Remote sensing in land-use planning: an application in west central Scotland using SPOT-simulation data

Abstract

The urban fringe area is often characterized by a conflict between competing demands for land from many types of development; thus it requires active planning to achieve a landscape compatible with green-belt designation. Data were obtained from the NRSC SPOT-simulation campaign for an area near eastern Glasgow in an exercise to assess the value of remotely sensed data for surveying the structure of this urban fringe area. Digital enhancement and classification methods were applied to the data, identifying eight rural and six urban land-cover classes. Cloud and cloud shadow prevented a statistical accuracy assessment being performed. The most useful results were obtained by first stratifying the area into urban and rural subdivisions, followed by an interactive classification approach to the training and classification of desired fringe classes involving an analyst with local knowledge. Results showed that important urbanfringe classes of land cover can be readily identified from SPOT data, but the 20 m resolution is insufficient to discriminate inner city detail. These interim conclusions using suboptimal simulation data imply that high-resolution satellite data, rectified to a map base, classified and accuracy assessed, can be used as a survey tool to aid the physical planning of urban-fringe areas.     

Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

This study systematically evaluated linear predictive models between vegetation indices (VI) derived from radiometrically corrected airborne imaging spectrometer (HyMap) data and field measurements of biophysical forest stand variables (n=40). Ratio-based and soil-line-related broadband VI were calculated after HyMap reflectance had been spectrally resampled to Landsat TM channels. Hyperspectral VI involved all possible types of two-band combinations of ratio VI (RVI) and perpendicular VI (PVI) and the red edge inflection point (REIP) computed from two techniques, inverted Gaussian Model and Lagrange Interpolation. Cross-validation procedure was used to assess the prediction power of the regression models. Analyses were performed on the entire data set or on subsets stratified according to stand age. A PVI based on wavebands at 1088 nm and 1148 nm was linearly related to leaf area index (LAI) (R²=0.67, RMSE=0.69 m² m⁻² (21% of the mean); after removal of one forest stand subjected to clearing measures: R²=0.77, RMSE=0.54 m² m⁻² (17% of the mean). A PVI based on wavebands at 885 nm and 948 nm was linearly related to the crown volume (VOL) (R²=0.79, RMSE=0.52). VOL was derived from measured biophysical variables through factor analysis (varimax rotation). The study demonstrates that for hyperspectral image data, linear regression models can be applied to quantify LAI and VOL with good accuracy. For broadband multispectral data, the accuracy was generally lower. It can be stated that the hyperspectral data set contains more information relevant to the estimation of the forest stand variables LAI and VOL than multispectral data. When the pooled data set was analysed, soil-line-related VI performed better than ratio-based VI. When age classes were analysed separately, hyperspectral VI performed considerably better than broadband VI. Best hyperspectral VI in relation with LAI were typically based on wavebands related to prominent water absorption features. Such VI are related to the total amount of canopy water; as the leaf water content is considered to be relatively constant in the study area, variations of LAI are retrieved.     

Remote sensing of bare surface soil moisture using EMAC/ESAR data

In this paper we present first results of bare surface soil moisture retrieval using data from the European Multisensor Airborne Campaign/ Experimental Synthetic Aperture Radar (EMAC/ESAR) collected on 9 April 1994 in the Zwalm catchment, Belgium. Data from EMAC Reflective Optics System Imaging Spectrometer (ROSIS) collected on 12 July 1994 over the same catchment were used to develop land use maps. Concurrent to the EMAC/ESAR overflights field data were collected in two subcatchments of the Zwalm catchment. The paper first presents the data processing procedures used for the radar images. Then we apply a theoretical backscattering model to investigate the sensitivity of EMAC/ESAR backscattering coefficients to surface parameters (topography, surface roughness, vegetation and soil moisture). By comparing the predicted backscattering coefficients to the observed ones, we can conclude that classical measurement techniques for surface roughness parameters in remote sensing campaigns are not accurate enough for retrieving soil moisture using theoretical models. A method based on simultaneous retrieval of surface roughness parameters and soil moisture using multiple ESAR measurements is hence proposed. Promising results for retrieved soil moisture confirm the validity of the proposed method.     

