alexa Spatiotemporal Change Detection Analysis of Turkish Lake Water Surface Area in Response to Anthropogenic Ecosystem Disturbances Using Long-Term Landsat TM/ETM+ Data | Open Access Journals
ISSN: 2157-7625
Journal of Ecosystem & Ecography
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Spatiotemporal Change Detection Analysis of Turkish Lake Water Surface Area in Response to Anthropogenic Ecosystem Disturbances Using Long-Term Landsat TM/ETM+ Data

Durmaz F, Karakaya N and Evrendilek F*

Department of Environmental Engineering, Abant Izzet Baysal University, Bolu, Turkey

Corresponding Author:
Evrendilek F
Faculty of Engineering & Architecture
Department of Environmental Engineering
Golkoy Campus, Abant Izzet Baysal
University, 14280 Bolu, Turkey
Tel: +90374 254 2665
Fax: +90374 253 4558
E-mail: [email protected]

Received April 26, 2016; Accepted May 30, 2016; Published June 07, 2016

Citation: Durmaz F, Karakaya N, Evrendilek F (2016) Spatiotemporal Change Detection Analysis of Turkish Lake Water Surface Area in Response to Anthropogenic Ecosystem Disturbances Using Long-Term Landsat TM/ETM+ Data. J Ecosys Ecograph 6: 188. doi:10.4172/2157-7625.1000188

Copyright: © 2016 Durmaz F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

The provision of diverse ecosystem goods and services by lakes is vital to ecosystem health and economic well-being of nations or regions. Securing ecologically safe lake water quality and quantity through sustainable uses and management practices concerns both present and future generations. The present study quantifies long-term impacts of human-induced disturbances including climate change on water surface areas of the 18 largest Turkish lakes. Spatiotemporal change detection analysis was carried out using long-term Landsat time series data between 1973 and 2014 with the aid of geographical information systems (GIS). Supervised and unsupervised classification techniques were combined to temporally differentiate and spatially delineate lake water surface areas using ancillary data. Over the period of about 40 years, lake surface area decreased for 15 lakes at a mean annual rate of 0.96 km2 but increased for three lakes at a mean annual rate of 0.17 km2. These spatiotemporal changes may be attributed to such human-induced pressures as drought, sectoral water uses/withdrawals, draining, and landfilling. These changes in turn lead to losses of or damages to both marketable and non-marketable ecosystem benefits that the lakes provide with humans at the local-to-regional spatial scales in the long-to-short-term temporal scales. The integration of remote sensing and GIS techniques adopted in this study allows for dynamic monitoring of not only lake water quality and quantity but also other natural resources, thus facilitating a timely and effective development of preventive and mitigative measures.

Keywords

Spatiotemporal monitoring; Ecosystem dynamics; Ecosystem health; Ecosystem disturbance regimes

Introduction

Related literature showed that lakes are of vital importance owing to their provision of a wide and diverse range of ecosystem goods and services unsubstitutable through technological progress or fix [1]. Some examples of such life-supporting ecosystem goods and services include regulation of hydrological and climatic regimes; provision of water for drinking, irrigation, fisheries, electricity generation, and recreation; protection of terrestrial and aquatic biodiversity; and scientific and cultural information. Though mostly limited to anthropocentric values, environmental valuation studies have recently intensified so as to reflect the monetary values of non-marketable ecosystem services and natural capital. For example, Mueller et al. [2] estimated the total value of ecosystem services in 2012 provided by Lake Rotorua (New Zealand) to vary between 64.3 million and 95.1 million USD and the total value loss associated with its eutrophication to vary between 9.7 million and 33.1 million USD (based on 1 USD = 1.45 New Zealand dollar in 2016).

