Index: Structure Intensive Pigment Index 1

Structure Intensive Pigment Index 1

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Basic information

Name	Structure Intensive Pigment Index 1
Abbreviation	SIPI1
Formula	$\frac{\mathrm{800nm}-\mathrm{445nm}}{\mathrm{800nm}-\mathrm{680nm}}$
Variables
Expl. of Variables
Wavelengths	445,680,800
Source	Original formula
Description

Visualisation of required spectral range

Sensors

Nr.	Name	Spectral Range	Bands	Specific Formula	Calculated	Comment
1	AHS	428.5-13140	80	$\frac{\mathrm{13}-1}{\mathrm{13}-9}$	Automatic
2	AISA	400-2506.7	498	$\frac{\mathrm{174}-\mathrm{20}}{\mathrm{174}-\mathrm{122}}$	Automatic
3	ALI	433-2350	10	$\frac{\mathrm{MS\_\_\_4}-\mathrm{MS\_\_\_1\text{'}}}{\mathrm{MS\_\_\_4}-\mathrm{MS\_\_\_3}}$	Automatic
4	ALOS	0-890	6	$\frac{5-2}{5-4}$	Automatic
5	ARIES-1	400-2587	105	$\frac{\mathrm{22}-3}{\mathrm{22}-\mathrm{15}}$	Automatic
6	ASAS	400-1020	62	$\frac{\mathrm{40}-5}{\mathrm{40}-\mathrm{28}}$	Automatic
7	AVIRIS	355.15-2515	224	$\frac{\mathrm{48}-\mathrm{10}}{\mathrm{48}-\mathrm{35}}$	Automatic
8	Azimuth Systems AZ-16	0-13000	12	$\frac{7-1}{7-5}$	Automatic
9	CASI spectral	391-905.5	96	$\frac{\mathrm{77}-\mathrm{11}}{\mathrm{77}-\mathrm{55}}$	Automatic
10	ChrisProbaM1	406-1003	62	$\frac{\mathrm{A44}-\mathrm{A2}}{\mathrm{A44}-\mathrm{A26}}$	Automatic
11	ChrisProbaM5	438-1036	37	$\frac{\mathrm{H24}-\mathrm{H1}}{\mathrm{H24}-\mathrm{H9}}$	Automatic
12	CZCS	433-12500	6	$\frac{5-1}{5-4}$	Automatic
13	Daedalus	0-13000	12	$\frac{7-1}{7-5}$	Automatic
14	DAIS-7915	400-12600	79	$\frac{\mathrm{22}-3}{\mathrm{22}-\mathrm{15}}$	Automatic
15	Deimos-2	420-890	5	$\frac{\mathrm{MS4}-\mathrm{MS1}}{\mathrm{MS4}-\mathrm{MS3}}$	Automatic
16	DubaiSat-1	420-890	5	$\frac{\mathrm{MS4\_Near\_Infrared}-\mathrm{MS1\_Blue}}{\mathrm{MS4\_Near\_Infrared}-\mathrm{MS3\_Red}}$	Automatic
17	EnMap	420-2450	244	$\frac{\mathrm{59}-4}{\mathrm{59}-\mathrm{40}}$	Automatic
18	GLI	375-12500	36	$\frac{\mathrm{23}-4}{\mathrm{23}-\mathrm{12}}$	Automatic
19	HYDICE	400-2500	210	$\frac{\mathrm{40}-5}{\mathrm{40}-\mathrm{28}}$	Automatic
20	HyMap	429-2493.8	126	$\frac{\mathrm{25}-2}{\mathrm{25}-\mathrm{17}}$	Automatic
21	Hyperion	349.896-2582.28	242	$\frac{\mathrm{B45}-\mathrm{B10}}{\mathrm{B45}-\mathrm{B33}}$	Automatic
22	IKONOS-2	445-900	5	$\frac{\mathrm{nahe\_Infrarot}-\mathrm{Blau}}{\mathrm{nahe\_Infrarot}-\mathrm{Rot}}$	Automatic
23	PHI	400-1000.35	244	$\frac{\mathrm{163}-\mathrm{18}}{\mathrm{163}-\mathrm{114}}$	Automatic
24	Pleiades-1	430-950	5	$\frac{\mathrm{NIR1}-\mathrm{Blue}}{\mathrm{NIR1}-\mathrm{Red}}$	Automatic
25	PROBA-V	440-1635	4	$\frac{\mathrm{NIR}-\mathrm{BLUE}}{\mathrm{NIR}-\mathrm{RED}}$	Automatic
26	RapidEye	440-850	5	$\frac{\mathrm{Near\_Infrared}-\mathrm{Blue}}{\mathrm{Near\_Infrared}-\mathrm{Red}}$	Automatic
27	SCIAMACHY	240-2380	15	$\frac{\mathrm{PMD4\_NIR}-\mathrm{VIS1}}{\mathrm{PMD4\_NIR}-\mathrm{PMD3\_VIS}}$	Automatic
28	SeaWiFS	412-905	8	$\frac{7-2}{7-6}$	Automatic
29	Sentinel-2A	433-2280	13	$\frac{8-1}{8-4}$	Automatic
30	VIIRS	412-13350	22	$\frac{\mathrm{DNB}-\mathrm{M2}}{\mathrm{DNB}-\mathrm{I1}}$	Automatic
31	WorldView-2	400-1040	9	$\frac{\mathrm{NIR1}-\mathrm{Coastal\_Band}}{\mathrm{NIR1}-\mathrm{Red}}$	Automatic
32	WorldView-3	400-2365	29	$\frac{\mathrm{Near\_IR1}-\mathrm{Coastal}}{\mathrm{Near\_IR1}-\mathrm{Red}}$	Automatic

