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2022RS6_RemoteSensingofVegetationFin2 (1).pptx
2022RS6_RemoteSensingofVegetationFin2 (1).pptx
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Remote Sensing of Vegetation 1
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Lecture objectives Phenological cycle Vegetation indices • Vegetation index (VI) • Normalized difference vegetation index (NDVI) • Enhanced vegetation index (EVI) 2
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Vegetation Indices • Topics: – What are Vegetation Indices? – Why do they work? – Band Ratios – emphasize leaf area index (LAI), % green cover, chlorophyll content, green biomass. – NDVI: Normalized Difference Vegetation Index – EVI: Enhanced Vegetation Index 3
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Phenological cycle characteristics What is phenology? periodic biological phenomena that are correlated with climatic (annual) conditions Tells when Remote Sensing (R S) data should be collected When the crops are planted? When they are harvested? When do they reach their full development? And when they have not yet developed. 4
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Phenological cycle characteristics Winter Wheat Phenology snow cover SEP OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG crop establishment greening up heading mature Harvest 50 108 days 28 34 29 21 Dead 10 14 26 14 14 21 13 25 47 9 5 ripe Sow Tillering Dormancy Growth Jointing Heading Emergence resumes Boot Soft Hard dough dough 5 Maximum Coverage
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125 Soybeans a. 100 75 100% Phenological Soybeans 50 25 cm height snow cover 50% ground cover Cycles of JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Soybeans and Dormant or multicropped Initial growth Development Maturity Harvest Corn in South 300 b. Carolina 250 Corn Corn 200 100% 150 125 100 75 50% 50 snow cover 25 cm height JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 12-14 Tassle Jensen, 2000 Dormant or multicropped 8-leaf Blister Dent/Harvest Dormant or multicropped leaf 10 - 12 leaf
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100 a. 75 Winter Wheat Phenological Winter Wheat 50 25 cm 100% snow cover ground Cycles of Winter cover JAN FEB 50% MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Wheat, Cotton, Tillering Jointing Booting Head Harvest Dormant or multicropped Seed and Tobacco in 150 125 Winter Wheat Phenology Cotton b. South Carolina Cotton 100 75 100% 50 50% ground snow cover cover 25 cm height JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Dormant or multicropped Seeding Fruiting Boll Maturity/harvest Pre-bloom 125 c. 100 Tobacco http://farm4.staticflickr.com/3137/ Tobacco 2997265506_1996582916_z.jpg 75 100% 50 snow cover 50% 25 cm height JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Dormant or multicropped Transplanting Development Maturity/harvest Dormant or multicropped Jensen, 2000 Topping
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What are Vegetation Indices? A Vegetation Index (VI) is a “synthetic image layer” created from the existing bands of a multispectral image This new layer often provides unique and valuable information not found in any of the other individual bands. For example: VIs have been shown to quantify or predict vegetation biomass, productivity, leaf area, and/or vegetative ground cover. 8
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Normalized Difference Vegetation Index (NDVI) NDVI is a simple numerical indicator that can be used to analyze remote sensing measurements, and Assess whether the target being observed contains live green vegetation or not. 9
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Normalized Difference Vegetation Index (NDVI) Very low values of NDVI (0.1 and below) correspond to barren areas of rock , sand, or snow. Moderate values represent shrub and grassland (0.2 to 0.3), while high values indicate temperate NIR red and tropical rainforests (0.6 to 0.8). NDVI [1] NIR red 10
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The most unique feature of the vegetation reflectance curve is the low red reflectance and high NIR reflectance. Healthy Vegetation Cover NIR Red NIR/Red Bare Soil Dr y Water Soil Low High Low High ~ 0.1 ~1 Vegetation Very High Low Very High 0.4 Clear Water 2.6 Near Infrared Mid Infrared Wavelength (m) m) 11
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Vegetation Indices (VIs) There are several VIs, most are functionally equivalent Most use a combination of the red and near infrared bands • Simple Ratio (SR ) • Normalized Difference Vegetation Index (NDVI) • Enhanced vegetation index (EVI) 12
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Simple Ratio (SR ) Cohen (1991) suggests that the first true vegetation index was the Simple Ratio (SR ) Image ratioing serves to highlight subtle variations in the spectral responses of various surface covers. Landsat: Band 4/Band 3 NIR SR Re d 13
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Normalized Difference Vegetation Index (NDVI) Rouse et al. (1974) developed the generic NDVI NDVI values are real numbers ranging from -1 to 1, Well vegetated areas have higher values (NIR >> red reflectance) Water (and sometimes shadow) have negative values (red reflectance > NIR reflectance) Rock , dry soil, and senesced vegetation have values near zero (red reflectance = NIR reflectance). NIR red NDVI NIR red 14
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Example NDVI Image Red Near Infrared NDVI 15
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NDVI of AVHRR Imagery Progression through the season... Low NDVI VALUE High 18
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Enhanced Vegetation Index (EVI) RNIR RRe d EVI (1 L) RNIR C1 RRe d C2 RBlue L Where C1, C2 coefficients adjusting for atmospheric effects and L is a soil adjustment factor. • They are empirically determined as C1=6.0, C2=7.5 and L=1.0. • EVI has improved sensitivity to high biomass regions. Huete and Justice, 1999 MODIS vegetation index. http://modarch.gsfc.nasa.gov/MODIS/LAND/#vegetation-indices 19
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• In addition to the standard VIs, there are several transformation equations that each create several new images. • Linear transformations – PCA (principal component analysis) – K-T (Kauth-Thomas) – Tasseled cap transform 21