Every lake ecosystem with declining water quality and quantity adversely affects all the ecosystem components including people both directly and indirectly. The most pronounced signals of degradation and destruction of lake ecosystems occur in the form of drying, algal blooms, water color changes, and death of aquatic organisms. Main driving forces behind the degradation and destruction include rapid rates of population growth and consumption, poverty, and the inadequate level of integration of the awareness to secure non-marketable but lifesupporting ecosystem services with decision-making mechanisms [3]. Global climate change, and land-use and land-cover (LULC) changes due to migrations, urban sprawl, lack of land suitability/compatibility analyses, and mismanagement practices are the two main factors that threaten lake water quality and quantity [4-6]. In the face of humaninduced pressures on the environment unprecedented in terms of their rate and magnitude such as climate change, there is an urgent need for dynamic monitoring, decision-support and early warning systems so that institutional and societal will regarding the sustainable use and management of natural resources can be put into practice [7]. The objective of this study was to quantify spatiotemporal changes in surface water areas of the 18 largest Turkish lakes analyzing long-term Landsat time series imageries over about 40 years with GIS.

Materials and Methods

18 Turkish lakes with the largest surface areas were selected as the study areas (Table 1). Mean annual air temperature data between 1968 and 2013 were acquired from the Turkish State Meteorological Service (http://www.mgm.gov.tr/en-US/forecast-5days.aspx) in order to relate temperature changes to lake water surface areal changes as a proxy for climate change impacts. Population data in 2015 for the regions where the lakes occur were obtained from the Turkish Statistical Institute (http://www.turkstat.gov.tr/Start.do) and were used as an indicator of urbanization- and population growth-related environmental impacts.

Landsat TM/ETM+ data between 1973 and 2014 were acquired from the US Geological Survey database (http://earthexplorer.usgs. gov/). The selection of the imagery was based on the summer period of June to October, and the ones with less than 10% cloudiness. ArcGIS 10.2 was used in the generation of LULC classifications based on the combined use of supervised and unsupervised techniques with composites of related bands of the Landsat imagery. The five LULC classes of built-up land, water body, forest land, agricultural land including grassland and rangeland, and barren land were classified initially and aggregated into the two classes of water body and the other lands. Raster data of the 82 Landsat images were converted into polygons to estimate changes in lake surface areas.

