Geography Reference
In-Depth Information
in addition to the application of remote sensing in land use/land cover classifi-
cation. This Chap. 2 also reviews the literature on the current state of knowledge
on regional scale crop area estimate approaches. This includes crop area estimates
using remotely sensed data, the importance of temporal and spatial resolution, and
the ability of satellite imagery to discriminate among crops.
The Chap. 3 describes the study area of the Euphrates River Basin, Syria. In
this chapter the location, irrigation projects, climate, morphology, soil, hydrology,
land use/land cover and human impacts are discussed. Chapter 4 describes the
common resources that were available for this study, including satellite data, maps,
field reference data, statistics and another ancillary data. Chapter 5 discusses the
pre-processing techniques applied to the satellite images in order to obtain data
with low calibration errors as a prerequisite for interpretation and comparison.
Emphasis was placed on the geometric and radiometric accuracy of the processed
data. In addition, research methodology, image processing, image classification
and accuracy assessment are outlined in this chapter. In Chap. 6 , results, analysis
and thematic interpretations are discussed. The overall summary, general con-
clusions and recommendations of the research study are provided in Chap. 7 .
References
Abuzar, M., McAllister, A., & Morris, M. (2001). Classification of seasonal images for
monitoring irrigated crops in a salinity-affected area of Australia. International Journal of
Remote Sensing, 22(5), 717-726.
ACSAD. (2001). Surface water resources in the basins of the Euphrates and Tigris rivers (p. 168).
Damascus-Syria.
Allen, J. D. (1990). A look at the remote sensing applications program of the National
Agricultural Statistics Service. Journal of Official Statistics, 6(4), 393-409.
Beaumont, P. (1996). Agricultural and environmental changes in the upper Euphrates catchment
of Turkey and Syria and their political and economic implications. Applied Geography, 16(2),
137-157.
Blaes, X., Vanhalle, L., & Defourny, P. (2005). Efficiency of crop identification based on optical
and SAR image time series. Remote Sensing of Environment, 96(3-4), 352-365.
Campbell, B. C. (2002). Introduction to remote sensing. London: Taylor & Francis.
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monitoring of agricultural crop status: Effect of time of year, crop type and crop condition
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Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., & Lambin, E. (2004). Digital change
detection methods in ecosystem monitoring: A review. International Journal of Remote
Sensing, 25(9), 1565-1596.
Dheeravath, V., Thenkabail, P. S., Chandrakantha, G., Noojipady, P., Reddy, G. P. O., Biradar, C.
M., et al. (2010). Irrigated areas of India derived using MODIS 500 m time series for the years
2001-2003. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1), 42-59.
Draeger, W. (1976). Monitoring irrigated land acreage using Landsat imagery: An application
example. USGS Open-file Report No. 76-630, (pp. 23). USGS, Sioux Falls, S.D.
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