Land use/land cover change and their effects on landscape patterns in the Yanqi Basin, Xinjiang (China)

Human modification of land use and land cover change (LUCC) drives the change of landscape patterns and limits the availability of products and services for human and livestock. LUCC can undermine environmental health. Thus, this study aimed to develop an understanding of LUCC in the Yanqi Basin, Xinjiang, China, an arid area experiencing dramatic water and land resource use. A time series of satellite images (1964, 1973, 1989, 1999, and 2009) were used to calculate the index of landscape patterns to study the processes involved in changes to land uses and landscape patterns and the influence of this changes on landscape patterns. The results show that land uses in the Yanqi Basin have changed dramatically since 1964 with grassland being mainly converted to cropland. Landscape fragmentation and diversity have decreased in the study area, although landscape fragmentation increased from 1964 to 1999 and then decreased by 2009. The index of landscape diversity decreased from 1.64 in 1964 to 0.71 in 2009. The heterogeneity and complexity of the landscape increased during this period. In contrast, the index of dominance decreased from 0.85 in 1964 to 0.83 in 2009. Land use change drives landscape patterns of the development of the watershed toward diversity and a fragmented structure. Population growth, economic development, and industrial policies were the dominant driving forces behind LUCC in the Yanqi Basin. Sustainable use of land resources is a significant factor in maintaining economic development and environmental protection in this arid inland river basin.     

Monitoring land use/land cover changes using CORINE land cover data: a case study of Silivri coastal zone in Metropolitan Istanbul

The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use–land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Gretaer Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively.     

Spatio-temporal analysis of land use/land cover change and its effects on soil erosion (Case study in the Oplenac wine-producing area,Serbia)

In this paper, various spatial modelling techniques were applied to analyse changes in soil cover and their impact on soil erosion in the Oplenac wine-producing area in Serbia in the past (1985 and 2013) and in the future (with predictions for 2041). The Integrated Valuation of Ecosystem Services and Trade-offs Sediment Delivery Ratio (InVEST SDR) model and the Modules for Land Use Change Evaluation (MOLUSCE) model, integrated with methods of remote sensing, were successfully applied and were shown to be valid tools for predicting the impact of Land Use Land Cover (LULC) changes when estimating soil loss. The results revealed that the greatest impact of land use changes between 1985 and 2013 was on a reduction in areas under vineyards and an extension of meadow and pasturelands as an individual and social response to economic conditions during the research period. The forecast for 2041 reflected the trends observed in the previous period, with the greatest changes witnessing an increase in urban areas and a decrease in areas of arable land. It was also found that the effect of LULC changes on spatio-temporal patterns in the Oplenac wine-producing area did not have a major impact on soil loss, meaning this area, with its good agro-climatic characteristics, is suitable for the intensification of agricultural production.     

Modeling land use/land cover change using remote sensing and geographic information systems: case study of the Seyhan Basin,Turkey

Land use and land cover (LULC) changes affect several natural environmental factors, including soil erosion, hydrological balance, biodiversity, and the climate, which ultimately impact societal well-being. Therefore, LULC changes are an important aspect of land management. One method used to analyze LULC changes is the mathematical modeling approach. In this study, Cellular Automata and Markov Chain (CA-MC) models were used to predict the LULC changes in the Seyhan Basin in Turkey that are likely to occur by 2036. Satellite multispectral imagery acquired in the years 1995, 2006, and 2016 were classified using the object-based classification method and used as the input data for the CA-MC model. Subsequently, the post-classification comparison technique was used to determine the parameters of the model to be simulated. The Markov Chain analyses and the multi-criteria evaluation (MCE) method were used to produce a transition probability matrix and land suitability maps, respectively. The model was validated using the Kappa index, which reached an overall level of 77%. Finally, the LULC changes were mapped for the year 2036 based on transition rules and a transition area matrix. The LULC prediction for the year 2036 showed a 50% increase in the built-up area class and a 7% decrease in the open spaces class compared to the LULC status of the reference year 2016. About an 8% increase in agricultural land is also likely to occur in 2036. About a 4% increase in shrub land and a 5% decrease in forest areas are also predicted.     

