Radar Remote Sensing Research Articles

Special Issue on Marine and Maritime Radar Remote Sensing

Special Issue on Marine and Maritime Radar Remote Sensing

Potential and Limitations of Radar Remote Sensing for Humanitarian Operations

Methods of earth observation deliver quick and reliable information covering large areas, which can be used for the management of natural disasters and humanitarian crises. However, optical sensors reach their limits in areas affected by cloud cover or atmospheric haze, while radar satellites are predominantly unaffected by atmospheric conditions. This paper discusses the application of radar imagery for the assistance of humanitarian operations. The opening section describes the need for complementary information gained from radar data as well as the challenges which arise when working with imaging systems. Subsequently, examples for the use of various sensors are given based on our own findings, and a literature review for various application domains. These include the monitoring of natural resources, the distribution of human settlements or dwellings, and the retrieval of hydrologic parameters. Against this background, limitations and how they were handled in selected studies are discussed. A summary reflects the findings in the light of new developments and discusses challenges for the future.

Использование различных оптических и радарных данных дистанционного зондирования при оперативном космическом мониторинге паводков в Казахстане

Использование различных оптических и радарных данных дистанционного зондирования при оперативном космическом мониторинге паводков в Казахстане

Special Issue on Marine and Maritime Radar Remote Sensing

Special Issue on Marine and Maritime Radar Remote Sensing

A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring

The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies) concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification) was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

Preface to the Special Issue on “Innovative Applications of Radar and LiDAR Remote Sensing”

Preface to the Special Issue on “Innovative Applications of Radar and LiDAR Remote Sensing”

Principle,Application and Prospects of Synthetic Aperture Radar (SAR) Remote Sensing in Archaeology

Principle,Application and Prospects of Synthetic Aperture Radar (SAR) Remote Sensing in Archaeology

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies.

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.

Radar Remote Sensing Estimates of Waves and Wave Forcing at a Tidal Inlet

AbstractThe time and space variability of wave transformation through a tidal inlet is investigated with radar remote sensing. The frequency of wave breaking and the net wave breaking dissipation at high spatial resolution is estimated using image sequences acquired with a land-based X-band marine radar. Using the radar intensity data, transformed to normalized radar cross section σ0, the temporal and spatial distributions of wave breaking are identified using a threshold developed via the data probability density function. In addition, the inlet bathymetry is determined via depth inversion of the radar-derived frequencies and wavenumbers of the surface waves using a preexisting algorithm (cBathy). Wave height transformation is calculated through the 1D cross-shore energy flux equation incorporating the radar-estimated breaking distribution and bathymetry. The accuracy of the methodology is tested by comparison with in situ wave height observations over a 9-day period, obtaining correlation values R = 0.68 to 0.96, and root-mean-square errors from 0.05 to 0.19 m. Predicted wave forcing, computed as the along-inlet gradient of the cross-shore radiation stress was onshore during high-wave conditions, in good agreement (R = 0.95) with observations.

Multi-temporal Multi-spectral and Radar Remote Sensing for Agricultural Monitoring in the Braila Plain

The objective of the paper is to investigate the sensitivity of Landsat OLI and C-band radar signals to monitor an agricultural area affected by soil salinization and land degradation. The chosen test area - Braila Plain has the special particularities such as: dry climate, high annual average temperatures (9-110C), very dry and hot summers which cause a large potential evapotranspiration and conduct to a moisture deficit in soil, alkaline soils, winter winds with an average speed of 2.7 - 3.4 m/s. The soil type and climate conditions favor the culture of maize (50%), wheat and successive crops (16%), alpha-alpha (18%), sugar beet (6%), sunflower (7%), vegetables and other crops (3%). Taking into account the soil type, climate conditions and geomorphological characteristics of the studied area, the paper focuses on evaluation of Sentinel-1 sensor capabilities to monitor soil degradation and surface soil moisture. A multi-temporal series of Sentinel-1 data gathered from October 2014 until January 2015 is used. Crop growing stages are investigated with multi-temporal Landsat OLI and MODIS data. The normalized difference vegetation index (NDVI), specific leaf area index, land thermal index, soil moisture index and soil salinity information are retrieved from Landsat data. The potential evapotranspiration is computed from MODIS data to evaluate the effects of soil salinity on growing crops. The results confirm soil degradation and the synergy of using multi-spectral and radar data for crops monitoring.

Trends in Commercial Radar Remote Sensing Industry [Industrial Profiles

The last two decades have seen an unprecedented development in the satellite-based Earth observation industry. The combination of an increasing number of operational satellites, the higher resolution of the acquired data and the advances in the processing techniques have enabled a wider adoption of satellite data and the development of a diverse range of products and applications. Although the market is still strongly biased toward electro-optically derived imagery a rising tide of acceptance and usage of satellite derived Synthetic Aperture Radar (SAR) data can be noticed over the last few years. This trend is a result of the increasing availability of commercial SAR satellite data, development of sophisticated processing and analysis tools and industry driven training effort conducted to familiarize image analysts with the specifics of SAR imagery, its interpretation and its utility.