Remote sensing applications in the Southeast Sumatra coastal environment

The coastal lowland swamps, rivers and estuarine areas north of Palembang, South Sumatra constitute a resource base likely to be extensively exploited during the next several years. Activities such as swamp forest logging, extensive fisheries, movement of government sponsored transmigrants and Buginese settlers into the area have intensified in recent years. Palembang is an important port which is difficult to maintain at sufficient depth to allow use by deep water ships, thereby creating interest in a coastal port location. In the near future it will be necessary to develop a multiple resource use management strategy based on national priorities, local needs and ecological constraints. Landforms, vegetation patterns, sediment and erosion sites, land use dynamics, settlement patterns and albedo are analysed from a time series of aerial photographs and LANDSAT imagery. The results, correlated with field data, indicate patterns of ecological constraints and resource use dynamics that have implications for development over much of the eastern coast of Sumatra.     

Remote sensing techniques in estuaries and coastal zones an update

This paper reviews briefly the current state of the use of remote sensing in estuaries and coastal waters. This covers the established uses, the recent developments in relation to hyperspectral imaging systems (imaging spectrometers), interferometric SAR and lidar bathymetry. The opportunities that are expected to occur soon, as 1-m resolution space-flown systems become available, are also discussed.     

Remote sensing of species mixtures in conifer plantations using LiDAR height and intensity data

In even-aged, single species conifer plantations LiDAR height data can be modelled to provide accurate estimates of tree height and volume. However, it is apparent that growth models developed for single species stands are not directly transferable to a more general situation of mixed species plantations. This paper evaluates the ability of small footprint, dual-return, pulsed airborne LiDAR data to estimate the proportion of the productive species when mixed with a nurse crop in closed canopy plantations. A study area located in Galloway Forest District in Scotland is used as an example of Lodgepole pine and Sitka spruce mixed plantation; this area contains good examples of a wide range of pure and mixed species plantation types. Three species groups are studied: areas of pure Sitka spruce, areas of pure Lodgepole pine and areas where the two species have been planted together. Two approaches are assessed for detection of plantation mixtures: the first uses LiDAR intensity data to separate spruce and pine species and the second uses LiDAR-derived canopy density measures, coefficient of variation, skewness, percent of ground returns (which provides a measure of canopy openness) and the mean canopy height, which enables areas with height variations to be identified. From analysis of LiDAR data extracted from 54 study plots using logistic regression, the coefficient of variation and LiDAR intensity data provide the most useful predictors of the proportion of spruce in a pine/spruce mixture with coefficients of determination (R²) of 0.914 and 0.930 respectively. The method could be developed as a mapping tool, which in combination with existing inventory data should help to improve timber volume forecasting for mixed species even-aged plantations.     

Remote sensing of aerosols optical thickness over various sites using SeaWiFS or VEGETATION and ground measurements

A key problem in aerosol retrieval is to distinguish between surface and atmospheric contributions to the variability in the satellite signal. A major contribution in the surface-related variability is caused by the non-Lambertian nature of the Earth surface reflectance and the fact that the illumination/observation geometry varies considerably between successive observations of the same area (with a polar orbiting sensor). In principle, if the surface boundary condition can be specified with sufficient accuracy by means of a bidirectional reflectance distribution function (BRDF), the two contributions can be unfolded and aerosol information retrieved. This approach has been tested using combined datasets made of satellite measured “top of atmosphere” (TOA) radiance and corresponding ground estimation of the aerosol optical thickness. Studying a time series of data, taking into account geometrical conditions and assuming the ground BRDF to be constant during the time period, a coupled surface/atmosphere model was used to investigate the retrieval of aerosol optical thickness (AOT) over several sites. By fitting a subset of satellite observations associated with ground photometer data, a best fit of BRDF model parameters could be determined. This surface characterization is then used to reduce the model unknowns to AOT only and thereby to permit its retrieval from the satellite data alone, by means of a simple inversion process. The study was conducted on three European AERONET sites and using satellite data from both the VEGETATION and Sea viewing Wide Field of view (SeaWiFS) sensors. In all cases, the AOT retrieved from satellite was in good agreement with the measurements.     

Remote sensing of aerosols over the oceans using AVHRR data Theory,practice and applications

Abstract

The basic features of single- and dual-channel aerosol retrieval algorithms based on matching radiances measured in AVHRR channels -1 (～0.58-0.68 μm) and -2( ～0.73-1.10μm) with model computations will be described. The use of the NOAA/NESDIS single-channel algorithm will be illustrated with examples of detection and mapping of enhanced atmospheric turbidity over the oceans. The effects of variations in the physical and radiative properties of atmospheric aerosols, and in atmospheric ozone and water vapour, will be briefly discussed in the light of model sensitivity analyses.     

