Landsat image data quality studies

The July 1982 launch of Landsat-4 was immediately followed by a two-year comprehensive set of detailed investigations sponsored by the National Aeronautics and Space Administration (NASA) at Goddard Space Flight Center (GSFC). The Landsat Image Data Quality Analysis (LIDQA) research plans for these investigations were specified prior to launch, so that minimum time would be lost in assessing the performance of the long-awaited Thematic Mapper (TM) sensor that Landsat-4 carried in addition to a fourth Multispectral Scanner (MSS). The LIDQA investigations have been substantially completed, and have shown that the TM is a very good spaceborne multispectral radiometer, and has met or exceeded most of its design goals. TM's new short-wave infrared (SWIR) spectral capability yielded improved mineral and plant discrimination compared to the MSS, as anticipated by ground-based and airborne TM simulations. Moreover, the improved spatial resolution and geometric accuracy of Landsat-4 and the TM have resulted in satellite image maps exceeding 1:100,000 U.S. map accuracy standards. Finally, based on an information entropy measure, principal component analysis, and classification results, TM data has been shown to approach its theoretical limit in information content per pixel, exceeding the MSS by at least a factor of two.     

Applicationof remote sensing techniques in geological studies of various mineralized belts in India. (National paper on IGCP — 143)

Geological interpretation, analysis and evaluation of LANDSAT and airborne MSS data, panchromatic and colour infrred photographs and spectral reflectance data for a number of test sites in different mineralized belts in India have led to certain significant results. Lithological discrimination on digitally processed enhanced MSS data products has helped in further subdivisions of major rock groups. Lineament pattern analyses reveals three prominent sets of fractures in Indian Precambrian Shield with predominant ENE-WSW megalineament probably representing earliest deep crustal fractures and subsequent NNW-SSE and NE-SW fractures, associated with polyphase tectonic movements. Correlation of structures and mineralization indicate structural control for most of the mineralized belts with intersecting locii type concentration of ore deposits in some cases. In a few cases control of mineralization is lithology and stratigraphy. Spectral groundtruth and laboratory studies indicate that major rock types have characteristic spectral patterns (signatures) which would be useful for lithological mapping by automatic classification techniques. The work also has led to the improvement of enhanced MSS data products for geological studies.     

Preliminary evaluation of the landsat-4 thematic mapper data for mineral exploration

Landsat-4 Thematic Mapper (TM) data recorded over an arid terrain were analyzed to determine the applicability of using of TM data for identifying and mapping hydrothermally altered, potentially mineralized rocks. Clays, micas, and other minerals bearing the OH anion in specific crystal lattice positions have absorption bands in the 2.2-μm region (TM channel 7, TM7) and commonly lack features in the 1.6-μm region (TM5). Channel ratios TM5/TM7, TM5/TM4, and TM3/TM1 were combined into a color-ratio-composite (CRC) image and used to distinguish hydrothermally altered rocks, unaltered rocks, and vegetation. These distinctions are made possible by using the TM5 and TM7, channels which are not available in the Landsat multispectral scanner (MSS). Digital masking was used to eliminate ambiguities due to water and shadows. However, some ambiguities in identification resulted between altered volcanic rocks and unaltered sedimentary deposits that contained clays, carbonates, and gypsum, and between altered volcanic rocks and volcanic tuffs diagenetically altered to zeolites. However, compared to MSS data, TM data should greatly improve the ability to map hydrothermally altered rocks in arid terrains.     

Estimating canopy cover in drylands with Landsat MSS data

The relationship between canopy cover and spectral characteristics of the corresponding areas was studied in a semi-arid savannah environment in Kordofan, The Sudan.The canopy cover was measured in 32 test plots through air photo interpretation. Achieved values were correlated with multitemporal Landsat MSS raw data and manipulated data.The highest correlation coefficients in general were obtained between crown cover and spectral data recorded during the dry season.The inverse relationship between amount of woody vegetation and nIR reflectance (MSS 6, MSS 7) was striking. This implied that other factors than a healthy foliage characterized the spectral responses.Destructive measurements of woody biomass were carried out to establish a relationship between woody wet weight and crown diameter for future biomass studies.     

Remote-sensing technology applied to forest assessment in California

Remote-sensing technology has been thoroughly evaluated for the analysis of California forest policy. A statewide, 1.6-acre-resolution, digital land-cover data base of Landsat Multispectral Scanner (MSS) classification has been produced. Three major resource regions have been analyzed in detail and one of them geographically integrated with 12 other physical and socioeconomic data layers to model fire and reforestation problems, using a geographic information system (GIS). A study of GIS design criteria has been conducted and the California Department of Forestry, the cooperator in all of these studies, is presently evaluating the alternatives and implementing certain aspects of them.     

