Mapping geology and structure using multispectral and hyperspectral data and evaluating topographic correction methods: case study, Salmon river mountains of east‐central Idaho

2005 ◽  
Author(s):  
Yardenia Martinez ◽  
Shuhab Khan ◽  
Paul Link ◽  
Nancy Glenn
Keyword(s):  
Hyperspectral Data ◽  
Topographic Correction ◽  
East Central ◽  
Salmon River ◽  
Central Idaho

Salmon River Arch revisited: new evidence for 1370 Ma rifting near the end of deposition in the Middle Proterozoic Belt basin

1996 ◽  
Vol 33 (7) ◽  
pp. 1037-1052 ◽  
Author(s):  
P. Ted Doughty ◽  
Kevin R. Chamberlain
Keyword(s):  
Tectonic Setting ◽  
Mafic Magma ◽  
Isotopic Analysis ◽  
Magma Intrusion ◽  
Magmatic Complex ◽  
East Central ◽  
Salmon River ◽  
Basin Subsidence ◽  
Belt Supergroup ◽  
Central Idaho

New U–Pb zircon dates on diabase, diorite, and migmatites within a large magmatic complex in east-central Idaho have refined the age and tectonic setting of the East Kootenay orogeny that affected the Belt basin ca. 1370 Ma. These data show that a large volume of mafic magma was injected into the basin in east-central Idaho and followed shortly thereafter by its own felsic differentiate and granitic plutons and metamorphism of the host sediments ca. 1370 Ma. These data show that the magmatic complex and associated gneisses in east-central Idaho are not pre-Belt basement, but contemporaneous in age with the Belt basin. Nd isotopic analysis of the magmatic rocks establishes that they are not derived from known Proterozoic or Archean basement terranes, but could have formed from the host Yellowjacket Formation or juvenile 1.7 Ga crust. Nd isotopic composition of gneisses and the Yellowjacket Formation are interpreted to support previous correlations between these rocks and the Belt Supergroup. Metamorphic barometry on 1370 Ma migmatites intercalated with the magmatic complex constrain the metamorphism to pressures of 450 MPa (14 km) initially and show that pressure increased to 650 MPa (20 km) before the end of metamorphism, which is consistent with magma intrusion into the bottom of the basin, followed by basin subsidence and sediment loading. We postulate that the East Kootenay orogeny is a pulse of bimodal magmatism, basin rifting, and renewed subsidence and sedimentation that shortly preceded the end of deposition in the Belt basin.

Preliminary interpretation of thrust-fault patterns in western Montana and east-central Idaho

1982 ◽  
Author(s):  
C.A. Wallace ◽  
E.T. Ruppel ◽  
J.E. Harrison ◽  
M.W. Reynolds
Keyword(s):  
Thrust Fault ◽  
Western Montana ◽  
East Central ◽  
Central Idaho

GEOLOGIC MAPPING OF NEOPROTEROZOIC TO ORDOVICIAN STRATA IN THE LOST RIVER AND LEMHI RANGES AND SALMON RIVER MOUNTAINS, CENTRAL IDAHO

2020 ◽  
Author(s):  
Paul K. Link ◽  
◽  
Daniel T. Brennan ◽  
David M. Pearson ◽  
Jacob Milton ◽  
...  
Keyword(s):  
Geologic Mapping ◽  
Salmon River ◽  
Central Idaho

Analytical Perspectives on Prehistoric Migration: A Case Study From East-Central Arizona

1997 ◽  
Vol 24 (5) ◽  
pp. 447-466 ◽  
Author(s):  
Joseph A. Ezzo ◽  
Clark M. Johnson ◽  
T.Douglas Price
Keyword(s):  
East Central ◽  
Prehistoric Migration ◽  
Central Arizona

scholarly journals Geospatial Serverless Computing: Architectures, Tools and Future Directions

2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey
Keyword(s):  
Big Data ◽  
Forest Cover ◽  
Mineral Resources ◽  
Hyperspectral Data ◽  
Real Time Analysis ◽  
First Case ◽  
Amazon Web Services ◽  
Aws Lambda ◽  
Physical Features

Several real-world applications involve the aggregation of physical features corresponding to different geographic and topographic phenomena. This information plays a crucial role in analyzing and predicting several events. The application areas, which often require a real-time analysis, include traffic flow, forest cover, disease monitoring and so on. Thus, most of the existing systems portray some limitations at various levels of processing and implementation. Some of the most commonly observed factors involve lack of reliability, scalability and exceeding computational costs. In this paper, we address different well-known scalable serverless frameworks i.e., Amazon Web Services (AWS) Lambda, Google Cloud Functions and Microsoft Azure Functions for the management of geospatial big data. We discuss some of the existing approaches that are popularly used in analyzing geospatial big data and indicate their limitations. We report the applicability of our proposed framework in context of Cloud Geographic Information System (GIS) platform. An account of some state-of-the-art technologies and tools relevant to our problem domain are discussed. We also visualize performance of the proposed framework in terms of reliability, scalability, speed and security parameters. Furthermore, we present the map overlay analysis, point-cluster analysis, the generated heatmap and clustering analysis. Some relevant statistical plots are also visualized. In this paper, we consider two application case-studies. The first case study was explored using the Mineral Resources Data System (MRDS) dataset, which refers to worldwide density of mineral resources in a country-wise fashion. The second case study was performed using the Fairfax Forecast Households dataset, which signifies the parcel-level household prediction for 30 consecutive years. The proposed model integrates a serverless framework to reduce timing constraints and it also improves the performance associated to geospatial data processing for high-dimensional hyperspectral data.

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