Vegetation dynamics, and land use and land cover change in the Bale Mountains, Ethiopia

Shifts in biological communities are occurring at rapid rates as human activities induced global climate change increases. Understanding the effects of the change on biodiversity is important to reduce loss of biodiversity and mass extinction, and to insure the long-term persistence of natural resources and natures’ services. Especially in remote landscapes of developing countries, precise knowledge about on-going processes is scarce. Here we apply satellite imagery to assess spatio-temporal land use and land cover change (LULCC) in the Bale Mountains for a period of four decades. This study aims to identify the main drivers of change in vegetation patterns and to discuss the implications of LULCC on spatial arrangements and trajectories of floral communities. Remote sensing data acquired from Landsat MSS, Landsat ETM + and SPOT for four time steps (1973, 1987, 2000, and 2008) were analyzed using 11 LULC units defined based on the dominant plant taxa and cover types of the habitat. Change detection matrices revealed that over the last 40?years, the area has changed from a quite natural to a more cultural landscape. Within a representative subset of the study area (7,957.5?km^?2), agricultural fields have increased from 1.71% to 9.34% of the total study area since 1973. Natural habitats such as upper montane forest, afroalpine grasslands, afromontane dwarf shrubs and herbaceous formations, and water bodies also increased. Conversely, afromontane grasslands have decreased in size by more than half (going from 19.3% to 8.77%). Closed Erica forest also shrank from 15.0% to 12.37%, and isolated Erica shrubs have decreased from 6.86% to 5.55%, and afroalpine dwarf shrubs and herbaceous formations reduced from 5.2% to 1.56%. Despite fluctuations the afromontane rainforest (Harenna forest), located south of the Bale Mountains, has remained relatively stable. In conclusion this study documents a rapid and ecosystem-specific change of this biodiversity hotspot due to intensified human activities (e.g., deforestation, agriculture, infrastructure expansion). Specifically, the ecotone between the afromontane and the afroalpine area represent a “hotspot of biodiversity loss” today. Taking into consideration the projections of regional climate warming and modified precipitation regimes, LULCC can be expected to become even more intensive in the near future. This is likely to impose unprecedented pressures on the largely endemic biota of the area.     

Change vector analysis to categorise land cover change processes using the tasselled cap as biophysical indicator

The continuous extraction of wood and the conversion of forest to small- and large-scale agricultural parcels is rapidly changing the land cover of the mount Cameroon region. The changes occur at varying spatial scales most often not more than 2ha for the small-scale subsistence farms and above 10ha for the extensive agricultural plantations of cocoa and palm. Given the importance of land use and land cover data in conservation planning, accurate and efficient techniques to provide up-to-date change information are required. A number of techniques for realising the detection of land cover dynamics using remotely sensed imagery have been formulated, tested and assessed with the results varying with respect to the change scenario under investigation, the information required and the imagery applied. In this study the Change Vector Analysis (CVA) technique was implemented on multitemporal multispectral Landsat data from the Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) sensors to monitor the dynamics of forest change in the mount Cameroon region. CVA was applied to multi-temporal data to compare the differences in the time-trajectory of the tasseled cap greenness and brightness for two successive time periods - 1987 and 2002. The tasseled cap was selected as biophysical indicator because it optimises the data viewing capabilities of vegetation, representing the basic types of land cover - vegetation, soil and water. Classes were created arbitrarily to predict the technique's potential in monitoring forest cover changes in the mount Cameroon region. The efficiency of the technique could not be fully assessed due to the inavailability of sufficient ground truth data. Assessment was based on the establishment of an error matrix of change versus no-change. The overall accuracy was 70%. The technique nevertheless demonstrated immense potentials in monitoring forest cover change dynamics especially when complemented with field studies.     

Trends in land use and land cover change in the protected and communal areas of the Zambezi Region,Namibia

Land management decisions have extensively modified land use and land cover in the Zambezi Region. These decisions are influenced by land tenure classifications, legislation, and livelihoods. Land use and land cover change is an important indicator for quantifying the effectiveness of different land management strategies. However, there has been no evidence on whether protected or communal land tenure is more affected by land use and land cover changes in southern Africa and particularly Namibia. Our study attempted to fill this gap by analyzing the relationship between land use and land cover change and land tenure regimes stratified according to protected and communal area in the Zambezi Region. Multi-temporal Landsat TM and ETM+ imagery were used to determine the temporal dynamics of land use and land cover change from 1984 to 2010. The landscape showed distinctive modifications over the study period; broad trends include the increase in forest land after 1991. However, changes were not uniform across the study areas. Two landscape development stages were deduced: (1) 1984–1991 represented high deforestation and gradual increase in shrub land; (2) 1991–2000 and 2000–2010 represented lower deforestation and slower agropastoral expansion. The results further show clear patterns of the dynamics, magnitude, and direction of land use and land cover change by tenure regime. The study concluded that land tenure has a direct impact on land use and land cover, since it may restrict some activities carried out on the land in the Zambezi Region.     

