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.     

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.     

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.     

Merging Landsat and spaceborne radar data over Tunisia

Synthetic Aperture Radar data were acquired over Tunisia by Seasat in Aug. 1978 and by SIR-A in Nov. 1981. The radar images are contrasted to the Landsat scenes overlapping the same area. The Landsat images were taken in Aug. 1978 and in Sept. 1981. In this study, subareas of the SIR-A and MSS images are registered to the corresponding Seasat data (1313 lines by 1970 samples). The test site is located East of Kairouan, Tunisia. It is a low relief area with subdesertic climatic conditions. This region was selected for it has been surveyed by both Seasat and SIR-A providing perpendicular radar illumination directions. The multispectral and multitemporal coregistered data set enables comparisons between the systems (radar versus MSS, and Seasat versus SIR-A), and change detection in the desertification processes and on the surface of the playas.     

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.     

Automatic lineament extraction in a heavily vegetated region using Landsat Enhanced Thematic Mapper (ETM+) imagery

Lineament extraction from satellite remotely sensed data has been one of the widely used applications of remote sensing in geology. In fact, recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. However, satellite remotely sensed data acquired in heavily vegetated regions such as tropical rainforest, are vulnerable to higher inherent noise levels attributed to the resultant effects of scattering by clouds and adjacency effects of highly inhomogeneous vegetation cover within the pixel dimension. In this study, we examined the effects of noise levels to lineament extraction using a fully automatic approach, consisting of a combination of edge-line detection algorithms. Ancillary information from a digitized topographic map and image classification was used to discriminate between cultural and natural lineaments from the extracted lineaments. Adapting the combination of edge detection and a line-linking algorithm, we have found the optimal parameters for automatic lineament extraction of such complex areas using Enhanced Thematic Mapper (ETM+) data. A noise level of 30% is the maximum threshold before artifacts are generated. It is therefore concluded that the combination of edge-based and line-linking digital image processing operations with the priori local optimal parameters is crucial in lineament feature extraction in heavily vegetated regions.     

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.     

Hierarchical object oriented classification using very high resolution imagery and LIDAR data over urban areas

Urban land cover information extraction is a hot topic within urban studies. Heterogeneous spectra of high resolution imagery—caused by the inner complexity of urban areas—make it difficult. In this paper a hierarchical object oriented classification method over an urban area is presented. Combining QuickBird imagery and light detection and ranging (LIDAR) data, nine kinds of land cover objects were extracted. The Spectral Shape Index (SSI) method is used to distinguish water and shadow from black body mask, with 100% classification accuracy for water and 95.56% for shadow. Vegetation was extracted by using a Normalized Difference Vegetation Index (NDVI) image at first, and then a more accurate classification result of shrub and grassland is obtained by integrating the height information from LIDAR data. The classification accuracy of shrub was improved from 85.25% to 92.09% and from 82.86% to 97.06% for grassland. More granularity of this classification can be obtained by using this method. High buildings and low buildings can, for example, be distinguished from the original building class. Road class can also be further classified into roads and crossroads. The comparison of the classification accuracy between this method and the traditional pixel-based method indicates that the total accuracy is improved from 69.12% to 89.40%.     

Digital processing of spacelab imagery

A digital technique for processing and analyzing OH-cloud photographs to be retrieved from the ISRO-CNES collaborative experiment on the first Spacelab is presented and discussed here. The method adopted for processing the photographs incorporates into it the following major steps (i) digitising the OH photographs, (ii) applying corrections for vignetting, geometric distortions and brightness variations and (iii) superposing the geographic coordinates on the linearised OH photograph.     

The Big Pine Creek watershed and climate change: A trend analysis of Landsat surface reflectance and PRISM datasets over the last 3 decades

Recent variations in normal meteorological conditions indicate the earth’s climate is changing in ways that may impact delicate ecological balances in sensitive regions. Identifying how those changes are affecting the biosphere is essential if we are going to be able to adapt to those changes and to potentially mitigate their harmful consequences. This paper presents a time series study of an alpine ecosystem in the Big Pine Creek watershed in California’s Eastern Sierra Nevada Mountain’s. Raw Landsat data covering the years 1984 through 2011 is converted to observed surface reflectance and analyzed for trends that would indicate a change in the ecosystem. We found that over the time period of the study, observed surface reflectance shows a general decline across the spectrum while our analysis of environmental data demonstrates statistically significant increases in temperatures. While declining reflectance in the visible and short wave bands are indicators of increased surface cover, the fact that the IR band also shows declines is consistent with a decline in tree density. This study provides a useful insight into the ecological response of the Big Pine Creek watershed to recent climate change. These findings suggest that alpine ecosystems are particularly sensitive to increasing temperatures. If these results are replicated in other alpine watersheds it will demonstrate that the biosphere is already showing the effects of a warmer environment.     

Temporal analysis of suspended solid in Tokyo Bay by Landsat data

The amount of suspended solid (S.S.) discharged from Tokyo metropolitan area is estimated by use of multi-temporal Landsat data from 1979 to 1980. The method to estimate S.S. was verified with sea truth data which was observed with Landsat passes covering Tokyo Bay. The radiometric information is normalized against seasonal change of sun illuminations and atmospheric conditions. Path radiance estimation methods were discussed, because its effects are very sensitive to the estimation of S.S. concentration by Landsat MSS data. Temporal changes of S.S. distribution was also interpreted.     