Region Lake
name*
Lake
type
Province &
coordinates
Landsat date and type
1972-1979 1980-1989 1990-1999 2000-2009 2010-2014
Mediterranean Beyşehir(a) freshwater Konya
37°46′25″N 31°31′13″E
         16.07.1984
Landsat-5
08.08.1998
Landsat-5
27.08.2002
Landsat-7
03.07.2014
Landsat-8
  Eğirdir(b) freshwater Isparta
38°03′21″N 30°52′14″E
16.06.1975
Landsat-2
16.07.1984
Landsat-5
08.08.1998
Landsat-5
27.08.2002
Landsat-7
03.07.2014
Landsat-8
  Burdur(c) brackishwater Burdur
37°43′53″N 30°10′11″E
16.06.1975
Landsat-2
16.07.1984
Landsat-5
06.07.1995
Landsat-5
27.08.2002
Landsat-7
03.07.2014
Landsat-8
Eastern Anatolia Van(d) soda Van
38°36′56″N 42°55′10″E
07-08.06.1975
Landsat-2
31.07.1984 09.08.1984
Landsat-5
10.08.1999
19.08.1999
Landsat-5
  03.08.2014
12.08.2014
Landsat-8
  Çıldır(e) freshwater Ardahan
41°03′32″N 43°12′40″E
  22.06.1987
Landsat-5
  13.06.2001
Landsat-7
03.08.2014
Landsat-8
  Erçek(f) freshwater Van
38°40′12″N 48°35′18″E
14.07.1973
Landsat-2
28.06.1986
Landsat-5
    28.08.2014
Landsat-8
  Hazar(g) freshwater Elazığ
38°29′41″N 39°24′16″E
16.07.1975
Landsat-2
14.08.1984
Landsat-5
04.07.1998
Landsat-5
  17.08.2014
Landsat-8
  Nazik(h) freshwater Bitlis
38°51′21″N 42°17′13″E
06.09.1975
Landsat-2
13.07.1984
Landsat-5
  12.08.2000
Landsat-5
03.08.2014
Landsat-8
Aegean Bafa(i) freshwater Aydın
37°30′01″N 27°26′36″E
16.09.1975
Landsat-2
28.06.1984
Landsat-5
11.06.1995
Landsat-5
04.08.2003
Landsat-5
18.08.2014
Landsat-8
  Köyceğiz(j) freshwater Muğla
36°53′05″N 28°36′55″E
05.07.1975
Landsat-2
30.06.1987
Landsat-5
06.07.1995
Landsat-5
02.08.2002
Landsat-7
27.08.2014
Landsat-8
  Işıklı(k) freshwater Denizli
38°14′50″N 29°53′34″E
05.07.1975
Landsat-2
01.08.1987
Landsat-5
06.07.1995
Landsat-5
  27.08.2014
Landsat-8
  Acıgöl(l) brackishwater Afyonkarahisar
37°49′50″N 29°53′35″E
  30.06.1987
Landsat-5
06.07.1995
Landsat-5
02.08.2002
Landsat-7
27.08.2014
Landsat-8
Central
Anatolia
Tuz(m) saltwater Konya
38°45′51″N 33°21′00″E
07.08.1975
Landsat-2
12.08.1987
Landsat-5
01.08.1998
Landsat-5
17.06.2002
Landsat-7
13.08.2014
Landsat-8
  Akşehir(n) saltwater Konya
38°30′43″N 31°25′20″E
16.06.1975
Landsat-2
16 06 1984
Landsat-5
  31 07 2001
Landsat-5
20 08 2014
Landsat-8
Marmara İznik(o) freshwater Bursa
40°26′52″N 29°32′02″E
17.06.1975
Landsat-2
05.06.1987
Landsat-5
11.06.1995
Landsat-5
05.07.2001
Landsat-7
14.08.2014
Landsat-8
  Manyas(p) freshwater Balıkesir
40°12′06″N 25°56′55″E
18.07.1975
Landsat-2
05.06.1987
Landsat-5
11.07.1995
Landsat-5
05.07.2001
Landsat-7
01.07.2014
Landsat-8
  Uluabat(q) freshwater Bursa
40°08′58″N 28°36′53″E
18.07.1975
Landsat-2
05.06.1987
Landsat-5
11.06.1995
Landsat-5
05.07.2001
Landsat-7
01.07.2014
Landsat-8
  Sapanca(r) freshwater Sakarya
40°43′01″N 30°15′42″E
17.06.1975
Landsat-2
08.08.1984
Landsat-5
06.07.1995
Landsat-5
07.08.2004
Landsat-7
11.08.2014
Landsat-8
*The letters in parenthesis are presented to show the lake names in Figure 1.

Table 1: Types and dates of 82 Landsat imageries used in the present study to quantify spatiotemporal changes in water surface areas of the 18 largest lakes in the five major regions and 14 provinces of Turkey.

The statistical analyses of correlation matrix and multiple non-linear regression (MNLR) models were performed at the significance level (p) of less than 0.05 using Minitab 17. The Correlation coefficients (r) from the Pearson’s correlation matrix were used to detect the direction and strength of significant linear relationships. The direction, shape, rate and strength of significant non-linear relationships were quantified using the best-fit MNLR models based on adjusted coefficient of determination (r2adj).

ecosystem-ecography-surface-areas

Figure 1: Spatiotemporal changes in the surface areas of the 18 largest Turkish lakes based on Landsat time series data between 1973 and 2014 (The letters in parenthesis show the lake names presented in Table 1).

