IMAGE OF THE DAY
Pleiades Neo Satellite Image - Davis-Monthan Air Force Base - Tucson, Arizona
Copyright © AIRBUS 2021
Pleiades Neo satellite photo of the Davis-Monthan Air Force Base a "Boneyard" in Tucson, Arizona for retired military aircraft. The temperatures of the Arizona desert makes it ideal to prevent erosion of the aircrafts for reuse. The Pleiades Neo satellite constellation provide customers with 30cm panchromatic and 1.2m multispectral satellite imagery with six bands and will offer mono, stereo, and tri-stereo images for various mapping applications. View additional Pleiades Neo satellite imagery gallery.
With over four decades of experience, we use our unique understanding of the oil industry to help you assess risk and reduce expenses. By utilizing old and current multispectral satellite image data, spectral analysis, and sub-pixel classification, old well locations can be recovered and coordinates adjusted to improve the geophysical and geological interpretation "before" additional wells are drilled in the same area. This increases the success ratio considerably, especially when some of the old well locations have coordinate problems in excess of 1 km. Specialty services include recovery and coordinate adjustments of old wells, as well as seismic surveys in heavy jungle and desert terrain.
Multispectral imaging (VNIR), WorldView-3 Short Wave InfraRed (SWIR), and thematic mineral mapping allow researchers to collect reflectance data and absorption properties of soils, rock, and vegetation. By leveraging wavelengths and spectral reflectance data, spectral signatures, invisible to the human eye, can be established for mineral traces located on the surface. Our satellite imaging technology can yield unrivaled insight as to the composition of earth surfaces, greatly aiding geologists, scientists and researchers. This data could be utilized by trained photo geologists to interpret surface lithology, identify clays, oxides, soil types and identify potential locations of minerals, from high and medium resolution satellite imagery.
Satellite Imaging Corporation (SIC) has developed comprehensive policy and procedures to include QA and QC in the planning stage of every project involving the use of satellite, aerial, and UAV remote sensing data for GIS mapping. Using our extensive array of advanced satellite sensors to acquire new imagery, or use customer provided UAV imagery, we can provide you with unparalleled quality and geospatial accuracy to support your 2D or 3D GIS map applications such as precision agriculture mapping, land-cover classifications, change-detection from detailed VNIR, SWIR satellite imagery, Hyperspectral analysis to initiate or update Artificial Intelligence (AI), Machine Learning (ML), Computer Vision (CV) algorithms and management systems.
Mitigate business risks, accelerate pipeline planning, learn about the surface composition, and predict environmental impact using the solutions we have tailored to enhance mining and energy projects.
From construction site selection and evaluation to the assessment of existing structures, we have solutions designed to help facilitate every step of your project.
Defense agencies, military contractors, and law enforcement are continually faced with new challenges. We provide an unrivaled advantage when planning strategic and tactical operations, carrying out combat missions, and developing simulations.
Our geographic information systems (GIS) technology solutions for mapping data are produced in a manually, visually, and consumable manner.
When time counts, you can rely on our satellite image data — collected before and after a natural or manmade disaster — to provide crucial insight for disaster response efforts and insurance operations.
Our proven methods are to keep an eye on the environment, enhance coastline management efforts, assess forests, and facilitate the development of agricultural resources. Utilizing our cost-effective satellite and UAV remote sensing services and artificial neural network processing, we can improve the quality of the results retrieved at a lower cost using remote sensing algorithms.