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YOUR HIGH RESOLUTION SATELLITE DATA SOURCE

Geographic information systems and satellite monitoring

Proxima offers all types of space imagery
with the required characteristics.

What is Remote Sensing?

Remote sensing is the acquiring of information from a distance. Remote sensors, which provide a global perspective and a wealth of data about Earth systems, enable data-informed decision making based on the current and future state of our planet.

Optical remote sensing satellites use reflected light to detect electromagnetic energy on the Earth's surface. The energy level is represented by the electromagnetic spectrum, which is the range of energy emanating from the Sun. Electromagnetic energy is reflected from the Earth's surface to a satellite sensor, which collects and records information about this energy. This information is transmitted to the receiving station in the form of data, which is converted into an image.

Spatial resolution of satellite images

Spatial resolution is one of the key parameters of satellite imagery and refers to the level of detail that can be obtained from a scene. It is the size of a single pixel on the ground and can be measured in several ways. One of the most common is ground distance (GSD), the distance between the center points of each pixel. GSD is a measure of how large each pixel on earth is. The smaller number means better details.

As a rule, we divide spatial resolution into the following categories:

Low resolution: more than 60m / pixel
Medium resolution: 10-30m / pixel
High to very high resolution: 30cm-5m / pixel

Satellite data of low and medium resolution

Advantages:

Disadvantages:

A huge amount of free archive data with global coverage in the public domain.

Satellite imagery sources such as ESA Sentinel data and NASA / USGS Landsat data provide 40 years of archive data and different spectral ranges for various industries.

Limited possibilities in details, only large details are visible.

As mentioned above, although satellite data with low and medium resolution have significant advantages, they have a low level of detail.

The valuable spectral information contained in each low and medium resolution satellite image gives a significant advantage for using this data.

A large number of spectral analysis capabilities, low to medium resolution, although not high resolution, have significant advantages if you want to understand the big area.

If you want to define common objects such as bridges, street models, or land use, this kind of data is perfect. But you will not be able to distinguish smaller objects such as cars, houses or trees.

Use low to medium resolution images to make the most of their spectral value and if you are interested in understanding larger scale features over time.

High and Ultra High Resolution Satellite Data

Advantages:

Disadvantages:

Very high level of detail

The striking advantage of high-resolution satellite imagery is that you can distinguish and identify small objects, such as individual cars, houses, or trees.

Higher resolution comes with a higher price tag

When using high and very high resolution images, remember that accurate detail and high resolution images are only possible with better sensors and satellites. So it comes with a higher price tag.

Possibilities for setting tasks

With high-resolution commercial satellites, you can pinpoint exactly where and when you want to capture images. This, known as satellite targeting, allows you to flexibly tune satellite targets to survey the areas of interest (AOI) when you need them most.

Smaller area covered

Typically, the higher the resolution, the less the total land area is visible in the image. This is good news if you want to do fine-scale monitoring or analysis.

Space imagery processing levels:

Level 0

Level 0 snapshots are raw instrument data, exactly as they were collected by the sensor.

Level 1A

Radiometric correction of distortions caused by differences in sensitivity of individual sensors.

Level 1B

Radiometric correction at processing level 1A and geometric correction of systematic sensor distortions, including panoramic distortions, distortions caused by the rotation and curvature of the Earth, fluctuations in the altitude of the satellite orbit.

Level 2A

Image correction at 1B level and correction in accordance with the specified geometric projection without using ground control points. For geometric correction, a global digital elevation model (DEM, DEM) with a ground step of 1 km is used. The geometric correction used removes systematic sensor distortions and projects the image into a standard projection (UTM WGS-84) using known parameters (satellite ephemeris data, spatial position, etc.).

Level 2B

Image correction at 1B level and correction in accordance with a given geometric projection using ground control points;

Level 3

Image correction at 2B level plus correction using terrain DEM (orthorectification).

Level S

Correcting the image using the reference image.

Optical satellites

Proxima is the official distributor of foreign satellite operators and supplies all types of space imagery with the required characteristics.

KOMPSAT-2

Launch date: Jul 28, 2006
Orbital altitude: 685 km.
GSD: 1m PAN / 4m MS
Shooting swath width: 15 km.
Spectral channels:
Panchromatic: 500-900 nm
Blue: 450-520nm
Green: 520-600 nm
Red: 630-690 nm
NIR: 760-900 nm

KOMPSAT-3

Launch date: May 17, 2012
Orbital altitude: 685.13 km.
GSD: 0.5m PAN / 2.0m MS
Shooting swath width: 16 km
Spectral bands:
PAN: 450 ~ 900nm
Blue: 450 ~ 520nm
Green: 520 ~ 600nm
Red: 630 ~ 690nm
NIR: 760 ~ 900nm

