Home Articles Environmental Change Monitoring by Geoinformation Technology for Baghdad and its Neighboring Areas

Environmental Change Monitoring by Geoinformation Technology for Baghdad and its Neighboring Areas

Dr. Ayad Mohammed Fadhil
Assistant Professor,
Surveying Engineering Dept.,
Technical College / Baghdad,
Foundation of Technical Education,
Ministry of Higher Education and Scientific Research,
Baghdad – Iraq
[email protected]

Abstract
This research focuses on the environmental change monitoring in the middle region of Iraq, which comprises five governorates includes twelve counties in Baghdad governorate and parts of the neighboring governorates such as; Al-Anbar, Salah-Alddin, Dialah, and Babil. Multi temporal remotely sensed data (Landsat TM 1990 and ETM+ 2001), and county-level necessary data for the corresponding study period were utilized. The study aimed to monitoring, assessing, and mapping the environmental changes, and to developing a dynamic monitoring system for the study area in order to provide a useful reference to the researches, the academic establishments, and to the decision makers for their sustainable land recourses exploitation and environment management. The Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BSI), The Normalized Differential Water Index (NDWI), Tasseled Cap transformation Wetness indicator (TCW) algorithms, and Change detection techniques were adopted in this research. The results showed an increase in the vegetation cover, farm lands, soil moisture, and the built up areas, while the water bodies has gained a significant decrease in some studied counties during the study period.

1. Introduction
Nowadays the environmental changes are becoming the hot issues to human beings in the world. Land degradation and vast deforestation due to the industrialization and urbanization, wars, natural disasters such as flooding, drought caused by global warming are in common.

Remote sensing “RS” provides an efficient tool to monitor land-cover and environmental changes. Geographic Information System “GIS” is a powerful set of tools for collecting; storing, retrieving at will, transforming and displaying spatial data from the real world for a particular set of purpose (Burrough and McDonnel, 1998). Since 1972, Landsat satellites (series 1 to 7) have been providing repetitive, synoptic, global coverage of high-resolution multispectral imagery. Landsat data have potential applications for monitoring the conditions of the Earth’s land surface and the environment components.

An increasingly common application of remotely sensed data is for change detection. Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times. Change detection is an important process in monitoring and managing natural resources and urban development. (Singh, 1989).

Geoinformation technology (Remote Sensing ‘RS’, Geographic Information Systems ‘GIS’, and Global Positioning System ‘GPS’) and their integration form the basal and essential technical core of the system of geospace information science. The collection of remotely sensed data facilitates the synoptic analyses of earth-system function, patterning, and change at local, regional, and global scales over time; such data also provide a vital link between intensive, localized ecological research and the regional, national, and international conservation and management of biological diversity (Wilkie and Finn, 1996).

Iraq is situated in the south-west part of Asia. It lies between latitude 29 o 5′ and 37 o 22′ North, and between longitudes 38o 45′ and 48 o 45′ East. The area of Iraq covers 435,052 km2, it includes four main physical divisions;

  1. The Alluvial plain which forms quarter of Iraq’s area (132,000 km2).
  2. The desert plateau, which situated in the west of Iraq and forms about 1/2 of the country’s area (198,000 km2).
  3. The mountain region which situated in the northern and northeastern parts of Iraq. This region forms one quarter of Iraq’s area.
  4. The terrain region, which is a transitional region between the lowlands in the south and the high mountains region. It forms half of the mountain region.

Baghdad is the capital of Iraq and is situated in the middle part of the country. Iraq is mostly composed of broad, arid plains, but two easily flooded river valleys, the Tigris and the Euphrates, bisect the country diagonally from northwest to southeast. These river valleys are narrow and steep-walled for the first third of their path in Iraq but open into broad flood plain valleys (just north of Baghdad) that are the lowest and best watered terrain in the country. There are three fresh water lakes in central Iraq near Baghdad. Ath Tharthar Lake is the largest of the three. It is 55 km northwest of Baghdad. Al Habbaniyah Lake, the middle lake, is the smallest of the three, and Al-Razzaza Lake.

Satellite can repeatedly observe the wide area at once and continuously acquire the information about the ground features and environmental changes. Satellite sensors can detect the electro-magnetic radiation energy reflected from the earth over a wide range of spectrum with a visible and infrared wavelength, and record it in digital image. Moreover, as most of satellite images are analyzed through computer systems, it has many advantages to acquire the various information simultaneously rather than visual interpretation.

