Integrating aeromagnetic data and Landsat-8 imagery for detection of post-accretionary shear zones controlling hydrothermal alterations: The Allaqi-Heiani Suture zone,South Eastern Desert,Egypt

The Arabian-Nubian Shield (ANS) underwent a regional carbonation event with CO₂ fluxes derived from the mantle and circulated along post-accretionary shear zones, thus affecting the redistribution of gold mineralization. Formerly, the analyses of remotely-sensed data have suggested regions of gold mineralization linked to the post-accretionary structured framework, but the results were insufficient for detailed prospecting in the ANS. In this research, aeromagnetic data and Landsat-8 imagery were integrated for delineating new high potential zones of gold mineralization in the Allaqi-Heiani Suture (AHS) zone, the ANS, South Eastern Desert (SED) of Egypt. Aeromagnetic data were enhanced using the Center for exploration targeting (CET) grid enhancement technique to detect the main structures that control hydrothermal alterations in the study area. Principal Component Analysis (PCA) technique and ratios of spectral bands were applied to Landsat-8 data for mapping zones of hydrothermal alteration associated with gold mineralization. The traced structural elements from RTP, CET and Landsat-8 maps were statistically plotted and interpreted using rose diagrams. These diagrams indicated that the NW and NE trends are the most dominant in the RTP map and that the intersection zones obtained from the CET analysis are aligned along the NW-oriented trend. While the NNW, WNW and NE trends were the most dominant ones in Landsat maps. The integration of the results indicates several new high potential zones of gold and Cu/Ni mineralization types, which are mostly concentrated at the western part of the AHS zone. The hydrothermal alteration zones and associated gold mineralization are strongly linked to NW, NE, E-W and WNW trending lineaments. The approach used in this study can be applied to other parts of the ANS and other regions with similar geological conditions around the world.     

Mapping ocean dynamic structure using optical spectroscopic measurements from space

Ocean circulation is an important element in many of the large scale experiments planned for the World Climate Program. Satellite infrared data, particularly that from polar oribiting NOAA weather satellites, have demonstrated a capability for showing flow patterns in the ocean in areas where western boundary currents or upwelling provide sufficient thermal contrast. Many areas, however, have thermal contrasts too low to be mapped reliably and other tracers are needed.Images showing variations in the colour (spectral reflectance) of the surface layers of the ocean, from the Coastal Zone Color Scanner on Nimbus 7, have provided excellent examples of flow patterns traced by movements of water bodies having different phytoplankton content. Examples are presented here which show coastal flow patterns off the British Columbia coast, Gulf Stream flow between the New England sea mounts and the form of the Alaskan Stream.Such imagery has only recently become available, and could contribute greatly to a more detailed understanding of ocean circulation. The CZCS was launched in 1978 and is slowly degrading in operation. It appears that a six-year gap in supply of ocean colour imagery may now occur before a replacement can be launched. A large back-log of data remains to be analysed. The CZCS was the first to make this type of measurement and it seems certain that improved sensor designs could increase the value of the data. One such design being developed in Canada makes use of two dimensional arrays of optical detectors to provide greatly increased spectral resolution, and improved sensitivity.     

Canadian Landsat studies for monitoring resource development: A summary

This report summarizes a major paper reviewing Canadian work using Landsat imagery for monitoring the environmental effects of the development of both renewable and non-renewable resources. Landsat has definite advantages for studying resources. In particular, the data are able to show changes in surface cover indicating in many cases development or the exploitation of resources. Monitoring of areas and rates of change over time is possible. Outlined in the paper are examples related to three aspects of resource development. First is the use of Landsat for updating topographic maps for areas where recent developments have taken place. The second aspect is forestry, and examples related to the detection and measurement of clear cuts and recording of areas affected by spruce budworm are reported. Finally, studies of landscape changes produced by mining activities are presented.     

Prospecting in glaciated terrain-integrating airborne and Landsat MSS

The effects of a glacially enriched zone of trace elements on soils and vegetation in the Thetford Mines area of Quebec were investigated using ground information plus digital Multispectral Scanner (MSS) data from airborne and Landsat sensors. The enriched zone was developed during the last glaciation when a southeastward flowing glacier eroded and dispersed an ultrabasic outcrop that had anomalous levels of Ni, Cu, Co, Cr, Mg and Fe.The dispersal train of enriched trace elements was detectable over an area at least 70 × 15 km ‘down-ice’ from the outcrop. In this zone total Ni concentrations in the soil ranged from background levels of 10 ppm to levels in excess of 1800 ppm. The dominant tree species, $\text{Abies}$$\text{balsamea}$ (balsam fir) and $\text{Picea glauca}$ (white spruce) reflect the soil anomaly with higher concentrations of trace elements in their tissue and lower concentrations of chlorophyll.An unsupervised enhancement of Landsat imagery showed that a tonal discontinuity was caused by a vegetation segregation related to the heavy metal enrichment soils. A detailed study based on Landsat MSS data was able to establish regional patterns of chlorophyll production by certain plant species closely related to the ultrabasic dispersal train. Multi-channel airborne MSS data confirmed the Landsat soil-plant patterns.     

