Landscape Texture Research Articles

The Importance of Pocket Parks on Air Quality: A Comparative Approach

Population growth, increasing construction, and impervious surfaces are among the factors leading to the deterioration of the natural balance. Increasing population density has led to a gradual decrease in green areas for living spaces, transport routes and car parks. In addition, the rate of urbanisation and related environmental problems are one of the biggest threats to the sustainability of open green spaces. Accurate identification of problems, such as air, water, and soil pollution is critical to addressing current environmental problems and preventing future problems. Air pollution poses a significant threat to the global community and has sequential impacts on health systems, ecosystems and economies in both developed and developing countries. Cities are home to 50 per cent of the world's population and are expected to reach 70 per cent by 2050. The rapid urbanisation process leads to the transformation of natural and semi-natural landscapes into impervious surfaces and increased heat absorption rates. This study focuses on Jumeirah Island in Dubai. This artificial island is home to many businesses that support social life. Each café in these areas is located with public green areas in front of it and its own open spaces. In the study, 40 measurement points were established in two contrasting environmental conditions and air quality measurements were made manually. The stations are divided into blue and red stations and have contrasting characteristics. While the red measurement points have more green areas, water elements, qualified landscape texture, the blue measurement points have these characters to a lesser extent. Thanks to this comparison, the effect of vegetation texture and pocket parks on air quality in the study area was analysed. As a result of the analyses, the air quality in both areas was found to be good and acceptable, while the results at the red measurement points were found to be of better quality than the blue measurement stations. As a result of the study, the effect of water elements, qualified landscape design and vegetative texture on air quality has been proved with numerical data.

A Preliminary Study on the Transformation Strategy of Old Districts from the Perspective of Stock Planning ———Taking Xining City,Qinghai Province Tieluweimin District as an Example

In the process of rapid urbanization in China, urban diseases have gradually emerged, among which the dilapidation of old settlements, as one of the major urban diseases, has received widespread attention from society. From the experience of existing settlements’ transformation, the transformation mode of large-scale demolition and construction not only destroys the neighborhood’s landscape texture and the spirit of place, but also leads to the waste of resources and high development costs. The proposal of stock planning provides a new way of thinking for further rationalization of the way and method of transformation of old cities, which improves the efficiency of construction land and makes urban land more intensive. Based on the background of the transformation of old settlements and the exploration of the academic community, the study selects the Tieluweimin district of Xining City, Qinghai Province, which is adjacent to the railway station and related to the image of the gateway to the city, as a case study. From the perspective of stock planning, drawing on its relevant theories and practical experience, the study examins the existing problems of the district on the basis of a thorough research of the district, and at the same time, combined with its own features and characteristics, it examins the overall environment from the outdoor area, At the same time, combined with its own characteristics and features, it puts forward a “micro” transformation strategy for the district in four aspects: overall outdoor environment, infrastructure renovation, revitalization of cultural industries, and enhancement of management services, with a view to providing a realistic basis and strategic reference for the current transformation of old districts.

Ecological Wisdom and Inheritance Thinking of the Traditional Village’s Water Resources Management in Taihang Mountains

ABSTRACT In the context of China’s rapid urbanization, the landscape texture and ecosystem of traditional villages are being constructively damaged, especially the water ecosystem responsible for maintaining the sustainable development of villages. It is urgent to explore the green construction technology of traditional villages. However, some traditional villages in Taihang Mountain area exist and develop in the environment of drought and flood, which contains rich ecological water resources management wisdom. Therefore, in this paper, Taihang Mountain is selected as the research area to collect data through literature analysis, field research, and in-depth interviews. This study uses ArcGIS spatial analysis and statistical functions to analyze the acquired data and explore the water resources management practices of traditional villages based on three aspects: safety, function, and spirit. Then it summarizes four key inspirations for contemporary water resources management: “adapt to local conditions, pay equal attention to water use and prevention”; “division of labor and cooperation complement each other”, “low cost, low technology, low maintenance” and “make the best use of materials and compound functions”. These advantageous insights can be offered for the preservation of traditional villages, the enhancement of the living environment, and the management and growth of urban stormwater.

