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Spatiotemporal trends of urban land use/land cover and green infrastructure change in two Ethiopian cities: Bahir Dar and Hawassa
© The Author(s) 2018
Received: 19 January 2018
Accepted: 24 April 2018
Published: 8 May 2018
The Correction to this article has been published in Environmental Systems Research 2018 7:11
The spatiotemporal analysis of urban land use/land cover change (LULCC) helps to understand the dynamics of the changing environment of green infrastructure (GI) on the basis of sustainable city development. There are important links between spatiotemporal land use/land cover and GI change in urban areas. Therefore, the main objective of this study was to examine the spatiotemporal trends of urban land use/land cover and GI changes in Bahir Dar and Hawassa cities for the last four decades (1973–2015). Three different sets of Landsat satellite data were procured from EMA for Bahir Dar and Hawassa from 1973, 2000 and 2015 using Landsat 4 MSS, 7 TM and 8 OLI respectively. Based on this, using ERDAS Imagine (ver. 9.2) and Arc GIS (Ver.10.3) five LULCC classes were identified for analysis purpose.
The results show that vegetation decreased by 30 and 14% in Bahir Dar and Hawassa respectively for the period 1973–2015, while built-up areas expanded by 10 and 24% respectively in the two cities. These land use changes have significant impacts on spatiotemporal trends of GI in urban areas. GI has increased in Bahir Dar and Hawassa in association with built-up area expansion and deliberate activity of city administrations with effective implementation of spatial plans of corresponding cities.
There is a growing concern about GI in cities. Policy makers and stakeholders should also decide on how to use the land at present and in the future. LULCC policymaking processes should aim to balance GI and other types of land use/land cover for sustainable urban development. Urban LULCC has important effects on the urban GI system.
With a little more than 50% of the human population living in urban areas, urbanization is now recognized as a major phenomenon (UN 2014; Zhang et al. 2013). Social scientists, urban planners, and geographers have investigated the unprecedented urban concentration from many perspectives, including the geography, demographics, economies and spatial evolution of cities (McIntyre et al. 2000) as well as urban green infrastructure (Mell 2014). The process of urbanization involves the growth of urban population and built-up areas. The share of world urban population is expected to increase to 66% by 2050, and of this about 90% will be concentrated in Africa and Asia (UN 2014). This population increase will lead to fast growth of built-up areas that consumes the surrounding productive land and encroaches on the necessary ecosystems. At the same time, the horizontal rapid expansion of built-up areas will lead to discontinuous suburbs with low density and uneven pattern (Tewolde and Cabral 2011; Varshney 2013).
As urbanization increases and urban areas continue to grow fast, there is a concern on urban environment and its quality because the quality of urban environment directly influences the social and economic development of the city (Masser 2007; He et al. 2010). Many scholars hold the view that the urban environment represents a highly complex area depicting a continuum of different spatial, temporal and spectral variability in land use and land cover (Haregeweyn et al. 2012). Spatial variability arises due to the varied landscape: temporal variations are attributed to periodic seasonal changes over the year while spectral variability is due to the great variety of materials and structures associated with the urban area (Zoran 2007). It is thus necessary to analyze the spatiotemporal patterns of LULCC in order to understand the urban ecology (McIntyre et al. 2000; Abebe and Megento 2016).
Land use/land cover change (LULCC) refers to the earth’s territorial surface modification by human activities (Anderson et al. 1976; Meyer and Turner 1992; Lu et al. 2004; Muriuki et al. 2011; Ayalew et al. 2012). The process of LULCC affects biodiversity, climate, soil, and air in particular, and the ecosystem, in general, and it has become the greatest environmental concern for human beings to date (Long et al. 2007; Tsegaye et al. 2010; Hailemariam et al. 2016). LULCC is useful to understand environmental changes because it can provide a tool to assess ecosystem changes and their environmental implication at various temporal and spatial scales (Anderson et al. 1976; Haregeweyn et al. 2012).
Urban space consists of built-up areas that include variety of land uses in commercial, institutional and residential areas. It also consists of non-built area that is mostly dominated by greenery and open spaces (Moroney and Jones, 2006; Tzoulas et al. 2007; Mansor et al. 2010). Previous researches (Kong and Nakagoshi 2006; Phan and Nakagoshi 2007; Byomkesh et al. 2012) indicated that urban green spaces are those lands that are covered with natural or man-made vegetation but are present in built-up areas. However, the universally agreed definition is still arguable. Most developed countries have their own definition (Byomkesh et al. 2012). Therefore this research used as its working definition stated by the Ethiopian Ministry of Urban Development and Housing (MoUDH): green infrastructure typologies to include parks, sports fields, roadside and squares, plazas and festive areas, river and riverside areas, lakes and lakeside areas, watershed areas, urban agriculture development, woodlots and green belts (inside and surrounding forests), private compounds and surroundings, institutional compounds and surroundings (both governmental and non-governmental), communal housing compounds and surroundings (condominiums, real estate, etc.), religious institutions compounds and surroundings, neighborhood open spaces, cemeteries, nursery sites, and green roofs and walls (MoUDH 2015).