Degradation monitoring in Silvo-pastoral systems: A case study of the Mediterranean region of Turkey

To identify policies that will promote positive effects and mitigate negative ones of grazing is a major challenge in the Silvo-pastoral system. This paper presents the role of examining land-cover change trajectories by remote sensing imagery in grazing policy monitoring. The study was conducted for Duzlercami forest ecosystem located in the Mediterranean geographical region of Turkey and administrated by the General Directorate of Forestry (GDF) of the Ministry of Forestry and Water Affairs. Time series land-cover datasets from Landsat images between 1988 and 2016 were collected and classified. To link the conversions among trajectories and grazing policy, class level landscape metrics derived from the classified images were used. To validate the approach, yearly grazing-plans managed by GDF and populations of livestock were used. Results of this research have indicated that even though there is a yearly grazing plan, overgrazing can happen on the pilot site, and it can be easily identified by the destruction of woody vegetation. The notable correlation (r²?=?0.89) between degraded woody vegetation and cattle population has occurred in the last 30?years in the landscape, and Landsat imagery can effectively support the grazing policy mapping and monitoring.     

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.     

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh–Dokhtar Volcanic Belt,Iran

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh–Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.     

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.     

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.     

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.     

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.     

Space platform albedo measurements as indicators of change in arid lands

The change in albedo of arid lands is an indicator of changes in their condition and quality, including density of vegetative cover, erosion, deposition, surficial soil moisture, and man-made change. In general, darkening of an arid land surface indicates an increase in land quality while brightening indicates a decrease in quality, primarily owing to changes in vegetation.Landsat multiband images taken on different dates can be converted to black-and-white albedo images. Subtraction of one image from another, pixel by pixel, results in an albedo change map that can be density sliced to show areas that have brightened or darkened by selected percentages. These maps are then checked in the field to determine the reasons for the changes and to evaluate the changes in land condition and quality.The albedo change mapping technique has been successfully used in the arid lands of western Utah and northern Arizona and has recently been used for detection of coal strip mining activities in northern Alabama.     

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Land surface temperature (LST) is an important factor in global change studies, heat balance and as control for climate change. A comparative study of LST over parts of the Singhbhum Shear Zone in India was undertaken using various emissivity and temperature retrieval algorithms applied on visible and near infrared (VNIR), and thermal infrared (TIR) bands of high resolution Landsat-7 ETM+ imagery. LST results obtained from satellite data of October 26, 2001 and November 2, 2001 through various algorithms were validated with ground measurements collected during satellite overpass. In addition, LST products of MODIS and ASTER were compared with Landsat-7 ETM+ and ground truth data to explore the possibility of using multi-sensor approach in LST monitoring. An image-based dark object subtraction (DOS3) algorithm, which is yet to be tested for LST retrieval, was applied on VNIR bands to obtain atmospheric corrected surface reflectance images. Normalized difference vegetation index (NDVI) was estimated from VNIR reflectance image. Various surface emissivity retrieval algorithms based on NDVI and vegetation proportion were applied to ascertain emissivities of the various land cover categories in the study area in the spectral range of 10.4–12.5 μm. A minimum emissivity value of about 0.95 was observed over the reflective rock body with a maximum of about 0.99 over dense forest. A strong correlation was established between Landsat ETM+ reflectance band 3 and emissivity. Single channel based algorithms were adopted for surface radiance and brightness temperature. Finally, emissivity correction was applied on ‘brightness temperature’ to obtain LST. Estimated LST values obtained from various algorithms were compared with field ground measurements for different land cover categories. LST values obtained after using Valor’s emissivity and single channel equations were best correlated with ground truth temperature. Minimum LST is observed over dense forest as about 26 °C and maximum LST is observed over rock body of about 38 °C. The estimated LST showed that rock bodies, bare soils and built-up areas exhibit higher surface temperatures, while water bodies, agricultural croplands and dense vegetations have lower surface temperatures during the daytime. The accuracy of the estimated LST was within ±2 °C. LST comparison of ASTER and MODIS with Landsat has a maximum difference of 2 °C. Strong correlation was found between LST and spectral radiance of band 6 of Landsat-7 ETM+. Result corroborates the fact that surface temperatures over land use/land cover types are greatly influenced by the amount of vegetation present.     

