The impact of land use/land cover change on environmental quality in Toowoomba regional area using remote sensing and GIS

Introduction

The concept of land use change and transformation has dominated geographical and scientific researches in the recent times, putting into the lamp lights the various activities of man that contributes to these changes and transformations. Man’s activities are both destructive as well as constructive in regard to modifications occurring on land. Different man’s activities such as agriculture, industrialization and settlement are some of the key factors that have contributed to the constant modifications occurring currently in various places around the globe. The extent of transformation and changes in patterns of land use are, however, higher and rapid in the highly industrialized countries than in the developing nations. Changes in land use patterns and characteristics affects man’s life in different ways depending on the extent of modifications that have been realized, the technological advancements, population characteristics, etc. (Xian, Crane and Su, 2007). As a result, of these changes and the effects borne by them on the society, the human ecosystems and living conditions in various regions have also been affected significantly in relative to the changes occurring around them.

The changes in the nature of the landscape, land use patterns and land cover patterns occur gradually and take long to be realized. These changes occur as a result of the changes occurring in the human conditions such as development patterns, population changes and consequently, changes in human demands for food, clothing and shelter over time, urbanization and urban sprawl (Xiao et al., 2006). Else, the non-anthropogenic factors such as the natural changes in climate conditions over time have also contributed immensely to the changes experienced in land use systems and patterns in various places around the globe. For instance, the changes in carbon concentrations resulting from natural emissions such as volcanic activities, sea surface heating, etc. have equally contributed to the changes in land use patterns and organizations in different places around the globe.

The effects of these changes upon the human society are however great and affects development pattern and prospects in different perspectives. One primary effect that the expanding land use utilization is accruing to the immediate environments is the increasing encroachment into the wetlands. The effects if these encroachments have further presented devastating impacts on land use patterns around the encroached areas significantly including the changes in agricultural practices, settlement patterns and the changes in infrastructural developments, etc (Verburg, van de Steeg, Veldkamp and Willemen, 2009). Toowoomba region has not be exempted from these changes as well as the associated impacts. The major contributing factors here, like in any other region, is the swelling human population that is putting increasing demands on the available natural resources, urban developments and sprawls over time and other related human and natural aspects.

Monitoring the changes in land use patterns and wetlands developments has emerged as an important aspect for environmental planning and management. The national governments and other environmental bodies are mandated to taking custody of the environment have used land use changes and patterns to develop suitable plans that helps to address the confluence between the  human activities and the environment as the sole provider of life on earth. In doing this, several techniques have been developed to assist in envisioning and displaying these changes as they occur in various places around the globe. The developments in technological applications such as geographical information systems (GIS), NDVI and NDWI profiling, etc. have enabled accurate and consistent environmental monitoring for planning and development purposes. Some of these techniques have been discussed in this review. Further the use of Landsat images have developed presently to help in developing adequate information concerning land use changes and patterns in different places. This section of the research shall review some of the breakthroughs in the applications of GIS and RS techniques in unveiling and documenting the changes in land use patterns in different parts of the world. Else, the literature review shall also investigate various instances where NDVI and NDWI (Gao, 1996) profiling have been utilized to document changes in vegetation characteristics as induced by human and natural factors. 

Brief descriptions about GIS and Remote sensing techniques

The impacts of human being upon the environment are becoming one of the most important factors for extensive research consideration. The emergence of GIS and remote sensing technique have provided a clearly illustrated basis upon which scientists can understand the spatial and temporal confluence between humans and their surrounding environments (Legesse, Vallet-Coulomb and Gasse, 2004). Land use changes and patterns are the immediate impacts that the activities of man bear on the environment. The histories of GIS and remote sensing are associated with the emergence and developments of technological applications into the studies nature and its relationships with the human society.  To understand the impacts that GIS and remote sensing have had on the scientific studies of the natural ecosystems and the society, understanding their emergence, development and how they function is crucial to delineating these limits.

