Synthesis of geophysical data with space-acquired imagery: A review

Geophysical data obtained from ground and airborne platforms have been used in the development of regional geologic models for many years. Space-acquired data and imagery have a shorter but similar history of applications. All these data may be synthesized either manually or digitally. Manual synthesis methods consist of overlaying and comparing maps, whereas digital synthesis methods consist of computer storage and analysis of registered digital data sets.A data base may include topographic, geologic, soils, aeromagnetic, gravity, radiometric, electromagnetic and geochemical data, and Landsat, Seasat, and Heat Capacity Mapping Mission (HCMM) images, all of which can be evaluated individually or compared in multiple layers (overlays).Stereographic models, useful in the correlation and interpretation of geophysical data, have been created from Landsat images by using aeromagnetic, gravity, geochemical, or topographic values to offset Landsat pixels, thus introducing parallax and permitting stereoscopic viewing.Statistical correlation has been used to determine the applicability of specific data sets to the development of geologic or exploration models. Various arithmetic functions have proven useful in developing models from such data sets.     

The role of image processing in mineral exploration: Why stop at Landsat?

Digital image processing procedures can be applied to data other than Landsat. Registered images of ancillary data such as may be derived from airborne magnetic and radiometric surveys provide new insights into existing data and extend the usefulness of satellite imagery. In times of increasing costs and difficulty of exploration better information handling is at a premium. It should be remembered that the field geologist is the ultimate end-user of most geological information, and as such the data should be easily useable and interpretable by him.     

Geological exploration and landuse using Landsat data,Sierra Leone,West Africa

Band 7 Landsat Imagery was successfully used to map broad outcrop belts in Sierra Leone because of the lithological control of topography and vegetation. Digital analysis in specific areas suggest the usefulness of certain techniques in mapping excavated areas and to indicate areas of future mineral exploration.     

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.     

An ensemble deep learning based shoreline segmentation approach (WaterNet) from Landsat 8 OLI images

Shorelines constantly vary due to natural, urbanization and anthropogenic effects such as global warming, population growth, and environmental pollution. Sustainable monitoring of coastal changes is vital in terms of coastal resource management, environmental preservation and planning. Publicly available Landsat 8 OLI (Operational Land Manager) images provide accurate, reliable, temporal and up-to-date information about coastal areas. Recently, the use of machine learning and deep learning algorithms have become widespread. In this study, we used our public Landsat 8 OLI satellite image dataset to create a majority voting method which is an ensemble automatic shoreline segmentation system (WaterNet) to obtain shorelines automatically. For this purpose, different deep learning architectures have been utilized namely as Standard U-Net, Dilated U-Net, Fractal U-Net, FC-DenseNet, and Pix2Pix. Also, we have suggested a novel framework to create labeling data from OpenStreetMap service to create a unique dataset called YTU-WaterNet. According to the results, IoU and F1 scores have been calculated as 99.59% and 99.79% for the WaterNet. The results indicate that the WaterNet method outperforms other methods in terms of shoreline extraction from Landsat 8 OLI satellite images.     

Utility of landsat data in mineral exploration — a case study from Orissa,India

The utility of Landsat data in geosciences has been established beyond doubt. In this paper utility of Landsat data in mineral exploration has been highlighted.The geologic and geomorphic interpretation of Landsat data brought out two very significant and characteristic features in scene 152-046 in the southern part of Orissa. One was distinct tonal anomaly and other was occurance of flat planated surface devoid of vegetation and drainage on top of hills. This when checked on ground at Gandhmardan was found to be bauxite bearing lateritic plateau. When this known information was extrapolated over other regions in scenes 151-046 and 152-046, all other bauxitic — lateritic plateaus were picked up very easily on Landsat imagery.The information was further extrapolated in the southern scene No.152-047 where without doing much detailed geologic and geomorphic interpretation almost all other bauxitic — lateritic bodies occuring in the region were picked up. This proves the utility of Landsat data in mineral exploration.Moreover delineation of extent of such bodies could be done very accurately on Landsat imagery thus saving considerable time in the exploration programme.     