改进的GPS掩星滑动频谱方法

在大气多路径和噪声的条件下,高斯白噪声会造成滑动频谱方法获得的弯曲角与真值之间的偏离,无法获得较好的反演结果。为此,文章提出了一种改进的滑动频谱方法,即利用信号的振幅和谱能量信息对滑动频谱方法进行修正,削弱了信号中噪声的影响,与真值较为接近。分别用改进前后两种方法对中华卫星三号计划（Constellation Observing System for Meteorology, Ionosphere and Climate,COSMIC）的掩星进行反演,并将其折射率计算结果和通过全谱反演方法获得的折射率一起,与欧洲中期天气预报中心（European Centre for Medium Range Weather Forecasts,ECMWF）的分析场资料进行了统计比较。结果表明：改进的滑动频谱方法删除了信号中的部分噪声,减少了系统偏差;与全谱反演方法进行比较,发现两者具有相当的反演精度。     

Sensor data for forest policy information

NASA-Ames Research Center has investigated the role and performance capabilities of the Landsat Multi-Spectral Scanner (MSS) for forest policy analysis for the past four years in cooperation with the California Department of Forestry. A thorough series of studies, from a statewide land cover map to smaller, highly detailed studies including collateral data, have been conducted with a view to comprehensive forest policy needs. The strengths and limitations of MSS data have been evaluated. Some observations about the information needed from new satellite sensors such as the Thematic Mapper are discussed against this background.     

Investigations of the Krasnoyarsk Reservoir waters based on the multispectral satellite data

In this work historical investigations and modern results of classification of the Krasnoyarsk Reservoir are presented. The paper presents results of studying the dynamics of phytopigments and other optically active components, using multispectral satellite data. Several approaches to interpreting satellite data for optically complex inland water bodies are offered. Based on results of historical investigations it is shown that the spatial distribution of phytoplankton in the reservoir stems back to the time of its formation. Color index in the red spectral region (CIR) is introduced. A relationship between the color index and chlorophyll concentration is investigated. The CIR, derived from the AVHRR data, has been found to be related to chlorophyll concentration. Based on MODIS data, the waters of the Krasnoyarsk Reservoir have been classified in accordance with their optical spectral variability, using the technique of unsupervised IsoData classification. An empirical relationship between multispectral MODIS data and the ground-truth measurements of chlorophyll concentration has been found.     

Evaluation of thematic mapper data for mapping forest,agricultural and soil resources

Color composite TM film products which include TM5, TM4, and a visible band (TM1, TM2, or TM3) are superior to composites which exclude TM4 for discriminating most forest and agricultural cover types and estimating area proportions for inventory and sampling purposes. Clustering a subset of TM data results in a spectral class map which groups diverse forest cover types into spectrally and ecologically similar areas suitable for use as a stratification base in traditional forest inventory practices. Analysis of simulated Thematic Mapper data indicate that the location and number of TM spectral bands are suitable for detecting differences in major soil properties and characterizing soil spectral curve form and magnitude.     

星下目标的光谱反射特性分析及云层的自动识别

本文着重讨论了遥感数据的实时分类和星载相机快门的自动关启问题.首先建立了计算各类目标景象亮度的物理模型,分析了大气等因素对遥感数据的影响及各类自然目标的光谱反射特性,计算了三十四种目标在九种大气条件下的亮度值.进而提出了识别植被、土壤、水、冰雪和云等五类目标的最佳波段和分类函数及分类流程图,得到了很高的分类精度.然后又特别讨论了云层和所有非云目标(包括混合目标)的分类问题,并用密度计测量了十张MSS卫星图片上的180个目标的亮度值.最后提出了云层开关的实现途径和系统设计的基本思想.      

Deep learning-based framework for monitoring of debris-covered glacier from remotely sensed images

In recent years, deep learning (DL) methods have proven their efficiency for various computer vision (CV) tasks such as image classification, natural language processing, and object detection. However, training a DL model is expensive in terms of both complexities of the network structure and the amount of labeled data needed. In addition, the imbalance among available labeled data for different classes of interest may also adversely affect the model accuracy. This paper addresses these issues using a new convolutional neural network (CNN) based architecture. The proposed network incorporates both spatial and spectral information that combines two sub-networks: spatial-CNN and spectral-CNN. The spectral-CNN extracts spectral information, while spatial-CNN captures spatial information. Moreover, to make the features more robust, a multiscale spatial CNN architecture is introduced using different kernels. The final feature vector is formed by concatenating the outputs obtained from both spatial-CNN and spectral-CNN. To address the data imbalance problem, a generative adversarial network (GAN) was used to generate data for the underrepresented class. Finally, relatively a shallower network architecture was used to reduce the number of parameters in the network and improve the processing speed. The proposed model was trained and tested on Senitel-2 images for the classification of the debris-covered glacier. The results showed that the proposed method is well-suited for mapping and monitoring debris-covered glaciers at a large scale with high classification accuracy. In addition, we compared the proposed method with conventional machine learning approaches, support vector machine (SVM), random forest (RF) and multilayer perceptron (MLP).     

