Introduction - Historical Land Use/Land Cover Classification Using Remote Sensing - page 4

The quality of the agricultural information systems in Syria and the cropped
areas estimate range from timely and reliable to virtually non-existent. Estimates
are based on past trends (e.g., ground survey or census), and are sometimes
adjusted by subjective judgment, rather than on objective information. There exists
an established need for the nations of the world to better manage the planet's
agricultural production, with improved seasonal information on crop prospects for
important producing regions. This need, coupled with the state of technical
development and the conceptual processing of remote sensing, has brought into
focus the possibility of applying remote sensing and related technology, to the task
of developing a technical concept for agricultural monitoring (Erb 1980 ). The
reliance on remote sensing techniques and using its data in Earth Observing
Studies has many important advantages for these studies in comparison to other
old and classical approaches. These remotely sensed data are objective, well-
timed, and recurrent and thus they could be able to present results (e.g., classifi-
cation results) with a higher accuracy. During the last four decades, satellite-
obtained information in the agriculture sector, using low spatial resolution images
to high spatial resolution images, was helpful in the decision-making processes of
governments. Agricultural production is highly dynamic and depends on compli-
cated interactions of prices, weather, soils and technology all over the world. This
production has an influence on the global food market. For the purposes of agri-
cultural studies, there is the need for accurate data at a specific time. Here, because
the meaningful forces (e.g., economic, food, policy and environmental impacts) of
major strategic crops, it is significant to know the local distribution and the acreage
of these types of crops. For these reasons, remote sensing, either alone or in
combination with ground surveys (important for training samples gathering,
classification use and ground truth points used for accuracing the classification
results), has been used in crop acreage assessment (Erb 1980 ; Allen 1990 ;
Wardlow and Stephen 2008 ).
The use of remote sensing data and its applications for distinguishing between
types of agricultural crop and interior crop characteristics was widely researched
during the last four decades (Cloutis et al. 1996 ; Blaes et al. 2005 ; Ozdogan 2010 ).
The well improved tendencies involving particular types of crop, maturity, levels
of the nutrient, and their reflectance values within the spectral bands and in cor-
relation to the vegetation indices (VIs), are becoming more accurate and are
helpful when the availability of ground truth data is limited (Senay et al. 2000 ).
Techniques of satellite remote sensing have a fundamental role in irrigation
management. Some applications of satellite remote sensing techniques for irri-
gation management are: crop acreage; crop condition; crop yield; and performance
of irrigation canal system. These techniques were applied effectively in monitoring
irrigated lands in many areas around the world under a variety of climatic con-
ditions. It offers a synoptic and a suitable temporal coverage of agricultural lands
in several spectral regions. Its archived data offers comparison of imagery among
dates, and yielding change over time. Up to now, there are many studies that have
used remotely sensed imagery, mainly at high spatial resolutions such as
LANDSAT, to observe and classify irrigated agriculture. The early studies focused