The application of space imagery to geology and mineral exploration in the USSR — A case history

A short history of the application of space images to geology and mineral exploration in the U.S.S.R. is given with special emphasis to circular features observed on small scale and low-resolution pictures within the Precambrian terrain. These features are believed to correspond to the oldest basins of volcano-sedimentary deposition or, in other words, to primary cells of basic proto-crust. Metallogenic significance of circular features is also discussed. Remote sensing in oil-gas field exploration and in the study of recent tectonics are also dealt with.     

Stereoscopic observations from meteorological satellites

The capability of making stereoscopic observations of clouds from meteorological satellites is a new basic analysis tool with a broad spectrum of applications. Stereoscopic observations from satellites were first made using the early vidicon tube weather satellites (e.g., Ondrejka and Conover [1]). However, the only high quality meteorological stereoscopy from low orbit has been done from Apollo and Skylab, (e.g., Shenk $\text{et al.}$ [2] and Black [3], [4]). Stereoscopy from geosynchronous satellites was proposed by Shenk [5] and Bristor and Pichel [6] in 1974 which allowed Minzner $\text{et al.}$ [7] to demonstrate the first quantitative cloud height analysis. In 1978 Bryson [8] and desJardins [9] independently developed digital processing techniques to remap stereo images which made possible precision height measurement and spectacular display of stereograms (Hasler $\text{et al.}$ [10], and Hasler [11]). In 1980 the Japanese Geosynchronous Satellite (GMS) and the U.S. GOES-West satellite were synchronized to obtain stereo over the central Pacific as described by Fujita and Dodge [12] and in this paper. Recently the authors have remapped images from a Low Earth Orbiter (LEO) to the coordinate system of a Geosynchronous Earth Orbiter (GEO) and obtained stereoscopic cloud height measurements which promise to have quality comparable to previous all GEO stereo. It has also been determined that the north-south imaging scan rate of some GEOs can be slowed or reversed. Therefore the feasibility of obtaining stereoscopic observations world wide from combinations of operational GEO and LEO satellites has been demonstrated.Stereoscopy from satellites has many advantages over infrared techniques for the observation of cloud structure because it depends only on basic geometric relationships. Digital remapping of GEO and LEO satellite images is imperative for precision stereo height measurement and high quality displays because of the curvature of the earth and the large angular separation of the two satellites. A general solution for accurate height computation depends on precise navigation of the two satellites. Validation of the geosynchronous satellite stereo using high altitude mountain lakes and vertically pointing aircraft lidar leads to a height accuracy estimate of ± 500 m for typical clouds which have been studied. Applications of the satellite stereo include: 1) cloud top and base height measurements, 2) cloud-wind height assignment, 3) vertical motion estimates for convective clouds (Mack $\text{et al.}$ [13], [14]), 4) temperature vs. height measurements when stereo is used together with infrared observations and 5) cloud emissivity measurements when stereo, infrared and temperature sounding are used together (see Szejwach $\text{et al.}$ [15]).When true satellite stereo image pairs are not available, synthetic stereo may be generated. The combination of multispectral satellite data using computer produced stereo image pairs is a dramatic example of synthetic stereoscopic display. The classic case uses the combination of infrared and visible data as first demonstrated by Pichel $\text{et al.}$ [16]. Hasler $\text{et at.}$ [17], Mosher and Young [18] and Lorenz [19], have expanded this concept to display many channels of data from various radiometers as well as real and simulated data fields.A future system of stereoscopic satellites would be comprised of both low orbiters (as suggested by Lorenz and Schmidt [20], [19]) and a global system of geosynchronous satellites. The low earth orbiters would provide stereo coverage day and night and include the poles. An optimum global system of stereoscopic geosynchronous satellites would require international standarization of scan rate and direction, and scan times (synchronization) and resolution of at least 1 km in all imaging channels. A stereoscopic satellite system as suggested here would make an extremely important contribution to the understanding and prediction of the atmosphere.     