Results and Discussion

Spatiotemporal changes in the surface areas of the 18 largest Turkish lakes chosen in this study were quantified using the Landsat time series and presented in Figure 1. The total water surface area of the 18 largest lakes selected in this study comprised 0.9% (7009 km2) of Turkey. The maximum and minimum surface areas belong to Lakes Van (3549 km2 ) and Acıgöl (23.7 km2), respectively. When the first and last (2014) dates of the Landsat images were compared, our findings showed that the total water surface area decreased by 548.8 km2 for the 15 lakes but increased by 19.7 km2 for the three lakes (Table 2). Water surface areas of Lakes Van, Erçek and Eğirdir increased at rates of 0.3%, 1%, and 1.8% over the entire periods, respectively. The overall mean amount and rate of decrease in the Turkish lake water surface areas were estimated at 13.5% (29 + 61 km2 ) and 0.4% year-1 (0.8 + 2 km2 year-1), respectively. Since mean values are sensitive to outliers, median values were also computed which indicated that the overall median amount and rate of decrease in the Turkish lake water surface areas were 5.2% (3.6 km2 ) and 0.1% year-1 (0.1 km2 year-1), respectively. Relative to the year 2014, the 39-year maximum amount of decrease and increase in the water surface areas took place with 249 km2 (73.4%) for Lake Akşehir and 10.8 km2 (1.8%) for Lake Van, respectively. Similarly, maximum rate of decrease and increase in the water surface areas was estimated for Lake Akşehir at 6.37 km2 yıl-1 (1.8% year-1) and for Lake Van at 0.28 km2 year-1 (0.01% year-1), respectively (Table 2).

Increased growth rates of population and urbanization are one of the main root causes of anthropogenic disturbances of lake ecosystems. According to the 2015 population data (Table 3) for the regions where the lakes are located, the Marmara region where the surface area of all the four lakes decreased ranked in the first place. The same case applied to the two lakes in the Central Anatolia region and to the four lakes in the Aegean region that ranked second and third in population in 2015, respectively (Table 3). However, the water surface area increased in two of the five lakes in the Eastern Anatolia region that ranked last in population.