Green space is sometime synonymous with green infrastructure, though the latter is more inclusive than the former. Green space helps reduce heat effects of buildings, provides shadow to pedestrians and ground and has the ability to improve air quality and the environment (Noor et al. 2013). The development of urban green infrastructure planning and management practices requires important information from LULCC studies (Yang et al. 2014). Previous studies implied that traditional investigation of urban environment was not considered GI (Miller and Hobbs 2002). The urban green infrastructure, however, enables urban residents to experience outdoors visually and kinetically. Green infrastructure network in any urban area is significant because it attempts to provide optimal experiential qualities to urban residents and to overcome the negative effects of living in the urban built environment (Mansor et al. 2010). Moreover, based on a deeper understanding of the relationships between the LULCC and GI change require that the underlying mechanisms, patterns, and processes of land conversion as well as the response of urban environment should be addressed throughout official decision-making processes (Zhang et al. 2013). The planners and decision-makers could fully evaluate the consequences of different land development scenarios and therefore have scientific basis with which to improve future planning and regulations of GI. In terms of GI, the spatiotemporal analysis of LULCC can help to understand the dynamics of the changing environment of GI and form the basis for sustainable development and provide a fundamental piece of information required for policy making and planning (Hu et al. 2008; Teferi et al. 2016).
Though LULCC is not a recent phenomenon in Ethiopia (Hailemariam et al. 2016), it is exacerbated by the scale, speed and long-term nature of urbanization and modernization (Msoffe et al. 2011). Existing studies on LULCC in Ethiopia have focused on land degradation and associated consequences due to expansion of cultivation and deforestation (Taddese 2001; Feoli and Vuerich 2002; Amsalu et al. 2007; Meshesha et al. 2010; Tsegaye et al. 2010). There is little effort to understand LULCC in relation to green infrastructure changes in urban areas.
This study highlights the important links between spatiotemporal land use/land cover and green infrastructure change in urban areas. In this research, green infrastructure is taken as one category of land use/land cover that is an interconnected network of multifunctional, predominantly un-built, spaces that support ecological and social activities (Kambites and Owen 2006; Tzoulas et al. 2007; MoUDH 2015). The transformation of land use/land cover types leads to a change in the structure and function of green infrastructure services (Lei and Zhu 2017). The need to balance economic, social and ecological ecosystems is becoming increasingly urgent because LULCC is in the direction of rapid urbanization (Song et al. 2016). This study aims to investigate the rapid urban expansion on LULCC and GI, and its development and planning. Our research focused on (1) The rates of LULCC in Bahir Dar and Hawasa between 1973 and 2015, (2) LULCC trends during the 1973–2000 and 2000–2015 periods for both Bahir Dar and Hawassa, (3) Which land-cover types were most affected by the change process, and (4) The rates of changes and conversion from other land cover types to green spaces and urban areas over the period 1973–2015.
According to the National Meteorological Agency (NMA), Bahir Dar has an average annual temperature and precipitation of 19.6 °C and 1419 mm respectively (NMA 2013). It is situated in the woina-dega1 agro-ecological zone and experiences uni-modal rainfall over a 3-month period from mid-June to mid-September. Hawassa has an average annual temperature and precipitation of 20.8 °C and 993.4 mm respectively (NMA 2013). It is one of the major urban areas of Ethiopia located inside the greater Ethiopian rift valley. It experiences uni-modal rainfall over a 3-month period from mid-June to mid-September and has woina-dega agro ecological zone.
These two cities are among the largest and the fastest growing urban centres in Ethiopia. The population of Bahir Dar city grew from 96,140 in 1994, the second census period, to 155,428 in 2007, the third census period (CSA 2007). The rate of growth between the two censuses periods was 3.7%. According to the CSA (2017), the population of Bahir Dar is estimated to be 348,429. The population of Hawassa was 69,169 in 1994 and it grew to 157,139 in 2007 showing a growth rate of 6% (CSA 1994, 2007). The CSA estimated the population of Hawassa in 2017 to be 315,267 (CSA 2017).
Bahir Dar and Hawassa cities were selected as research sites for this study in addition to rapid population increase is that both are lakeside cities, regional capitals, fast growing cities and have relatively better availability of green infrastructure as compared to other cities and towns in the country. According to Municipality of Hawassa (2015) and Municipality of Bahir Dar (2015) Hawassa and Bahir Dar has 21.96 and 17.44% GI coverage respectively.
This study uses three different sets of Landsat satellite data for Bahir Dar and Hawassa over four decades (1973–2015). These satellite images were procured from the Ethiopian mapping agency (EMA) in GeoTIFF file format projected in UTM projection and WGS 84 datum universal transverse Mercator (UTM), Zone 37° North coordinate system. The three Landsat satellite images with 30 m resolution were acquired for January 1973, January 2000 and January 2015. A study by Sadidy et al. (2009) pointed out that Landsat images with varying resolution are among the most widely used data sources in order to gain important input for mapping and planning projects. The Landsat images were geo-referenced to the digitized map of the corresponding area using first-order polynomial transformation and nearest neighborhood resembling (Yuan et al. 2005; Murat et al. 2006).
There are many change detection approaches for remotely sensed images (Yuan et al. 2005). Among these, the post-classification comparison method is particularly attractive due to its nature of clearly identified change (Hung and Wu 2005; Muttitanon and Tripathi 2005; Yuan et al. 2005). This study employs the post-classification method to detect changes.
LULC maps for both Bahir Dar and Hawassa for 1973, 2000 and 2015 were prepared for the study areas by independently supervised classifications using a maximum likelihood algorithm classifier. Hence, the five land-cover classes are as follows: urban built-up, vegetation, water body, green spaces, and crop land were mapped.