Black hole spectral states and physical connections

The dramatic changes seen in the X-ray spectral and timing properties of accreting black hole candidates (BHCs) provide important clues about the accretion and jet formation processes that occur in these systems. Dividing the different source behaviors into spectral states provides a framework for studying BHCs. To date, there have been three main classification schemes with Luminosity-based, Component-based, or Transition-based criteria. The canonical, Luminosity-based criteria and physical models that are based on this concept do not provide clear explanations for several phenomena, including hysteresis of spectral states and the presence of jets. I discuss the re-definitions of states, focusing on an application of the Component-based states to more than 400 RXTE observations of the recurrent BHC 4U 1630–47. We compare the X-ray properties for the recent 2002–2004 outburst to those of an earlier (1998) outburst, during which radio jets were observed. The results suggest a connection between hysteresis of states and major jet ejections, and it is possible that both of these are related to the evolution of the inner radius of the optically thick accretion disk.     

Object-based rice mapping using time-series and phenological data

Remote sensing techniques are often used in mapping rice, but high quality time-series remote sensing data are difficult to obtain due to the cloudy weather of rice growing areas and long satellite revisit interval. As such, rice mapping is usually based on mono-temporal Landsat TM/ETM+ data, which have large uncertainties due to the spectral similarity of different vegetation types. Moreover, conventional pixel-based classification method is unable to meet the required accuracy for rice mapping. Therefore, this study proposes a new strategy for mapping rice in cloud-prone areas using fused data of Landsat-8 OLI time-series and phenological parameters, based on the object-based method. We determine the critical growth stages of paddy rice from observed phenological data and MODIS-NDVI time-series data. The spatial and temporal adaptive reflectance fusion model (STARFM) is used to blend the MODIS and Landsat data to obtain a multi-temporal Landsat-like dataset for classification. Finally, an object-oriented algorithm is used to extract rice paddies from the Landsat-like, time-series dataset. The validation experiments show that the proposed method can provide high accuracy rice mapping, with an overall accuracy of 92.38% and a kappa coefficient of 0.85.     

Hydrologic appraisal of rivers plan-form at confluence zone — A case study using Landsat MSS data

In river systems confluences and bifurcations are typical features whose effects are largely dependent on the specific characteristics of the rivers involved. The study makes an attempt to analyse the planform configuration at the confluence zone of the Wainganga and Khobragadi rivers in the central part of India. The data used are the Landsat MSS CCT data of date 17.12.1972 for scene 154-046 and black and white aerial photographs of November, 1969. Supervised method of classification using maximum likelihood classification method is employed. The study confirms that the discharge and sediment transport in the individual rivers constitute the dominating factors in the changes of planform geometry at a confluence. The usefulness of the Landsat MSS data and digital analysis techniques. for generating the necessary data inputs for the study is also validated.     

Examining LiDAR – WorldView-3 data synergy to generate a detailed stand map in a mixed forest in the north-west of Turkey

Although stand delineation approach based on aerial photographs and field survey produces high accuracy maps, it is labour-intensive and time consuming. Furthermore, conventional forest stand maps may have some uncertainties that can hardly be verified due to the experiments and skills of photo-interpreters. Therefore, researchers have been seeking more objective and cost-effective methods for forest mapping. LiDAR (Light Detection and Ranging) data have a high potential to automatically delineate forest stands. Unlike optical sensors, LiDAR height data provides information about both the horizontal and vertical structural characteristics of forest stands. However, it deprives of spectral data that may be successfully used in separating tree species. In this study, we investigate the potential of LiDAR – WorldView-3 data synergy for the automatic generation of a detailed forest stand map which can be used for a tactical forest management plan. Firstly, image segmentation was applied to LiDAR data alone and LiDAR/WorldView-3 data set in order to obtain the most suitable image objects representing forest stands. Visual inspection of the segmentation results showed that image objects based on the LiDAR/WorldView-3 data set were more compatible with the reference forest stand boundaries. After the segmentation process, the LiDAR and LiDAR/WorldView-3 data sets were independently classified using object-based classification method. We tested two levels of classification. The first was a detailed classification with 14 classes considering reference stand types. The second was the rough classification with 9 classes where some stand types were combined. The mean, standard deviation and texture features of LiDAR metrics and spectral information were used in the classification. The accuracy assessment results of LiDAR data showed that the Overall Accuracy (OA) was calculated as 0.31 and 0.43, and the Kappa Index (KIA) was calculated as 0.26 and 0.32 for the detailed and rough classifications, respectively. For the LiDAR/WorldView-3 data set, the OA values were calculated as 0.50 and 0.61, and the KIA were calculated as 0.46 and 0.55 for the detailed and rough classifications, respectively. These results showed that the forest stand map derived from the LiDAR/WorldView-3 data synergy is more compatible with the reference forest stand map. In conclusion, it can be said that the forest stand maps produced in this study may provide strategic forest planning needs, but it is not sufficient for tactical forest management plans.     