U.S. operational space program for climate observations

Satellites provide two important characteristics to earth climate studies not available from other, conventional sources: (1) full global coverage, and (2) consistency within the data set. This latter arises from the fact that the satellite data are usually derived from one instrument (or at least from a small number) whereas other sources involve large numbers of separate instruments and hence exhibit a substantial standard deviation. Satellite data, of course, are more subject to bias and must therefore be carefully validated, usually via ground truth.The ISCCP and ISLSCP are examples of the increasing reliance on satellite data for climate studies. In addition to the multispectral images, quantitative products of importance are: (1) atmospheric temperature structure, (2) snow cover, (3) precipitation, (4) vegetation index, (5) maximum/minimum temperature, (6) insolation, and (7) earth radiation balance. The U.S. civil space program is presently committed to its current geostationary (GOES) and polar (NOAA) programs through this decade and to continue both programs into the next decade with spacecraft carrying improved and augmented instrumentation. GOES VISSR Atmospheric Sounder (VAS) data, presently in research status and available only for special observation periods, will become available operationally in 1987 from the current spacecraft series. GOES-Next will provide additional spectral channels, simultaneous imaging, atmospheric soundings, and possibly increased resolution starting in 1990. The NOAA follow-on spacecraft, in the same time frame, is expected to provide additional spectral channels, improved passive microwave radiometry, and possibly increased spatial resolution. The Landsat program is expected to be continued by a commercial operator following the useful life of Landsat-5. All three follow-on programs are presently at various stages of definition and procurement. Final definition may not be completed until late in 1984. However, their status as of the time of this presentation will be reviewed in detail.     

A simulation study for anticipated accuracy of lunar gravity field model by SELENE tracking data

Results of numerical simulations are presented to examine the global gravity field recovery capability of the Japanese lunar exploration project SELENE (SELenological and ENgineering Explorer) which will be launched in 2007. New characteristics of the SELENE lunar gravimetry include 4-way satellite-to-satellite Doppler tracking of main orbiter and differential VLBI tracking of two small free-flier satellites. It is shown that the proposed satellite constellation will provide the first truly global satellite tracking data coverage. The expected results from these data are; (1) drastic reduction in far-side gravity error, (2) estimation of many gravity coefficients by the observation, not by a priori information, and (3) one order of magnitude improvement over existing gravity models for low-degree field.     

A comparison of different regression models for downscaling Landsat and MODIS land surface temperature images over heterogeneous landscape

Remotely sensed high spatial resolution thermal images are required for various applications in natural resource management. At present, availability of high spatial resolution (<200 m) thermal images are limited. The temporal resolution of such images is also low. Whereas, coarser spatial resolution (∼1000 m) thermal images with high revisiting capability (∼1 day) are freely available. To bridge this gap, present study attempts to downscale coarser spatial resolution thermal image to finer spatial resolution using relationships between land surface temperature (LST) and vegetation indices over a heterogeneous landscape of India. Five regression based models namely (i) Disaggregation of Radiometric Temperature (DisTrad), (ii) Temperature Sharpening (TsHARP), (iii) TsHARP with local variant, (iv) Least median square regression downscaling (LMS_DS) and (v) Pace regression downscaling (PR_DS) are applied to downscale LST of Landsat Thematic Mapper (TM) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) images. All the five models are first evaluated on Landsat image aggregated to 960 m resolution and downscaled to 480 m and 240 m resolution. The downscale accuracy is achieved using LMS_DS and PR_DS models at 240 m resolution at 0.61 °C and 0.75 °C respectively. MODIS data downscaled from 1000 m to 250 m spatial resolution results root mean square error (RMSE) of 1.43 °C and 1.62 °C for LMS_DS and PR_DS models, respectively. The LMS_DS model is less sensitive to outliers in heterogeneous landscape and provides higher accuracy when compared to other models. Downscaling model is found to be suitable for agricultural and vegetated landscapes up to a spatial resolution of 250 m but not applicable to water bodies, dry river bed sand sandy open areas.     