It is thus of importance to undertake an interdisciplinary research on the evaluation of the environmental changes and provide a monitoring prototype and useful references to the local governments for their sustainable development planning and environmental management.

The objectives of this study were assessing, monitoring, and mapping the environmental changes in Baghdad and its neighboring areas by using Geoinformation technology and change detection techniques, and developing a dynamic monitoring system of environmental changes at a county level GIS environment.

   

2. Study Area
The study area extends between latitude N 32° 13′ to N 34° 07′, longitude E 42° 43′ to 44° 41′. It covers an area of 26,943 km2, accounting 6.193% of the total area of Iraq. The study area is located in The Alluvial plain which the hot desert climate prevails in the sedimentary plain and the western plateau. It extends among parts of five governorates in the middle part of Iraq, which form Baghdad city (capital of Iraq) the eastern side of it, with a population of 7.5 million.

Annual rainfall ranges between 50-200 mm, most of the rain comes between October and April .It is characterized by great temperature variation between the day and night, summer and winter, the maximum of which reaches 45-50o c (Ministry of Planning, 2002). Figure 1 shows the location map of the study area in the middle part of Iraq and the Landsat ETM+ satellite image for the year of 2001.


Figure.1 Location Map of the Study Area in Baghdad and its Neighboring Areas and the ETM+ satellite image for the year of 2001.

3. Materials and Methods

3.1 Remote Sensing Data
Multi-temporal Landsat (WRS2: 169/37) TM (dated March 04, 1990) and ETM+ (dated March 18, 2001) imageries remotely sensed dataset were assembled and analysed for environmental changes analysis in the study area. The spatial resolution of one pixel of TM and ETM images were 28.5m by 28.5m.

3.2 Preprocessing

3.2.1. Radiometric Correction and Image Normalisation
The Landsat images were calibrated for sensor differences, converted into spectral radiance and normalized for illumination properties through differences in sun-elevation angle and sun-earth distance by recalculating the pixel values into at-satellite reflectance.

Rectification and registration of TM and ETM+ imageries were based on control points collected from vector files for the big and small rivers of the study area. Fifty control points were selected from the study areas.

3.2.2 Image to image registration
The remotely sensed data (TM 1990 and ETM 2001) were geometrically corrected in the datum WGS84 and projection UTM N38 using the first order (linear) of polynomial function and Nearest Neighbor rectification re-sampling. The RMS error of the image-to-image rectification comes between 0.35 and 0.41 pixels.

3.3 The Normalized Difference Vegetation Index (NDVI)
Rouse et al. (1974) initially proposed the Normalized Difference Vegetation Index (NDVI). The NDVI derived from the ratio of band 3 and band 4 in Landsat TM and ETM images data was applied for monitoring vegetation changes in the study area within the years of 1990 and 2001.

3.4 Bare Soil Index (BSI)
Bare Soil Index (BSI) was computed to identify the bare soil which includes bare areas (houses, roads, urban and rural built up areas, and eroded areas. The bare soil areas are enhanced using the BSI index (Jamalabad and Abkar, 2004).

3.5 The Normalized Differential Water Index (NDWI)
The Normalized Differential Water Index was used to oversee the situation of water in the study area. The ratio between Red and SWIR spectral region clearly enhanced water bodies to the brighter pixels (CPM, 2003).

3.6 Tasseled Cap transformation Wetness indicator (TCW)
Tasseled Cap transformation (Crist et al. 1984 and 1986) is one of the available methods for enhancing spectral information content of Landsat TM and ETM data. Tasseled Cap transformation especially optimizes data viewing for vegetation studies. Tasseled Cap index was calculated from data of the related six TM and ETM bands. One of the six tasseled cap transformation bands (wetness indicator “TCW”) which used as an indicator for the soil moisture was used in this study. Reflectance-based Tasseled Cap features range from -0.5 to 1.4. To facilitate the calculation, it was normalised to the extent from 0 to 255.

3.7 Change Discrimination
In order to detect, assess, and mapping the environmental changes of the study area during the period from 1990 to 2001, Landsat TM and ETM imageries dataset were used. Change detection involves the use of multi-temporal image data sets to discriminate the changes between dates of imaging. There are two ways were adopted in this research to detect the changes in case of using satellite image data set; 1) comparison of two independent enhanced images (two dates), 2) image differencing; in the image differencing procedure for change detection, the corresponding pixel values (DNs) from one date (t1) are simply subtracted from those of the other (t2). That produced three levels of information: negative change, positive change, and no change (Jensen et al., 1982; Lambin, 1994 and 1997). Thresholding and masking (fig.2) produced the vegetation and environmental information maps for the years 1990 and 2001. Each type of change was quantified to county-level by GIS technique.


