Drainage map of Colorado

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Preliminary map of Central Colorado showing the region surveyed in 1873 and 1874

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Philips' map of Egypt and the Soudan, including the Valley of the Nile, the Red Sea, Abyssinia, Arabia, etc

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Natal : nach: map of the Colony of the Cape of Good Hope and neighbouring territories 1895

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Geological sketch map of New Zealand constructed from official surveys and the explorations of F. von Hochstetter, Julius Haast and others

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Track of HSMS Sophia tracing the extent of navigable water along the main northern ice between Spitzbergen and Greenland September 1868 : also showing the nature of the ice and temperature and depth of the sea

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Geological map of Europe exhibiting the different systems of rocks according to the most recent researches and inedited materials by Roderick I. Murchison and James Nicol ; constructed by A. Keith Johnston

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Map of the United States and territories showing the extent of public surveys and military reservations, land grant R.R., rail roads, canals, and other details ...

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

A new map of Denmark, Norway, Sweden, & Moscovy shewing their present general divisions, cheif, [!] cities or towns, rivers, mountains, &c.

[N. 1:8500000].

A new map of Denmark and Sweden. According to ye newest and most exact observations. By H. Moll, geographer.

Kahdessa osassa painettu kartta.

A new & accurate map of the North Pole with all the countries hitherto discovered situated near or adjacent to it as well as some others more remote. Drawn from the latest and best authorities and regulated by astronom.l observat.ns by Eman. Bowen.

0-meridiaani: Lontoo. - Koordinaattiasteikko: N90°-55°[50°].

Viipuri : kartta ja opas = plankarta och vägledning = map of the town = Plan der Stadt.

1:4000.

Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.