A ~25 slide presentation that explains the underlying principles and some applications of InSAR, with a particular focus on the measurement of deformation due to earthquakes. The presentation could be used in a lecture or lab setting, or provided to students for review out of class. The slides are annotated with additional background information designed to assist instructors.
A ~25 slide presentation that explains the underlying principles and some applications of InSAR, with a particular focus on the measurement of deformation due to earthquakes. The presentation could be used in a lecture or lab setting, or provided to students for review out of class. The slides are annotated with additional background information designed to assist instructors.
Global positioning system and its mathematical form.
By Mustahsan Khan _ BS(physics-Nanotechnology) (International Islamic University Islamabad) Pakistan.
Global positioning system and its mathematical form.
By Mustahsan Khan _ BS(physics-Nanotechnology) (International Islamic University Islamabad) Pakistan.
In the modern age, High-resolution radar images can be achieved by employing SAR technique. It is well
known that SAR can provide several times better image resolution than conventional radars. The exploration for efficient
image denoising methods still remains a valid challenge for researchers. Despite the difficulty of the recently proposed
methods, mostly of the algorithms have not yet attained a pleasing level of applicability; each algorithm has its
assumptions, advantages, and limitations. This paper presents a review of synthetic aperture radar. Behind a brief
introduction in our work we are especially targeting the noise called backscattered noise in SAR terminology which
causes the appearance of speckle Potential future work in the area of air flight navigation, mapping Weather Monitoring
& during natural disaster like earth quake. The SAR having the capability, to make human visibility beyond optical
vision, is also discussed.
Presentation made by Prof. Adriano Camps (Universitat Politècnica de Catalunya) at ICMARS 2010 (India, 16-December-2010) on the MIRAS instrument aboard ESA's SMOS mission.
The purpose of choosing this topic is to aware you about sentinel satellites that leads to new discoveries and ultimately changes the arena of Remote Sensing.
Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+,
and EO-1 ALI sensors
Gyanesh Chander a,⁎, Brian L. Markham b, Dennis L. Helder c
a SGT, Inc. 1 contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198-0001, USA
b National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
c South Dakota State University (SDSU), Brookings, SD 57007, USA
Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+,
and EO-1 ALI sensors
Gyanesh Chander a,⁎, Brian L. Markham b, Dennis L. Helder c
a SGT, Inc. 1 contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198-0001, USA
b National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
c South Dakota State University (SDSU), Brookings, SD 57007, USA
Similar to Evaluating the effect of soil moisture, surface temperature and humidity variations on MODIS-derived NDVI values (20)
An Introduction to Google Colab as a development Platform using Python as a programming language. Mentioning Tips that are beneficial to make the development experience much easier.
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https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
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Evaluating the effect of soil moisture, surface temperature and humidity variations on MODIS-derived NDVI values
1. Evaluating the effect of soil moisture, surface temperature and
humidity variations on MODIS-derived NDVI values
Term Project Report
Environmental Remote Sensing and Satellite Image Processing
WEN507
Prepared by:
Ashraf A. Hasania
Wafa F.Al Yamani
Yehia Eissa
Yomna Mahmoud Ibrahim Hassan
2. AMSR-E Overview
AMSR-E stands for Advanced Microwave Scanning Radiometer- Earth Observing Systems, which is a
twelve-channel, six-frequency, dual-polarized,passive-microwave radiometer system.[1] It is one of the
instruments carried by Nasa’s Aqua satellite project[2]. AMSR-E detects faint microwave emissions from
the Earth's surface and atmosphere[3].The AMSR-E instrument provides measurements of terrestrial,
oceanic, and atmospheric parameters for the investigation of global water and energy cycles, including
precipitation rate, sea surface temperature, sea ice concentration, snow water equivalent, soil moisture,
surface wetness, wind speed, atmospheric cloud water, and water vapor[4].
AMSR-E
The AMSR-E instrument aboard Aqua measures brightness temperatures at six frequencies (6.92, 10.65,
18.7, 23.8, 36.5, and 89.0 GHz) with vertical and horizontal polarizations at each frequency for a total of
12 channels. It achieves global swath coverage every two days or less, separately for ascending and
descending passes, except for a small region near the poles. The mean footprint diameter ranges from
60km at 6.92 GHz to 5km at 89 GHz. The AMSR-E land surface products of surface soil moisture,
vegetation water content and surface temperature are available on a daily basis in 25km Equal-AreaScalable Earth grid (EASE grid) with a global cylindrical, equal area projection true at 300N and 300S[8].
AMSR-E improves upon past microwave radiometers. The spatial resolution of AMSR-E data doubles
that of Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager
(SSM/I) data. Also, AMSR-E combines into one sensor all the channels that SMMR and SSM/I had
individually [1]. The following table compares operating characteristics of AMSR-E with previous
sensors
The following table lists the pertinent performance characteristics of AMSR-E.
