What is a vegetation index?

Transcription

1 Vegetation indexes

2 What is a vegetation index? A tool: a vegetation index is a mathematical formula used to estimate the likelihood of vegetation presence in remotely sensed data A product: the result of applying the formula to real data is als called vegetation index

3 Where are we?

4 Two types All vegetation indexes derive from measurements on at least two bands two main types of V.I. can be distinguished empirical indexes; optimized indexes.

5 1 group: empirical indexes Empirical indexes: most indexes were determined by experiments, without caring for the exact physical meaning of the result. empirical indexes are a-dimensional detectors of vegetation presence. without an exact physical meaning.

6 2 group: optimized indexes Optimized indexes: More recent (>1990) than empirical indexes; optimized to estimate a specific vegetation characteristic based on a specific instruments. Estimates, rather than indexes, but the name has remained for historical reasons.

7 Comparison Empirical indexes: Optimized indexes: Simple and quick to compute, (nearly) sensor-independent Sensitive to non-relevant parameters (moisture, illumination) No physical quantities, just indicators Complex to compute, sensorspecific The result is a defined geophysical quantity Make comparisons possible between different sites and sensors

8 What are they based on? Healty green vegetation has a characteristic interaction with energy in the visible and near-infrared region. Visible: chlorophyll adsobs power to perform photosynthesis, especially in the red and blue bands. Near infrared: the internal structure of leaves is strongly reflective (spongy parenchyma, part of the mesophyll)

9 Chlorophyll nm 453 nm 642 nm 662 nm

10 it.wikipedia.org Mesophyll

11 Other classification Jackson and Huete (1991) classification of vegetation indexes: slope-based distance-based transformed (tasseled cap) Jackson. R.D. and Huete. A.R Interpreting vegetation indexes. Prev. Vet. Med. 11. pp

12 slope-based V.I. Ideally, the sheer slope of R-NIR line should be related to vegetation abundance: In practice, adjustments needed In principle, always R-NIR comparison Examples: RATIO, NDVI, RVI, NRVI, TVI, CTVI, TTVI. NIR IV crescente R

13 RATIO index Introduced by Jordan in 1969 for ground-based forest mapping, and then applied to satellite images Simplest formula: RATIO = NIR/R Non-linear behaviour C.F. Jordan. Derivation of leaf-area index from quality of light on the forest floor. Ecology 50 (1969). pp

14 Normalized Differential V.I. (NDVI) Proposed by Rouse in 1974 for Landsat MSS: wrt RATIO has the advantage of producing a linear scale theoretically between -1 and +1. Vegetation is assumed to be present for values >0; the higher, the more vegetation, but unlikely to reach beyond Most commonly used V.I. NDVI = NIR R NIR + R

15 Distance-based V.I. The main objective of these vegetation indexes is to minimize the interference of soil in case of sparse vegeation many mixed pixels typical for arid and semi-arid regions The prototype is the so-called PVI (Perpendicular Vegetation Index). from which many others were derived

16 R/NIR scattergram of desert soil and related vegetation, from the ETL (Satterwhite. et al ) spectral library plus others from various sources including USGS (Clark. et al ). Soil line

17 Perpendicular Vegetation Index (PVI) suggested by Richardson e Wiegand (1977), parent of distance-based indexes. perpendicular distance from soil line NIR vegetation water R

18 PCA For typical spaceborne multispectral instruments: PC1 is related to albedo PC2 is related to the quantity of vegetation this can be exploited to generate a new family of vegetation indexes Statistical measurements allowed to fix the best coefficients (eigenvectors) to generate specific vegetation indexes

19 Tasseled Cap Computes 4 new orthogonal axes soil brightness (SBI) greenness (GVI) yellow (YVI) non-such (NSI) The second axis is the Green Vegetation Index Coefficients: SBI = (MSS ) + (MSS ) + (MSS ) + (MSS ) GVI = (MSS ) + (MSS ) + (MSS ) + (MSS ) YVI = (MSS ) + (MSS ) + (MSS ) + (MSS ) NSI = (MSS ) + (MSS ) + (MSS ) + (MSS )

20 MSS to TM Tasseled Cap for LANDSAT Thematic Mapper: Bright = (TM ) + (TM ) + (TM ) + (TM ) + (TM ) + (TM ) Green = (TM ) + (TM ) + (TM ) + (TM ) + (TM ) + (TM ) Third. or Moist = (TM ) + (TM ) + (TM ) + (TM ) + (TM ) + (TM )

21 Why cap? In the three main scattergrams, vegetation pixel set takes a cap shape

22 NDVI example False colour image of Crimea Extracted NDVI map:

23 Tasseled Cap example TM TM TM Squaw Creek National Wildlife Refuge. northwest Missouri

24 NDVI Tasseled cap