Remote sensing

Remote sensing is defined broadly as the science or art of obtaining information from objects without having direct physical contact with these objects. Remote sensing techniques were used mainly during the Second World War to provide large-scale information about the adversaries of war (Lauver, Busby, and Whistler, 2002). Since then, the technique has expanded and become one of the dominating techniques used in various scientific studies on earth. Technological applications such as computers have further helped to advance the applications and utilization of remote sensing technologies leading to the refining of its definition. Maktav, Erbek, and J¨urgens (2005) for instance defines modern RS as the art of taking airborne or space borne information. Remote sensing techniques have enabled the development of a coherent and consistent understanding about the world in general helping to promote the human understanding about the world.

The wide array of multispectral data provided by the airborne cameras provides a clear spatial and temporal understanding of the changes that have occurred on earth within a given period of time. Such data have been utilized in studying the spatial and temporal changes in crops cover, forests cover expansion and reduction, soils development, urban sprawl and land degradation activities among others. The period beginning 1990s have seen increasing logarithmic applications of RS data and information in natural ecosystems management (Muzein, and Csaplovics, 2006). For instance, the tool has been used intensively in land management, management of coastal ecologies, researches on biodiversity, wildlife and other ecosystems studies. Further, improvements in radiometric sensitivities, spectral resolutions, and spatial as well as temporal feedbacks have further increased the applications of remote sensing technology in the studies of the natural ecosystems. As a result, new scanning systems used for remote sensing purposes such as RADAR, SONAR, LIDAR and optical remote sensing have evolved to provide digital images with high resolutions to facilitate the understanding of the human ecosystems in a detailed manner (Osborne, Alonso, and Bryant, 2001). These have improved the details of natural resources provided by the LANDSATS Olsson and Pilesjö (2002) thus expanding the scope and applications and usefulness of RS techniques    

Geographic Information System

The advent of GIS can be traced back to the ancient periods of cartography (the art of map drawing). The GIS technology is a blend of computers technology and the cartographic knowledge which began in the 1960s and developed with the developments in computer applications (Berlanga-Robles, and Ruiz-Luna, 2002). Today, GIS applications can integrate different kinds of data into one single hub for easier comparison and understanding based on the users’ demands. Such information that can be piled together on a GIS map include information on climate, the terrain characteristics, environmental conditions, economic activities, social data, agronomic information as well as other humanistic data (Burger, and Kelting, 1999). As such, GIS has developed to become the most applicable tool used for the study of the human and natural systems regarding the depiction of the spatial and temporal characteristics. The ability of GIS technologies to incorporate raster data provided through remote sensing into the GIS vector data has further widened the scope of this technology (Fu, Liu, Chen, Lu, Qiu, 2004). Today, the multi-user GIS systems and web mapping techniques have expanded the trends in mapping and analysis especially in the developed worlds. Today, real time remote sensing and animations using GIS techniques have given a brand new dimension to the use and applications of remote sensing technologies.  

GIS and remote sensing in ecosystems monitoring

The ecosystems monitoring and management is a rising area of concern among the conservation scientists. Changes in the natural habitats have caused grievous menaces in the present world thus calling for the need to monitor and manage them effectively. As the human society continues to expand over time, the natural ecosystems are gradually being replaced by man-made ecosystems, destroyed through human encroachments and modified to fit in the humans’ perspectives. GIS and remote sensing technologies have been used in two main perspectives to study and monitor ecosystems changes over time and space (Jat, Garg, and Khare, 2008; Ji et al. 2009). These include direct observations of the natural landscapes and communities of organisms inhabiting them and the indirect observations (Ji et al. 2009) and monitoring techniques (Lu, Wu., Yan, Wang, 2011).