Remote sensing‐supported mapping of the activity of a subterranean landscape engineer across an afro‐alpine ecosystem

AbstractSubterranean animals act as ecosystem engineers, for example, through soil perturbation and herbivory, shaping their environments worldwide. As the occurrence of animals is often linked to above‐ground features such as plant species composition or landscape textures, satellite‐based remote sensing approaches can be used to predict the distribution of subterranean species. Here, we combine in‐situ collected vegetation composition data with remotely sensed data to improve the prediction of a subterranean species across a large spatial scale. We compared three machine learning‐based modeling strategies, including field and satellite‐based remote sensing data to different extents, in order to predict the distribution of the subterranean giant root‐rat GRR, Tachyoryctes macrocephalus, an endangered rodent species endemic to the Bale Mountains in southeast Ethiopia. We included no, some and extensive fieldwork data in the modeling to test how these data improved prediction quality. We found prediction quality to be particularly dependent on the spatial coverage of the training data. Species distributions were best predicted by using texture metrics and eyeball‐selected data points of landscape marks created by the GRR. Vegetation composition as a predictor showed the lowest contribution to model performance and lacked spatial accuracy. Our results suggest that the time‐consuming collection of vegetation data in the field is not necessarily required for the prediction of subterranean species that leave traceable above‐ground landscape marks like the GRR. Instead, remotely sensed and spatially eyeball‐selected presence data of subterranean species could profoundly enhance predictions. The usage of remote sensing‐derived texture metrics has great potential for improving the distribution modeling of subterranean species, especially in arid ecosystems.

Vegetation Dispersion, Interspersion, and Landscape Preference.

The spatial aggregation/dispersion of the vegetation in a landscape affects landscape texture, with potentially important implications for its perception. The aim of the study was to investigate how plant dispersion and interspersion in small-scale landscapes could affect garden preference. Dispersion referred to the proximity and distance between plants, and interspersion referred to the degree of intermixing between plants of different species. Fifty-six participants evaluated 40 pairs of landscapes that differed in terms of plant dispersion or plant interspersion. Participants were asked to rate their preference for each pair of landscapes. Furthermore, eye movements were recorded during the viewing time, and the number of fixations and fixation time were computed for each landscape image. Overall, plants arranged in a more dispersed and a more interspersed design resulted in a higher landscape preference. Dispersion was more effective than interspersion in affecting landscape preference. The number of fixations and fixation time were higher when viewing landscapes with plants arranged in a high-dispersion and high-interspersion layout.

Tectonic Control of the Nanggulan Formation Based on Morphometric Analysis in Kulon Progo, Indonesia

DOI:10.17014/ijog.9.2.147-157Outcrop of Nanggulan Formation, surrounded by Old Andesite Formation (OAF) in the eastern part of Kulon Progo Dome, is very limited. Tectonic control is interpreted as a contributing factor. Tectonic activity can be shown by a morphometric aspect. The research purpose was to calculate the valley floor - valley height ratio, stream gradient index, and drainage density of Nanggulan and Old Andesite Formations. The method used is field survey and Shuttle Radar Topography Mission analysis. The field survey focused on Clumprit, Klepu, and Kalisonggo Rivers. The total number of valley segments for the Nanggulan Formation is 223 with the valley length of 4.62 km, while OAF is 101 with a valley length of 3.55 km. SRTM analysis showed that the valley segment in OAF was 55, and valley length was 1.48 km. The valley floor - valley height ratio measured in the Nanggulan Formation is ten valleys and OAF is eight valleys. In Nanggulan Formation, the valley floor - valley height ratio value is from 1.00 to 5.46 (low uplift), whilst in OAF, the results vary: as 1.35 to 4.58 (low uplift), 0.59 (medium uplift), and 0.43 (high uplift). The stream gradient index value of the Nanggulan Formation is 460.47 (medium tectonic), while OAF is 723.84 (high tectonic). The drainage density value of the Nanggulan Formation is 10.35 km/km2 (very smooth landscape texture) and OAF is 10.35 km/km2 (somewhat smooth landscape texture). Morphometry proves that Nanggulan Formation tectonic activity is more active, causing the Nanggulan Formation to be exposed to the surface.

Высотная организация равнинных ландшафтов (на примере Центрального Черноземья России)

Absolute and relative terrain altitudes are an important factor in the genesis of geosystems. They determine differences in morphometry indicators, intensity and direction of landscape-forming processes, and landscape patterns. The study objective is to identify the relationships between altitudes and landscape metrics at four scale levels. The forest-steppe zone of the Central Black Earth Region of Russia was chosen as a study area. Authors of the article created a digital elevation model and a landscape map for the area, then conducted morphometric, hydrological, insolation, and textural analyses. Applying grids with different cell-sizes, the analyses results were obtained and stored into a spatial database. Authors divided the obtained indicators into three groups: condition, process, result. The regression analysis showed that the dependence of the relief dissection parameters on the absolute altitudes decreases with the increase of the study scale. The dependence of the indicators of landscape-forming processes and landscape textures on the relative heights increase when the study scale decreases. Ranking of the greed cells by indicators of absolute and relative heights made it possible to identify morphologically and dynamically unified altitudinal landscape systems. As one of the research results, the authors of the article devised a taxonomic scheme of altitudinal landscape systems, which included the division, class, subclass, type, subtype, family, genus, species, and subspecies categories.

