Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Land cover changes on the coastal zone of Candarli Bay, Turkey using remotely sensed data

Land cover of the Earth is changing dramatically because of human activities. Information about changes is useful for management of natural resources. Rapid land cover changes have taken place in many coastal areas of Turkey over the last two decades due to urbanization and land degradation. In this paper, land cover change dynamics were investigated by the combined use of satellite remote sensing and geographical information systems. The main objective of the study was to determine land-cover transition rates among land cover types in coastal areas of Turkey. A time series of Landsat TM and ASTER images were used to gather land cover change data of the coastal line of Candarli Bay, Izmir, Turkey. The images were classified using supervised classification and a post-classification comparison approach was used in change detection. The results show significant increase in urban areas but decrease in semi natural and agricultural areas.     

Analysing urban expansion and land use suitability for the city of Kahramanmaraş, Turkey, and its surrounding region

This study aimed at quantifying changes in urban area of the city of Kahramanmara? (K.Mara?) between 1948 and 2006, and analysing suitability of existing land use (LU) to the land potential. Urban change information was derived from two black-white monoscopic aerial photographs, and IKONOS and the QuickBird images acquired in 1948, 1985, 2000 and 2006, respectively. QuickBird image and soil map with 1:25,000 scale were used to analyze suitability of the current LU pattern to the land potential. The findings showed that the urban area of K.Mara? has expanded approximately 13 times during the past six decades. According to current LU and the soil map, productive and moderately productive soils were largely (73.2%) allocated for agricultural activities, which means that there was a strong consistency between the agricultural LU type and the land capability. However, widespread agriculture on the non-productive soils, and urbanization on the fertile agricultural lands were assessed as unsuitable from sustainable LU viewpoint. Considering this phenomenon, it is possible to say that rapid urban expansion has a growing pressure on the fertile agricultural soils. Monitoring LU changes, particularly urbanization, and developing effective LU plans based on the land capability were determined as the most important approaches to encourage sustainable use of land.     

太湖流域景观生态风险评估

在GIS和RS技术支持下,以遥感数据和土地利用数据为基础,以行政区划为评价单元,构建景观生态风险评价模型,定量评价了研究区内景观生态风险的时空动态变化特征。结果表明,较低风险区主要分布于以苕溪为主的山地丘陵区,中等风险区主要分布于农业发达的平原区,较高风险区及高风险区主要集中于沿湖经济发达区。     

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe’s WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product’s overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.     

Remote sensing and GIS-based integrated analysis of land cover change in Duzce plain and its surroundings (north western Turkey)

The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1—urban fabric, 2—industrial, commercial and transport units, 3—heterogeneous agricultural areas, 4—forests, and 5—inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.     

Monitoring the impacts of urbanization and industrialization on the agricultural land and environment of the Torbali, Izmir region, Turkey

The aim of this research is to determine agricultural land loss and environmental pollution caused by industrialization and urban sprawl using the Geographical Information System (GIS) and Remote Sensing technique (RS). Remotely sensed data is the most powerful tool for monitoring land use changes and GIS is the best way to store and reproduce various kinds of integrated data. Considering the rapid increase of population the loss of fertile agricultural soils is a very dangerous situation for the future of the country. Thus, people are living in the cities in (with adverse) conditions of insufficient drinking water, infrastructure problems, inadequate landscape and many unsolved (extreme) environmental problems. During the last 36 years, unplanned urbanization and industrialization have led to the use of agricultural areas for non-agricultural purposes in the Torbali (Izmir) region, which has the most fertile soils of the Aegean Region. Within this study, a database was created on the parameters of land loss and environmental pollution by means of field observation, interpretation of satellite images (ASTER), aerial photos(1/25.000 scale), topographic map ,soil map, and 1/5.000 scale cadastral map. Results of previous researches and the archives of Torbali municipality were used as ancillary data. In the research, urbanization and industrialization of the town was studied by (using) GIS and RS between 1965 and 2001. Since 1965, 4.742.357 m² agricultural land, mostly of first and second land use capability classes, has been lost due to unplanned urban and industrial developments. Urbanization and industrialization involved an area of which 58% was being used as irrigated lands, 25 % rain feed (rain fed lands)and 17 % for olive growing.     

