-boreal forest aboveground biomass (AGB) estimation with airborne P-band data. The test site locates in southern Sweden called Remningstorp test site, and the in-situ forest AGB ranges from 14 t/ha to 245 t/ha at stand level. Multi-baseline P-band Pol-InSAR data in repeat-path mode collected during March and May in 2007 at Remningstorp test site was used. We found that the correlation coefficient (R) between backscattering coefficient of P-band HH polarization and the in-situ forest biomass reached 0.87. The R for P-band VV backscattering power at 5 m is 0.71 and 10 m is 0.72. Backscattering coefficient in HH polarization and vertical backscattering power at 5 m and 10 m were applied to construct a model for hemi-boreal forest AGB estimation by backward step-wise regression and cross-validation approach. The results showed that the estimated forest AGB ranges from 19 to 240 t/ha, and the constructed model obtained a higher R and smaller RMSE, the value of R is 0.91, RMSE is 30.43 t/ha at Remningstorp test site.     

Evaluation of polarimetric capabilities of dual polarized Sentinel-1 and TerraSAR-X data to improve the PSInSAR algorithm using amplitude dispersion index optimization

Polarimetric data is an additional source of information in PSI technique to improve its performance in land subsidence estimation. The combination of polarimetric data and radar interferometry can lead to an increase in coherence and the number of PS pixels. In this paper, we evaluated and compared the dual polarized Sentinel-1A (S1A) and TerraSAR-X (TSX) data to improve the PSInSAR algorithm. The improvement of this research is based on minimizing Amplitude Dispersion Index (ADI) by finding the optimum scattering mechanism to increase the number of PSC and PS pixels. The proposed method was tested using a dataset of 40 dual-pol SAR data (VV/VH) acquired by S1A and 20 dual-pol SAR data (HH/VV) acquired by TSX. The results revealed that using the TSX data, the number of PS pixels increased about 3 times in ESPO method than using the conventional channels, e.g., HH, and VV. This increase in S1A data was about 1.7 times in ESPO method. In addition, we investigated the efficiency of the three polarimetric optimization methods i.e. ESPO, BGSM, and Best for the dual polarized S1A and TSX data. Results showed that the PS density increased about 1.9 times in BGSM and about 1.5 times in Best method in TSX data. However, in S1A data, PS density increased about 1.1 times in BGSM. The Best method was not successful in increasing the PS density using the S1A data. Also, the effectiveness of the method was evaluated in urban and non-urban regions. The experimental results showed that the method was successful in significantly increasing the number of final PS pixels in both regions.     

Envisat ASAR数据在沿海防护林提取中的应用

沿海防护林的建设与生态环境和经济发展密切相关。本文以福建省漳浦县沿海防护林地区为例,利用2005年多时相、多极化的ENVISATASAR(Environmental Satellite Advanced Synthetic Aperture Radar)数据,分析了典型地物后向散射极化和时间特性。沿海防护林的后向散射随时间变化较小,VV极化能较好的体现沿海防护林的表面形态和特征,VH极化可以将水体和沿海防护林很好的区分开来,植被间的差异在HH极化中得到较好的反映。针对不同的极化组合情况,采用面向对象的方法提取沿海防护林信息,并对提取结果进行了对比分析,认为多极化的数据更有利于防护林信息的提取。     

A multi-level segmentation methodology for dual-polarized SAR data

An innovative methodology for dual-polarized Synthetic Aperture Radar (SAR) data segmentation is proposed. The methodology is based on the thresholding of the 1D-histograms of the two images produced by the dual polarimetric bands. Thresholding of the histograms is performed using a nonparametric algorithm. Histograms after thresholding are combined together in a two dimensional histogram-based space in order to define sub-spaces, which are used for image segmentation. Sub-spaces are further divided based on two criteria which lead to a multi-level segmentation approach. Dual-polarized TerraSAR-X data, both HH and VV, are used in a study area located in the southwestern United Kingdom.     

Investigating the correlation between radar backscatter and in situ soil property measurements

Utilizing remote sensing techniques to extract soil properties can facilitate several engineering applications for large-scale monitoring and modeling purposes such as earthen levees monitoring, landslide mapping, and off-road mobility modeling. This study presents results of statistical analyses to investigate potential correlations between multiple polarization radar backscatter and various physical soil properties. The study was conducted on an approximately 3 km long section of earthen levees along the lower Mississippi river as part of the development of remote levee monitoring methods. Polarimetric synthetic aperture radar imagery from UAVSAR was used along with an extensive set of in situ soil properties. The following properties were analyzed from the top 30–50 cm of soil: texture (sand and clay fraction), penetration resistance (sleeve friction and cone tip resistance), saturated hydraulic conductivity, field capacity, permanent wilting point, and porosity. The results showed some correlation between the cross-polarized (HV) radar backscatter coefficients and most of these properties. A few soil properties, like clay fraction, showed similar but weaker correlations with the co-polarized channels (HH and VV). The correlations between the soil properties and radar backscatter were analyzed separately for the river side and land side of the levee. It was found that the magnitude and direction of the correlation for most of the soil properties noticeably differed between the river and the land sides. The findings of this study can be a good starting point for scattering modelers in a pursuit of better models for radar scattering at cross polarizations which would include more diverse set of soil parameters.     