Perhaps this is the widest area of application for GIS and remote sensing techniques in the modern scientific studies. While monitoring the ecosystems, the spatial and temporal changes of the same must be developed to enhance the understanding about how much of the changes have been realized over what period of time. Else, such knowledge helps to develop policies and plans on the appropriate actions to take in order to conserve the natural habitats. Modelling and mapping of land use patterns and cover are the most common monitoring systems. The preceding section looks at the aspects of modeling and mapping of the spatial and temporal changes in the natural ecosystems as a means of monitoring the changes occurring through time. 

Mapping of land use and land cover systems

The role of GIS in natural ecosystems monitoring has been achieved successfully from the perspectives of mapping. Land cover mapping involves the transfer of the raster data covered in remotely sensed data into the digital format produced on maps. The entire process of transfer is referred to as digitization. The mapped data is then geo-referenced (geo-dated) to make them specific and referenced to given landscapes.  The land cover and land use systems keep changing from time to time, in terms of areal coverage (the spatial change) (Anderson, Hardy, Roach, and Witmer, 1976), and characteristics over time (temporal changes) (Nemeth, Ventura, and Yuan, 2013). The major contributors to these changes are both natural as well as human-induced. Declining land cover and land use systems also affects the economic characteristics of these areas (Ezeomedo and Igbokwe, 2013). Mapping these natural ecosystems properties therefore is unavoidable for purposes of natural resources planning and management. Lu, Wu and Wang (2010) used HJ-1A/B satellite images to map the water bodies based on the near-infrared. The study compared the effectiveness of a combination of NDVI-NDWI and the single applications of the NDVI and NDWI. The results indicated that a combination of the two (NDVI-NDWI) produced a higher quality result compared to the single models.  

Various techniques are available for mapping and digitizing the raster data from remote sensing platforms into digital information that can be read and interpreted on maps. The techniques can be divided into three main classes: automatic, semi-automatic and manual digitization techniques (Reis, S., 2008). These digitization techniques help to convert raster images into vector maps with defined boundaries describing the areas of interest. Scanning and screens digitizations are the most commonly used methods direct digitization techniques (Rawat, and Kumar, 2015). Programs that can change the scanned raster images into vector maps can also be used to perform the digitization for purposes of mapping. The resultant maps can then be used to depict the changes in land use systems from one region to another within the map as well as from time to time. This is commonly evident in time series maps (Butt, Shabbir, Ahmad and Aziz, 2015). VerPoorter, Kutser and Tranvik (2012) used Landsat multispectrum images to map the expanse and quality of the water bodies. Through the generated maps, VerPoorter, Kutser and Tranvik (2012) developed a clear understanding of the changes taking place on the water bodies. The maps gave both qualitative and quantitative information on the water bodies. 

Modelling land use and land cover change

Modelling is the modern approach to natural resources management and land use change monitoring and characterization over time. Modeling the land use changes and patterns involves the use of remote sensing data as well as the GIS modeling tools (Pauleit, Ennos, and Golding, 2005). Modelling helps to delineate the changes in land use systems and patterns over time and within space based on given baseline. The NDVI maps have been used on most occasions as surrogate maps used for referencing natural land cover systems (Sharma, Janauer, Mondal, Bakimchandra, Garg, 2012). Osborne, Alonso and Bryant (2001) used GIS data and the remote sensing techniques to model the habitats. Using the remote sensing images and the geodetic information generated from these sources, Osborne, Alonso and Bryant (2001) developed a time-bound and spatial-based model that describes the temporal changes in the size and qualitative conditions of the habitat giving a better understanding of the factors resulting into the changes. Niklas (2005) also used the GIS and remote sensing tools to model the biomass for non-woody and woody plants. The model included the organisms both on the ground and other biological organisms above the ground.   