Land use land cover change (LULCC) classification schemes used in this study
Urban built-up area
Includes areas with all types of artificial surfaces, including residential, commercial, and industrial land uses as well as transportation infrastructure
Includes areas with dense vegetation cover, such as those covered with shrubs forming closed canopies, trees and other vegetation that is relatively tall and dense, as well as areas covered with both indigenous and exotic trees
Includes lakes, rivers, ponds
Green spaces in built-up areas
An area of grass, trees, or other vegetation set apart for recreational or aesthetic purposes inside urban built environment. It includes urban parks, greenery, roundabouts, public squares and plaza, open Spaces, medians and sport fields
Includes grazing areas, cultivated lands, community open lands and areas along the lake shore that are used for agricultural purposes when the lake level retreats following the long dry-season. Information obtained from local residents indicates that the units categorized in this category can generally be used in one way or another for agricultural purposes
In the present study, each image of Landsat 4 MSS, Landsat 7 TM and Landsat 8 OLI for both cities were independently classified for the three-time periods (1973, 2000 and 2015). The ground referenced data were gathered by combining Google Earth data and GPS points during the field survey and the resulting samples were imported to the ERDAS Imagine software and the intersection files were generated.
Accuracy assessment for classified images of Bahir Dar and Hawassa
Overall classification accuracy (%)
Overall kappa coefficient
Overall classification accuracy (%)
Overall kappa coefficient
Landsat 4 MSSa
Landsat 4 MSS
Landsat 7 TMb
Landsat 7 TM
Landsat 8 OLIc
Landsat 8 OLI
Urban expansion analysis
Land use/land cover change and urban expansion
LULCC pattern and change in Bahir Dar (1973–2015) and Hawassa (1973–2015)
Green space in built-up area
Urban built-up area
Green space in urban area
Urban built-up area
The data presented in Table 3a shows that in 1973, the vegetation cover in Bahir Dar was 40% and this was reduced to 25% in 2000 and 10% in 2015. On the other hand, crop land increased from 45% in 1973 to 48% in 2000 and further to 53% in 2015. This change in land cover could indicate a shift from vegetation to cropland use. Table 3b depicts that in Hawassa both vegetation and crop land showed a decline. The vegetation cover declined from 18% in 1973 to 9% in 2000 and 4% in 2015. Similarly crop land declined from 31% in 1973 to 25% in 2000 and 3% in 2015. It should be noted that the water body located in the study areas namely Lake Tana in Bahir Dar and Lake Hawassa in Hawassa showed no significant change (Table 3a, b). The changes in green spaces and urban area expansion are presented in detail.
Percentage of LULCC in (ha) in Hawassa and Bahir Dar during (1973–2015)
Urban built up area
Green space in urban area
In general, the results show that 53% of Bahir Dar and 48% of Hawassa land use/land cover remained unchanged over the 1973–2015 periods. On the other hand, 47% of Bahir Dar and 52% of Hawassa land use/land cover changed during 1973–2015. This indicates that there is a higher change of LULCC in Hawassa than in Bahir Dar in the last four decades (Table 4 and Fig. 2a, b).
The driving factors for this rapid LULCC are the rapid growth of urban population and the horizontal expansion of urban areas (see below). In line with this, the population in Bahir Dar has more than tripled between 1994 and 2017 (96,140 in 1994 and 348,429 in 2017) and quadrupled in Hawassa between 1994 and 2017 (69,169 in 1994 and 315,267 in 2017). The Landsat images analysis reveals, however, that land cover change is faster since 2000 than it was during the 1990s. The following discussion focuses on two types of land use changes namely the urban expansion and the green space in both cities.
Following the technique in formula 7, the annual rates of urban expansion are analyzed from two perspectives. The first is the expansion in LULCC as a result of the sprawl of each city, which is the horizontal expansion while the second is the changes in LULCC that occurred within the 1973 boundaries of the cities during the period 1973–2015. This type of change is referred to as intensification increases in the density of dwellings and other infrastructure within existing built-up areas.
Horizontal urban expansion of Bahir Dar and Hawassa (1973–2015)
Urban area (ha)
Urban area (ha)
% Change (ha year−1)
Using the technique presented in formula 8, the LCR result for Bahir Dar is 0.002, 0.003 and 0.015 for the years 1973, 2000 and 2015 respectively. Likewise, the LCR for Hawassa is 0.023, 0.005 and 0.009 for the years 1973, 2000 and 2015 respectively. It can be seen that the LCR result is in accordance with LULCC result and is higher for Bahir Dar except for the year 1973 and 2000.
Changes in green space in built-up area
Table 1 defined green space in urban area as an area of grass, trees, or other vegetation set apart for recreational or aesthetic purposes inside urban built environment. It includes urban parks, greenery, roundabouts, public squares and plaza, open spaces, medians and sport fields. It is clear that this type of land use is created by the city government as part of its land use planning schemes.
The data presented in Table 3a, b clearly show that green spaces in Bahir Dar and Hawassa have increased significantly between 1973 and 2015. In Bahir Dar, green space increased by 2742.8 ha while it increased by 706.6 ha in Hawassa between the years 1973 and 2015. The percentage increase is much higher for Bahir Dar than for Hawassa. This is because of both the small base and the higher additions of green spaces in Bahir Dar than in Hawassa. Hawassa, however, has a higher percent increase for the period 2000–2015 than Bahir Dar. The land cover types mostly changed to green infrastructure are vegetation and cropland.
