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Guide for calculate the basic remote sensing indices in ArcGIS and QGIS.
Procedure, authors and general notes during calculation
By Alan García Haro
This document presents the basic equations for retrieving land indices from Landsat,
Sentinel and MODIS satellites images. Particularly, the document presents basic
characteristics of the satellite, authors and brief explanation of the input criteria for each
calculation.
CONTENT
BANDS PROPERTIES ................................................................................................... 2
Landsat-8 OLI/TIRS ..................................................................................................... 2
Landsat-7 ETM ............................................................................................................. 2
Landsat-4-5 TM ............................................................................................................ 3
Sentinel-2 ....................................................................................................................... 3
MODIS products ........................................................................................................... 4
NATURAL COLOR ........................................................................................................ 4
DIGITAL NUMBERS TO UNITS ................................................................................. 5
LANDSAT-8 Top of Atmosphere Reflectance ............................................................. 5
LANDSAT-8 Top of Atmosphere Radiance (Spectral Radiance) ............................... 6
Sentinel-2 Top of Atmosphere Reflectance .................................................................. 6
LAND COVER INDICATORS ...................................................................................... 7
Normalized Difference Vegetation Index (NDVI) ....................................................... 7
Normalized Difference Vegetation Index (NDVI) from MODIS ................................ 7
Normalized Difference Building Index (NDBI) .......................................................... 7
Normalized Difference Water Index (NDWI) .............................................................. 7
Modified Normalized Difference Vegetation Index (MNDWI) .................................. 8
Enhanced Built-Up and Bareness Index (EBBI) ........................................................ 8
Soil-adjusted Vegetation Index (SAVI) ........................................................................ 8
Index based Built up Index (IBI) ................................................................................. 9
Shortwave Albedo .......................................................................................................... 9
THERMAL INDICATORS .......................................................................................... 10
Land Surface Temperature (LST) from Landsat imagery by emissivity correction
method ......................................................................................................................... 10
Brightness Temperature ............................................................................................. 10
Surfaces Radiation Constant (Plancks – Boltzman) ................................................. 10
Emissivity By Simplified NDVI Theresholds Method ............................................... 11
Land Surface Temperature (LST) from MODIS ....................................................... 12
REFERENCIAS ............................................................................................................ 13
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BANDS PROPERTIES
Landsat-8 OLI/TIRS
2013- present
Bands Landsat 8 Wavelength
