modisRice: Classification based on NDVI, EVI and LSWI thresholds

In RiceMap: Mapping rice area with time series of MODIS images

Description

Third function based on a series of four functions developed for mapping rice areas using MODIS data. Generates six classes based on NDVI, EVI, LSWI thresholds.

Usage

modisRice(inpath, informat, outformat="raster", tiles="all")

Arguments

inpath	path with cleaned modis files
informat	File format of the input files can either be "raster" (.grd) or "GTiff" (.tif).
outformat	File format desired by user can either be "raster" (.grd) or "GTiff" (.tif).
tiles	vertical and horizontal tile number of MODIS, tiles should follow the format in the MODIS filename, e.g. "h29v07"

Details

The algorithm uses thresholds based on NDVI, EVI, and LSWI to classify rice and non rice pixels. It generates the following classes:

	Class	detection method
	Flooding/transplanting	(lswi + 0.05 >= evi) | (lswi + 0.05 >= ndvi); LSWI either approaches or is higher than NDVI or EVI may signal flooding in paddy rie fields
	Permanent water	(ndvi < 0.1) & (ndvi < lswi); thse are rivers, lakes, ocean
	Forest	NDVI values >= 0.7 over atleast 20 8-day composites during the year.
	Shrub	LSWI values >= 0.10; these are evergreen shrublands and woodlands
	notrice	combined all classes that were not classified as rice; these are permanent water, forest and shrub
	Perhapsrice	flooding/transplanting pixels and those that were not classified as notrice

Author(s)

Sonia Asilo

References

Xiao, X., Boles, S., Frolking, S. et.al. 2006. Mapping paddy rice agriculture in Southeast Asia using multi-temporal MODIS images. Remote Sensing of Environment 100, pages, 95-113.

See Also

modisClean, modisVeg, vi

RiceMap documentation built on May 2, 2019, 5:16 p.m.