Analyzing and Predicting Land Use and Land Cover Changes in New Jersey Using Multi-Layer Perceptron–Markov Chain Model

This study analyzed the changes of land use and land cover (LULC) in New Jersey in the United States from 2007 to 2012. The goal was to identify the driving factors of these changes and to project the five-year trend to 2100. LULC data was obtained from the New Jersey Department of Environmental Protection. The original 86 classes were reclassified to 11 classes. Data analysis and projection were performed using TerrSet 2020. Results from 2007 to 2012 showed that the rate of LULC changes was relatively small. Most changes happened to brush/grasslands, mixed forest lands, farmlands and urban/developed lands. Urban/developed lands and the mixed-forest cover gained while farmlands lost. Using a multi-layer perceptron–Markov chain (MLP–MC) model, we projected the 2015 LULC and validated by actual data to produce a 2100 LULC. Changes from 2012 to 2100 showed that urban/developed lands, as well as brush/grasslands, would continue to gain, while farmlands would lose, although the projected landscape texture would likely be identical to the 2012 landscape. Human and natural factors were discussed. It was concluded that the MLP–MC model could be a useful model to predict short-term LULC change. Unexpected factors are likely to interfere in a long-term projection.

Area-Wide Prediction of Vertebrate and Invertebrate Hole Density and Depth across a Climate Gradient in Chile Based on UAV and Machine Learning

Burrowing animals are important ecosystem engineers affecting soil properties, as their burrowing activity leads to the redistribution of nutrients and soil carbon sequestration. The magnitude of these effects depends on the spatial density and depth of such burrows, but a method to derive this type of spatially explicit data is still lacking. In this study, we test the potential of using consumer-oriented UAV RGB imagery to determine the density and depth of holes created by burrowing animals at four study sites along a climate gradient in Chile, by combining UAV data with empirical field plot observations and machine learning techniques. To enhance the limited spectral information in RGB imagery, we derived spatial layers representing vegetation type and height and used landscape textures and diversity to predict hole parameters. Across-site models for hole density generally performed better than those for depth, where the best-performing model was for the invertebrate hole density (R2 = 0.62). The best models at individual study sites were obtained for hole density in the arid climate zone (R2 = 0.75 and 0.68 for invertebrates and vertebrates, respectively). Hole depth models only showed good to fair performance. Regarding predictor importance, the models heavily relied on vegetation height, texture metrics, and diversity indices.

METHODOLOGICAL PROPOSALS FOR ADDRESSING AGROECOLOGICAL DESIGN IN PERIURBAN AREAS: A CASE STUDY IN THE EDGES OF MILAN (ITALY)

This study aims to develop an ecological-based design model, applying the theoretical basis of landscape ecology and phytosociology on a pilot area located in the Milan South-Eastern rural edges. The goal was to integrate an all-inclusive approach for agroecological regeneration. Three main guidelines were identified: 1. the rehabilitation of landscape texture; 2. internal diversification; 3. environmental consistency. The study led to a global evaluation of the ecological functionality of the different environmental compartments, analysing their weaknesses and resiliences. Consequently, design criterions were defined, regarding the landscape level (ecotopes diversification) and the single ecotope level (vegetational standards), reconfiguring the current uses and functions and enhancing the biological and structural diversity within the agroecosystem. Finally, an evaluation of the benefits on ecological functionality was carried out, as well as a qualitative assessment of the ecosystem services that can be delivered. This approach enabled to make direct comparisons between actual and project scenarios, supporting the readability of the rebalancing effects attainable on the environmental, social and economic scale.

Investigating the urban–rural integrated town development strategy on the basis of the study of rural forms in Nantong, China

Urban–rural integrated development is the priority task of China due to the wide development gap between cities and villages caused by the most rapid economic growth in history. In the province–city–town–village administrative system of China, town, as the smallest urban form, is the social, economic, and cultural center of a rural area and becomes the key to many development problems. An improved township enhances living standards and creates numerous jobs in rural areas, and it will provide opportunities for urban–rural sustainable integration. This paper introduces three typical rural forms in Nantong and demonstrates the objective fact that rural form is an important manifestation of residents’ living habits, historical context, and the regional characteristics of rural areas. Then, this study aims to find the close inner relationship between rural form and town development through a comparative study of morphological indicators. Therefore, on the basis of full understanding of rural forms, this study proposes that town development from the perspective of serving the countryside, improving the quality of life of rural residents, and protecting the rural landscape texture with regional characteristics is the development mode conforming to the spirit of sustainable development.