Table1: AMSR-E Performance Characteristics[1]
Quantifying Bit Number
12-bit
Center Frequency (GHz)
6.925 10.65 18.7 23.8 36.5 89.0
Bandwidth (MHz)
350
Sensitivity (K)
0.3
Mean Spatial Resolution (km)
56
10-bit
100
200 400 1000 3000
0.6
38
21
1.1
24
12
5.4
3. MODIS
“MODIS is an Earth sciences instrument package aboard two different satellites, Terra and Aqua in
similar but counter rotating orbits. The first MODIS Flight Instrument, ProtoFlight Model or PFM, is
aboard the Terra (EOS AM-1) spacecraft. Terra successfully launched on December 18, 1999. The second
MODIS flight instrument, Flight Model 1 or FM1, is aboard the Aqua (EOS PM-1) spacecraft; it was
successfully launched on May 4, 2002. These MODIS instruments offer an unprecedented look at
terrestrial, atmospheric, and ocean phenomenology for a wide and diverse community of users throughout
the world” [5].
Radiometric Characteristics
Unlike other satellite imagery and products, MODIS data is systematically converted into
derived atmospheric, oceanic, and terrestrial products. The MODIS surface reflectance product is
part of the latter. All seven land bands are corrected for atmospheric effects with an algorithm
that uses aerosol and water vapor information collected by the sensor. The algorithm corrects for
thin cirrus clouds, aerosols, and atmospheric gasses. The result is an estimation of surface
reflectance as if it had been measured on the surface, without the effects of atmospheric
absorption or scattering. [9] The table below describes wavelengths represented by the 36 bands
and their applications included here:
Table2: wavelengths represented by the 36 bands and their applications [9]
Primary Use
Band
Bandwidth1
(nanometer)
Spectral
Required
Radiance2
SNR3
Land/Cloud/Aerosols
Boundaries
Land/Cloud/Aerosols
Properties
1(red)
2(NIR)
3(blue)
4(green)
5(SWIR)
6(SWIR)
7(SWIR)
8
9
10
11
12
13
14
15
16
17
18
19
620 - 670
841 - 876
459 - 479
545 - 565
1230 - 1250
1628 - 1652
2105 - 2155
405 - 420
438 - 448
483 - 493
526 - 536
546 - 556
662 - 672
673 - 683
743 - 753
862 - 877
890 - 920
931 - 941
915 - 965
21.8
24.7
35.3
29
5.4
7.3
1
44.9
41.9
32.1
27.9
21
9.5
8.7
10.2
6.2
10
3.6
15
128
201
243
228
74
275
110
880
838
802
754
750
910
1087
586
516
167
57
250
Band
Bandwidth1
Spectral
Required
Ocean Color/
Phytoplankton/
Biogeochemistry
Atmospheric
Water Vapor
Primary Use
4. (micrometer)
Surface/Cloud
Temperature
Atmospheric
Temperature
Cirrus Clouds
Water Vapor
Cloud Properties
Ozone
Surface/Cloud
Temperature
Cloud Top
Altitude
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Radiance2 (W/m2 -µm-sr)
NE[delta]T(K)4
3.660 - 3.840
3.929 - 3.989
3.929 - 3.989
4.020 - 4.080
4.433 - 4.498
4.482 - 4.549
1.360 - 1.390
6.535 - 6.895
7.175 - 7.475
8.400 - 8.700
9.580 - 9.880
10.780 - 11.280
11.770 - 12.270
13.185 - 13.485
13.485 - 13.785
13.785 - 14.085
14.085 - 14.385
0.45(300K)
2.38(335K)
0.67(300K)
0.79(300K)
0.17(250K)
0.59(275K)
6
1.16(240K)
2.18(250K)
9.58(300K)
3.69(250K)
9.55(300K)
8.94(300K)
4.52(260K)
3.76(250K)
3.11(240K)
2.08(220K)
0.05
2
0.07
0.07
0.25
0.25
150(SNR)
0.25
0.25
0.05
0.25
0.05
0.05
0.25
0.25
0.25
0.35
MODIS has spatial resolutions of 250m (bands 1-2), 500m (bands 3-7), and 1000m (bands 8-36) [9]
AMSR-E and MODIS sensors differences
Though lower in spatial resolution than MODIS optical bands, AMSR-E microwave measurements are
typically less affected by clouds, water vapor, aerosol or solar illumination, making them complementary
to MODIS real time measurements over regions of clouds and haze [6]. In cloudy area of the Earth,
MODIS limits the sensor’s ability to quantify biophysical processes in heterogeneous landscape. A
passive microwave sensor AMSR-E is not subject to cloud contamination although its spatial resolution is
relatively coarse [7].
References:
[1] http://nsidc.org/data/docs/daac/amsre_instrument.gd.html
[2] http://aqua.nasa.gov/about/
[3]
http://sharaku.eorc.jaxa.jp/AMSR/ov_amsre/index.html
[4] http://nsidc.org/data/amsre/
[5] http://10ksnookers.blogspot.com/2008/03/what-is-modis.html
[6] http://eastfire.gmu.edu/temp/eastfirewatch/homemain_files/DasguptaSPIE.pdf
[7] Gonzales, W. T. Blending MODIS and AMSR_E to predict daily land surfacewater coverage. Tokyo:
Institute of Industrial Science.
[8] J.Qua, S. D. Combining MODIS and AMSR_E based vegetation moisture retrievals for improved fire
risk monitoring. USA: George Mason University.
[9] http://www.landcover.org/library/guide/techguide_modis.pdf