Applications

Nr.	Name	Comment
1	Vegetation
2	Vegetation - Chlorophyll

References

Nr.	Author/Title	Year	Comment
1	Apan, Armando; Held, Alex; Phinn, Stuart; Markley, John - Formulation and assessment of narrow-band vegetation indices from EO-1 hyperion imagery for discriminating sugarcane disease	2003
2	Blackburn, G. A. - Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves	1998
3	le Maire, G.; Francois, C.; Dufrene, E. - Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements	2004
4	Main, Russell; Cho, Moses Azong; Mathieu, Renaud; O’Kennedy, Martha M.; Ramoelo, Abel; Koch, Susan - An investigation into robust spectral indices for leaf chlorophyll estimation	2011
5	Penuelas J., Baret F., Filella I. - Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance	1995
6	Peñuelas, J.; Filella, I. - Visible and near-infrared reflectance techniques for diagnosing plant physiological status	1998
7	Pu, Ruiliang; Gong, Peng; Yu, Qian - Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index	2008
8	Royo, C.; Aparicio, N.; Villegas, D.; Casadesus, J.; Monneveux, P.; Araus, J. L. - Usefulness of spectral reflectance indices as durum wheat yield predictors under contrasting Mediterranean conditions	2003
9	Strachan, Ian B.; Pattey, Elizabeth; Boisvert, Johanne B. - Impact of nitrogen and environmental conditions on corn as detected by hyperspectral reflectance	2002
10	Zarco-Tejada, P. J.; Miller, J. R.; Noland, T. L.; Mohammed, G. H.; Sampson, P. H. - Scaling-up and model inversion methods with narrow-band optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data	2001

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Visualisation of Sensor-Bands

Index:

Sensors:

AHS

AISA

ALI

ALOS

ARIES-1

ASAS

AVIRIS

Azimuth Systems AZ-16

CASI spectral

ChrisProbaM1

ChrisProbaM5

CZCS

Daedalus

DAIS-7915

Deimos-2

DubaiSat-1

EnMap

GLI

HYDICE

HyMap

Hyperion

IKONOS-2

PHI

Pleiades-1

PROBA-V

RapidEye

SCIAMACHY

SeaWiFS

Sentinel-2A

VIIRS

WorldView-2

WorldView-3

List of Indices