Figure 2. Differencing image shows the dryness of Al-Habbaniya Lake during the study period from 1990 to 2001.

3.8 Ancillary Data and Software Packages
County-level socio-economic, meteorological data, and software such as ERMapper for image processing, ArcView GIS for analysing and presenting the results, Statistical Graphics, NCSS, and Microsoft Excel were utilised in this research.

4. Results and Discussion
NDVI, BSI, NDWI, and TCW indices were computed in multi-temporal Landsat images and tried to analyze the environmental changes in respect of vegetation, agriculture, water, meteorological data, and people activities. The studied indices have produced relative results based on electromagnetic spectrum recorded in the images. Principally the NDVI shows brighter in healthy vegetation areas whereas BSI seems brighter in bare land areas. Water can be seen as brighter in NDWI index where TCW areas more highlight the soil moisture.

4.1 NDVI
The results of the NDVI were presented in table 1 and figures 3, 4. The results showed that vegetation cover in the entire study area was 1,701 km2 in the year 1990, while it increased to 2,636 km2 in the year 2001; it forms 0.06 and 0.10% respectively. Kadhumiya County (Baghdad governorate) recorded the highest percentage in vegetation increase during the study period, when the vegetation cover percentage was 37.315 in 1990; it reached to 42.525% in the year of 2001. The smallest increase values in the vegetation cover was with Heet County (Anbar governorate), it was 0.594 and 1.174% respectively. The highest vegetation increase rate in the study area was in Balad County (Salah-Alddin governorate), while Abu Ghraib County (Baghdad governorate) had the lowest rate (1.154 km2. year-1). The overall average of the vegetation cover increase rate in the study area was 7.079 km2. year-1. The statistical analysis showed this index has a significant correlation with (TCW_p) tasseled cap wetness positive change (0.903).

Table 1. County-level NDVI results of the study area for the period from 1990 to 2001


Figure 3. County-level NDVI Map of the Study Area for the Year 1990.


Figure 4. County-level NDVI Map of the Study Area for the Year 2001.

4.2 BSI
The results (tab.2 and fig.5) showed a general increase in the bare soils in the study area, it was 406.328 km2 accounting 1.508% of the total study area. The highest increase rate in the bare soils during the study area was 66.768 km2.Year-1in Falluja County (Salah Alddin governorate), while the biggest decrease rate in the bare soils area was (-26.309) km2.Year-1 in Heet County. The highest increase in the bare soils was in Falluja and Ramadi counties 734.450 and 308.744 km2 respectively. Baghdad’ counties values had appeared a decrease in the bare soils area despite of its increase in the built up area, which can refer to the increase of the vegetation area in the district during the study period.

The statistical data of the census showed a general increase in the population of the whole study area. The results of the statistical analysis showed that this index has a significant correlation with (TCW_n) tasseled cap wetness negative change (0.901).

Table 2. County-level BSI results of the study area for the period from 1990 to 2001


Figure 5. The bare soils area values in the study period from 1990 to 2001.

   

4.3 NDWI
The NDWI was used to investigate the situation of surface water bodies in the study area. The results (table 3) revealed that there was a significant decrease in the surface water bodies area has happened during the study period. Initially Falluja county (Anbar governorate) has the biggest surface water bodies area among the studied counties; consequently it gained a significant diminution in its water bodies area from 1,105 to 902 km2 in the years 1990 and 2001, respectively. The highest and the lowest change rate were 0.886 and -18.453 km2.Year-1 in A’adhamiya and Falluja, respectively. In the studied Baghdad’s counties (Abu Ghraib, A’adhamiya, Kadhumiya, Mada’ain, and Mahmudiya) have got and increase in their surface water bodies area from 0.898 km2 in the year 1990 to 1.173 km2 in the year 2001. That increase coupled with the increase in the vegetation cover area of the five counties of Baghdad governorate.