(micrometers)
Resolution
(meters)
Band 1 - Ultra Blue (coastal/aerosol) 0.435 - 0.451 30
Band 2 – Blue 0.452 - 0.512 30
Band 3 – Green 0.533 - 0.590 30
Band 4 – Red 0.636 - 0.673 30
Band 5 - Near Infrared (NIR) 0.851 - 0.879 30
Band 6 - Shortwave Infrared (SWIR) 1 1.566 - 1.651 30
Band 7 - Shortwave Infrared (SWIR) 2 2.107 - 2.294 30
Band 8 - Panchromatic 0.503 - 0.676 15
Band 9 – Cirrus 1.363 - 1.384 30
Band 10 - Thermal Infrared (TIRS) 1 10.60 - 11.19 100 * (30)
Band 11 - Thermal Infrared (TIRS) 2 11.50 - 12.51 100 * (30)
(Barsi, Lee, Kvaran, Markham, & Pedelty, 2014)
Landsat-7 ETM
1999-present
Bands Landsat 7 Wavelength
(micrometers)
Resolution
(meters)
Band 1 – Blue 0.45 - 0.52 30
Band 2 – Green 0.52 - 0.60 30
Band 3 – Red 0.63 - 0.69 30
Band 4 - Near Infrared (NIR) 0.77 - 0.90 30
Band 5 - Shortwave Infrared (SWIR) 1 1.55 - 1.75 30
Band 6 – Thermal 10.40 – 12.50 60*(30)
Band 7 - Shortwave Infrared (SWIR) 2 2.09 - 2.35 30
Band 8 - Panchromatic 0.52 - 0.90 15
(Barsi, Lee, Kvaran, Markham, & Pedelty, 2014)
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Landsat-4-5 TM
1982-2011
Bands Landsat 4 & 5 Wavelength
(micrometers)
Resolution
(meters)
Band 1 – Blue 0.45 - 0.52 30
Band 2 – Green 0.52 - 0.60 30
Band 3 – Red 0.63 - 0.69 30
Band 4 - Near Infrared (NIR) 0.76 - 0.90 30
Band 5 - Shortwave Infrared (SWIR) 1 1.55 - 1.75 30
Band 6 - Thermal 10.40 – 12.50 120*(30)
Band 7 - Shortwave Infrared (SWIR) 2 2.08 - 2.35 30
(Barsi, Lee, Kvaran, Markham, & Pedelty, 2014)
Sentinel-2
2015-present
Sentinel-2A Sentinel-2B
Sentinel-2 bands
Central
wavelength
(nm)
Bandwidth
(nm)
Central
wavelength
(nm)
Bandwidth
(nm)
Spatial
resolution
(m)
Band 1 – Coastal aerosol 442.7 21 442.2 21 60
Band 2 – Blue 492.4 66 492.1 66 10
Band 3 – Green 559.8 36 559.0 36 10
Band 4 – Red 664.6 31 664.9 31 10
Band 5 – Vegetation red edge 704.1 15 703.8 16 20
Band 6 – Vegetation red edge 740.5 15 739.1 15 20
Band 7 – Vegetation red edge 782.8 20 779.7 20 20
Band 8 – NIR 832.8 106 832.9 106 10
Band 8A – Narrow NIR 864.7 21 864.0 22 20
Band 9 – Water vapour 945.1 20 943.2 21 60
Band 10 – SWIR – Cirrus 1373.5 31 1376.9 30 60
Band 11 – SWIR 1613.7 91 1610.4 94 20
Band 12 – SWIR 2202.4 175 2185.7 185 20
(European Spacial Agency (ESA), 2017)
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MODIS products
Terra 1999-present; Aqua 2002-present
Level 1
MODIS Raw Radiances
MODIS Calibrated Radiances
MODIS Geolocation Fields
MODIS Atmosphere Products
MODIS Aerosol Product
MODIS Total Precipitable Water
MODIS Cloud Product
MODIS Atmospheric Profiles
MODIS Atmosphere Joint Product
MODIS Atmosphere Gridded Product
MODIS Cloud Mask
MODIS Land Products
MODIS Surface Reflectance
MODIS Land Surface Temperature and
Emissivity (MOD11)
MODIS Land Surface Temperature and
Emissivity (MOD21)
MODIS Land Cover Products
MODIS Vegetation Index Products (NDVI and
EVI)
MODIS Thermal Anomalies - Active Fires
MODIS Fraction of Photosynthetically Active
Radiation (FPAR) / Leaf Area Index (LAI)
MODIS Evapotranspiration
MODIS Gross Primary Productivity (GPP) / Net
Primary Productivity (NPP)
MODIS Bidirectional Reflectance Distribution
Function (BRDF) / Albedo Parameter
MODIS Vegetation Continuous Fields
MODIS Water Mask
MODIS Burned Area Product
MODIS Cryosphere Products
MODIS Snow Cover
MODIS Sea Ice and Ice Surface Temperature
MODIS Ocean Products
MODIS Sea Surface Temperature
MODIS Remote Sensing Reflectance
MODIS Chlorophyll-a Concentration
MODIS Diffuse Attenuation at 490 nm
MODIS Particulate Organic Carbon
MODIS Particulate Inorganic Carbon
MODIS Normalized Fluorescence Line Height
(FLH)
MODIS Instantaneous Photosynthetically
Available Radiation
MODIS Daily Mean Photosynthetically Available
Radiation
(National Aeronautics and Space Administration (NASA), 2017)
NATURAL COLOR
Bands combination for generate natural color view of the imagery.