In comparing green space and built-up area expansion, it can be seen that built-up area in Bahir Dar increased by 10% in 1973–2015 and this is proportional to green space increment of 11% of green space for the same period. The built-up area in Hawassa however increased (24%) more than green space (17%) though both have a rising tendency.
A comparative perspective between Hawassa and Bahir Dar shows that green space increment in Hawassa (33%) is by far more than Bahir Dar (23%) (Table 4). The reason could be that Hawassa has witnessed a decline in both vegetation and crop land which must have contributed to built-up and green spaces in the city. On the other hand, in Bahir Dar though vegetation has decreased, crop land has increased there by competing with the increase in built up and green space. Therefore care should be taken to conserve these lands.
Land use land cover types most affected
The land cover proportions obtained from the successive (enhanced) classifications revealed that in 1973, Bahir Dar was dominated by crop land (45% of total area), followed by vegetation (40%) (Table 3a). However, after a quarter of a century, in 2000, vegetation occupied only 25% of the total area, and crop land increased and occupied 48%. The change was further intensified after 2000 as vegetation was reduced to 10% and crop land was increased to 53%. Moreover, as presented in Table 4 urban built-up area increased by 45% ha per year during the period 1973–2015.
The data presented in Table 3b indicates that in 1973, Hawassa was dominated by crop land (31%) and vegetation (17%). However, in 2000 or after a quarter of a century, vegetation occupied only 9% and crop land decreased and covered 25%. The urban built-up area on the other hand increased alarmingly by 30%, with an expansion of 7% ha per year during the periods of 1973–2015. This implies that in both cities, urban-built up area is the land use type that showed marked increase while crop land and vegetation land have different trends. The Landsat images analysis confirmed that the major land cover conversions were from the vegetation cover classes to crop land and built-up classes (Fig. 2a, b). This is further confirmed by examination of net changes of the five land use/land cover classes 1973–2015 due to intensification of the built-up area. The result shows that built-up increased by 22% in Bahir Dar, whereas the cropland land increased by net-change of 17% at the expense of vegetation which showed a decrease by net-change of 63%. A similar analysis for the periods 1973–2015 in Hawassa revealed that net-change in built-up area is 45%. During the entire study period (1973–2015), crop land and vegetation decreased by net-change of 54 and 27% respectively (Table 4). Green space is also one of the land use categories that showed a rapid increase with a higher-level gain than loss in both cities.
This study showed that land use/land cover is imperative for understanding the GI conditions of urban areas. Land use/land cover can be used for planning and monitoring the status of GI. On the other hand, GI study requires land use/land cover change detection in order to understand GI within the setting of other land use/land covers. Some researches for instance, Li et al. (2015) indicated that LULCC can be an important indicator to link GI and human activities in urban ecosystems. Liu et al. (2014) also examine LULCC and urbanization effect on urban environment. Although, there are studies on farm land effects of LULCC or urbanization (Pauleit et al. 2005), this study has made the first attempt to explore the combined effect of LUCC and GI under the rapid urbanization on farm land in fast growing cities of Bahir Dar and Hawassa 1973–2015.
The green infrastructure concept has come into the table of discussion in the last few decades and is used for urban green environment improvement (Tzoulas et al. 2007). In this study, the foregoing data showed that green spaces in both study cities have increased. The increasing trend of green infrastructure in Bahir Dar and Hawassa during the period 1973–2015 was due to continued and drastic increment of built-up areas at the cost of other land cover types (vegetation and cropland). Some studies (Noor et al. 2013) indicated that the issue of green infrastructure has become major concern throughout the world particularly among developing countries due to the obvious negative impacts which occurred as the result of loss of green infrastructure in terms of visual quality, environmental quality and health quality with in fast growing cities and towns.
A study by Luck and Wu (2002) recognized that urbanization is one of the most important driving forces behind LULCC in Jinan city (China). Kong and Nakagoshi (2006) also reported that the driving forces are the policies that affect the development and management of urban GI. However, Byomkesh et al. (2012) noted, the causes of changes in GI, among other things, are rapid population growth driven by rural–urban migration, economic development and a lack of awareness among city managers and city dwellers. In addition, the use of political power to influence the illegal conversion and leasing of GI, a lack of appropriate rules and regulations to protect urban GI, limited budget for the management and maintenance of urban GI, are also factors that contribute to GI change. In their study about analysis of LULCC and urban expansion of Nairobi city, Mundia and Aniya (2005) noted the analysis of LULCC shows that the biggest challenge to city planners’ is perhaps to maintain an internal balance between economic activity, population growth, infrastructure and services not limiting impacts on the natural environment. In order to maintain ecological balance and proper functioning of ecosystems, comprehensive GI planning and management strategy needs to be formulated. Educating the people to increase their awareness about the role and importance of GI for healthy environment is necessary. It is worth mentioning that comprehensive land use planning would contribute to enhance GI and sustainability and livability of urban development.
