Effects of land cover changes induced by large physical disturbances on hydrological responses in Central Taiwan

This study analyzes the significant impacts of typhoons and earthquakes on land cover change and hydrological response. The occurrence of landslides following typhoons and earthquakes is a major indicator of natural disturbance. The hydrological response of the Chenyulan watershed to land use change was assessed from 1996 to 2005. Land use changes revealed by seven remote images corresponded to typhoons and a catastrophic earthquake in central Taiwan. Hydrological response is discussed as the change in quantities and statistical distributions of hydrological components. The land cover change results indicate that the proportion of landslide relative to total area increased to 6.1% after the Chi-Chi earthquake, representing the largest increase during the study period. The study watershed is dominated by forest land cover. Comparisons of hydrological components reveal that the disturbance significantly affects base flow and direct runoff. The hydrological modeling results demonstrate that the change in forest area correlates with the variation of base flow and direct runoff. Base flow and direct runoff are sensitive to land use in discussions of distinction. The proposed approach quantifies the effect of typhoons and earthquakes on land cover changes.     

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.     

Monitoring and assessment of land use status by GIS

The objectives of this study were to assess land suitability andto monitor the spatial and temporal changes in land use types (LUTs)by using GIS. The study was conducted in an irrigated area of 920ha, located in the East Mediterranean region of Turkey. Archiveddata of LUTs were utilized. Data analysis was conducted by usingArcInfo and ArcView GIS softwares. The land characteristics werecompared with land requirements of present LUTs by taking intoaccount the land evaluation results. Three major soil series andtwelve different LUTs were identified. Corn and citrus were themost planted LUTs in the assessment period. Generated mapsdemonstrated how LUTs changed spatially and temporally. Most LUTswere clustered in certain areas indicating that farmer'sselection of LUTs was affected by their habits and neighbor'sbehavior. Land suitability assessment results indicated thatCanakci and Mursel soil series were found to be highly suitable forall LUTs while Arikli soil series was determined to be moderately suitablecitrus, vegetables and watermelon. Citrus plantationmaps overlaid on soil series maps demonstrated that the citrushas not been planted completely on suitable areas. Landsuitability assessment showed that citrus plantation in Arikliseries would result in 40% yield loss and 58% of land is notused at its potential.     

Application of integrated GIS and multimedia modeling on NPS pollution evaluation

In Taiwan, nonpoint source (NPS) pollution is one of the major causes of the impairment of surface waters. I-Liao Creek, located in southern Taiwan, flows approximately 90 km and drains toward the Kaoping River. Field investigation results indicate that NPS pollution from agricultural activities is one of the main water pollution sources in the I-Liao Creek Basin. Assessing the potential of NPS pollution to assist in the planning of best management practice (BMP) is significant for improving pollution prevention and control in the I-Liao Creek Basin. In this study, land use identification in the I-Liao Creek Basin was performed by properly integrating the skills of geographic information system (GIS) and global positioning system (GPS). In this analysis, 35 types of land use patterns in the watershed area of the basin are classified with the aid of Erdas Imagine process system and ArcView GIS system. Results indicate that betel palm farms, orchard farms, and tea gardens dominate the farmland areas in the basin, and are scattered around on both sides of the river corridor. An integrated watershed management model (IWMM) was applied for simulating the water quality and evaluating NPS pollutant loads to the I-Liao Creek. The model was calibrated and verified with collected water quality and soil data, and was used to investigate potential NPS pollution management plans. Simulated results indicate that NPS pollution has significant contributions to the nutrient loads to the I-Liao Creek during the wet season. Results also reveal that NPS pollution plays an important role in the deterioration of downstream water quality and caused significant increase in nutrient loads into the basin's water bodies. Simulated results show that source control, land use management, and grassy buffer strip are applicable and feasible BMPs for NPS nutrient loads reduction. GIS system is an important method for land use identification and waste load estimation in the basin. Linking the information of land utilization with the NPS pollution simulation model may further provide essential information of potential NPS pollution for all subregions in the river basin. Results and experience obtained from this study will be helpful in designing the watershed management and NPS pollution control strategies for other similar river basins.     

Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey)

Various natural hazards such as landslides, avalanches, floods and debris flows can result in enormous property damages and human casualties in Eastern Black Sea region of Turkey. Mountainous topographic character and high frequency of heavy rain are the main factors for landslide occurrence in Ardesen, Rize. For this reason, the main target of the present study is to evaluate the landslide hazards using a sequence of historical aerial photographs in Ardesen (Rize), Turkey, by Photogrammetry and Geographical Information System (GIS). Landslide locations in the study area were identified by interpretation of aerial photographs dated in 1973 and 2002, and by field surveys. In the study, the selected factors conditioning landslides are lithology, slope gradient, slope aspect, vegetation cover, land class, climate, rainfall and proximity to roads. These factors were considered as effective on the occurrence of landslides. The areas under landslide threat were analyzed and mapped considering the landslide conditioning factors. Some of the conditioning factors were investigated and estimated by employing visual interpretation of aerial photos and topographic data. The results showed that the slope, lithology, terrain roughness, proximity to roads, and the cover type played important roles on landslide occurrence. The results also showed that degree of landslides was affected by the number of houses constructed in the region. As a consequence, the method employed in the study provides important benefits for landslide hazard mitigation efforts, because a combination of both photogrammetric techniques and GIS is presented.     

Landslides susceptibility change over time according to terrain conditions in a mountain area of the tropic region

Susceptibility to landslides in mountain areas results from the interaction of various factors related to relief formation and soil development. The assessment of landslide susceptibility has generally taken into account individual events, or it has been aimed at establishing relationships between landslide-inventory maps and maps of environmental factors, without considering that such relationships can change in space and time. In this work, temporal and space changes in landslides were analysed in six different combinations of date and geomorphological conditions, including two different geological units, in a mountainous area in the north-centre of Venezuela, in northern South America. Landslide inventories from different years were compared with a number of environmental factors by means of logistic regression analysis. The resulting equations predicted landslide susceptibility from a range of geomorphometric parameters and a vegetation index, with diverse accuracy, in the study area. The variation of the obtained models and their prediction accuracy between geological units and dates suggests that the complexity of the landslide processes and their explanatory factors changed over space and time in the studied area. This calls into question the use of a single model to evaluate landslide susceptibility over large regions.     

Investigation of landslide potential parameters on Zonguldak–Ereğli Highway and adverse effects of landslides in the region

Landslides are natural phenomena in the same class of natural disasters as earthquakes, floods, hurricanes, erosion, and volcanic eruptions that adversely affect human lives and property. Owing to their widespread occurrence, landslides are easily visible and able to be partially understood by people witnessing them. Nevertheless, to comprehend the detail of their formation and determine their potential, it is necessary to undertake geodetic, geological, and geophysical measurements in regions prone to landslides. By analyzing these measurements, it is possible to better ascertain those regions predisposed to landslides and thus provide the means to prevent loss of life and property. The city of Zonguldak, situated in the Western Black Sea region of Turkey, has a high occurrence of landslides owing to its harsh topography with rugged and steep slopes and rainfall in almost every season. Furthermore, the diurnal temperature ranging up to 10 °C in all seasons, especially in winter, plays a crucial role in rock disintegration in this region. Other factors damage ground composition and trigger landslides, such as underground mining operations, road construction that collapses rocky hills using explosives, and excavation works in steep terrain for building construction. This study gives a detailed account of the causes and adverse effects of landslides and their parameters through examples of landslide occurrences in the region, together with the results and analyses of two periods of geodetic measurements conducted on the Zonguldak–Ere?li Highway in Il?ksu district.     

结合GIS探析吉林省东部生态建设分区战略

以地理信息系统(GIS)为技术支持,以生态系统组成和空间结构为指标,对吉林省东部的生态建设分区进行研究。借助AreView分析工具,从吉林省2000年的1:100000土地利用数字化地图中,提取东部山区土地利用数据,进行生态系统的结构研究,并在此基础上划分出东部山区生态系统的生态经济类型,为土地资源的有效利用和生产力的合理布局提供决策支持。     

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.     

Using Resource Economics to Anticipate Forest Land Use Change in the U.S. Mid-Atlantic Region

Demands for forest, farm, and developed land are evolving in the U.S. mid-Atlantic region. The demand for land in developed uses, as well as demands for various forest and farm products are changing in response to population growth, demographic shifts, and market forces. As demand factors change so do relative land values. Land area in future forest, farm, and developed uses may shift as landowners re-evaluate relative net benefits from land use alternatives. This study examines the effects of various land demand and supply factors on the determination of land use patterns in the mid-Atlantic region. Driving variables include costs and benefits from various uses, population density, and measures of land quality. Model parameters are estimated using a binomial logit procedure. Results from the study are used to estimate proportions of forest area on a county by county basis. Simulated forest landscapes under hypothetical future conditions are prepared and illustrated using geographic information system (GIS) techniques.     

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.     