  Lake
name
Baseline
Landsat
image date
  Landsat
image date
  Area
(km2)
  Amount of change   Rate of change
(%) (km2) (% yıl-1) (km2 yıl-1)
Beyşehir 16.07.1984   665.2        
  08.08.1998 610.6 -8.2 -54.6 -0.59 -3.9
  27.08.2002 628.3 -5.5 -36.9 -0.31 -2.05
  03.07.2014 636.4 -4.3 -28.8 -0.14 -0.96
Eğirdir 16.06.1975   448.2        
  16.07.1984 471.6 5.2 23.4 0.58 2.6
  08.08.1998 455.8 1.7 7.6 0.07 0.33
  27.08.2002 452.9 1 4.7 0.04 0.17
  03.07.2014 456.1 1.8 7.9 0.05 0.2
Burdur 16.06.1975   207.8        
  16.07.1984 206.5 -0.6 -1.3 -0.07 -0.14
  06.07.1995 171.0 -17.7 -36.8 -0.89 -1.84
  27.08.2002 151.4 -27.1 -56.4 -1.01 -2.09
  03.07.2014 135.4 -34.8 -72.4 -0.89 -1.86
Van 07-08.06.1975   3538.0        
  31.07.1984-09.08.1984 3563.0 0.7 24.8 0.08 2.76
  10-19.08.1999 3566.0 0.8 27.2 0.03 1.13
  03-12.08.2014 3549.0 0.3 10.8 0.01 0.28
Çıldır 22.06.1987   125.1        
  13.06.2001 124.7 -0.3 -0.4 -0.02 -0.03
  03.08.2014 122.9 -1.8 -2.2 -0.07 -0.08
Erçek 14.07.1973   105.0        
  28.06.1986 103.5 -1.4 -1.5 -0.11 -0.12
  28.08.2014 106.1 1 1.1 0.03 0.03
Hazar 16.07.1975   78.0        
  14.08.1984 77.8 -0.3 -0.2 -0.03 -0.02
  04.07.1998 79.9 2.4 1.9 0.11 0.08
  17.08.2014 77.8 -0.3 -0.2 -0.01 -0.01
Nazik 06.09.1975   46.3        
  13.07.1984 46.7 0.9 0.4 0.1 0.04
  12.08.2000 45.5 -1.7 -0.8 -0.07 -0.03
  03.08.2014 45.1 -2.6 -1.2 -0.07 -0.03
Bafa 16.09.1975   61.7        
  28.06.1984 65.4 6 3.7 0.67 0.41
  11.06.1995 65.5 6.2 3.8 0.31 0.19
  04.08.2003 66.7 8.1 5 0.29 0.18
  18.08.2014 57.4 -7 -4.3 -0.18 -0.11
Köyceğiz 05.07.1975   53.1        
  30.06.1987 53.5 0.8 0.4 0.06 0.03
  06.07.1995 52.9 -0.4 -0.2 -0.02 -0.01
  02.08.2002 53.5 0.8 0.4 0.03 0.01
  27.08.2014 53.0 -0.2 -0.1 -0.005 -0.003
Işıklı 05.07.1975   50.4        
  01.08.1987 55.4 9.9 5 0.83 0.42
  06.07.1995 51.1 1.4 0.7 0.07 0.04
  27.08.2014 40.4 -19.8 -10 -0.51 -0.26
Acıgöl 30.06.1987   54.9        
  06.07.1995 51.7 -5.8 -3.2 -0.73 -0.4
  02.08.2002 48.2 -12.2 -6.7 -0.81 -0.45
  27.08.2014 23.7 -56.8 -31.2 -2.1 -1.16
Tuz 07.08.1975   1103.0        
  12.08.1987 1091.0 -1.1 -12.1 -0.09 -1.01
  01.08.1998 1353.0 22.6 249.6 0.98 10.85
  17.06.2002 1054.0 -4.5 -49.3 -0.17 -1.83
  13.08.2014 1009.0 -8.6 -94.4 -0.22 -2.42
Akşehir 16.06.1975   338.6        
  16.06.1984 369.3 9.1 30.7 1.01 3.41
  31.07.2001 142.4 -57.9 -196.2 -2.23 -7.55
  20.08.2014 90.0 -73.4 -248.6 -1.88 -6.37
İznik 17.06.1975   303.5        
  05.06.1987 303.3 -0.1 -0.2 -0.01 -0.02
  11.06.1995 297.9 -1.8 -5.6 -0.09 -0.28
  05.07.2001 301.7 -0.6 -1.8 -0.02 -0.07
  14.08.2014 300.8 -0.9 -2.7 -0.02 -0.07
Manyas 18.07.1975   162.5        
  05.06.1987 168.6 3.8 6.1 0.31 0.51
  11.07.1995 160.5 -1.2 -2 -0.06 -0.1
  05.07.2001 148.5 -8.6 -14 -0.33 -0.54
  01.07.2014 146.8 -9.7 -15.7 -0.25 -0.4
Uluabat 18.07.1975   142.8        
  05.06.1987 148.6 4.1 5.8 0.34 0.48
  11.06.1995 140.4 -1.7 -2.4 -0.08 -0.12
  05.07.2001 115.7 -19 -27.1 -0.73 -1.04
  01.07.2014 114.9 -19.5 -27.9 -0.5 -0.72
Sapanca 17.06.1975   46.6        
  08.08.1984 45.7 -1.9 -0.9 -0.21 -0.1
  06.07.1995 44.9 -3.6 -1.7 -0.18 -0.09
  07.08.2004 44.9 -3.6 -1.7 -0.13 -0.06
  11.08.2014 43.8 -6 -2.8 -0.15 -0.07
Grand total value in 2014 7009 -243 -523 -7 -14
Grand mean value in 2014   -13.5 -29.0 -0.4 -0.8
Standard deviation   21 61 1 2
Median value in 2014   -5.2 -3.6 -0.1 -0.1

Table 2: Long-term spatiotemporal change regimes of water surface areas of the 18 largest Turkish lakes relative to the baseline Landsat images.

According to the 45-year mean annual air temperature (MAT) data for the 14 provinces, the maximum and minimum MAT increases were observed for Ardahan (Lake Çıldır) by 46.2% and for Balıkesir (Lake Manyas) by 0.2%, respectively (Table 4). Though not found to the amount and rate of changes in the lake surface areas based on the correlation matrix analysis, a significant linear relationship of the longterm MAT increase (%) was detected to latitude (r = 0.51; p = 0.03), longitude (r = 0.61; p = 0.007), and elevation above sea level (r = 0.54; p = 0.01) (n = 18). However, significant non-linear relationships between the long-term MAT increase and the amount and rate of changes in the lake surface areas were captured using the best-fit MNLR models. Given r2 adj values of the best-fit MNLR models, the three-way interaction term of long-term MAT increase × lake surface area × region accounted for 69.5% and 70.0% of variations in the amount (%) and rate (% year- 1) of changes in the lake surface area, respectively (p = 0.2 and 0.25, respectively). Likewise, together with this three-way interaction term, the two-way interaction of long-term MAT increase × region explained 94.7% of variation in the amount of changes (km2), while the three-way interaction term alone elucidated 67.3% of variation in the rate (km2 year-1) of changes in the lake surface area (p = 0.001).