Studies on the applications of GIS and Remote sensing techniques in land use/ land cover analysis

Several studies have been conducted in the fields of GIS and remote sensing to determine their applications in different sectors. The applications of the two software have experienced tremendous applications in various fields of study. The studies of natural resources for instance, have benefited a great deal from the developments in GIS and remote sensing. This section provides an analysis of some of the studies that have utilized these techniques to study different aspects of nature. To begin with GIS techniques have been utilized a great deal to model the changes in land use and utilization patterns and characteristics in different parts of the world. The GIS technique has been used widely in depicting spatial and temporal changes in human land use and land cover activities occurring in various places (Olsson, and Pilesjö, 2002). The GIS tool functions by detecting/ sensing emissions generated by various phenomena over the surface of the earth. Different phenomena generate and emit different qualities and characteristics of emissions which define the uniqueness of these features from others. As a result, the GIS tools have been used widely in the present world to produce models depicting spatial and temporal land use changes as well as land cover systems (Sleeter et al. 2012). Drummond and Loveland (2010) study for instance, developed a cohesive and comprehensive spatial-temporal analysis of the changes in forest cover in the United States over time. The study highlighted that the declining agricultural activities such as farming, expansion of settlements in forested areas and the consequent decline in industrial expansion have contributed to the expansion of forest cover in the region over time.

The impacts of urban sprawl upon the land use systems in areas surrounding the urban centres have been studied by researchers such as Xiao et al (2006). Xiao et al (2006) utilized GIS data and the remote sensing images to compile a consistent analysis of the changes in land use patterns in Shijiazhuang, China from 1987 to 2001. Relying on the remotely sensed images for the region covering the period 1934 – 2001, the study characterized the spatial changes in urban change characteristics of the region into three main classes. These included the special objectives oriented changes, the social-politically instigated changes and the normalized urban growth systems. The RS images are a suitable complementary analytical tools used to complement the GIS data generated from researches. Comparisons between these two classes of data have realized practical depiction of the status of land use changes as well as land cover changes through space and time (Wilson, Growns, Lemon, 2008). Based on the image analysis generated using the GIS and RS tools, the spatial and temporal changes in land use patterns between different regions have been developed in the studies of Yuan (2008).

Remotely sensed images are derived from satellite images taken from great heights up in the sky. The images have spatial and temporal characteristics since they are captured by satellites mounted on the orbit of the earth (Campos, Oleschko, Etchevers, and Claudia, 2007). For instance, Yuan (2008) study encompassed the satellite images captured in 1971-2003 and depicting the changes in land use patterns in the regions of Minnesota from 1971 to 2003. Modelling researches reported in various studies use remotely sensed data with the GIS data generated from the ground. The relationships between RS and GIS that makes them particularly useful in compiling land use changes is due to the fact that RS data (merely aerial photographs) provide broad characteristics of the land scape including water cover, forested areas, crop lands and other land use activities without specifying the salient characteristics of each (Faryadi, and Taheri, 2009). However GIS information provides the underlying details, by going into the Nitti gritty of the vegetation and landscape characteristics in these regions.  

          Unlike GIS information, RS information cannot distinguish the specific changes occurring on the natural landscapes such as the changing vegetation characteristics evident in different regions, water and soil qualities and temperature characteristics of a given area. However, the technique gives adequate information on the expanse/ size, and the changes that have occurred in terms of size and other broad characteristics over time (Guo, Wu, Liu, and Li, 2011). Depending on the resolution power of the remote sensing camera, a lot of information imminent on the land surface can be discerned (Guo, Wu, Liu, and Li, 2011). The bulk of information provided through the remote sensing technique can then be refined to develop coherence and in-depth understanding of the specific change characteristics evident in the specific regions. As seen from these studies, the resolution powers of the technological applications chosen by the researchers define the quality of the phenomena studied. The higher the resolution power, the greater are the details gathered and vice versa (Hanqiu, 2006; Yuan, 2008). By reviewing the literature on the applications of these technologies, this study shall derive the best combinations that will give the best results from the studies.          