The decrease in most of the surface water bodies of the study area refer to many reasons; such as to the decrease in the flow of the Euphrates and Tigris Rivers from the upstream countries. As well as to the using of rivers and lake’s water for the irrigation in the study area due to the agriculture is not possible without irrigation in the middle and southern parts of Iraq. Figures 6 and 7 show the water bodies maps for the study area in the years 1990 and 2001.

Table 3. County-level NDWI results of the study area for the period from 1990 to 2001.


Figure 6. County-level NDVI Map of the Study Area for the Year 1990.


Figure 7. County-level NDWI Map of the Study Area for the Year 2001.

4.4 TCW
A Tasseled Cap transformation “wetness indicator” applied on the TM and ETM images to extract the soil moisture information for the study area. The statistical analysis has shown this indicator has significant high correlations with the other used indicators, such as between wetness positive change “TCW_p” and NDVI (0.903), wetness negative change “TCW_n” and BSI (0.902). The results showed that Dujail County had the highest percentage value (22.455%) of the wetness positive change (soil moisture increase), while Heet has the lowest percentage (0.874) of this index. Kadhumiya County showed the highest value (7.451%) of the wetness negative change (7.451%) while Heet showed the highest value of wetness no change (98.439%). Table 6 and figures 7 and 8 show the results.

Table 4. County-level Tasseled Cap Wetness indicator TCW results of the study area for the period from 1990 to 2001.

According to the obtained results, it was clear that there was an increase of 934.46 km2, and 406.328 km2 in the vegetation cover (NDVI) and the bare soils (BSI), respectively. On the other hand the surface water bodies are seemed to have dramatic decrease of 401.777 km2.

By the statistical analysis, the NDVI’s results showed highest significant correlation with TCW_p (0.903), while the NDWI appeared a significant correlation with TCW_n (0.937). The BSI revealed a strong correlation with the TCW_n (0.902), which means the most effective on the vegetation cover status in the study area, was the soil moisture.


Figure 8. County-level Wetness Negative Change Map of the Study Area during the Period from 1990 to 2001


Figure 9. County-level Wetness Positive Change Map of the Study Area during the Period from 1990 to 2001

Design of the Dynamic Monitoring System
Based on the above results, a dynamic monitoring system of environmental changes (fig.10) was developed in Arc/View GIS version 3.3. The county level soil resources data and pattern map, environmental components changes during the study period and their corresponding data are integrated in the monitoring system. It includes the following thematic layers:

  1. Bare soil layer of the year 1990 for the study area, which extracted from the Landsat TM imagery dataset (169/37).
  2. Bare soil layer of the year 2001 for the study area, which extracted from the Landsat ETM imagery dataset (169/37).
  3. Vegetation cover layer of the year 1990 for the study area, which extracted from the Landsat TM imagery dataset (169/37).
  4. Vegetation cover layer of the year 2001 for the study area, which extracted from the Landsat ETM imagery dataset (169/37).
  5. Surface water body layer of the year 1990 for the study area, which extracted from the Landsat TM imagery dataset (169/37).
  6. Surface water body layer of the year 2001 for the study area, which extracted from the Landsat TM imagery dataset (169/37).
  7. TCW negative change layer for the study area, which extracted from the Landsat (169/37) TM1990 and ETM2001 imageries datasets.
  8. TCW positive change layer for the study area, which extracted from the Landsat (169/37) TM1990 and ETM2001 imageries datasets.
  9. Landsat TM1990 (169/37) composite RGB741 (tif format) image for the study area.
  10. Landsat ETM2001 (169/37) composite RGB741 (tif format) image for the study area.


Figure 10. Studied Environmental Changes Map in the study area for the period from 1990 to 2001.

5. Conclusions
The use of satellite imagery and other data sources manipulated and integrated in a GIS environment provides an essential and valuable information base from which the cause and future environmental change can be extracted.

In general view, the results of the study area showed an increase in the NDVI, BSI, and tasseled cap wetness indicator (TCW_p). That results revealed to the increase of the vegetation cover, the increase of the urban and rural built up areas, the increase in the soil moisture resulted by the irrigation and watering for the planting crops and plants depending mainly on the two rivers Tigris and Euphrates in the study area. All that accompanied with the increase in the urban and rural population in the study area.

This study demonstrates the effectiveness of the remote sensing and GIS technologies in detecting, assessing, mapping, and monitoring the environmental changes. The outcome of this type of studies represents a valuable resource for decision makers to guard against the environmental changes, and for future development projects in Iraq.

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