Color
Infrared:
NIR,
RED,
GREEN
Natural
Color:
RED,
GREEN,
BLUE
(U.S. Geological Survey, 2016)
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DIGITAL NUMBERS TO UNITS
LANDSAT-8 Top of Atmosphere Reflectance
FORMULA (Rouse, Haas, Schell, & Deering, 1974) (U.S. Geological Survey, 2016)
𝜌 = 𝑀𝜌 × 𝑄𝑐𝑎𝑙 + 𝐴𝜌
𝜌: spectral reflectance without sun correction
𝑀𝜌: reflectance multiplicative scaling factor
𝐴𝜌: reflectance additive scaling factor
𝑄𝑐𝑎𝑙: band DN values
SUN ELEVATION CORRECTION (U.S. Geological Survey, 2016):
𝜌𝜆 =𝜌
sin(𝜃𝜋 180⁄ )
𝜌𝜆: spectral reflectance corrected
𝜃: sun elevation in degrees 𝜃𝜋
180: function to turn degrees into radians
CALCULATION:
1. REFLECTANCE
=(REFLECTANCE_MULT*DN_BAND+REFLECTANCE_ADD)
2. SUN ELEVATION CORRECTION
=(REFLECTANCE)/(Sin(SUN_ELEVATION*π/180)
3. NEGATIVE VALUES TO CERO
=Con(REFLECTANCE<0.0,0.0,REFLECTANCE)
ArcGIS code
integrated:
Con(((BAND * 0.00002 -
0.1)/(Sin(SUN_ELEVATION*3.141592654/180)))<0.0,0.0,((BAND
* 0.00002 - 0.1)/(Sin(SUN_ELEVATION*3.141592654/180))))
QGIS code:
(((BAND*0.00002-0.1)/(sin(
SUN_ELEVATION*3.141592654/180)))>=0)*((BAND*0.00002 -
0.1)/(sin(SUN_ELEVATION*3.141592654/180)))
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LANDSAT-8 Top of Atmosphere Radiance (Spectral Radiance)
BAND TIRS1 preferred (Barsi, y otros, 2014)
FORMULA (U.S. Geological Survey, 2016):
𝐿𝜆 = 𝑀𝐿 × 𝐷𝑁𝑏𝑎𝑛𝑑 + 𝐴𝐿
𝐿𝜆: spectral radiance
𝑀𝐿: radiance multiplicative scaling factor (RADIANCE_MULT_BAND)
𝐴𝐿: radiance additive scaling factor (RADIANCE_ADD_BAND)
𝐷𝑁𝑏𝑎𝑛𝑑: raw band digital numbers
CALCULATION:
1. RADIANCE_MULT_BAND*DN_BAND+RADIANCE_ADD_BAND
GIS code Landsat-8:
TIR1 * 0.0003342 + 0.1
Sentinel-2 Top of Atmosphere Reflectance
Level 1C of Sentinel-2 imagery is already preprocessed in TOA reflectance values and
geometrically corrected. Although it still needed to apply a scale factor to the
downloaded raw images (European Space Agency (ESA), 2015).
𝜌𝜆 =𝑄𝑐𝑎𝑙
𝐹𝜌
𝜌𝜆: spectral reflectance geometrically corrected
𝐹𝜌: reflectance scaling factor (Sentinel-2 1C = 10000)
𝑄𝑐𝑎𝑙: band DN values geometrically corrected
ArcGIS code:
Float(BAND)/10000
QGIS code:
BAND/10000
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LAND COVER INDICATORS
Normalized Difference Vegetation Index (NDVI)
REFLECTANCE BANDS RED & NIR. FORMULA (Weier & Herring, 2000):
𝑁𝐷𝑉𝐼 =(𝜌𝑁𝐼𝑅 − 𝜌𝑟𝑒𝑑)
(𝜌𝑁𝐼𝑅 + 𝜌𝑟𝑒𝑑)
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
GIS code: (NIRref - REDref) / (NIRref + REDref)
Normalized Difference Vegetation Index (NDVI) from MODIS
Scaling correction (National Aeronautics and Space Administration (NASA), 2017):
𝑁𝐷𝑉𝐼 = 𝑁𝐷𝑉𝐼𝐷𝑁 ∗ 0.0001
𝑁𝐷𝑉𝐼𝐷𝑁: raw MODIS NDVI in digital number
GIS code: MODIS_NDVIdn * 0.0001
Normalized Difference Building Index (NDBI)
REFLECTANCE BANDS NIR & SWIR1. FORMULA (Zha, Gao, & Ni, 2003):
𝑁𝐷𝐵𝐼 =(𝜌𝑆𝑊𝐼𝑅1 − 𝜌𝑁𝐼𝑅)
(𝜌𝑆𝑊𝐼𝑅1 + 𝜌𝑁𝐼𝑅)
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
GIS code: (SWIR1ref - NIRref) / (SWIR1ref + NIRref)
Normalized Difference Water Index (NDWI)
Reflectance bands GREEN & NIR. FORMULA (McFeeters, 1996):
𝑁𝐷𝑊𝐼 =(𝜌𝑔𝑟𝑒𝑒𝑛 − 𝜌𝑁𝐼𝑅)
(𝜌𝑔𝑟𝑒𝑒𝑛 + 𝜌𝑁𝐼𝑅)
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
GIS code: (GREENref - NIRref) / (GREENref + NIRref)
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Modified Normalized Difference Vegetation Index (MNDWI)
REFLECTANCE BANDS GREEN & SWIR1. FORMULA (Xu, 2006):
𝑀𝑁𝐷𝑊𝐼 =(𝜌𝑔𝑟𝑒𝑒𝑛 − 𝜌𝑆𝑊𝐼𝑅1)
(𝜌𝑔𝑟𝑒𝑒𝑛 + 𝜌𝑆𝑊𝐼𝑅1)
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
GIS code: (GREENref - SWIR1ref) / (GREENref + SWIR1ref)
Enhanced Built-Up and Bareness Index (EBBI)
DIGITAL NUMBERS BANDS SWIR1, NIR AND TIR1
The index +1 >-1 scale depends of the digital numbers of previous 8-bits imagery. That
is why a 256 division is need it to adjust values. A little loss of data is expected in scaling.