Using the GIS data generated from the Mankato area of Minnesota alongside aerial photographs from QuickBird images, Yuan (2008) was able to compile a comprehensive changes in land use and land cover systems in the region taking into account the influences of changes in temperature, surface run offs and water quality, air pollution and aspects of carbon sequestration on these changes. Through these fine analyses, a lot of details can be derived which is related to the bulk of information generated from the remotely sensed data to develop a modeled understanding of the associated factors and impacts (Guzman, and Al-Kaisi, 2011). GIS and remote sensing data play a crucial role in compiling patterns of land use changes as well as land cover changes through time and space (spatial-temporal analysis). The differences in resolutions of the images captures from the RS sensed images gives adequate information about the nature and rough characteristics of the features captured within.

The ability of the GIS technique to detect different emissions and distinguish the qualities propagated from these rays gives it a wide array of application in the studies of the natural landscape. Studies of the wetland ecosystems are one of the areas in which GIS applications have gained tremendous applicability. The developing technological applications have influenced the advancements of the GIS and remote sensing applications in natural studies. For instance, Hanqiu (2006) modified the NDWI to use the MIR instead of the normal NIR bands. The results indicated a clearer information obtained compared to using the NIR bands. Archana and Sanjay (2008) on the other hands combined the RS technique NDWI to study the dynamisms on the wetlands ecosystems based on the IRS satellite pictures. This study presented a different aspect to the use of remote sensing techniques that is gaining rapid popularity in the recent past. Like other studies such as (Davranche, Lefebvre, and Poulin, 2010). Archana and Sanjay (2008) also utilized the NDWI techniques to study the dynamisms migratory patterns of birds in relation to the changes in wetlands. This study will however limit its applications to the studies on wetlands changes and dynamisms.   

The studies on wetlands ecosystems distributions and changes over time have formed the core part of scientific studies regarding the changes occurring within the natural environment. As Fung, and Siu (2000) highlights, the wetlands distributions are a critical influence to the occurrence of land cover and thus influence the land use systems occurring in these regions. For instance Davranche, Lefebvre, and Poulin (2010) utilized the SPOT-5 seasonal time series to depict the changes in wetlands growths and developments over time. Through these, the expansion and shrinking of the wetlands have been delineated to better understand the changes in land use activities as well as the plant cover distributions over time. The revelations generated here helps to acquaint the scientists with adequate information on the land cover changes through time as well as the spatial distribution of the land cover systems. Similar quality environmental qualities based on the wetlands analysis have been conducted by Fung, and Siu, (2000) by examining the changes in NDVI over time. Based on the NDVI changes, the quality of the land cover is determined and thus the intensity of the land use systems adopted in the regions. By determining the changes in the NDVI and NDWI, this research shall establish the associated changes that have occurred in the land use characteristics as well as the land cover systems in the Toowoomba region. This will help in understanding the spatial and temporal trends in the changes of the three aspects.

Other than the distributions of the wetlands ecosystems, the changes in soil characteristics, the slope characteristics as well as other related landscape characteristics, the changes in land soil qualities also affect the distributions in land use and land cover characteristics in different regions of the world (Wang, Fu, Qiu, and Chen, 2001). Several other studies have also looked at the changes in soil quality characteristics as well as the slope characteristics to define the land cover and land use characteristics in the respective regions. Akbari, Azimi, and Bin Ramli, (2014) for instance, in their studies looked at the influence of the slope characteristics as well as the depth in cultivated ecosystems to determine the distribution of the land cover characteristics as well the land use activities conducted in the regions at different times. The slope characteristics were found to affect the distribution of plat cover significantly by influencing the distribution of the minerals that affects plants distributions along the slope (Jackson-Gilbert et al. 201). The steeper the slope, the lesser the minerals and thus, the lesser is the land cover and consequently the intensity in land use activities (Akbari, Azimi, and Bin Ramli, 2014; Poyatos, Latron, and Llorens, 2003).