一种被动更新LBTS的HLA时间管理方案

LBTS(Lower Bound Time Stamp)查询是影响时间管理性能的重要因素.为提高高层体系结构(HLA,High Level Architecture)中时间管理的性能,提出了一种减小最小时间戳下限LBTS传递次数的优化方法,将主动查询LBTS变成当LBTS改变时才通知相应的受控成员.应用可靠组播服务,降低了时间管理的通讯代价,将算法应用在具有自主知识产权的AST-RTI(Advanced Simulation Technology-Run Time Infrastructure)中,应用系统证明能有效提高RTI的实时性.最后针对RTI时间管理机制在仿真应用中带来的问题以及解决方法进行了讨论.      

Experimental evaluation of the processes resulting from the introduction of the transgenic microorganism Escherichia coli Z905/pPHL7 (lux+) into aquatic microcosms.

The processes resulting from the introduction of the tranagenic microorganism (TM) E. coli Z905/pPHL7 into aquatic microcosms have been modeled experimentally. It has been shown that the TM E. coli is able to adapt to a long co-existence with indigenous heterotrophic microflora in variously structured microcosms. In more complex microcosms the numerical dynamics of the introduced E. coli Z905/pPHL7 population is more stable. In the TM populations staying in the microcosms for a prolonged time, changes are recorded in the phenotypic expression of plasmid genes (ampicillin resistance and the luminescence level) and chromosome genes (morphological and physiological traits). However, in our study microcosms, the recombinant plasmid persisted in the TM cells for 6 years after the introduction, and as the population adapts to the conditions of the microcosms, the efficiency of the cloned gene expression in the cells is restored. In the microcosms with high microalgal counts (10(7) cells/ml), cells with a high threshold of sensitivity to ampicillin dominate in the population of the TM E. coli Z905/pPHL7.     

First results from the LUCID-Timepix spacecraft payload onboard the TechDemoSat-1 satellite in Low Earth Orbit

The Langton Ultimate Cosmic ray Intensity Detector (LUCID) is a payload onboard the satellite TechDemoSat-1, used to study the radiation environment in Low Earth Orbit ($～$635?km). LUCID operated from 2014 to 2017, collecting over 2.1 million frames of radiation data from its five Timepix detectors on board. LUCID is one of the first uses of the Timepix detector technology in open space, with the data providing useful insight into the performance of this technology in new environments. It provides high-sensitivity imaging measurements of the mixed radiation field, with a wide dynamic range in terms of spectral response, particle type and direction. The data has been analysed using computing resources provided by GridPP, with a new machine learning algorithm that uses the Tensorflow framework. This algorithm provides a new approach to processing Medipix data, using a training set of human labelled tracks, providing greater particle classification accuracy than other algorithms. For managing the LUCID data, we have developed an online platform called Timepix Analysis Platform at School (TAPAS). This provides a swift and simple way for users to analyse data that they collect using Timepix detectors from both LUCID and other experiments. We also present some possible future uses of the LUCID data and Medipix detectors in space.     

A strategy for mineral and energy resource independence

Data acquired by Landsats 1, 2, and 3, are beginning to provide the information on which an improved mineral and energy resource exploration strategy can be based. Landsat 4 is expected to augment this capability with its higher resolution (30 m) and additional spectral bands in the Thematic Mapper (TM) designed specifically to discriminate clay minerals associated with mineral alteration. In addition, a new global magnetic anomaly map, derived from the recent Magsat mission, has recently been compiled by the National Aeronautics and Space Administration (NASA), the U.S. Geological Survey (USGS), and others. Preliminary, extremely small-scale renditions of this map indicate that global coverage is nearly complete and that the map will improve upon a previous one derived from Polar Orbiting Geophysical Observatory (POGO) data. Digital processing of the Landsat image data and Magsat geophysical data can be used to create three-dimensional stereoscopic models for which Landsat images provide surface reference to deep structural anomalies.Comparative studies of national Landsat lineament maps, Magsat stereoscopic models, and metallogenic information derived from the Computerized Resources Information Bank (CRIB) inventory of U.S. mineral resources, provide a way of identifying and selecting exploration areas that have mineral resource potential. Landsat images and computer-compatible tapes can provide new and better mosaics and also provide the capability for a closer look at promising sites.