Visual thematic mapping from Landsat and collateral data in support of mineral development

Over the past ten years, the authors and their associates have used Landsat images and collateral data to prepare visual thematic maps. The data are used in a projection-compositor (Procom) system that enlarges Landsat images and other data to scales as great as 1:15 000. Revisions of existing maps for simple themes (e.g. topographic maps) can be completed quickly, accurately and inexpensively. Complex themes, such as geological formations and structures, can be mapped through the optical merging of collateral data sets (e.g. Landsat, geophysics, geology) at a common scale. Such mapping has led to the recognition of a non-parallactic means of obtaining whole image stereo-models with large vertical exaggerations using Landsat images.     

Stereoscopic imaging from polar orbit and synthetic stereo imaging

The photogrammetric determination of cloud top heights from stereoscopic satellite images seems to be a very good solution to this hitherto unresolved problem. Whereas in the U.S.A., stereoscopic imaging is done by use of geosynchronous weather satellites, in Europe such a system cannot be used because there is only one geosynchronous satellite (METEOSAT). An alternative could be a Stero Line Scanner (SLS) operating on a polar orbiter.SLS would scan twice, forward and backward, producing in this way two image strips for steroscopic viewing and photogrammetric measurements from pole to pole. Because of the cloud motion between the two scans, a SLS needs additional independent height information for reference points, e.g. from a Laser Ranger (LAR). The advantage of this method is that cloud motion, and therefore wind, can also be determined for these reference points. Another solution is a system of two SLS satellites flying one after the other and scanning the same area simultaneously. This allows cloud motion determination across the whole image. The use of infrared channels also allows night operation and provides additional data such as improved seas surface temperatures.The DFVLR is currently studying these problems. Synthetic stereoscopic imaging is being used in a forerunner programm to the SLS project and also for simulation in SLS studies.     

Mapping recent agricultural developments in China from satellite data

Landsat data have been employed to study and map agricultural developments in three regions of China: 1) Pearl River delta; 2) Nen River basin; and 3) Xinjiang Autonomous Region. Manual interpretation procedures used in conjunction with multi-date Landsat images and collateral information permitted rice yields to be estimated for the Pearl River delta in 1978. A combination of manual and computer-assisted analyses of Landsat data of Northeast China revealed that more than 15,000 km² of agricultural land in a 184,500 km² study area had been reclaimed from rangeland and marshland. These analyses also indicated a shift in cropping practices, with the foodcrops wheat and corn replacing cash crops such as soybeans. In the arid west, Landsat image data provided valuable input to a geographic information system (GIS). It appears the GIS approach will prove useful for evaluating agricultural land potential in the remote areas of China.     

NASA''S strategy for Mars exploration in the 1990s and beyond

NASA's Office of Space Science is changing its approach to all its missions, both current and future. Budget realities are necessitating that we change the way we do business and the way we look at NASA's role in the U.S. Government. These challenges are being met by a new and innovative approach that focuses on achieving a balanced world-class space science program that requires less U.S. resources while providing an enhanced role for technology and education as integral components of our Research and Development (R&D) programs. Our Mars exploration plans, especially the Mars Surveyor program, are a key feature of this new NASA approach to space science. The Mars Surveyor program will be affordable, engaging to the public with global and close-up images of Mars, have high scientific value, employ a distributed risk strategy (two launches per opportunity), and will use significant advanced technologies.     

木星磁场及磁场模型的对比分析

木星具有太阳系最强的行星磁场,是木星探测面临的基本环境。首先对磁场环境及其数学模型进行了调研,并在研究木星磁场模型以及磁场的数学原理的基础上,使用MATLAB数学工具实现了木星主磁场的计算,对VIP4、VIT4、O6和V1_17ev（eigenvector,特征向量）4个模型与磁测数据进行了对比及分析。研究结果表明这4个模型计算得到的磁场强度范围较为一致,但在全球磁场分布上存在差异,尤其是对磁南极位置的识别上,4个模型的结果都不相同;在对模型计算结果与探测数据的探讨分析中,发现4个模型与探测数据的符合较为一致,偏差均较小。可为木星探测的环境保障提供必要的理论基础和计算模型支撑。     