Digitally produced landsat map images

Two experimental, digitally produced and enhanced, 1:250 000 scale Landsat mosaic maps are described. The first is a map of the Kingdom of Lesotho, produced in collaboration with the Lesotho Director of Surveys and Mapping. It consists of a mosaic of four contiguous Landsat scenes, collected on two consecutive days, digitally enhanced and overlaid with conventional map data (political boundaries, roads, etc). The map is expected to provide useful information on topography, landforms, etc. for planning purposes.The second map, produced in collaboration with the South African Geological Survey, is an experimental map sheet of the Barberton area, consisting of a digital mosaic of two contiguous Landsat scenes. By means of a colour space transformation, stratigraphic geological map information in digital form was combined with the terrain information as contained in the first principal component of the Landsat data.     

Prediction of landslides using ASTER imagery and data mining models

The aim of this study was to identify landslide-related factors using only remotely sensed data and to present landslide susceptibility maps using a geographic information system, data-mining models, an artificial neural network (ANN), and an adaptive neuro-fuzzy interface system (ANFIS). Landslide-related factors were identified in Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. The slope, aspect, and curvature of topographic features were calculated from a digital elevation model that was made using the ASTER imagery. Lineaments, land-cover, and normalized difference vegetative index layers were also extracted from the imagery. Landslide-susceptible areas were analyzed and mapped based on occurrence factors using the ANN and ANFIS. The generalized bell-shaped built-in membership function of the ANFIS was applied to landslide susceptibility mapping. Analytical results were validated using landslide test location data. In the validation results, the ANN model showed 80.42% prediction accuracy and the ANFIS model showed 86.55% prediction accuracy. These results suggest that the ANFIS model has a better performance than does the ANN in predicting landslide susceptibility.     

Status of space science and technology — An Australian perspective

The “Tyranny of Distance” has had a profound influence on Australian history and reaction to it has been an important factor in determining national scientific and technological goals. Because of its size and geographical remoteness, Australia is one of the countries to have gained substantially from the applications of space technology particularly in the fields of communications, meteorology and remote sensing. Australia is the fifth largest investor in INTELSAT which carries a major fraction of the nation's overseas telecommunications. A domestic satellite system, AUSSAT, is being acquired to improve telecommunications within the country. Australia is heavily dependent on satellite data for routine meteorological forecasting. Data from the Australian Landsat Station are in strong demand, particularly for mineral exploration. In the field of space science, Australia is collaborating with Canada and the United States in feasibility studies for STARLAB, a free-flying UV-optical one metre telescope proposed for launch by the US Space Shuttle beginning in 1989. These scientific and technological programs in which Australia is participating are all dependent upon the space programs of other nations and in describing the status of space science and technology from an Australian perspective some comments will be made on particular aspects of the space programs of the United States and Japan.     

Linear and circular structures of the Bohemian Massif — Comparison of satellite and geophysical data

Two structural schemes of the Bohemian Massif are presented and compared. The first one is a result of interpretation of various geophysical data and the second one is compiled on the basis of decoding of space imagery from different sources (Kosmos, Landsat etc.). Both schemes have many structural features in common, but there are diversities namely in the hierarchy of directions and regional distribution of linear structures. These problems are discussed in detail. For example, the most impressive system of structures is the NW-SE system in both schemes, whereas the NE-SW is more remarkable in the geophysical scheme; the N-S and the E-W systems are best expressed in the scheme of photolineaments. These facts are due to the genesis, age, development and dynamic characteristics of respective structural systems. The circular structural features namely those of large size are mostly remarkable in space imagery. At present, they are not distinguished genetically but only described regionally.     

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.     

Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions

By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.     

Spectral transformation of ASTER and Landsat TM bands for lithological mapping of Soghan ophiolite complex,south Iran

Spectral transformation methods, including correlation coefficient (CC) and Optimum Index Factor (OIF), band ratio (BR) and principal component analysis (PCA) were applied to ASTER and Landsat TM bands for lithological mapping of Soghan ophiolitic complex in south of Iran. The results indicated that the methods used evidently showed superior outputs for detecting lithological units in ophiolitic complexes. CC and OIF methods were used to establish enhanced Red–Green–Blue (RGB) color combination bands for discriminating lithological units. A specialized band ratio (4/1, 4/5, 4/7 in RGB) was developed using ASTER bands to differentiate lithological units in ophiolitic complexes. The band ratio effectively detected serpentinite dunite as host rock of chromite ore deposits from surrounding lithological units in the study area. Principal component images derived from first three bands of ASTER and Landsat TM produced well results for lithological mapping applications. ASTER bands contain improved spectral characteristics and higher spatial resolution for detecting serpentinite dunite in ophiolitic complexes. The developed approach used in this study offers great potential for lithological mapping using ASTER and Landsat TM bands, which contributes in economic geology for prospecting chromite ore deposits associated with ophiolitic complexes.