数据异常情况下遥感影像时间序列分类算法

针对时序遥感图像数据异常时卷积神经网络对其分类性能较差的问题,提出了一种端到端的多模式与多单模架构相结合的网络结构.首先,通过多元时序模型和单变量时间序列模型对多维时间序列进行多尺度特征提取;然后,基于像素空间坐标信息,通过自动编码形式完成遥感图像的时空序列特征的构建;最后,通过全连接层和softmax函数实现分类.在...     

Remote sensing image fusion using the curvelet transform

This paper presents an image fusion method suitable for pan-sharpening of multispectral (MS) bands, based on nonseparable multiresolution analysis (MRA). The low-resolution MS bands are resampled to the fine scale of the panchromatic (Pan) image and sharpened by injecting highpass directional details extracted from the high-resolution Pan image by means of the curvelet transform (CT). CT is a nonseparable MRA, whose basis functions are directional edges with progressively increasing resolution. The advantage of CT with respect to conventional separable MRA, either decimated or not, is twofold. Firstly, directional detail coefficients matching image edges may be preliminarily soft-thresholded to achieve a noise reduction that is better than that obtained in the separable wavelet domain. Secondly, modeling of the relationships between high-resolution detail coefficients of the MS bands and of the Pan image is more fitting, being accomplished in the directional multiresolution domain. Experiments are carried out on very-high-resolution MS + Pan images acquired by the QuickBird and Ikonos satellite systems. Fusion simulations on spatially degraded data, whose original MS bands are available for reference, show that the proposed curvelet-based fusion method performs slightly better than the state-of-the art. Fusion tests at the full scale reveal that an accurate and reliable Pan-sharpening, little affected by local inaccuracies even in the presence of complex and detailed urban landscapes, is achieved by the proposed method.     

Detection of surface soil variation using high-resolution satellite data: results from the U.K. SPOT-simulation investigation

Abstract

A problem in using multispectral scanner(MSS) data for soil and landsystem analysis in north-west Europe is the poor spatial resolution which is insufficient to provide adequate within-field data. The SPOT satellite system will provide MSS data at 20m resolution and panchromatic data at 10m resolution. For any given ground feature the SPOT MSS mode will provide considerably more sample areas than LANDSAT 80m data. The object of this study is to determine how far variation in surface soil parameters can be detected and quantified on the basis of SPOT data.     

Volcano monitoring using remote sensing data

Abstract

The paper brings out the theoretical basis and utility of near-infrared band data sets obtained from Earth resources satellites, in the estimation of very high temperatures witnessed during volcanic eruptions. The Landsat Thematic Mapper (TM) and Indian Remote Sensing Satellite (IRS) Linear Imaging Self Scanning System (LISS-II) data sets for the period 4 April 1991-4 August 1991 were used for studying the volcanic eruption at Barren Island (India). The effect of the sub-pixel size vent in the estimation of pixel-integrated temperature has been discussed. The volcanic vent temperature on 6 May 1991 was found to be 1084K. The availability of mid-IR bands (1-55-1-75 μm and 2.08-2.35μm spectral region) in Landsat-TM enabled bringing out the vent region in the false colour composite (FCC) generated using these and the near-IR (0.76-0.90μm) band. The very high or saturated values in mid-IR bands brought a good contrast between vent and its surroundings     

Remote sensing of vital signs using an ultra-wide-band radar

Remote vital signs monitoring and tracking are of great importance for various applications including but not limited to baby monitoring, elderly care, human activity behind barriers, bio-medical and more. This paper deals with the extraction of micro-Doppler (uDoppler) signatures of a person’s respiration and heart-beat using a single transmitter (TX), single receiver (RX) Ultra Wide Band (UWB) impulse radar. The received spectrum contains the respiration and heart fundamental beat frequencies and their corresponding integer multiplicity harmonies as well as their mutual inter-modulations that appears due to the micro-Doppler frequency-modulation of the sinusoidal nature of the moving torso and heart, a fact that poses a difficulty in extracting the correct heart-beat fundamental harmony. Moreover, the commonly used Discrete Fourier Transform (DFT) is insufficient for differentiating close proximity spectral components, thus, an adaptive, real-time, novel, spectral estimation algorithm is proposed and experimental results are given.     