Akbari, Azimi, and Bin Ramli (2014) observations and findings were confirmed in the works of Griffith et al. (2002) who studied the interrelationships between different landscapes based on the soil quality characteristics, slope characteristics etc. These interrelationships were then compared with the NDVIs and the stream water qualities of the in central plains of the US. The study confirmed the relationships between slope qualities and distributions of the wetlands, land cover and the land sue systems in the region. Like in the previous studies, to develop the relationships between the slopes characteristics and the changes that have occurred in Toowoomba regions in terms of land use patterns and the land cover systems, the study shall develop the DEM maps to depict the changes in slope characteristics over time, thus helping to explain the hydrological changes such the changes in the flow characteristics of the rivers and their associated tributaries over time. These changes are capable of affecting the land cover characteristics and consequently the land use systems evident in the regions (Hao, and Ren, 2009).      

As illustrated in the previous sections, the changes in topographical characteristics such as the nature of the slopes, slope compositions and angles affect the distribution and composition of the slopes in terms of mineral availability and thus vegetation characteristics. Xiaoye, and Zhenyu, (2010) developed DEM maps depicting the distribution of the rivers and their tributaries in Toowoomba region to help explain their relationships to the distributions of the land cover systems in the region. Else, the study also drew the link between the distribution and flow patterns of the region’s rivers and their tributaries to the distributions of the land use activities conducted in the region. The research confirmed the trend to the affirmative asserting that the slope characteristics influenced land cover distributions and thus the land use activities conducted in these regions. Unlike Xiaoye and Zhenyu (2010) study, this study shall look at the changes in land use characteristics as well as the land cover characteristics relative to the changes in topographical characteristics of the region through time and scale.

Conclusion

To conclude, the human landscape is one of the most dynamic phenomena on the earth surface. A lot of human and natural activities take place in various places around the globe thus affecting the orientation of the physical landscapes over time. In fact, any place inhabited by humans and on which the natural phenomena keep modifying the natural landscape undergo evolutionary changes over time. As a result the changes occurring on the surface of the land keep affecting the land cover characteristics as well as the land use activities adopted in these regions over time and space. The Toowoomba region, being inhabited by an increasing population through time and having experienced tremendous effects in terms of the changes in the natural characteristics over time, has not been an exception to the noted modifications. This study seeks to trace the changes through time by employing the use of technological applications such as the GIS and remote sensing technologies o depict and describe the changes that have occurred in Toowoomba regions over time. The assessment shall encompass changes in land use characteristics and land cover characteristics as influenced by both the natural and human induced factors. 

References

Akbari, A., Azimi, R and Bin Ramli, N.I. 2014. Influence of slope aspects and depth on soil properties in a cultivated ecosystem. EJGE, 19, 8601-8608

Anderson, J.R., Hardy, E.E., Roach, J.T., Witmer, R. E. 1976.  A Land Use and Land Cover Classification System for Use with Remote Sensor Data.  United States Government Printing Office.  Washington D.C.

Archana, S., Sanjay, K.J., 2008. Using Remote Sensing Data to Study Wetland Dynamics – A Case Study of Harike Wetland. Proceedings of Taal 2007: The 12th world Lake Conference, pp. 680-684. 

Berlanga-Robles, C.A. and Ruiz-Luna, A., 2002. Land use mapping and change detection in the coastal zone of northwest Mexico using remote sensing techniques. Journal of Coastal Research, 18(3): 514–522.

Burger, J.A. And Kelting, D.L., 1999. Using soil quality indicators to assess forest stand management. Forest Ecology and Management, 122, 155-166.

Butt, A., Shabbir, R., Ahmad,S.S. and Aziz, N., 2015. Land use change mapping and analysis using remote sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan. The Egyptian Journal of Remote Sensing and Space Sciences, 18, 251-259.

Campos, A., Oleschko, K., Etchevers, J., and Claudia, H.M. 2007. Exploring the effects of changes in land use on soil quality on the eastern slope of the Cofre de Perote Volcano (Mexico). Forest Ecology and Management, 248, 174-182.

Davranche, A., Lefebvre, G., and Poulin, B., 2010. Wetland monitoring using classification trees and SPOT-5 seasonal time series. Remote Sensing of Environment 114, 552–562.