FORMULA (As-syakur, Adnyana, Arthana, & Nuarsa, 2012):
𝐸𝐵𝐵𝐼 =(𝐷𝑁𝑆𝑊𝐼𝑅1 − 𝐷𝑁𝑁𝐼𝑅)
10√𝐷𝑁𝑆𝑊𝐼𝑅1 − 𝐷𝑁𝑇𝐼𝑅1
𝐷𝑁𝑏𝑎𝑛𝑑: digital numbers of band (8 bits)
ArcGIS code: (SWIR1dn-NIRdn)/(10*SquareRoot(SWIR1dn+TIR1dn))
ArcGIS 8-bits
correction
(Landsat-8):
((SWIR1dn/256)-
(NIRdn/256))/(10*SquareRoot((SWIR1dn/256)+(TIR1dn/256)))
QGIS code: (SWIR1dn-NIRdn)/(10*sqrt(SWIR1dn+TIR1dn))
QGIS code 8-
bits correction
(Landsat-8):
((SWIR1dn/256)-
(NIRdn/256))/(10*sqrt((SWIR1dn/256)+(TIR1dn/256)))
Soil-adjusted Vegetation Index (SAVI)
REFLECTANCE BANDS GREEN & SWIR1. FORMULA (Xu, 2006):
𝑆𝐴𝑉𝐼 = [𝜌𝑁𝐼𝑅 − 𝜌𝑟𝑒𝑑
𝜌𝑁𝐼𝑅 + 𝜌𝑟𝑒𝑑 + 𝐿] × (1 + 𝐿)
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
𝐿: soil brightness correction (Landsat = 0.5)
GIS code: ((NIRref – REDref) / (NIRref + REDref + 0.5))*1.5
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Index based Built up Index (IBI)
REFLECTANCE BANDS GREEN & SWIR1
FORMULA (Xu H. , 2008):
𝐼𝐵𝐼 = [𝑠𝑁𝐷𝐵𝐼 − (𝑠𝑆𝐴𝑉𝐼 + 𝑠𝑀𝑁𝐷𝑊𝐼)/2]
[𝑠𝑁𝐷𝐵𝐼 + (𝑠𝑆𝐴𝑉𝐼 + 𝑠𝑀𝑁𝐷𝑊𝐼)/2]
𝑠𝑖𝑛𝑑𝑒𝑥: rescaled index values to 0 to 1, instead of -1 to 1 as the index usually is
𝑠𝑖𝑛𝑑𝑒𝑥 =𝑖𝑛𝑑𝑒𝑥 + 1
2
Or IBI in one touch
𝐼𝐵𝐼 =[
2 × 𝜌𝑆𝑊𝐼𝑅1
𝜌𝑆𝑊𝐼𝑅1 + 𝜌𝑁𝐼𝑅− (
𝜌𝑁𝐼𝑅
𝜌𝑁𝐼𝑅 + 𝜌𝑅𝐸𝐷+
𝜌𝐺𝑅𝐸𝐸𝑁
𝜌𝐺𝑅𝐸𝐸𝑁 + 𝜌𝑆𝑊𝐼𝑅1)]
[2 × 𝜌𝑆𝑊𝐼𝑅1
𝜌𝑆𝑊𝐼𝑅1 + 𝜌𝑁𝐼𝑅+ (
𝜌𝑁𝐼𝑅
𝜌𝑁𝐼𝑅 + 𝜌𝑅𝐸𝐷+
𝜌𝐺𝑅𝐸𝐸𝑁
𝜌𝐺𝑅𝐸𝐸𝑁 + 𝜌𝑆𝑊𝐼𝑅1)]
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
GIS code
index
based:
(((NDBI+1)/2)-(((SAVI+1)/2)+ ((MNDWI+1)/2))/2)/
(((NDBI+1)/2)+(((SAVI+1)/2)+ ((MNDWI+1)/2))/2)
GIS code
IBI one
touch:
(((2 * SWIR1ref )/( SWIR1ref + NIRref ))-( NIRref /( NIRref + REDref
))+( GREENref /( GREENref + SWIR1ref )))/(((2* SWIR1ref )/(
SWIR1ref + NIRref ))+(( NIRref /( NIRref + REDref ))+( GREENref /(
GREENref + SWIR1ref ))))
Shortwave Albedo (Landsat TM/ETM+)
Reflectance of BLUE, RED, NIR, SWIR1 & SWIR2 BANDS
FORMULA (Liang, 2001) & NORMALIZED BY (Smith, 2010):
𝛼𝑠ℎ𝑜𝑟𝑡
=0.356𝜌𝑏𝑙𝑢𝑒 + 0.130𝜌𝑟𝑒𝑑 + 0.373𝜌𝑁𝐼𝑅 + 0.085𝜌𝑆𝑊𝐼𝑅1 + 0.072𝜌𝑆𝑊𝐼𝑅2 − 0.0018
0.356 + 0.130 + 0.373 + 0.085 + 0.072 − 0.0018
𝛼𝑠ℎ𝑜𝑟𝑡: shortwave radiance reflected (albedo). Best than visible or NIR albedo (Liang, 2001).
𝜌𝑏𝑎𝑛𝑑: spectral reflectance of band
GIS code: ((0.356*BLUEref)+(0.130*REDref)+(0.373*NIRref)+(0.085*SWIR1ref)+(
0.072*SWIR2ref)-(0.0018))/(1.016)