Images difference of ASAR data for rice crop mapping in Fuzhou,China

This paper introduces ENVISAT ASAR data application on rice field mapping in the Fuzhou area, using multi-temporal ASAR dual polarization data acquired in 2005. The procedure for ASAR data processing here includes data calibration, image registration, speckle reduction and conversion of data format from amplitude to dB for backscatter. The backscatter of rice increases with the rice growing stages, which was much different from other land covers. Based on image difference techniques, 6 schemes were designed with ASAR different temporal and polarization data for rice field mapping. Difference images between images in the early period of rice crop and growing or ripening period, are more suitable for rice extraction than those difference images between different polarizations in the same date. The most accurate result of late rice extraction was achieved based on the difference of HH polarization data acquired in October and August. Therefore, for rice field mapping, the temporal information is more important than polarization information. The data during the early growing season of rice is very important for high accuracy rice mapping.     

Applications of ALOS PALSAR for monitoring biophysical parameters of a degraded black mangrove (Avicennia germinans) forest

Within the last few decades mangrove forests worldwide have been experiencing high annual rates of loss and many of those that remain have undergone considerable degradation. To understand the condition of these forests, various optical remote sensing platforms have been used to map and monitor these wetlands, including the use of these data for biophysical parameter mapping. For many mangrove forests a reliable source of optical imagery is not possible given their location in quasi-permanent cloud cover or smoke covered regions. In such cases it is recommended that Synthetic Aperture Radar (SAR) be considered. The purpose of this investigation was to examine the relationships between various ALOS-PALSAR modes, acquired from eight images, and mangrove biophysical parameter data collected from a black mangrove (Avicennia germinans) dominated forest that has experienced considerable degradation. In total, structural data were collected from 61 plots representing the four common stand types found in this degraded forest of the Mexican Pacific: tall healthy mangrove (n = 17), dwarf healthy mangrove (n = 15), poor condition mangrove (n = 13), and predominantly dead mangrove (n = 16).Based on backscatter coefficients, significant negative correlation coefficients were observed between filtered single polarization ALOS PALSAR (6.25 m) HH backscatter and Leaf Area Index (LAI). When the dead stands were excluded (n = 45) the strength of these relationships increased. Moreover, significant negative correlation coefficients were observed with stand height, Basal Area (BA) and to a lesser degree with stem density and mean DBH. With the coarser spatial resolution dual-polarization and quad polarization data (12.5 m) only a few, and weaker, correlation coefficients were calculated between the mangrove parameters and the filtered HH backscatter. However, significant negative values were once again calculated for the HH when the 16 dead mangrove stands were removed from the sample. Conversely, strong positive significant correlation coefficients were calculated between the cross-polarization HV backscatter and LAI when the dead mangrove stands were considered. Although fewer in comparison to the HH correlations, a number of VV backscatter based relationships with mangrove parameters were observed from the quad polarization mode and, to a lesser extent, with the one single VV polarization data.In addition to backscatter coefficients, stepwise multiple regression models of the mangrove biophysical parameter data were developed based on texture parameters derived from the grey level co-occurrence matrix (GLCM) of the ALOS data. A similar pattern to the backscatter relationships was observed for models based on the single polarization unfiltered data, with fairly strong coefficients of determination calculated for LAI and stem height when the dead stands were excluded. In contrast, similar coefficients of determination with biophysical parameters were observed for the dual and quad polarization multiple regression models when the dead stands were both included and excluded from the analyses. An estimated mangrove LAI map of the study area, derived from a multiple regression model of the quad polarization texture parameters, showed comparable spatial patterns of degradation to a map derived from higher spatial resolution optical satellite data.     

Application of ENVISAT ASAR Data in Mapping Rice Crop Growth in Southern China

This research letter presents preliminary results of mapping rice crop growth using ENVISAT advanced synthetic aperture radar (ASAR) alternating polarization HH/HV data. Four ASAR HH/HV images were collected in the early rice-growth cycle in the test site in 2006, and the temporal response of ASAR data to the rice field was analyzed. The height and biomass of rice were measured during acquisition of ASAR data, and empirical relationships were established between the backscattering coefficient and these two parameters. Based on the temporal variation of the radar response, a method for mapping a rice growth area was developed using the combination of ASAR HH and HV polarization data between two acquisition dates. The results confirm that C-band SAR data have great potential in the development of an operational system for monitoring rice crop growth in Southern China.     