Drummond, M.A., and Loveland, T.R. 2010. Land-use Pressure and a Transition to Forest-cover Loss in the Eastern United State. Bioscience, 60(4): 286-298.

Ezeomedo, I., and Igbokwe, J., 2013. Mapping and Analysis of Land Use and Land Cover for a Sustainable Development Using High Resolution Satellite Images and GIS. FIG Working Week 2013 Environment for Sustainability Abuja, Nigeria, 6 – 10 May 2013.

Faryadi, S. and Taheri, S.2009. Interconnections of Urban Green Spaces and Environmental Quality of Tehran. International Journal of Environment Res., 3(2): 199-2008.

Fu, B., Liu, S., Chen, L., Lu, Y., Qiu, J. 2004. Soil quality regime in relation to land cover and slope position across a highly modified slope landscape. Ecological Research, 19, 111-118.

Fung, T., and Siu, W. 2000. Environmental quality and its changes, an analysis using NDVI. International Journal of Remote Sensing, 21(5): 1011-1024, DOI: 10.1080/014311600210407

Gao, B., 1996. NDWI A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water From Space. Remote Sensing Environment, 58, 257-266.

Griffith, J.A., et al. 2002. Interrelationships among landscapes, NDVI, and stream water quality in the U.S. central plains. Ecological Applications, 12(6): 1702–1718

Guo, P., Wu, W., Liu, H and Li, M. 2011. Effects of land use and topographical attributes on soil properties in an agricultural landscape. Soil Research, 49, 606-613.

Guzman, J.G., and Al-Kaisi, M.M., 2011. Landscape position effect on selected soil physical properties of reconstructed prairies in southcentral Iowa. Journal of soil and water conservation, 66(3): 183-191.

Hanqiu, X. 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14): 3025-3033. DOI: 10.1080/01431160600589179

Hao, H., and Ren, Z. 2009. Land Use/Land Cover Change (LUCC) and Eco-Environment Response to LUCC in Farming-Pastoral Zone, China. Agricultural Sciences in China, 8(1): 91-97.

Jackson-Gilbert, M.M., et al. 2015. Soil Fertility in relation to Landscape Position and Land Use/Cover Types: A Case Study of the Lake Kivu Pilot Learning Site. HindawiPublishing Corporation Advances in Agriculture. ID 752936.http://dx.doi.org/10.1155/2015/752936

Jat, M.K., Garg, P.K.,and Khare,D., 2008. Monitoring and modelling of urban sprawl using remote sensing and GIS techniques. International Journal of Applied Earth Observation and Geoinformation, 10(1): 26–43.

Ji, L., et al. 2009. Improving wetland mapping by using multi-source data sets. National 863 High Technology Research and Development Program of China. No. 2009AA12ZX1486531.

Legesse, D., Vallet-Coulomb, C., and Gasse, F. 2004. Analysis of the hydrological response of a tropical terminal lake, Lake Abiyata (Main Ethiopian Rift Valley) to changes in climate and human activities, J. Hydrol. Processes, 18: 487–504.

Lauver, C., Busby, W., and Whistler, J. 2002. Testing Model of Habitat Suitability for a Declining Grassland Bird. Environmental Management, 30: 88.

Lu, S., Wu., Yan, N., Wang, H., 2011. Water body mapping method with HJ-1A/B satellite imagery. International Journal of Applied Earth Observation and Geoinformation, 13, 428-434.

Maktav, D., Erbek, F.S. and J¨urgens, C., 2005. Remote sensing of urban areas. International Journal of Remote Sensing, 26(4): 655–659.

Muzein, B. and Csaplovics, E. 2006. Application of Remote Sensing and GIS to Assess Continuous Land Cover Changes in Forestlands of the Southwest Ethiopia. Proceeding of the Workshop “Remote Sensing and Geoinformartion Processing in the Assessment and Monitoring of Land Degradation and Desertification, Trier Germany. September 2005.