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THERMAL INDICATORS
Land Surface Temperature (LST) from Landsat imagery by emissivity correction
method
BAND TIRS1, TIRS2 Landsat 8 excluded by light contamination (Barsi, y otros, 2014).
FORMULA (Artis & Carnahan, 1982):
𝐿𝑆𝑇 = (𝑇𝐵
1 + (𝜆𝑇𝐵 𝛼⁄ ) ln 𝜀) − 273.15
𝑇: land surface temperature in Celsius
𝑇𝐵: brightness temperature in kelvin
𝜆: center wavelength of emitted radiance (BAND 10 or 11)
𝜀: emissivity (calculated by NDVI thresholds method
𝛼: surfaces radiation constant adjustment
CALCULATION:
1. LST=((BrightnessT)/(1+((CenterWavelenght*BrightnessT)/Planck_Boltzman_C
onstant)*Ln(Emissivity)))-273.15
GIS code: ((BrightTem)/(1+((10.895*(BrightTem)/14380)*Ln(Emissivity))))-273.15
Brightness Temperature
BAND TIRS1, FORMULA (U.S. Geological Survey, 2016):
𝑇𝐵 =𝐾2
ln (𝐾1
𝐿𝜆+ 1)
𝑇𝐵: brightness temperature in kelvin
𝐾1: Thermal conversion constant (K1_CONSTANT_BAND)
𝐾2: Thermal conversion constant (K2_CONSTANT_BAND)
𝐿𝜆: Spectral radiance
ArcGIS code: 1321.08 / Ln(( 774.89 / RADIANCE ) + 1)
QGIS code: 1321.08 / In(( 774.89 / RADIANCE ) + 1)
Surfaces Radiation Constant (Plancks – Boltzman)
FORMULA (Artis & Carnahan, 1982):
𝛼 =𝐻 × 𝑆
𝐶
H = PLANCKS CONSTANT (6.62607004*10^-34m^2 kg/s)
S = BOLTZMAN CONSTANT (1.38064852*10^-23m^2 kg s^-2 K^-1)
C = LIGHTSPEED (2.998*10^8 m/s)
H*C/S = (1.438*10^-34) = 14380
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Emissivity By Simplified NDVI Theresholds Method
FORMULA (Sobrino, Jiménez-Muñoz, & Paolini, 2004):
ελ = {
𝜀𝑠
𝜀𝑠
𝜀𝑠
} = {
𝜀𝑠,𝜀𝑚,
𝜀𝑣
𝜀𝑠: emissivity bare soil (NDVI<0.2)
𝜀𝑣: emissivity vegetation (NDVI>0.5)
𝜀𝑚: emissivity mixed areas (NDVI>0.2 & NDVI<0.5)
𝑃𝑉: vegetation proportion (Carlson & Ripley, 1997)
Calculation of vegetation proportion (Carlson & Ripley, 1997)
𝑃𝑉 = (𝑁𝐷𝑉𝐼 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛
𝑁𝐷𝑉𝐼𝑚𝑎𝑥 − 𝑁𝐷𝑉𝐼𝑚𝑎𝑥)
2
𝑁𝐷𝑉𝐼𝑚𝑖𝑛: limit to bare soil (0.2)
𝑁𝐷𝑉𝐼𝑚𝑎𝑥: limit to vegetation (0.5)
EMISSIVITY EXPLANATION (Sobrino, Jiménez-Muñoz, & Paolini, 2004):
𝜀 = 𝜀𝑉𝑃𝑉 + 𝜀𝑆(1 − 𝑃𝑉) + 𝑑𝜀
𝑑𝜀: effect of geometrical distribution of surfaces
𝑑𝜀 = (1 − 𝜀𝑠)(1 − 𝑃𝑉)𝐹𝜀𝑉
𝐹: shape factor assumed (0.55) (Sobrino, Caselles, & Becker, 1990)