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.     

Assessing post-industrial land cover change at the Pine Point Mine,NWT, Canada using multi-temporal Landsat analysis and landscape metrics

This study investigates land cover change near the abandoned Pine Point Mine in Canada’s Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine’s closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.     

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.     

Monitoring conservation effectiveness in a global biodiversity hotspot: the contribution of land cover change assessment

Tropical forests, which play critical roles in global biogeochemical cycles, radiation budgets and biodiversity, have undergone rapid changes in land cover in the last few decades. This study examines the complex process of land cover change in the biodiversity hotspot of Western Ghats, India, specifically investigating the effects of conservation measures within the Indira Gandhi Wildlife Sanctuary. Current vegetation patterns were mapped using an IRS P6 LISS III image and this was used together with Landsat MSS data from 1973 to map land cover transitions. Two major and divergent trends were observed. A dominant degradational trend can be attributed to agricultural expansion and infrastructure development while a successional trend, resulting from protection of the area, showed the resilience of the system after prolonged disturbances. The sanctuary appears susceptible to continuing disturbances under the current management regime but at lower rates than in surrounding unprotected areas. The study demonstrates that remotely sensed land cover assessments can have important contributions to monitoring land management strategies, understanding processes underpinning land use changes and helping to inform future conservation strategies.     

Modeling the effect of land use/land cover on nitrogen,phosphorous and dissolved oxygen loads in the Velhas River using the concept of exclusive contribution area

Non-point source water pollution is a major problem in most parts of the world, but is also very difficult to quantify and control since it is not easily separated from point sources and can theoretically originate from the whole watershed. In this article, we evaluate the relationship between land use and land cover and four water pollution parameters in a watershed in Southeast Brazil. The four parameters are nitrate, total ammonia nitrogen, total phosphorous, and dissolved oxygen. To help concentrate on non-point source pollution, only data from the wet seasons of the time period (2001–2013) were analysed, based on the fact that precipitation causes runoff which is the main cause of diffuse pollution. The parameters measured were transformed into loads, which were in turn associated with an exclusive contribution area, so that every measuring station could be considered independent. Analyses were also performed on riparian zones of different widths to verify if the effect of the land cover on the water quality of the stream decreases with the increased distance. Pearson correlation coefficients indicate that urban areas and agriculture/pasture tend to worsen water quality (source). Conversely, forest and riparian areas have a reducing effect on pollution (sink). The best results were obtained for total ammonia nitrogen and dissolved oxygen using the whole exclusive contribution areas with determination coefficients better than R²≈0.8. Nitrate and total phosphorous did not produce valid models. We suspect that the transformation delay from total ammonia nitrogen to nitrate might be an important factor for the poor result for this parameter. For phosphorous, we think that the phosphorous sink in the bottom sediment might be the most limiting factor explaining the failure of our models.     

Retrieval of total suspended matter (TSM) and chlorophyll-a (Chl-a) concentration from remote-sensing data for drinking water resources

The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. Water sampling works were conducted on 15 July 2007 and 13 September 2008 concurrent with the Indian Remote-Sensing Satellite (IRS-P6) overpass of the Shitoukoumen Reservoir. Both empirical regression and back-propagation artificial neural network (ANN) models were established to estimate Chl-a and TSM concentration with both in situ and satellite-received radiances signals. It was found that empirical models performed well on the TSM concentration estimation with better accuracy (R ² = 0.94, 0.91) than their performance on Chl-a concentration (R ² = 0.62, 0.75) with IRS-P6 imagery data, and the models accuracy marginally improved with in situ spectra data. Our results indicated that the ANN model performed better for both Chl-a (R ² = 0.91, 0.82) and TSM (R ² = 0.98, 0.94) concentration estimation through in situ collected spectra; the same trend followed for IRS-P6 imagery data (R ² = 0.75 and 0.90 for Chl-a; R ² = 0.97 and 0.95 for TSM). The relative root mean square errors (RMSEs) from the empirical model for TSM (Chl-a) were less than 15% (respectively 27.2%) with both in situ and IRS-P6 imagery data, while the RMSEs were less than 7.5% (respectively 18.4%) from the ANN model. Future work still needs to be undertaken to derive the dynamic characteristic of Shitoukoumen Reservoir water quality with remotely sensed IRS-P6 or Landsat-TM data. The algorithms developed in this study will also need to be tested and refined with more imagery data acquisitions combined with in situ spectra data.     

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.