Region
name
Number
of lakes
Population
in 2015
Marmara 4 23,608,079
Central Anatolia 2 12,381,363
Aegean 4 10,023,549
Mediterranean 3 9,906,771
Eastern Anatolia 5 5,927,630

Table 3:Population data in 2015 according to the regions where the 18 largest lakes selected in the study are located.

Location of
meteorological
station
Latitude Longitude Elevation 5-year MAT (oC) Change between the first and last
periods (%)
(decimal
degree)
(decimal
degree)
(m) 1968-1972 2000-2004 2009- 2013
Afyonkarahisar 38.77 30.55 1034 10.9 11.6 12.5 14.5
Ardahan 41.07 42.43 1829 3.5 4.0 5.2 46.2
Aydın 37.83 27.83 57 17.5 18.1 18.3 4.4
Balıkesir 39.65 27.87 3 14.6 14.6   0.2
Bitlis 38.37 42.1 1550 9.6 9.5 10.1 6.2
Burdur 37.72 30.27 967 13.0 13.3 14.2 9.7
Bursa 40.18 29.03 100 14.1 14.8 15.4 8.6
Denizli 37.77 29.07 426 15.5 16.7 17.5 12.9
Elazığ 38.68 39.23 991 12.9 13.0 13.8 7.7
Isparta 37.75 30.55 997 12.2 12.6 12.9 5.8
Konya 37.88 32.5 1026 11.4 11.6   1.7
Muğla 37.13 28.22 646 14.9 15.5 15.7 5.0
Sakarya 40.47 30.25 30 14.2 14.8 16.1 13.2
Van 38.53 43.35 1725 8.2 10.0 10.2 23.4

Table 4:Long-term (1968-2013) five-year mean annual air temperature (MAT,oC) data according to the 14 provinces where the 18 largest lakes selected in the study are located

As far as the disappearing, shrinking or warming lakes with the significant losses of ecosystem services are concerned, the most recent one among many examples of from around the world such as Aral Sea in central Asia is Lake Poopo, the second largest inland lake (3192 km2) in Bolivia [8]. Evidence suggests that the surface water temperatures of the world’s lakes have on average risen by 0.34°C per decade since 1985 [9]. The surface area of ponds in northern Alaska was estimated to have diminished by nearly a third and to have vanished by nearly a fifth over the last 60 years [10]. On the other hand, a total of 1099 new lakes in the Third Pole region including the Pamir-Hindu Kush-Karakoram- Himalayas and the Tibetan Plateau were found to have emerged due to rapid glacier melting using Landsat TM/ETM + data between 1990 and 2010 which amounted to a 23% increase in surface area [11].

Conclusions

Interaction and main effects of such main degradation drivers of lake water quality and quantity as increased growth rates of population and urbanization, climate change impacts (e.g. increased temperature, evapotranspiration, snow-melting and extreme weather events), LULC changes, and mismanagement practices (e.g. landfilling, drainage, and excessive amounts of agricultural, industrial, municipal, recreational and energetic water uses) remain to be explored in the future studies. Also, uncertainty and sensitivity analyses of quantified impacts need to be carried out for results of dynamic monitoring systems to be incorporated within the decision-making process. The establishment of spatiotemporally dynamic monitoring and database systems at the national and watershed scales based on remote sensing and GIS analyses provides the basis for the receipt of warning signals prior to occurrence of irreversible or socially unacceptable environmental damages, restoration/rehabilitation of damaged ecosystems, and the adoption of sustainable management practices.

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