This study has presented the LULCC and dynamics of urban expansion which is demonstrated by the interplay between biophysical, location site and socio-economic characteristics in shaping the growth of both cities. The spatial expansion of both Bahir Dar and Hawassa cities is very rapid during the last 10–15 years. The driving forces to this urban expansion resulted from population growth, economic reform and industrialization (Meyer and Turner 1992; Morrisette 1992; Rockwell 1992; Sanderson 1992). Increase in investment brings fast economic development which leads accelerated urban area expansion because the development of the industrial parks (Grubler 1992) in both cities. Industrial development is a major driving force for urbanization (Xu et al. 2000). Expansion direction is also necessary in city management and study of LULCC. The direction of urban expansion is importantly controlled by the topographical and physical factors. Urban expansion directions and land use conversions analysis indicates that deliberate planning is largely important in Bahir Dar and Hawassa urbanization process. Bahir Dar city expands towards South, West and North-East but no more expansion towards the North because of Lake Tana and towards the South-East due to bezawit ridge. Hawassa city expands towards East, North and South-East but not towards the West and South because of Lake Hawassa and amoragedel ridge respectively. These areas of both cities are considered as green belts of corresponding cities. The horizontal expansion of urban and suburban areas requires more land and drives the conversion of surrounding rural areas to urban land use/land cover (Farooq and Ahmad 2008; Mohan et al. 2011). Horizontal expansion has strong effects on other urban land uses, such as crop/agricultural land, green space, and forest lands (Mohan et al. 2011).
The results from the analysis of the Landsat images show that for the two cities the land cover types that have significantly contributed to gains for built-up area and the corresponding green space are crop land and vegetation. These two-land use/land cover types have fed built-up areas and green spaces while they show a drastic decline in their coverage. This is consistent with previous research (Xu et al. 2000) crop lands are under great pressure from rapid urban expansion. As it is explained in tables above in both cities the expansion rate is fast and many agricultural lands are changed into urban areas. Severe arable land loss will have a significant impact on the county’s further agricultural development. Obviously, dynamical monitoring of the expansion of urban areas is valuable for the sustainable development of the country. Rana (2011) noted rapid urbanization is always characterized by spatial extension in the periphery, which leads to exploitation of forest and crop land. This could be because of limited capacity of planning. The city authorities are facing huge lack in skilled manpower and sufficient resources to reach the detail plan stages (Islam 2002; Shafi 2003).
It is important to note that urban expansion and the loss of crop land have impacts on the surrounding farmers and the nearby water bodies in the study area. With regard to famers, loss of crop land and the associated urban expansion give rise to changes in the livelihood of farmers as they derive reduced income from farming (Haregeweyn et al. 2012). In relation to water bodies, the small decrease noted in both cities between 1973 and 2015 is associated with a retreat of the lakes caused by siltation and the subsequent use of this land for built-up areas. Field observation and satellite images analysis verify this because there are clear indicators of the retreat of Lake Tana and Lake Hawassa. Other related studies (Gashaw and Fentahun 2014; Wondrade and Tveite 2014; Teshale and Bantider 2015; Minale and Belete 2017) conducted in different parts of Ethiopia reported that the life of both artificial and natural lakes is threatened by a high sedimentation rate, with the sediment primarily being delivered from agricultural watersheds. At the city level, the results revealed that different anthropogenic activities had significantly affected the urban green infrastructure composition and configuration within the inner cities of both Bahir Dar and Hawassa.
Our findings are helpful for policy makers to better understand and address these complex relationships between urbanization, LUCC, and GI. It is important to develop improved land-use policies that balance LUCC, GI proportion and urbanization. The findings of this research have not only important policy implications for urban GI design and management, but also provide important information for other research areas such as urban environment and ecology.
The LULCC dynamics largely depend on dynamic relationships not only natural factors but also among population and policy/institutional factors. In this study we noted the spatiotemporal trends of urban land use/land cover and an aspect of green infrastructure change. Change detection is important to understand the magnitude and direction of change in any land use/land cover category in general and in green spaces in particular. Our result revealed that green infrastructure defined as urban parks, open spaces, greenery, roundabouts, public squares and plaza, medians and sport fields have increased in both cities during the period 1973–2015. Such increase is believed to be associated with urban expansion since the latter have increased in both cities. The mechanism is the implementation of land use planning at city level in order to cope up with the increasing urban expansion. The two cities could thus be taken as exemplary to other cities and towns in Ethiopia since the increase in green spaces is closely related to sustainable urban development.
In recent years there has been growing concern among planners about the green infrastructure in cities. In addition, policy makers and stakeholders should also decide on how to use the land at present and in the future. Therefore, LULCC policymaking processes should aim to balance green infrastructure and other types of land use/land cover for sustainable urban development. Generally, we can imply that urban land use/land cover have important effects on the urban green infrastructure system.
In conclusion, LULCC dynamics and GI analyses are imperative for understanding the landscape ecological conditions of urban environment. This study revealed that the vegetation and crop land are decreasing over the course of time due to the increasing pace of built-up area. This activity is causing the destruction of landscape ecological processes and the biodiversity in urban areas. Therefore, a comprehensive urban land use planning and GI management strategy should be implemented for proper functioning of the urban environment.
Woina-dega is a local term that defines mid altitude climate.
KG has conceived of the study and made contributions in the design, data collection and analysis, interpretation of results and revisions of the manuscript. TG-E has participated in the sequence alignment and critical commenting of the draft manuscript. He also participated in its design and coordination, and helped to draft and edits the manuscript. Both authors read and approved the final manuscript.
We would like to thank the anonymous reviewers and the editor for their genuine comments and corrections which helps the paper to be in its present form. Special thanks to Ethiopian Mapping Agency (EMA) for accessing the satellite imageries.
The authors declare that they have no competing interests.
Availability of data and materials
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The authors would like to thank Addis Ababa University for financial support for this research for both researchers and University of Gondar for financial support to the first researcher.