Remote sensing of Antarctic ozone depletion using GPS meteorology

The Antarctic ozone depletion has been characterized for the first time using global positioning system (GPS) meteorology through atmospheric precipitable water vapour (PWV). Based on observations conducted during 2009 at four selected stations in Antarctica, the PWV showed a few significant high peaks, and their variations agreed very well with the physical properties of the surface temperature. The relative humidity variation was relatively flat, and the pressure trend tended to decrease from August, lasting until spring, probably reflecting the warming air column and the influence of lower latitude air over the stations. Throughout the ozone depletion period, the PWV variability has been marked low compared to that of the total column ozone (TCO). This implies that more water vapour condenses in cold temperatures to form clouds that could annihilate ozone in the stratosphere. Based on a detailed comparison of PWV with TCO variation, we confirmed that the effect of GPS signals on the PWV variability during periods of ozone depletion was strongest in the troposphere compared to the stratosphere because of the polar vortex.     

基于FPGA的遥感数据采集与快视系统

提出了一种基于现场可编程门阵列（FPGA）的实时遥感卫星数据采集与快视系统的设计方案,该方案充分利用FPGA的硬件资源简化逻辑设计,并采用总线复用技术和内存映射文件的方法实现了采集和快视的实时并行处理以及海量数据的高速存取。     

Remote sensing for the identification of coastal plumes: case studies of Delaware Bay

Two Delaware coastal plume events are studied using various remote sensing data. Satellite images obtained from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) are processed and enhanced to identify coastal plumes from Delaware Bay. Both visible band and infrared sensors give similar results in terms of the plume boundary. The gradient images of both types of sensors show the twin‐front structure near Cape Henlopen, which is also captured in a Synthetic Aperture Radar (SAR) image. Six consecutive SST images are used to track plume variability due to tidal forcing and the features of the plume front are found to be different between ebb and flood tides. Five consecutive SST images taken during a pronounced upwelling‐favourable wind event show the plume widened and separated offshore, while cooler water upwelled onshore of the separated plume.     

基于深度学习的遥感图像去雾算法

针对遥感图像由于雾霾的存在导致图像清晰度下降的问题,提出了一种基于深度学习的图像去雾算法.首先将原有大气散射模型进行变形得到一个端到端的去雾模型,再将多个未知参数统一在一个参数中,运用多尺度卷积神经网络对未知参数进行估计,最后将参数估计值代入去雾模型中得到无雾图像.针对无参考图像数据集,先运用现有数据集对网络进行初步训练,再加入自建数据集对网络进行二次训练.实验结果表明,与相关去雾算法进行对比,该算法在视觉效果和客观指标上都有不同程度的提高,有效提升了遥感图像在雾霾天气状况下的清晰度.     

Remote sensing of coastal waters by airborne lidar and satellite radiometer Part 2: Measurements

Abstract

Active and passive remote sensing techniques for measurement of oceanic constituents have been compared using the ADRIA'84 dataset. A new method has been developed to retrieve the amount of nonchlorophyllous particles by airborne lidar measurements at three wavelengths. If the lidar measurements of chlorophyll-a and Gelbstoff are calibrated by in situ measurements, the fluorescence efficiencies can be estimated, Specific extinction coefficients for chlorophyll-a and nonchlorophyllous particles for the northern Adriatic Sea have been derived by comparing in situ and underwater irradiance measurements with radiative transfer calculations, using the ocean-atmosphere model by Fischer (1983). For the Coastal Zone Colour Scanner (CZCS), an algorithm for chlorophyll-a measurements was derived. The comparison with chlorophyll-a lidar measurements shows that different scales are resolved by both instruments. The CZCS-chlorophyll-a concentrations are influenced by Gelbstoff and nonchlorophyllous particles. It is possible to use airborne lidar measurements of chlorophyll-a for calibrating spaceborne radiometers, if the fluorescence efficiency of chlorophyll-a is known and if the lidar itself is calibrated. The comparison between Advanced Very High Resolution Radiometer (AVHRR) sea surface temperatures and CZCS measurements indicates that mesoscale structures in the ocean are much better indicated by measurements in the visible spectrum. Mesoscale structures are often masked by the warming of the ocean top layer when measuring in the infrared.