KOMPSAT-3A

Launch date: March 25, 2015
Orbital altitude: 528 km.
GSD: 0.4m PAN / 1.6m MS
Shooting swath width: 13 km
Spectral bands:
PAN: 450 ~ 900nm
Blue: 450 ~ 520nm
Green: 520 ~ 600nm
Red: 630 ~ 690nm
NIR: 760 ~ 900nm

SUPERVIEW

4 satellites in the constellation
Launch date: 2016, 2018
Orbital altitude: 530 km.
GSD: 0.4-0.5m PAN / 1.6-2.0m MS
Shooting swath width: 12 km
Stereo: Available
Spectral channels:
Panchromatic: 0.45-0.89 μm
Blue: 0.45-0.52μm
Green: 0.52-0.59 μm
Red: 0.63-0.69 μm
NIR: 0.77-0.89 μm

GAOFEN-1

Orbit altitude: 645 km
GSD: 2m PAN / 8m MS
Shooting swath width: 60 km
Spectral channels:
Panchromatic: 45-0.90 μm
Blue: 0.45-0.52 μm
Green: 0.52-0.59 μm
Red: 0.63-0.69 μm
NIR: 0.77-0.89 μm

GAOFEN-2

Launch date: Aug 2014
Orbital altitude: 631 km.
GSD: 0.8m PAN / 3.24m MS
Shooting swath width: 45 km
Spectral channels:
Panchromatic: 450-700 nm
Blue: 450-520nm
Green: 520-590 nm
Red: 630-690 nm
NIR: 770-890 nm

GAOFEN-7

Launch date: November 2019
Orbital altitude: 500 km.
GSD: 0.65m PAN / 2.6m MS
Shooting swath width: 20 km
Spectral channels:
Panchromatic: 450-700 nm
Blue: 450-520nm
Green: 520-590 nm
Red: 630-690 nm
NIR: 770-890 nm

JILIN GXA

Launch date: 2015
Orbital altitude: 650 km.
GSD: 0.72m PAN / 2.88m MS
Shooting swath width: 11.6 km
Spectral channels:
Panchromatic: 500-800 nm
Blue: 450-520nm
Green: 520-600 nm
Red: 630-690 nm
NIR: 690-800 nm

JL NIGHTVISION

9 satellites in a constellation
(JL-1SP03 / 04/05/06/07/08; JL-1GF03C01 / 02/03)
Night shooting, stereo, video
Launch date: 2017, 2020
Orbital altitude: 528 km; 535 km
GSD: 0.92m and 1.21m color video
Shooting strip width:
11 km * 4.5 km (JL-1SP03)
19 km * 4.5 km (JL-1SP04 / 05/06/07/08)
14.4 km * 6 km (JL-1GF03C01 / 02/03)

ALEPH-1

17 satellites in a constellation.
Launch date: April 2016
Orbital altitude: 470 km.
GSD: 0.7m MS / 25.0m HS
Shooting swath width: 5 km MS / 125 km HS
Spectral channels:
4 multispectral:
Red: 590-690 nm; Green: 510 - 580 nm; Blue: 450 - 510 nm; NIR: 750-900 nm
29 hyperspectral: 462-830 nm

GRUS

Launch date: December 27, 2018 (GRUS-1A), March 22, 2021 (GRUS-1B, 1C, 1D, 1E)
Orbit altitude: 600 km
GSD: 2.5m PAN / 5m MS
Shooting swath width: 57 km
Spectral channels:
Blue: 450-505 nm; Green: 515-585 nm; Red: 620-685 nm; Red edge: 705-745 nm; NIR: 770-900 nm

PLANETSCOPE

Launch date: Annually since 2014
Orbit altitude: 400/475 km
GSD: 3 / 3.7 m MS
Shooting swath width: 24 km
Spectral channels:
Blue: 0.455-0.515 nm; Green: 0.50-0.59 nm; Red: 0.59-0.67 nm; NIR: 0.78-0.86 nm

PLÉIADES 1A & 1B

2 satellites in a constellation
Launch date:
December 17, 2011; December 2, 2012
Orbital altitude: 694 km.
GSD: 0.5m PAN / 2.0m MS (after processing)
0.7m PAN / 2.8m MS (original)
Shooting swath width: 20 km
Spectral bands:
Panchromatic: 0.47-0.83 μm
Blue: 0.43-0.55 microns; Green: 0.50-0.62 microns; Red: 0.59-0.71 microns; NIR: 0.74-0.94 μm

SPOT-6, SPOT-7/Azersky

Launch date:
September 9, 2012 (SPOT-6), June 30, 2014 (SPOT-7 / Azersky)
Orbit altitude: 694 km
GSD: 1.5m PAN / 6.0m MS
Shooting swath width: 60 km
Spectral bands:
Panchromatic: 0.45-0.75 microns
Blue: 0.45-0.52 microns; Green: 0.53-0.60 microns; Red: 0.62-0.69 microns; NIR: 0.76-0.89 μm