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- Abebe MT, Megento TL (2016) The city of Addis Ababa from ‘Forest City’ to ‘Urban Heat Island’: assessment of urban green space dynamics. J Urban Environ Eng 10(2):254–262View ArticleGoogle Scholar
- Amsalu A, Stroosnijder L, de Graaf J (2007) Long-term dynamics in land resource use and the driving forces in the Beressa watershed, highlands of Ethiopia. J Environ Manag 83:448–459View ArticleGoogle Scholar
- Anderson JR, Hardy EE, Roach JT, Witmer RE (1976) A land-use and land-cover classification system for use with remote sensor data. US Geological Survey Professional Paper 964, Washington, DCGoogle Scholar
- Ayalew D, Kassahun D, Woldetsadik M (2012) Detection and analysis of land-use and land-cover changes in the Midwest escarpment of the Ethiopian Rift Valley. J Land Use Sci 7(3):239–260View ArticleGoogle Scholar
- Butt A, Shabbir R, Ahmad SS, Aziz N (2015) Land use change mapping and analysis using Remote Sensing and GIS: a case study of Simly watershed, Islamabad, Pakistan. Egypt J Remote Sens Space Sci 2015(18):251–259Google Scholar
- Byomkesh T, Nakagoshi N, Dewan AM (2012) Urbanization and green space dynamics in Greater Dhaka, Bangladesh. Landsc Ecol Eng 8:45–58View ArticleGoogle Scholar
- Chen G, Hay GJ, Carvalho LMT, Wulder MA (2012) Object-based change detection. Int J Remote Sens 33(14):4434–4457View ArticleGoogle Scholar
- Congalton RG, Green K (2009) Assessing the accuracy of remotely sensed data: principles and practices, 2nd edn. Taylor & Francis, Baco RatonGoogle Scholar
- CSA (1994) Statistical report. Addis Ababa, EthiopiaGoogle Scholar
- CSA (2007) Statistical report. Addis Ababa, EthiopiaGoogle Scholar
- CSA (2017) Statistical abstract. Addis Ababa, EthiopiaGoogle Scholar
- Dabboor M, Howell S, Shokr M, Yackel J (2014) The Jeffries–Matusita distance for the case of complex Wishart distribution as a separability criterion for fully polarimetric SAR data. Int J Remote Sens 35(19):6859–6873Google Scholar
- Fanan U, Dlama KI, Olusey IO (2011) Urban expansion and vegetal cover loss in and around Nigeria’s Federal Capital City. J Ecol Nat Environ 3(1):1–10Google Scholar
- Farooq S, Ahmad S (2008) Urban sprawl development around Aligarh city: a study aided by satellite remote sensing and GIS. J Indian Soc Remote Sens 36:77–88View ArticleGoogle Scholar
- Feoli E, Vuerich L (2002) Processes of environmental degradation and opportunities for rehabilitation in Adwa, Northern Ethiopia. Landsc Ecol 17(4):315–325View ArticleGoogle Scholar
- Foody GM (2002) Status of land covers classification accuracy assessment. Remote Sens Environ 80:185–201View ArticleGoogle Scholar
- Gashaw T, Fentahun T (2014) Evaluation of land use/land cover changes in east of lake Tana, Ethiopia. J Environ Earth Sci 4(11):49–53Google Scholar
- Grubler A (1992) Technology and global change: land-use, past and present. In: Meyer WB, Turner BL II (eds) Global land-use/land-cover change. Boulder, AIESGoogle Scholar
- Hailemariam SN, Teshome S, Teketay D (2016) Land use and land cover change in the Bale Mountain Eco-Region of Ethiopia during 1985 to 2015. Land 5:41View ArticleGoogle Scholar
- Haregeweyn N, Fikadu G, Tsunekawa A, Tsubo M, Tsegaye DM (2012) The dynamics of urban expansion and its impacts on land use/land cover change and small-scale farmers living near the urban fringe: a case study of Bahir Dar, Ethiopia. Landsc Urban Plann 106(2012):149–157View ArticleGoogle Scholar
- He C, Shi P, Xie D, Zhao Y (2010) Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach. Remote Sens Lett 1(4):213–221View ArticleGoogle Scholar
- Hu H, Liu W, Cao M (2008) Impact of land use and land cover changes on ecosystem services in Menglun, Xishuangbanna, South west China. Environ Monit Assess 146:147–156View ArticleGoogle Scholar
- Hung M, Wu Y (2005) Mapping and visualizing the Great Salt Lake landscape dynamics using multi-temporal satellite images, 1972–1996. Int J Remote Sens 26:1815–1834View ArticleGoogle Scholar
- Hussain M, Chen D, Cheng C, Wei H, Stanley D (2013) Change detection from remotely sensed images: from pixel-based to object-based approaches, ISPRS. J Photogramm Remote Sens 80(2013):91–106View ArticleGoogle Scholar
- Islam N (2002) The Bangladesh urban environment (Editorial Notes). CUS bulletin on urbanization and development, vol 43. Center for urban studies, DhakaGoogle Scholar
- Kambites C, Owen S (2006) Renewed prospects for green infrastructure planning in the UK. Plan Pract Res 21(4):483–496View ArticleGoogle Scholar
- Kong F, Nakagoshi N (2006) Spatial-temporal gradient analysis of urban green spaces in Jinan, China. Landsc Urban Plan 78:147–164View ArticleGoogle Scholar
- Lei C, Zhu L (2017) Spatio-temporal variability of land use/land cover change (LULCC) within the Huron river: effects on stream flows. Climate Risk Manag 19(2018):35–47Google Scholar