Expression of Fractals Through Neural Network Functions

To help understand the underlying mechanisms of neural networks (NNs), several groups have studied the number of linear regions $\ell $ of piecewise linear (PwL) functions, generated by deep neural networks (DNN). In particular, they showed that $\ell $ can grow exponentially with the number of network parameters $p$ , a property often used to explain the advantages of deep over shallow NNs. Nonetheless, a dimension argument shows that DNNs cannot generate all PwL functions with $\ell $ linear regions when $\ell > p$ . It is thus natural to seek to characterize specific families of functions with $\ell > p$ linear regions that can be constructed by DNNs. Iterated Function Systems (IFS) recursively construct a sequence of PwL functions $F_{k}$ with a number of linear regions which is exponential in $k$ . We show that $F_{k}$ can be generated by a NN using only $\mathcal {O}(k)$ parameters. IFS are used extensively to generate natural-looking landscape textures in artificial images as well as for compression of natural images. The surprisingly good performance of this compression suggests that human visual system may lock in on self-similarities. The combination of this phenomenon with the capacity of DNNs to efficiently approximate IFS may contribute to the success of DNNs, particularly striking for image processing tasks.

Contributions of landscape heterogeneity within the footprint of eddy-covariance towers to flux measurements

Flux measurements based on aerodynamic principles (e.g., eddy covariance method, or EC) assume the vegetation and landform within the footprint must be flat, large, and homogeneous, although very rarely do flux tower sites meet such requirements. Here, using two long term EC tower sites in Mongolian grasslands, we test a hypothesis that the magnitude and variation of EC flux measurements are partially dependent of landscape heterogeneity. We define landscape heterogeneity as the spatial composition and distribution of components within the footprint of a flux tower, which was quantified using high resolution WorldView-2 images to extract vegetation texture features (Contrast, Dissimilarity and Entropy). Bayesian analysis was performed to model the linkage of landscape heterogeneity with EC fluxes of CO2 in 8 intercardinal directions by dissecting it into 5 distances. We found that higher levels of landscape heterogeneity have an impact on flux measurements, especially under stable conditions. Specifically, a total of 24 Bayesian models based on the EVI-derived texture features passed the Gelman and Rubin convergence diagnostic statistic test. A positive relationship is shown between the percentage of footprint cover (Footprint%sector) and landscape texture features (Contrast and Dissimilarity), with the footprint cover acting as a function of heterogeneity under stable conditions. Negative effects were found when modeling CO2 flux (Fcsector) with Contrast under stable and unstable conditions, and with Dissimilarity and Entropy under stable conditions. With increases in high resolution remote sensing images and UAV technology (e.g., LiDAR), the results and approaches outlined in this study highlight new frontiers and opportunities for the FLUXNET community to integrate flux measurements and high-resolution remote sensing data, promoting a new generation of footprint models, and exploring the cohesive connections between flux measurements and the underlying processes (e.g., soil, physiological, ecosystem processes).

Landscape texture in anthropogenically transformed regions: The example of Upper Silesia and the Dąbrowa Coal Basin (southern Poland)

In recent years, we see growing importance of research on landscape texture, which enables scientists to assess landscape as to its esthetic (visual), planning, as well as ecological aspects. Analyses of landscape texture result in identification of landscape zones, classified according to their habitability, recreational potential and suitability for industry, which plays a crucial role for work on planning and strategic documents. The study area covers 12 selected municipalities of Upper Silesia and the Dąbrowa Coal Basin, which are highly industrialized regions. Combining an analysis of the degree of landscape enclosure/openness with an analysis of morphological diversity in the study area, the author identifies landscape texture units in accordance with the new, more detailed typology. This results in the emergence of 36 landscape texture types that take into account the land relief forms in the study area. For the needs of further analyses, these types are classified into three groups: open, mosaic and enclosed landscapes.

An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a “MODIS-concurrent” approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a “pre-MODIS era” approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT reflects a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from MODIS observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir reflectance ratios as a bridge between the Landsat and MODIS scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes. We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach respectively with that from the “concurrent” approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the “pre-MODIS era” LUT approach is highly consistent (R2=0.988, the scene-averaged low RMSE=0.009 and bias=−0.005) with that generated by the earlier “concurrent” approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the “pre-MODIS” LUT and “concurrent” approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.