GEOEYE-1

Launch date: September 6, 2008
Orbital altitude: 681 km.
GSD: 0.41m PAN / 1.65m MS
Positioning accuracy: <3m CE90
Shooting swath width: 15.3 km
Spectral channels:
Panchromatic: 450-800 nm
Blue: 450 - 510 nm
Green: 510 - 580 nm
Red: 655-690 nm
NIR: 780 - 920 nm

WORLDVIEW-1

Launch date: September 18, 2007
Orbital altitude: 496 km.
GSD: 0.5m
Shooting swath width: 17.7 km
Spectral channels:
Panchromatic: 400 - 900 nm

WORLDVIEW-2

Launch date: Oct 9, 2009
Orbital altitude: 770 km.
GSD: 0.46m PAN / 1.85m MS
Shooting swath width: 16.4 km
Spectral channels:
Panchromatic: 450-800 nm
Violet: 400-450 nm; Blue: 450 - 510 nm; Green: 510 - 580 nm; Yellow: 585-625 nm; Red: 630-690 nm; Red edge: 705-745 nm; NIR1: 770-895 nm; NIR2: 860-1040 nm

WORLDVIEW-3

Launch date: 13 Aug 2014
Orbital altitude: 617 km.
GSD: 0.31m PAN / 1.24m MS / 3.7 SWIR
Shooting swath width: 13.1 km
Spectral channels:
Panchromatic: 450-800 nm
Violet: 400-450 nm; Blue: 450 - 510 nm; Green: 510 - 580 nm; Yellow: 585-625 nm; Red: 630-690 nm; Red edge: 705-745 nm; NIR1: 770-895 nm; NIR2: 860-1040 nm
8 SWIR channels from 1195 to 2365 nm

WORLDVIEW-4 (архив)

Launch date: Nov 11, 2016
Released: January 7, 2019
Orbital altitude: 617 km.
GSD: 0.31m PAN / 1.24m MS
Shooting swath width: 13.1 km
Spectral channels:
Panchromatic: 450-800 nm
Red: 655-690 nm
Green: 510 - 580 nm
Blue: 450 - 510 nm
NIR: 780 - 920 nm

IKONOS (архив)

Launch date: September 24, 1999
Released: January 22, 2015
Orbital altitude: 530 km.
GSD: 0.82m PAN / 3.28m MS
Shooting swath width: 11.3 km
Spectral channels:
Panchromatic: 450-700 nm
Blue: 450-520nm
Green: 520-590 nm
Red: 630-690 nm
NIR: 770-890 nm

QUICKBIRD (архив)

Launch date: Oct 18, 2001
Released: January 27, 2015
Orbital altitude: 482 km.
GSD: 0.61m PAN / 2.44m MS
Shooting swath width: 18 km
Spectral bands:
Panchromatic 405 - 1053 nm
Blue: 430 - 545 nm
Green: 466-620 nm
Red: 590-710 nm
NIR: 715 - 918 nm

ORDER SATELLITE IMAGERY FROM PROXIMA IN 3 EASY STEPS

Create a shapefile WGS84 compatible over your Area of Interest. Or define your coordinates.

Send us your files/coordinates or image catalogue IDs to [email protected]

We will reply with results within 12 hours. We will first inform you on what is currently available in our extensive Image Library, and we would estimate how long it would take to acquire new imagery.

INDUSTRIES

Our goal is to make customers happy and help them get what they want

Oil and gas

Satellite imagery helps to effectively solve the most important tasks, from the search and extraction of new resources to environmental monitoring.

Geology and mining

Remote sensing data are effectively used in the creation of engineering-geological maps and topographic plans. They allow performing geoecological monitoring and forecasting of emergency situations.

Agriculture

Satellite imagery is used for crop classification, crop condition assessment and forecasting, monitoring of agricultural operations and methods.

Forestry

Satellite imagery helps to respond to emergencies, monitor and manage forest assets, and detect illegal deforestation.

Water industry

Experts use remote sensing data to determine the boundaries of water bodies, their area and volumes, study turbidity and turbulence, mapping flood areas and snow cover boundaries, and the dynamics of their change.

Urban planing and civil government

Satellite imagery for urban and territorial development can be used to collect strategic planning information pertaining to an area or an entire city.

Transportation

Geographic information systems can be effectively used for the design and monitoring of transport infrastructure and communication facilities.

Ecology

Environmental protection is a priority for all inhabitants of the Earth. Satellite images that collect information from the Earth's surface are indispensable in environmental research and environmental monitoring.

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