多频率InSAR提取沼泽湿地DEM精度对比分析

选取3种波长的干涉SAR数据对提取沼泽湿地区域的DEM,并随机从1：10 000地形图中选取111个点数据进行精度验证,最后对比分析了沼泽湿地植被对于不同SAR波长的干涉相干性差异。结果表明：L-band ALOS-1 PALSAR精细模式的HH单视复数数据与1：10 000地形图数据吻合度较好,76.58%的高程值差异在3 m以内,其相干系数比C-band Sentinel-1A IW模式的VV单视复数数据和X-band TerraSAR HH单视复数数据要高;更适合利用雷达干涉测量技术提取沼泽湿地的DEM;不同湿地植被类型的相干系数有较大差异,岛状林和灌草结合的湿地植被分布区相干系数值较大,而浅水沼泽植被区和深水沼泽植被区相对较低。     

Discriminating transplanted and direct seeded rice using Sentinel-1 intensity data

Improved rice crop and water management practices that make the sustainable use of resources more efficient are important interventions towards a more food secure future. A remote sensing-based detection of different rice crop management practices, such as crop establishment method (transplanting or direct seeding), can provide timely and cost-effective information on which practices are used as well as their spread and change over time as different management practices are adopted. Establishment method cannot be easily observed since it is a rapid event, but it can be inferred from resulting observable differences in land surface characteristics (i.e. field condition) and crop development (i.e. delayed or prolonged stages) that take place over a longer time. To examine this, we used temporal information from Synthetic Aperture Radar (SAR) backscatter to detect differences in field condition and rice growth, then related those to crop establishment practices in Nueva Ecija (Philippines). Specifically, multi-temporal, dual-polarised, C-band backscatter data at 20m spatial resolution was acquired from Sentinel-1A every 12 days over the study area during the dry season, from November 2016 to May 2017. Farmer surveys and field observations were conducted in four selected municipalities across the study area in 2017, providing information on field boundaries and crop management practices for 61 fields. Mean backscatter values were generated per rice field per SAR acquisition date. We matched the SAR acquisition dates with the reported dates for land management activities and with the estimated dates for when the crop growth stages occurred. The Mann-Whitney U test was used to identify significant differences in backscatter between the two practices during the land management activities and crop growth stages. Significant differences in cross-polarised, co-polarised and band ratio backscatter values were observed in the early growing season, specifically during land preparation, crop establishment, rice tillering and stem elongation. These findings indicate the possibility to discriminate crop establishment methods by SAR at those stages, suggesting that there is more opportunity for discrimination than has been presented in previous studies. Further testing in a wider range of environments, seasons, and management practices should be done to determine how reliably rice establishment methods can be detected. The increased use of dry and wet direct seeding has implications for many remote sensing-based rice detection methods that rely on a strong water signal (typical of transplanting) during the early season.     

广东肇庆地区SIR-C森林雷达后向散射特征分析

森林雷达后向散射特征的研究是森林微波遥感应用的重要前提。本文利用不连续树冠森林微波后向散射模型模拟了肇庆地区松树林的雷达后向散射特征,并与从ＳＩＲ－Ｃ图像提取的雷达后向散射特征进行对比,从而分析和探讨了该区松树的雷达后向散射机制。     

X波段VV极化地面杂波测量研究

对X波段，VV极化的外场地杂波试验进行了总结，包括测量系统，原理，测试内容，并提供了后向散射系数测量结果和分析，测量地形包括干草地，裸露土壤和绿麦地。     

Estimation of rice grain yield from dual-polarization Radarsat-2 SAR data by integrating a rice canopy scattering model and a genetic algorithm

Fast and accurate estimation of rice yield plays a role in forecasting rice productivity for ensuring regional or national food security. Microwave synthetic aperture radar (SAR) data has been proved to have a great potential for rice monitoring and parameters retrieval. In this study, a rice canopy scattering model (RCSM) was revised and then was applied to simulate the backscatter of rice canopy. The combination of RCSM and genetic algorithm (GA) was proposed for retrieving two important rice parameters relating to grain yield, ear length and ear number density, from a C-band, dual-polarization (HH and HV) Radarsat-2 SAR data. The stability of retrieved results of GA inversion was also evaluated by changing various parameter configurations.Results show that RCSM can effectively simulate backscattering coefficients of rice canopy at HH and HV mode with an error of <1 dB. Reasonable selection of GA’s parameters is essential for stability and efficiency of rice parameter retrieval. Two rice parameters are retrieved by the proposed RCSM-GA technology with better accuracy. The rice ear length are estimated with error of <1.5 cm, and ear number density with error of <23 #/m². Rice grain yields are effectively estimated and mapped by the retrieved ear length and number density via a simple yield regression equation. This study further illustrates the capability of C-band Radarsat-2 SAR data on retrieval of rice ear parameters and the practicability of radar remote sensing technology for operational yield estimation.     

目标分解技术在植被覆盖条件下土壤水分计算中的应用

目标分解技术利用协方差距阵的特征值和特征矢量，将极化雷达后向散射测量值分解为单向散射，双向散射和交叉极化散射三个分量，并建立了植被覆盖地表的一阶物理离散散射模型。通过分解的各分量与该模型的比较，建立重轨极化雷达测量数据估算土壤水分的方法，采用Washita‘92实验区多时相全极化L波段JPL/AIRSAR图像雷达测量数据，利用分解的散射测量值，我们评估了在同一入射角，单频（L波段），多路条件下，分解理论在进行土壤水分估计时减少植被影响的能力。结果表明利用目标分解理论和重轨极化雷达数据可以估算植被覆盖区域土壤水分的变化情况。