- Li W, Bai Y, Zhou W, Han C, Han L (2015) Land use significantly affects the distribution of urban green space: case study of Shanghai, China. J Urban Plan Dev 141(3):A4014001View ArticleGoogle Scholar
- Liu Y, Huang X, Yang H, Zhong T (2014) Environmental effects of land-use/cover change caused by urbanization and policies in Southwest China Karst area—a case study of Guiyang. Habitat Int 44(2014):339–348View ArticleGoogle Scholar
- Long H, Tang G, Li X, Heilig GK (2007) Socio-economic deriving forces of land-use change in Kunshan, the Yangtze River Delta economic area of China. J Environ Manag 83(3):351–364View ArticleGoogle Scholar
- Lu D, Weng Q (2007) A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens 28(5):823–870View ArticleGoogle Scholar
- Lu D, Mausel P, Brondízio E, Moran E (2004) Change detection techniques. Int J Remote Sens 25(12):2365–2401View ArticleGoogle Scholar
- Luck M, Wu J (2002) A gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA. Landsc Ecol 17:327–339View ArticleGoogle Scholar
- Mansor M, Said I, Mohamad I (2012) Experiential contacts with green infrastructure’s diversity and well-being of urban community. Asian J Environ Behav Stud 49:33–48Google Scholar
- Mas JF (1999) Monitoring land-cover changes: a comparison of change detection techniques. Int J Remote Sens 20(1):139–152View ArticleGoogle Scholar
- Masser I (2007) Managing our urban future: the role of remote sensing and geographic information systems. Habitat Int 25:503–512View ArticleGoogle Scholar
- McIntyre N, Knowles-Yánez K, Hope D (2000) Urban ecology as an interdisciplinary field: differences in the use of urban between the social and natural sciences. Urban Ecosyst 4:5–24View ArticleGoogle Scholar
- Mell C (2014) Aligning fragmented planning structures through a green infrastructure approach to urban development in the UK and USA. Urban For Urban Green 13(2014):612–620View ArticleGoogle Scholar
- Meshesha D, Tsunekawa A, Tsubo M (2010) Continuing land degradation and its cause-effect in Ethiopia’s Central Rift Valley. Land Degrad Dev 23(2):130–143View ArticleGoogle Scholar
- Meyer WB, Turner BL (1992) Human population growth and global land-use/cover change. Annu Rev Ecol Syst 23(1):39–61View ArticleGoogle Scholar
- Miller J, Hobbs R (2002) Conservation where people live and work. Conserv Biol 16:330–337View ArticleGoogle Scholar
- Minale AS, Belete W (2017) Land use distribution and change in lake Tana sub basin. In: Stave K, Goshu G, Aynalem S (eds) Social and ecological system dynamics. AESS interdisciplinary environmental studies and sciences series. Springer, ChamGoogle Scholar
- Mohan M, Pathan S, Narendrareddy K, Kandya A, Pandey S (2011) Dynamics of urbanization and its impact on land use/land cover: a case study of megacity Delhi. J Environ Prot 2:1274–1283View ArticleGoogle Scholar
- Moroney J, Jones D (2006) Biodiversity space in urban environments: implications of changing lot size. Aust Plan 43(4):22–27View ArticleGoogle Scholar
- Morrisette PM (1992) Developing a political typology of global patterns of land and resource use. In: Meyer WB, Turner BL II (eds) Global land-use/land-cover change. Boulder, AIESGoogle Scholar
- MoUDH (2015) Ethiopia national urban green infrastructure standard, Addis Ababa, EthiopiaGoogle Scholar
- Msoffe FU, Kifugo SC, Said MY, Neselle MO, Gardingen PV, Reid RS, Ogutu JO, Herero M, de Leeuw J (2011) Drivers and impacts of land-use change in the Maasai Steppe of northern Tanzania: an ecological, social and political analysis. J Land Use Sci 6(4):261–281View ArticleGoogle Scholar
- Mundia CN, Aniya M (2005) Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. Int J Remote Sens 26(13):2831–2849View ArticleGoogle Scholar
- Murat H, Selçuk R, Mustafa A (2006) Detection of spatial-temporal changes of development potential of Aksaray city using remote sensing and GIS. In: Shaping the change, XXIII FIG congress, Munich, Germany, October 8–13Google Scholar
- Muriuki G, Seabrook L, McAlpine C, Jacobson C, Price B, Baxter G (2011) Land cover change under unplanned human settlements: a study of the Chyulu hills squatters, Kenya. Landsc Urban Plan 99(2011):154–165View ArticleGoogle Scholar
- Muttitanon W, Tripathi N (2005) Land use/cover changes in the coastal zone of Ban Don bay, Thailand using Landsat 5 TM data. Int J Remote Sens 26:2311–2323View ArticleGoogle Scholar
- NMA (2013) National meteorological station report. Federal democratic republic of Ethiopia, Addis AbabaGoogle Scholar
- Noor NM, Abdullah A, Manzahari H (2013) Land cover change detection analysis on urban green area loss using GIS and remote sensing techniques. J Malays Inst Plan 2013(11):125–138Google Scholar
- Pauleit S, Ennos R, Golding Y (2005) Modeling the environmental impacts of urban land use and land cover change—a study in Merseyside, UK. Landsc Urban Plan 71(2–4):295–310View ArticleGoogle Scholar
- Phan DU, Nakagoshi N (2007) Analyzing urban green space pattern and eco-network in Hanoi, Vietnam. Landsc Ecol Eng 3:143–157View ArticleGoogle Scholar