Emissivity values
LAND COVER TYPE (Sobrino, Jiménez-
Muñoz, & Paolini, 2004)
(Stathopoulou & Cartalis,
2007)
Urban/densely built - 0.946
Suburban/medium built - 0.964
Industrial/commercial - -
Mixed urban area / Urban use* 0.973 0.950
Agriculture / Rural area** 0.990 0.980
Forest - -
Water surface - 0.990
* Emissivity of bare soil
** Emissivity of vegetated surfaces
Pág. 12
Mixed areas (Sobrino, Jiménez-Muñoz, Soria, Romaguera, & Guanter, 2008):
𝜀𝑚 = 0.018𝑃𝑉 + 0.971
Mixed areas in urban context (Stathopoulou & Cartalis, 2007):
𝜀𝑚 = 0.017𝑃𝑉 + 0.963
Part by part calculation ArcGIS code (urban context):
E Es + Em + Ev
εsNDVI Con(NDVI<0.2, 0.95, 0.0)
εvNDVI Con(NDVI>0.5, 0.98, 0.0)
Pv Square((NDVI-0.2) / (0.5-0.2))
εmNDVI Con((NDVI>=0.2 & NDVI<=0.5), (0.017 * Pv + 0.963,0.0),0.0)
Full code:
ArcGIS:
(Con(NDVI<0.2, 0.95, 0.0))+(Con((NDVI>=0.2) & (NDVI<=0.5),
0.017*(Square((NDVI-0.2)/(0.5-0.2)))+0.963,0.0))+(Con(NDVI>0.5, 0.98,
0.0))
QGIS:
( ( NDVI < 0.2 ) * 0.95 ) + ( ( NDVI> 0.5) * 0.98 ) + ( ( ( NDVI>= 0.2 )
AND (NDVI<= 0.5 ) ) * ( 0.017 * ( ( ( NDVI-0.2 ) / ( 0.5 -0.2 ) ) * ( (
NDVI-0.2 ) / ( 0.5 -0.2 ) ) ) + 0.963 ) )
Land Surface Temperature (LST) from MODIS
Scaling correction (National Aeronautics and Space Administration (NASA), 2017):
𝐿𝑆𝑇𝐶 = (𝐿𝑆𝑇𝐷𝑁 ∗ 0.02) − 273.15
𝐿𝑆𝑇𝐶: land surface temperature in Celsius
𝐿𝑆𝑇𝐷𝑁: raw MODIS land surface temperature in digital number
GIS code:
MODIS_LSTdn * 0.02 - 273.15
Pág. 13
REFERENCIAS
Artis, D. A., & Carnahan, W. H. (1982). Survey of emissivity variability in
thermography of urban areas. Remote Sensing of Environment, 12(4), 313-329.
doi:10.1016/0034-4257(82)90043-8
As-syakur, A. R., Adnyana, I. W., Arthana, I. W., & Nuarsa, I. W. (2012). Enhanced
Built-Up and Bareness Index (EBBI) for Mapping Built-Up and Bare Land in an
Urban Area. Remote Sensing, 4(10), 2957-2970. doi:10.3390/rs4102957
Barsi, J., Lee, K., Kvaran, G., Markham, B., & Pedelty, J. (2014). The Spectral
Response of the Landsat-8 Operational Land Imager. Remote Sensing(6), 10232-
10251. doi:10.3390/rs61010232
Barsi, J., Schott, J., Hook, S., Raqueno, N., Markham, B., & Radocinski, R. (2014).
Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration.
Remote Sensing, 6(11), 11607-11626. doi:10.3390/rs61111607
Carlson, T. N., & Ripley, D. A. (1997). On the relation between NDVI, fractional
vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3),
241-252. doi:10.1016/S0034-4257(97)00104-1
European Space Agency (ESA). (2015). Sentinel-2 User Handbook. Retrieved from
ESA Sentinel Online:
https://sentinel.esa.int/documents/247904/685211/Sentinel-2_User_Handbook
European Spacial Agency (ESA). (2017). MultiSpectral Instrument (MSI) Overview.
Retrieved from European Space Agency (ESA):
https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/msi-instrument
Liang, S. (2001). Narrowband to broadband conversions of land surface albedo I:
Algorithms. Remote Sensing of Environment, 76(2), 213-238.
doi:10.1016/S0034-4257(00)00205-4
McFeeters, S. (1996). The use of the Normalized Difference Water Index (NDWI) in
the delineation of open water features. International Journal of Remote Sensing,
17(7), 1425-1432. doi:10.1080/01431169608948714
National Aeronautics and Space Administration (NASA). (2017). Data Products.
Retrieved from MODIS. Moderate Resolution Imaging Spectroradiometer:
https://modis.gsfc.nasa.gov/data/dataprod/
Rouse, J., Haas, R., Schell, J., & Deering, D. (1974). Monitoring vegetation sytems in
the great plains with ERTS. Goddard Space Flight Center 3d ERTS-1
Symposium (pp. 309–317). Washington, DC: NASA. Retrieved from
https://ntrs.nasa.gov/search.jsp?R=19740022614
Smith, R. (2010, Marzo). The heat budget of the earth's surface deduces from space.
Center for Earth Observation. Yale University. Retrieved from Center for Earth
Observation. Reference Documents: https://yceo.yale.edu/links/reference-
documents
Pág. 14
Sobrino, J., Caselles, V., & Becker, F. (1990). Significance of the remotely sensed
thermal infrared measurements obtained over a citrus orchard. ISPRS Journal of
Photogrammetry and Remote Sensing, 44(6), 343-354. doi:10.1016/0924-
2716(90)90077-O
Sobrino, J., Jiménez-Muñoz, J., & Paolini, L. (2004). Land surface temperature retrieval
from LANDSAT TM 5. Remote Sensing of Environment, 90(4), 434-440.
doi:10.1016/j.rse.2004.02.003
Sobrino, J., Jiménez-Muñoz, J., Soria, G., Romaguera, M., & Guanter, L. (2008). Land
Surface Emissivity Retrieval From Different VNIR and TIR Sensors. IEEE
Transactions on Geoscience and Remote Sensing, 46, 316-327.
doi:10.1109/TGRS.2007.904834
Stathopoulou, M., & Cartalis, C. (2007). Daytime urban heat islands from Landsat
ETM+ and Corine land cover data: An application to major cities in Greece.
Solar Energy, 358-368. Retrieved from
https://doi.org/10.1016/j.solener.2006.06.014
U.S. Geological Survey. (2016, Marzo 26). Landsat 8 Data Users Handbook Version
2.0. Retrieved from Landsat missions. U.S. Geological Survey:
https://landsat.usgs.gov/
Weier, J., & Herring, D. (2000, Agosto 30). Measuring Vegetación (NDVI & EVI).
Retrieved Agosto 17, 2017, from NASA Earth Observatory:
https://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_veg
etation_1.php
Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance
open water features in remotely sensed imagery. International Journal of
Remote Sensing, 27(14), 3025-3033. doi:10.1080/01431160600589179
Xu, H. (2008). A new index for delineating built-up land features in satellite imagery.
International Journal of Remote Sensing, 4269–4276.
Zha, Y., Gao, Y., & Ni, S. (2003). Use of normalized difference built-up index in
automatically mapping urban areas from TM imagery. International Journal of
Remote Sensing(24), 583–594.