Combination of Statistical Similarity Measure and Derivative Morphological Profile Approach for Oil Slick Detection in SAR Images

Synthetic Aperture Radar (SAR) is widely used to detect and monitor oil pollution on the sea surface. As it is sensitive to surface roughness, the presence of oil film on the sea surface decreases the backscattering of this target type resulting in a dark feature patches in SAR images. In this paper, a new approach for oil slicks detection is presented. It is mainly based on SAR image texture analysis using the combination of a statistical similarity measure and a derivative morphological profile. Oil slicks signature is extracted trough two steps procedure. First, SAR image inspection is performed in order to highlight the dark spots suspected to be oil slicks. The inspection is achieved through a similarity measure between a local probability density function (lpdf) of clean water and the lpdf of the area to be inspected. The local distribution is estimated in the neighbourhood of each pixel and compared to a reference one using the Kullback-Leibler KL distance between distributions. Second, and once spots highlighted, texture features extraction using the Derivative Morphological Profile is porformed in order to improve the detection results. algorithm has been applied to Envisat Advanced Synthetic Aperture Radar (ASAR) and European Remote Sensing (ERS) images and it yields an accurate segmentation results. Indeed, the features extraction improves the detection slicks probability Pd of ASAR, respectively ERS, images from 93.08 %to 97.37 %and from 96.32 to 99.57 % on one hand, and reduces the false alarms probability respectively from 6.92 to 2.63 %and from 3.68 to 0.59 % on the other hand.

Моделирование помех от земной поверхности для определенной местности с помощью радиолокационных изображений и других данных дистанционного зондирования

Моделирование помех от земной поверхности для определенной местности с помощью радиолокационных изображений и других данных дистанционного зондирования

Inherent Limitations in High-Frequency Radar Remote Sensing Based on Bragg Scattering From the Ocean Surface

In this paper, the existence and statistical properties of the first-order (Bragg) fluctuations in high-frequency (HF) radar Doppler spectra due to ocean wave random phase are investigated. Here, a pulsed radar waveform is used and the ocean surface is assumed to first order to be a time-varying random rough surface representable as a zero-mean, Gaussian process. Theoretical analysis for the source of the Bragg fluctuations begins with the radar backscattered electric fields in the time domain. The statistical properties of the Bragg fluctuations are investigated through simulation for various radar operating frequencies and pulse widths. The magnitude and significance of the Bragg fluctuations are discussed in terms of the operating parameters. The results can be used in setting minimum error bounds for HF radar ocean surface current measurement.

Synthetic Aperture Radar Remote Sensing of Shear-Driven Atmospheric Internal Gravity Waves in the Vicinity of a Warm Front

Abstract The synthetic aperture radar ocean surface signature of atmospheric internal gravity waves in the vicinity of a synoptic-scale warm front is examined via a classic Kelvin–Helmholtz velocity profile with a rigid lower boundary and a sloping interface. The horizontal distance that the waves extend from the surface warm front is consistent with a bifurcation along the warm frontal inversion from unstable to neutral solutions. Similarity theories are derived for the wave span and the location of maximum growth rate relative to the surface front position. The theoretical maximum wave growth rate is demonstrated to occur near this bifurcation point and, hence, to explain the observed pattern of wave amplitude. Finally, a wave crest-tracing procedure is developed to explain the observed acute orientation of waves with respect to the surface warm front.

Electromagnetic Models of Co/Cross Polarization of Bicontinuous/DMRT in Radar Remote Sensing of Terrestrial Snow at X- and Ku-band for CoReH2O and SCLP Applications

In this paper, we study the scattering properties of the terrestrial dry snow by modeling the snow structure as Bi-continuous media. The model is applied to study the snow scattering characteristics at X-band and Ku-band that are two frequencies in the proposed Cold Regions Hydrology High-resolution Observatory (CoReH2O) mission by ESA and the proposed Snow and Cold Land Process (SCLP) mission by NASA. There are two variables in the Bi-continuous media that can be adjusted to generate various snow microstructures. The different snow structures are illustrated. The extinction properties and phase matrices are studied through the Monte Carlo simulations. For each realization, the Maxwell Equations are solved numerically to take into account the coherent wave interactions among the inhomogeneties. We demonstrated the frequency dependences of scattering coefficients, which can vary depending on the setup parameters of the bicontinuous media. The power law are compared with experiment data of extinction coefficients of terrestrial snow. The calculated extinction and phase matrices are combined in the Dense Media Radiative Transfer theory (DMRT). We obtain the 1st order solution by using the iterative method. The surface scattering from the snow-ground interface is included by searching the look up table of NMM3D. The results of co-polarization and cross polarization are compared with the POLSCAT Ku-band airborne data and X-band TerraSAR-X satellite data in North Slope, Alaska.

