ds at the object
n using Landsat
Turkey, the best
nd cover types is
nagery for these
. land cover/use
the Atatürk Dam
th water reserve
am Lake with a
nded land is 817
Atatürk dam is
n area of 8,724
jir is 526 m. The
rigated from the
entral part of the
rigation District.
n of rolling hills
ria (Fig 2). Two
in the study are
9?Q'Q"E
(August 2011).
ey with the study
le.
es of the Eastern
ence. The annual
average temperature is 18 °C and annual rainfall is around 350
mm. There is significant seasonal variation in precipitation, with
most precipitation occurring between November and April. The
area receives almost no rain during the summer, at which time
irrigation becomes crucial.
The Sanliurfa-Harran Plain Irrigation Project is the first realized
scheme within the Lower Euphrates Project. The water is
brought to Sanliurfa- Harran Plain by the Sanliurfa tunnel
system consisting of two parallel tunnels each 26.4-km long and
with an 7.62-m inside diameter and a carrying capacity of 328
m? /sec. These tunnels were completed successively in 1995 and
in 1998. The irrigation capacity of Sanliurfa and Harran canals
are almost 500 km? and 1000 km”.
Several different crops including cotton, cereals, maize, and
vegetables are cultivated in the Harran Plain. While there is a
variety, cotton and cereals dominate the agricultural scene in
any given year (Ozdogan et al., 2006).
3. METHODOLOGY
Remote sensing has been an effective tool for monitoring
imigated fields under a variety of climatic conditions and
locations. The thematic analysis of multi-temporal data series
requires differences between images to result exclusively from
changes in surface properties, necessitating a precise geometric
and radiometric correction of incorporated images (Song et al.,
2001).
Monitoring the changes in the Atatürk Dam Lake and summer
irrigated fields in the Harran Plain require multiple sources of
data. In the first part of this study, land cover/use changes on
agricultural fields under the Atatürk Dam Lake and its vicinity
have been identified between the periods of 1984 to 1992.
Reserve changes and inundated agricultural fields have been
identified by change detection using multi temporal Landsat
imagery within these periods.
After the 10-year period of completion and the filling up of the
reservoir in 1992, Landsat and meteorological time-series
analyses are examined to assess the impact of the Atatürk Dam
Lake on irrigated agricultural areas in the Harran Plain. For the
last 9-year period from 2002 to 2011, the relationships between
seasonal water reserve changes and irrigated plains under
changing climatic factors primarily driving vegetation activity
on the watershed have been analyzed consecutively using the
appropriate tools. A total number of 99 Landsat images have
been used in order to constitute time series analysis and to
determine the changes on these fields in conjunction with
climatic datasets. For all images, geometric corrections
including digital elevation information and Tasseled Cap
transformations were carried out to attain changes in surface
Res and denoting disturbance of Landsat reflectance
ata.
Tasseled Cap transformation was originally developed for early
Landsat sensors (multispectral scanner and thematic mapper)
(Crist & Cicone, 1984; Kauth & Thomas, 1976), its linear
coefficients have more recently been modified for applicability
to Enhanced Thematic Mapper Plus (ETM+) imagery. In order
to use the tasseled cap coefficients (Huang et al., 2002) for the
Landsat 5 TM sensor, conversion of the Landsat 5 TM DN data
into data that is equivalent to data recorded by the Landsat 7
ETM+ sensor is needed due to the calibration differences
between the two sensors. This process is described by
Vogelmann et al. (2001) in reverse; that is, they converted from
Landsat 7 ETM+ data to Landsat 5 TM equivalent. To convert
from Landsat 5 TM DN data to Landsat 7 ETM+ DN data, the
following expression is used (Eq. 1):
DN! —(slope, * DN5) -intercept ; (1)
where DN7 is the Landsat 7 ETM+ equivalent DN data, DNS is
the Landsat 5 TM DN data, and the slope and intercept are
band-specific numbers.
Before converting to reflectance data, all images with DN
values were converted to radiance. While radiance is the
quantity actually measured by the Landsat sensors, a conversion
to reflectance facilitates better comparison among different
scenes. It was obtained by removing differences caused by the
position of the sun and the differing amounts of energy output
by the sun in each band. The reflectance can be thought of as a
“planetary albedo,” or fraction of the sun’s energy that is
reflected by the surface. During the conversion from DN data to
reflectance, it is possible to create small negative reflectance
values which are set to zero.
Each image was taken during the mid-to-late summer months
from 1992 through 2011 in order to investigate the change
detection on Harran Plain and environmental impacts due to
water reserve changes in Atatürk Dam Lake. All images were
radiometrically corrected and then converted into reflectance
values and then tasseled cap procedure was used to create a
vegetation index that measures three vegetation dimensions—
brightness, greenness and wetness (Crist and Krauth, 1986).
Table 1 gives an overview of the Landsat based Tasseled Cap
coefficients (Huang et al., 2002).
Table 1. Tassled Cap coefficients for Landsat (Huang et al.,
2002).
Band 1 Band2 Band 3 Band 4 Band5 Band 7
B 0.3561 0.3972 0.3904 0.6966 0.2286 0.1596
G -0344 -03544 -0.4556 0.6966 -0.0242 -0.2630
W 0.2626 0.2141 0.0926 0.0656 -0.7629 -0.5388
Remote sensing change detection is performed using the
Disturbance Index described in Healey et al. (2005), an index
specifically designed to detect changes in vegetated land cover
types. The Disturbance Index is a transformation of the Tasseled
Cap data space and is calculated using the three normalized
Tasseled Cap indices (brightness, greenness and wetness) from
Landsat TM/ETM--data (Healey et al., 2005; Kauth & Thomas,
1976; Masek et al., 2008). The index is computed as a linear
combination of the three normalized Tasseled Cap values (Eq.
2):
G-G WW
A eran)
Bg Go W,
where B,, G, , W, are the normalized (rescaled) brightness,
greenness, and wetness, indices respectively, and B PE Gu»
Wu and By, Gg, W,, are mean and standard deviation of
these three Tasseled Cap spaces. The re-scaling process
normalizes pixel values across Tasseled Cap bands with respect
to overall changes in reflectance, such as seasonal changes or
changes induced by directional reflectance effects, thereby