Computer constructed imagery of distant plasma interaction boundaries

Computer constructed sketches of plasma boundaries arising from the interaction between the solar wind and the magnetosphere can serve as both didactic and research tools. In particular, the structure of the Earth's bow shock can be represented as a nonuniform surface according to the instantaneous orientation of the IMF, and temporal changes in structural distribution can be modeled as a sequence of sketches based on observed sequences of spacecraft-based measurements. Viewed rapidly, such a sequence of sketches can be the basis for representation of plasma processes by computer animation.     

Application potential of SPOT imagery for topographic mapping

The high resolution and good geometric configuration possible with SPOT gives a high potential for the production of 1:100 000 topographic maps. Studies at University College London have investigated this potential with the aid of a simple instrument which will introduce the necessary corrections to level 1b photographic images and orthophotographs and allow stereoscopic viewing of SPOT images and the ability to compile a line map. Accuracy has been investigated by computing ground co-ordinates from image co-ordinates and pixel positions. The methods used and results obtained in this work are described.Work is now going on to investigate the use of digital image processors in the mapping procedures and the use of analytical plotting instruments, and comments on this work and on future developments are made.     

Landsat thematic mapper studies of land cover spatial variability related to hydrology

The Landsat 4 and 5 Thematic Mapper (TM) provides increased spatial, spectral, and radiometric capability relative to the Multispectral Scanner (MSS). Visual inspection of TM imagery confirms this. Land cover detail is evident that would be of use in watershed management and planning activities. Specific studies have been conducted in Georgia, West Virginia, Michigan and Maryland to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations. These studies show that only modest improvements in classification accuracy (Anderson Level I/II) have been achieved using existing classification approaches. An attempt to identify the visibly apparent interstate highways and secondary and residential streets in TM data via conventional approaches failed due to an inability to derive separable spectral signatures. The basis for a non-parametric approach to classification is presented in which roads are identified by locating linear local minima in the greenness transformed dimension. Preliminary results indicate that such a method provides more reliable road locations than MSS or TM used singly.     

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.     

Assessment of plant vitality detection through fluorescence and reflectance imagery

Recent studies of the vegetation fluorescence show that it can be successfully used as an intrinsic indicator of plant photosynthetic activity. With respect to the vegetation spectral reflectance, the chlorophyll (Chl) fluorescence is more specific as an observable of basic biophysical processes in the plant cells. Laser induced fluorescence is widely used in near range remote sensing, but it is not suitable for the global monitoring of vegetation. Decades of active fluorometry studies have collected useful information of leaf reaction to natural and anthropogenic stress. Still the passive fluorescence, the one that could be registered from satellite orbit has still to prove its advantage over widely used reflectance signature. The weakness of the signal and the lack of experience with passive fluorescence measurements require extensive technical, theoretical and experimental studies. New imaging fluorometres are to be designed for measuring steady state fluorescence in controlled and natural conditions.

In order to compare reflectance and steady state fluorescence sensitivity to stress impact, a set of experiments have been conducted under controlled illumination conditions in a bio-chamber, designed by the author’s team. The equipment allows plant vitality to be monitored both by passive fluorescence and spectral reflectance imaging. Different types of stress factors (heat and drought stress, acid impact) were investigated to demonstrate equipments ability in monitoring changes of fluorescence signal. Selected fluorescence images of foliage illustrate an early detection of plant dysfunction and the temporal and spatial spreading of the stress impact. Analysis shows that fluorescence imaging of green plants can be developed as a highly effective early warning remote sensing method, which could have application for an ecosystems’ monitoring along with high-spectral reflectance imagery.     

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.     

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.     

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.     

Landsat monitoring of desert vegetation growth, 1972–1979 using a plant-shadowing model

Landsat digital data spanning the period 1972–1979 were analyzed to monitor the status of vegetation within and outside an exclosure in the northern Sinai (precipitation 100–150 mm/year). This 6×6 km exclosure was fenced off in the summer of 1974 and subsequently has been free from the anthropogenic pressures (overgrazing, cultivation in small fields, and harvesting of dry plants as firewood) that continued outside the exclosure. The recovery of the ecosystem within the exclosure is monitored applying a previously tested model. The model quantitatively describes the reduction in the reflectivity to zenith due to shadowing effects by mostly vertical plants. The darkening (reduction in the reflectivity) in the exclosure was compared to the status before the fencing-off and to the essentially unchanging bare sands outside the exclosure. The vegetation protrusion parameter s (sum of the products of plant height times diameter for a unit area of the surface), calculated from Landsat digital data for the exclosure, increased from essentially zero in 1972 and 1973 to about 0.18 in 1975 and changed only within narrow limits from 1975 to 1979. The s value of 0.18 indicates that if the clumps of the plants protruding from the surface in the exclosure were laid horizontally on the soil, they would cover 18 percent of the area. This parameter provides a quantitative measure of the condition of the ecosystem, but the relation to the total green and/or brown biomass remains to be determined.