A Perspective on Radar Remote Sensing of Soil Moisture

The sensitivity of microwave scattering to the dielectric properties and the geometric structure of soil surfaces makes radar remote sensing a challenge for a wide range of environmental issues directly related to the condition of natural surfaces. Especially, the potential for retrieving soil moisture with a high spatial and/or temporal resolution represents a significant contribution to hydrological and ecological modeling. This paper aims to review the current state of the art in SAR technology and methodological issues towards the discovery of a new potential accurate monitoring of soil moisture changes. In this paper, important parameters or constraints significantly affect the sensitivity of the measurements to soil moisture, such as roughness statistics, spatial resolution, and local topography, are discussed to improve the applicability of SAR remote sensing techniques. This study particularly intends to discuss important notes for developing smart and reliable methods capable of retrieving geophysical information.

Geology Application of Radar Remote Sensing Technology and Its Development

SAR remote\|sensing instruments with the capabilities of all weather and all day/night, penetration, and terrain detection, especially the development of new imaging radar technologies, i.e. polarimetric SAR (PolSAR) and interferometric SAR (INSAR), provide unique geological environmental information, quite different from, yet complementary to passive systems such as visible, infrared and passive microwave radiometers. As active instruments, they provide their own illumination, which is minimally affected by weather conditions and time of day or night. SAR instruments are sensitive to topographic features, surface roughness, and to changes in dielectric constant. In addition, the synthetic aperture technique of SAR image formation provides very high resolution imagery (in the several meters to several hundred meters range). These characteristics of SAR data make them extraordinarily useful for many operational geologic mapping and monitoring activities.\;SAR data provide unique information about geology, such as lineament features, fault zone, stratum outcrop,and volcanic formation, as well as critical data for geological hazards and mine resource assessments. Interferometric measurement capabilities uniquely provided by SAR are required to generate global topographic maps, to monitor surface topographic change, and to monitor earthquake and volcanic movement. Multiparameter SAR data are crucial for accurate lithology classification, measuring terrain change, delineation of geology mapping. \;The development of geology application of radar remote sensing technology is reviewed in this paper through the development of SAR, that is, from single\|band, single polarization to multi-band, multi-polarization, then to PolSAR and INSAR.

Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

During 1996–2006, the Ministry of Agriculture and Forestry in Finland (MAFF), MTT Agrifood Research and the Finnish Geodetic Institute performed a joint remote sensing satellite research project. It evaluated the applicability of optical satellite (Landsat, SPOT) data for cereal yield estimations in the annual crop inventory program. Four Optical Vegetation Indices models (I: Infrared polynomial, II: NDVI, III: GEMI, IV: PARND/FAPAR) were validated to estimate cereal baseline yield levels (yb) using solely optical harmonized satellite data (Optical Minimum Dataset). The optimized Model II (NDVI) yb level was 4,240 kg/ha (R2 0.73, RMSE 297 kg/ha) for wheat and 4390 kg/ha (R2 0.61, RMSE 449 kg/ha) for barley and Model I yb was 3,480 kg/ha for oats (R2 0.76, RMSE 258 kg/ha). Optical VGI yield estimates were validated with CropWatN crop model yield estimates using SPOT and NOAA data (mean R2 0.71, RMSE 436 kg/ha) and with composite SAR/ASAR and NDVI models (mean R2 0.61, RMSE 402 kg/ha) using both reflectance and backscattering data. CropWatN and Composite SAR/ASAR &amp; NDVI model mean yields were 4,754/4,170 kg/ha for wheat, 4,192/3,848 kg/ha for barley and 4,992/2,935 kg/ha for oats.

Near-Space Microwave Radar Remote Sensing: Potentials and Challenge Analysis

Near-space, defined as the region between 20 km and 100 km, offers many new capabilities that are not accessible to low earth orbit (LEO) satellites and airplanes, because it is above storm and not constrained by either the orbital mechanics of satellites or the high fuel consumption of airplanes. By placing radar transmitter/receiver in near-space platforms, many functions that are currently performed with satellites or airplanes could be performed in a cheaper way. Inspired by these advantages, this paper introduces several near-space vehicle-based radar configurations, such as near-space passive bistatic radar and high-resolution wide-swath (HRWS) synthetic aperture radar (SAR). Their potential applications, technical challenges and possible solutions are investigated. It is shown that near-space is a satisfactory solution to some specific remote sensing applications. Firstly, near-space passive bistatic radar using opportunistic illuminators offers a solution to persistent regional remote sensing, which is particularly interest for protecting homeland security or monitoring regional environment. Secondly, near-space provides an optimal solution to relative HRWS SAR imaging. Moreover, as motion compensation is a common technical challenge for the described radars, an active transponder-based motion compensation is also described.