The Performance Evaluation of Glass Fiber Reinforced Concrete (GFRC)

This study is intended to propose the performance standards and performance test standards of artificial rocks through investigation of standards, guidelines and other literature home and abroad, testing, and site-survey. As a result, the selected performance requirements include a total of 15 items: structural safety (flexural, compressive, impact strength), durability (crack, corrosion resistance, fire resistance), landscape (texture, discoloration, color), environmental load reduction (CO2 reduction rate, materials recycling rate, water quality and soil), and ecological performance (biodiversity, ecological similarity, ecosystem function damage reduction).

An algorithm for the retrieval of 30-m snow-free albedo from Landsat surface reflectance and MODIS BRDF

We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos may be used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of ±0.02–0.05 for these validation sites during available clear days in 2003–2005, with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.

Landscape texture set to scale

Why, in many landscapes, does ridge–valley spacing show such regularity? The combination of high-resolution data and an elegant model offers a solution to this long-standing puzzle, for some cases at least. Seen from above, it's clear that in many hilly landscapes the ridges and valleys appear uniformly spaced. Current physically based models of landscape evolution produce realistic looking topography, but cannot predict the 'wavelength' typical of evenly spaced ridges and valleys in natural landscapes. Taylor Perron and colleagues use equations of mass conservation and sediment transport to derive a characteristic length scale that is directly proportional to the ridge–valley wavelength in models of landform evolution and at five field study sites across the United States, including Nappa Valley in California and Point of the Mountain in Utah. The findings provide a quantitative explanation for one of the most widely observed characteristics of landscapes and suggest that valley spacing records the effects of material properties and climate on erosional processes.

Assessing functional landscape connectivity for disturbance propagation on regional scales—A cost-surface model approach applied to surface fire spread

Leaning on concepts from landscape ecology and functional landscape connectivity, we formulated and developed an operational definition of regional connectivity using a cost-surface modelling approach to assess fire connectivity whereby its structural and spatial components are explicitly isolated. Once the model is calibrated, it allows comparing different scenarios of vegetation composition and moisture contents. The use of commonly available input data and an easy to implement method to code resistance to fire propagation for a given landscape facilitates the application of this approach to other areas of interest. Functional landscape connectivity with regard to fire propagation is expressed through cost surfaces that are computed from a fire friction map and a random set of ignition points. The spatial complexity of the cost surfaces is assumed to be proportional to the landscape connectivity, and its fractal properties are used to measure and describe such spatial complexity. The fractal dimension of a cost-surface serves to assess the regional connectivity in terms of the spatial structure of frictions to fire spread, while the mean value of a cost-surface describes the overall resistance to fire propagation across the landscape in a lumped, non-spatial form. The fire friction map is derived using objective and empirically confirmed techniques enabling to account for the major factors of general fire behaviour. Furthermore, an easy to implement and repeatable method is presented to select the optimum size of random sets of ignition points, implicitly fine-tuned to the spatial variation of the input data. The model was tested on running a number of landscape scenarios based on a NFFL fuel model map. An initial series of runs served to select an optimum number of ignition points and to assess the model sensitivity to fuel moisture. Then, a set of three scenarios of vegetation cover change was devised by replacing a fast fuel model by slower fuels, and the existing network of fuelbreaks was also overlaid. The model performed as expected by quantifying the differential resistance to fire spread implicit to such scenarios. As an overall result, our model indicates that reducing the length scale of the landscape texture has a greater effect preventing fire connectivity than creating large, homogeneous patches of fire resistant vegetation.

The role of remote sensing in finding hydrothermal mineral deposits on earth.

The identification of surface mineralogical composition using hyperspectral sensors is now the major remote sensing opportunity for exploration geologists seeking refined vectors to potential ore-bearing hydrothermal systems. This involves no less than remote, visible and infrared spectroscopy of the molecular composition of geological materials from remote platforms using a large number of calibrated spectral bands. From field-portable systems to those flying in high-flying aircraft on the edges of space, it is now possible to define a long list of minerals and their weathering products detectable at these wavelengths. These include hydroxyl-bearing minerals such as hydrothermal clays, sulfates, ammonium-bearing minerals, phyllosilicates, iron oxides, carbonates, and a wide range of silicates. Indeed, even the chemical composition of micas and chlorites has been mapped remotely using subtle wavelength shifts in their diagnostic reflectance spectra, indicating varying degrees of Na, K, Al, Mg and Fe substitution. Spatial zones, relative abundances and assemblages of these minerals allow geologists to reconstruct the mineralogical, chemical and sometimes thermal disposition of ancient hydrothermal systems in their search for optimal drilling targets. Such minerals not only result directly from the hydrothermal processes involved but may also 'expose' older host rocks caught up in the process and brought to the surface. New microwave radar systems are also shedding new light on landscape processes, textures and structure and occasionally penetrating dry surface layers to reveal buried structures.