Extraction of hydrothermal alterations from ASTER SWIR data from east Zanjan,northern Iran

The use of satellite images for mineral exploration has been very successful in pointing out the presence of minerals such as smectite and kaolinite which are important in the identification of hydrothermal alterations. Shortwave infrared (SWIR) bands from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the wavelength of ASTER SWIR bands between 1.65 and 2.43 μm has a good potential for mapping a hydrothermal alteration minerals such as alunite, pyrophyllite, kaolinite, illite–muscovite–sericite, and carbonate. In this range, hydroxide minerals which have been produced by hydrothermal alteration exhibit good absorption compared to shorter or longer wavelengths. In this research which aims to remove atmospheric and topographic effects from ASTER SWIR data, the authors used the log-residual method (LRM) with the minimum noise fraction (MNF) transformation to create a pixel purity index (PPI) which was used to extract the most spectrally pure pixels from multispectral images. Spectral analyses of the clay mineralogy of the study area (east Zanjan, in northern Iran) were obtained by matching the unknown spectra of the purest pixels to the U.S. Geological Survey (USGS) mineral library. Three methods, spectral feature fitting (SFF), spectral angle mapping (SAM), and binary encoding (BE) were used to generate a score between 0 and 1, where a value of 1 indicates a perfect match showing the exact mineral type. In this way, it was possible to identify certain mineral classes, including chlorite, carbonate, calcite–dolomite–magnesite, kaolinite–smectite, alunite, and illite. In this research, two main propylitic and phyllic–argillic zones could be separated using their compositions of these minerals. These two alteration zones are important for porphyry copper deposits and gold mineralization in this part of Iran.     

Enhanced Landsat and HCMM imagery for mineral exploration in contrasting areas of subtropical humid and semi-arid terrain

The role of multispectral and thermal imagery in mineral exploration is evaluated for two areas with favourable geological conditions within contrasting physical environments — one in the semi-arid low tree and shrub savannas of western Queensland and northern South Australia, the other in the humid subtropical forest zone of western Yunnan, China.For both areas Landsat imagery was used to identify structures and lithologies favourable for mineralization and locate ironstones/gossans indicative of mineralized bedrock. HCMM imagery was used alongside Landsat imagery to identify former and ephemeral drainage patterns important for the interpretation of geochemical data over covered ground in Australia. Interpretations were made of enhanced colour composites, outputs of MSS band ratios and colour rotated images generated from both NASA film products and CCTs. These were checked by field studies during which plant, soil and rock chip samples for subsequent metals analyses were collected from areas of anomalous vegetation and from barren ironstones. Some rock chip samples from Australia contained concentrations of copper or lead or small amounts of other metals. In China geobotanical anomalies over ironstones from which soil and rock samples yielded copper, lead, zinc, tin and silver suggest the presence of a major belt of potential multi-metal mineralization.     

NASA/NOAA/USAID implementation of the South Pacific severe storm detection and warning system project

The U.S. Agency for International Development has sponsored this project for implementation by NASA for the Fiji Meteorological Service at the International Airport in Nadi, Fiji. The project will allow precise tracking of all South Pacific tropical cyclones with frequent, high-resolution reception of both the Japanese GMS and the U.S. GOES-West visible and IR cloud images.An interactive computer system will allow color display, data set integration, and cyclone motion/tracking through image-registered time-sequences of images. In addition, the computer will be used for running storm surge numerical models to warn of flood tides in advance of approaching cyclones. The computer will compile storm image sequence climatologies for the development of future storm track prediction algorithms.The full system implementation, checkout and training is scheduled for completion within the next 12 months. This paper will describe the need and use of the system by the Fiji Meteorological Service, data reception, interactive computer techniques, training, and the actual benefits to be derived from the implementation of this system in Fiji for tracking and warning of storm threats throughout the South Pacific Ocean.