Determining land use changes by radar-optic fused images and monitoring its environmental impacts in Edremit region of western Turkey

Rapid and unplanned urbanization and industrialization are the main reasons of environmental problems. If urban growth is not based on resource sustainability criteria and urban plans are not applied, natural and human resources are damaged dramatically. In this study, land use change and urban expansion in Edremit region of Turkey is determined by means of remote sensing techniques between 1971 and 2002. To improve the accuracy of land use/cover maps, the contribution of SAR images to optic images in defining land cover types was investigated. To determine the situation of land use/cover types in 2002 accurately, Landsat-5 images and Radarsat-1 images were fused, and the land use/cover types were defined from the fused images. Comparisons with the ground truth reveal that land use maps generated using the fuse technique are improved about 6% with an accuracy of 81.20%. To define land use types and urban expansion, screen digitizing and classification methods were used. The results of the study indicate that the urban areas have been increased 1,826 ha across the agricultural fields which are in land use capability classes of I and II, and significant environmental changes such as land degradation and degeneration of ground water quality occurred.     

Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey)

In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.     

Use of USLE/GIS Methodology for Predicting Soil Loss in a Semiarid Agricultural Watershed

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.     

Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches

Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution 1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid.     

Assessing Development Pressure in the Chesapeake Bay Watershed: An Evaluation of Two Land-Use Change Models

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations.     

The burning of fuelwood in South Africa: When is it sustainable?

Fuelwood harvesting is considered sustainable when consumption is equal to or less than production. An empirical model was developed to estimate potential fuelwood production from savannas. The model is based on the observation that in semiarid savannas, biomass production is linearly dependent on rainfall. Woody basal area is linked to mean annual precipitation, and aboveground woody biomass is proportional to basal area. Production averages 4% of standing woody biomass and is corrected to exclude stems that are too small for harvesting. The model assumes that the entire area consists of seminatural savanna. Corrections for the land lost as a result of land transformation and degradation would have to be included. Data on land loss can most effectively be obtained from satellite imagery, with appropriate ground calibration. The model is based on limited data sets but in most instances has been validated against independently collected data. The model yields a reasonable prediction at a national and regional level, but estimates for limited areas or specific points on the ground may differ substantially from the predicted values. Model results indicate a potential for sustainable fuelwood production at the national level, but specific regions are using fuelwood at nonsustainable levels.     

Environmental change monitoring in the arid and semi-arid regions: a case study Al-Basrah Province, Iraq

In recent years, land use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. This research utilizes the integrated remote sensing and geographic information systems (GIS) in the southern part of Iraq (Basrah Province was taken as a case) to monitor, map, and quantify the environmental change using a 1:250,000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation land, sand land, urban area, unused land, and water bodies. Supervised classification and normalized difference buildup index, normalized difference vegetation index, normalized difference bare land index, the normalized differential water index, crust index (CI) algorithms, and change detection techniques were adopted in this research and used, respectively, to retrieve its class boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. The results showed that the urban area, sand lands, and bare lands had increased by the rate of 1.2%, 0.8%, and 0.4% per year, with area expansion from 3,299.1, 4,119.1 km², and 3,201.9 km² in 1990 to 3,794.9, 4,557.7, and 3,351.7 km² in 2003, respectively. While the vegetation cover and water body classes were about 43.5% in 1990, the percentage decreased to about 39.6% in 2003. This study demonstrates the effectiveness of the remote sensing and GIS technologies in detecting, assessing, mapping, and monitoring the environmental changes.     

Analysis of the spatio-temporal and semantic aspects of land-cover/use change dynamics 1991–2001 in Albania at national and district levels

In the turmoil of a rapidly changing economy the Albanian government needs accurate and timely information for management of their natural resources and formulation of land-use policies. The transformation of the forestry sector has required major changes in the legal, regulatory and management framework. The World Bank financed Albanian National Forest Inventory project provides an analysis of spatially explicit land-cover/use change dynamics in the period 1991–2001 using the FAO/UNEP Land Cover Classification System for codification of classes, satellite remote sensing and field survey for data collection and elements of the object-oriented geo-database approach to handle changes as an evolution of land-cover/use objects, i.e. polygons, over time to facilitate change dynamics analysis.Analysis results at national level show the trend of natural resources depletion in the form of modifications and conversions that lead to a gradual shift from land-cover/use types with a tree cover to less dense tree covers or even a complete removal of trees. Policy failure (e.g., corruption, lack of law enforcement) is seen as the underlying cause. Another major trend is urbanisation of areas near large urban centres that change urban-rural linkages. Furthermore, after privatisation agricultural areas increased in the hills where environmental effects may be detrimental, while prime agricultural land in the plains is lost to urbanisation.At district level, the local variability of spatially explicit land-cover/use changes shows different types of natural resources depletion. The distribution of changes indicates a regional prevalence, thus a decentralised approach to the natural resources management could be advocated.     

Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method

Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth’s surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Earth’s surface. Moreover, landslides can be triggered by human activities such as underground mining. This study aims to identify landslide susceptibility areas by analyzing landslide-related factors, including land subsidence triggered by underground mining. The area of interest was Kozlu, Turkey, where underground mining has been in progress for the past 100 years. Thus, to identify landslide risk zones, the multicriteria decision analysis method, together with the analytical hierarchy method, was used. The datasets included were topography, land cover, geological settings, and mining-induced land subsidence. The spatial extent of land subsidence was estimated using a previously published model. A landslide susceptibility map (LSM) was developed using a purposely developed GIS-based software. The results were compared with a terrain deformation map, which was developed in a separate study using the differential synthetic aperture radar interferometry (DInSAR) technique. The results showed a substantial correlation between the LSM and DInSAR map. Furthermore, it was found that ~?88% of the very high and high landslide risk areas coincided with location of the past landslide events. These facts suggest that the algorithm and data sources used were sufficient to produce a sufficiently accurate LSM, which may be used for various purposes such as urban planning.     

A DSS for sustainable development and environmental protection of agricultural regions

This paper presents a decision support system (DSS) for sustainable development and environmental protection of agricultural regions developed in the framework of the Interreg-Archimed project entitled WaterMap (development and utilization of vulnerability maps for the monitoring and management of groundwater resources in the ARCHIMED areas). Its aim is to optimize the production plan of an agricultural region taking in account the available resources, the environmental parameters, and the vulnerability map of the region. The DSS is based on an optimization multicriteria model. The spatial integration of vulnerability maps in the DSS enables regional authorities to design policies for optimal agricultural development and groundwater protection from the agricultural land uses. The DSS can further be used to simulate different scenarios and policies by the local stakeholders due to changes on different social, economic, and environmental parameters. In this way, they can achieve alternative production plans and agricultural land uses as well as to estimate economic, social, and environmental impacts of different policies. The DSS is computerized and supported by a set of relational databases. The corresponding software has been developed in a Microsoft Windows XP platform, using Microsoft Visual Basic, Microsoft Access, and the LINDO library. For demonstration reasons, the paper includes an application of the DSS in a region of Northern Greece.     

Performance Evaluation of the SLEUTH Model in the Shenyang Metropolitan Area of Northeastern China

Performance evaluation is crucial for the development and improvement of an urban cellular automata model, such as SLEUTH. In this paper, we employed multiple methods for map comparison and model validation to evaluate the simulation performance of the SLEUTH urban growth model in the Shenyang metropolitan area of China. These multiple methods included the relative operating characteristic (ROC) curve statistic, multiple-resolutions error budget, and landscape metrics. They were used to quantitatively examine model performance in terms of the amount and spatial location of urban development, urban spatial pattern and prediction ability. The assessment results showed that SLEUTH performed well in the way of the quantitative simulation of urban growth for this case study. Similar to other urban growth models, however, the simulation accuracy for spatial location of new development at the pixel scale and urban spatial pattern still needs to be improved greatly. These inaccuracies might be attributed to the structure and nature of SLEUTH, local urban development characteristics, and the temporal and spatial scale of its application. Finally, many valuable suggestions had been put forward to improve simulation performance of SLEUTH model for spatial location of urban development in the Shenyang metropolitan area.     

Land quality assessment and sustainable land use in Salt Lake (Tuz Gölü) specially protected area

Land quality assessment is of great important for decisions on sustainable land uses and the conservation of ecosystems of high biodiversity value. The main objective of this study was to determine properties of land quality of specially protected area of the Salt Lake using CORINE land quality assessment methodology and to propose a revision for this model. In addition to field study and laboratory analysis, digital soil map, digital elevation model, satellite image and climatic data were used and analyzed with remote sensing and geographic information systems techniques to generate actual land quality map and to form database for study area. Results show that 42.1% of the study area has high quality, 28.7% was classified as moderate quality and 4.0% was determined as low quality. On the other hand, some places classified as moderate quality, were not accurately classified. These places should be low land quality due to content of high salt concentration. Therefore, to resolve this insufficient situation, some soil parameters such as chemical properties should be collaborated with this model. In this case, moderate land quality level of the study area decreased from 28.7 to 12.3%, whereas 4.0% of low quality land of the study area increased to 20.8%. In addition, this research was also carried out to provide guidance for planner or decision makers about specially protected area of the Salt Lake.