- Puyravaud JP (2003) Standardizing the classification of annual rate of deforestation. For Ecol Manag 177(1–3):593–596View ArticleGoogle Scholar
- Radoux J, Bogaert P, Fasbender D, Defourny P (2011) Thematic accuracy assessment of geographic object-based image classification. Int J Geographical Inf Sci 25(6):895–911View ArticleGoogle Scholar
- Rana MP (2011) Urbanization and sustainability: challenges and strategies for sustainable urban development in Bangladesh. Environ Dev Sustain 13:237–256View ArticleGoogle Scholar
- Robertson LD, King DJ (2011) Comparison of pixel- and object-based classification in land cover change mapping. Int J Remote Sens 32(6):1505–1529View ArticleGoogle Scholar
- Rockwell R (1992) Culture and cultural change as driving forces in global land-use/cover changes. In: Meyer WB, Turner BLI II (eds) Global land-use/land-cover change. Boulder, AIESGoogle Scholar
- Sadidy J, Firouzabadi P, Entezari A (2009) The use of radar sat and land sat image fusion algorithms and different supervised classification methods to use map accuracy—case study. Sari lain-Iran. http://www.isprs.org/procedding/XXXVI/5-C55/papers-Sadidy_javad.pdf. Accessed 19 Oct 2015
- Sanderson S (1992) Institutional dynamics behind land use change. In: Meyer WB, Turner BL II (eds) Global land-use/land-cover change. Boulder, AIESGoogle Scholar
- Shafi SA (2003) Use of planning tools as a guide to balanced urban development. CUS Bulletin on urbanization and development, vol 44. Center for urban studies, DhakaGoogle Scholar
- Sharma L, Pandey PC, Nathawat MS (2012) Assessment of land consumption rate with urban dynamics change using geospatial techniques. J Land Use Sci 7(2):135–148View ArticleGoogle Scholar
- Song X, Chang K, Yang L, Scheffran J (2016) Change in environmental benefits of urban land use and its drivers in Chinese cities, 2000–2010. Int J Environ Res Public Health 13:535View ArticleGoogle Scholar
- Taddese G (2001) Land degradation: a challenge to Ethiopia. Environ Manag 27(6):815–824View ArticleGoogle Scholar
- Teferi E, Bewket W, Belay S (2016) Effect of land use land cover on selected soil quality indicators in the head water area of the Blue Nile basin of Ethiopia. Environ Monit Assess 2016(188):1–12Google Scholar
- Teshale RR, Bantider A (2015) Land use land cover dynamics in Hawassa tabor and alemura ridge and its surroundings in the case of SNNPR, Ethiopia, Doctoral dissertation, Haramaya universityGoogle Scholar
- Tewolde MG, Cabral P (2011) Urban sprawl analysis and modeling in Asmara, Eritrea. Remote Sens 2011(3):2148–2165View ArticleGoogle Scholar
- Thompson M (1996) Standard land cover classification scheme for remote sensing application in South Africa. S Afr J Sci 92:34–42Google Scholar
- Tsegaye D, Moe S, Vedeld P, Aynekulu E (2010) Land-use/cover dynamics in Northern afar rangelands, Ethiopia, agriculture. Ecosyst Environ 139(2010):174–180View ArticleGoogle Scholar
- Tzoulas K, Korpela K, Venn S, Yli-Pelkonen V, Ka´zmierczak A, Niemela J, James P (2007) Promoting ecosystem and human health in urban areas using green infrastructure: a literature review. Landsc Urban Plan 81(2007):167–178View ArticleGoogle Scholar
- UN (2014) World urbanization prospect, department of economic and social affairs, New YorkGoogle Scholar
- Valdkamp E, Weitz A, Staritsky I, Huising E (1992) Deforestation trends in the Atlantic zone of Costa rica: a case study. Land Degrad Rehabil 3:71–84View ArticleGoogle Scholar
- Varshney A (2013) Improved NDBI differencing algorithm for built-up regions change detection from remote-sensing data: an automated approach. Remote Sens Lett 4(5):504–512View ArticleGoogle Scholar
- Wondrade N, Tveite DH (2014) GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed, Ethiopia. Environ Monit Assess 186(3):1765–1780View ArticleGoogle Scholar
- Xu H, Wang X, Xiao G (2000) A remote sensing and GIS integrated study on urbanization with its impact on arable lands: Fuqing city, Fujian province, China. Land Degrad Dev 11:301–314View ArticleGoogle Scholar
- Yang J, Huang C, Zhang Z, Wang L (2014) The temporal trend of urban green coverage in major Chinese cities between 1990 and 2010. Urban For Urban Green 13(2014):19–27View ArticleGoogle Scholar
- Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME (2005) Land cover classification and change analysis of the twin cities (Minnesota) metropolitan area by multitemporal Landsat remote sensing. Remote Sens Environ 98(2–3):317–328View ArticleGoogle Scholar
- Zhang H, Qi ZF, Ye XY, Cai YB, Ma WC, Chen MN (2013) Analysis of land use/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China. Appl Geogr 44:121–133View ArticleGoogle Scholar
- Zhou W, Troy A (2008) An object-oriented approach for analyzing and characterizing urban landscape at the parcel level. Int J Remote Sens 29(11):3119–3135View ArticleGoogle Scholar
- Zoran M (2007) Urban environmental quality assessment by satellite and in situ monitoring data. In: AIP conference proceedings 899, 407Google Scholar