Nemeth, K., Ventura, G., and Yuan, G-L. 2013. Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at an Urban Area, Tirupati, India. The Scientific World Journal. ID. 268623.

Niklas, K. 2005. Modelling Below- and Above-ground Biomass for Non-woody and Woody Plants. Annals of Botany, 95: 315–321

Olsson, L. and Pilesjö, P. 2002. Approaches to Spatially Distributed Hydrological Modelling in a GIS Environment. In: Skidmore, A. (ed): Environmental modelling with GIS and remote sensing. Taylor & Francis, London. Pp. 166-198

Osborne, P., Alonso, J., and Bryant, R. 2001. Modelling landscape-scale habitat use using GIS and remote sensing: a case study with great bustards. Journal of Applied Ecology, 38: 458-471.

Pauleit, S., Ennos, R., and Golding, Y. 2005. Modeling the environmental impacts of urban land use and land cover change—a study in Merseyside, UK. Landscape and Urban Planning, 71, 295-310.

Poyatos, R., Latron, J. and Llorens, P. 2003. Land Use and Land Cover Change after Agricultural Abandonment. Mountain Research and Development, 23(4):262-268

Rawat, J.S., and Kumar, M., 2015. Monitoring land use/cover change using remote sensing using and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand. The Egyptian Journal of Remote Sensing and Space Sciences, 18, 77-84.

Reis, S., 2008. Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey. Sensors, 8, 6188-6202. DOI: 10.3390/s8106188

Sharma, N., Janauer, G., Mondal, M.S., Bakimchandra, O., Garg, R.D., 2012. Assessing Wetland Landscape Dynamics in the Deepor Beel of Brahmaputra Basin Using Geospatial Tools. Asian Journal of Geoinformatics, 12(1):

Sleeter, B.M., et al. 2012. Scenarios of land use and land cover change in the conterminous United States: Utilizing the special report on emission scenarios at ecoregional scale. Global Environmental Change, 22, 896-914

Sreenivasulu, G., Jayaraju, N., Kishore, K., and Lakshmi P.T. 2014. Land use and land cover analysis using remote sensing and GIS: A case study in and around Rajampet, Kadapa District, Andhara Pradesh. Indian Journal Science Res., 8(1): 123-129.

Verburg, P.H., Van de Steeg, Veldkamp, A. and Willemen, L., 2009. From land cover change to land function dynamics: A major challenge to improve land characterization. Journal of Environmental Management, 90, 1327-1335.

VerPoorter, C. Kutser, T., and Tranvik, L., 2012. Automated mapping of water bodies using landsat multispectrum data. Limnol. Oceanogr.: Methods 10, 1037–1050.

Wang, J., Fu, B., Qiu, Y., and Chen, L., 2001. Soil nutrients in relation to land use and landscape position in the semi-arid small catchment on the loess plateau in China. Journal of Arid Environments, 48, 537-550. Doi:10.1006/jare.2000.0763

Wilson, B.R., Growns, I., Lemon, J., 2008. Land-use effects on soil properties on the north-western slopes of New South Wales: Implications for soil condition assessment. Australian Journal of Soil Research, 46, 359-367.

Xian, G., Crane, M., and Su, J. 2007. An analysis of urban development and its environmental impact on the Tampa Bay watershed. Journal of Environmental Management, 85, 965-976.  

Xiao, J. et al. 2006. Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landscape and Urban Planning, 75, 69-80.

Xiaoye, L. and Zhenyu, Z. 2010. Extracting Drainage Network from High Resolution DEM in     Toowoomba, Queensland. SSSI Queensland Conference, 2010.

Yuan, F. 2008. Land‐cover change and environmental impact analysis in the Greater Mankato      area of Minnesota using remote sensing and GIS modelling. International Journal of   Remote Sensing, 29(4): 1169-1184. DOI: 10.1080/01431160701294703

 

 

 

 

 

 

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