Linking satellite and field survey data,through the use of gis,as implemented in Great Britain in the Countryside Survey 1990 project

The Institute of Terrestrial Ecology (ITE) has been studying land use and the effects of land use on ecology for two decades. A series of national field surveys have been undertaken by the Land Use Section of ITE since 1978, the most recent being Countryside Survey 1990 (CS1990). The three-year project brought together field survey and remote sensing data which were analyzed using Geographical Information Systems (GIS). National and regional land-cover patterns were described and changes estimated.The data collected by the field survey part of CS1990 recorded stratified samples based on a land classification. Thematic maps for surveyed 1-km squares covered physiography, agriculture and semi-natural vegetation, forestry, structures and boundaries. The same sites were surveyed in 1984 and 1990 with 14 000 digital maps produced describing both years. GIS was used to generate stock figures for each year, and overlay allowed change between survey dates to be estimated.GIS was used to compare data collected from both field survey and satellite imagery so that both sets of information could be qualified when expressed as national figures.This paper describes the historical development of the ITE Land Classification, examines the way in which data were collected for surveys, with particular reference to Countryside Survey 1990, and shows how satellite and field survey data can be linked through GIS.     

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.     

Vegetation recovery patterns assessment at landslides caused by catastrophic earthquake: A case study in central Taiwan

The catastrophic earthquake, 7.3 on the Richter scale, occurred on September 21, 1999 in Central Taiwan. Much of standing vegetation on slopes was eliminated and massive, scattered landslides were induced at the Jou-Jou Mountain area of the Wu-Chi basin in Nantou County. We evaluated three methods for assessing landslide hazard and vegetation recovery conditions. (1) Self-organizing map (SOM) neural network coupled with fuzzy technique was used to quickly extract the landslide. (2) The NDVI-based vegetation recovery index derived from multi-temporal SPOT satellite images was used to evaluate vegetation recovery rate in the denudation sites. (3) The spatial distribution index (SDI) based on land-cover topographic location was employed to analyze vegetation recovery patterns, including the invading, surviving and mixed patterns at the Jou-Jou Mountain area. On September 27, 1999, there were 849.20 ha of landslide area extracted using the self-organizing map and fuzzy technique combined model. After six years of natural vegetation succession, the landslide has gradually restored, and vegetation recovery rate reached up to 86%. On-site observation shows that many native pioneer plants have invaded onto the denudation sites even if disturbed by several typhoons. Two native surviving plants, Arundo formosana Hack and Pinus taiwanensis Hayata, play a vital role in natural vegetation succession in this area, especially for the sites on ridgeline and steep slopes.     

Using the analytical hierarchy process to assess the environmental vulnerabilities of basins in Taiwan

Every year, Taiwan endures typhoons and earthquakes; these natural hazards often induce landslides and debris flows. Therefore, watershed management strategies must consider the environmental vulnerabilities of local basins. Because many factors affect basin ecosystems, this study applied multiple criteria analysis and the analytical hierarchy process (AHP) to evaluate seven criteria in three phases (geographic phase, hydrologic phase, and societal phase). This study focused on five major basins in Taiwan: the Tan-Shui River Basin, the Ta-Chia River Basin, the Cho-Shui River Basin, the Tseng-Wen River Basin, and the Kao-Ping River Basin. The objectives were a comprehensive examination of the environmental characteristics of these basins and a comprehensive assessment of their environmental vulnerabilities. The results of a survey and AHP analysis showed that landslide area is the most important factor for basin environmental vulnerability. Of all these basins, the Cho-Shui River Basin in central Taiwan has the greatest environmental vulnerability.     

Assessing land take by urban development and its impact on carbon storage: Findings from two case studies in Italy

Land take due to urbanization triggers a series of negative environmental impacts with direct effects on quality of life for people living in cities. Changes in ecosystem services are associated with land take, among which is the immediate C loss due to land use conversion. Land use change monitoring represents the first step in quantifying land take and its drivers and impacts. To this end, we propose an innovative methodology for monitoring land take and its effects on ecosystem services (in particular, C loss) under multi-scale contexts. The devised approach was tested in two areas with similar sizes, but different land take levels during the time-span 1990–2008 in Central Italy (the Province of Rome and the Molise Region). The estimates of total coverage of built up areas were calculated using point sampling. The area of the urban patches including each sampling point classified as built up areas in the year 1990 and/or in the year 2008 is used to estimate total abundance and average area of built up areas. Biophysical and economic values for carbon loss associated with land take were calculated using InVEST.Although land take was 7–8 times higher in the Province of Rome (from 15.1% in 1990 to 20.4% in 2008) than in Molise region, our findings show that its relative impact on C storage is higher in the latter, where the urban growth consistently affects not only croplands but also semi-natural land uses such as grasslands and other wooded lands. The total C loss due to land take has been estimated in 1.6 million Mg C, corresponding to almost 355 million €.Finally, the paper discusses the main characteristics of urban growth and their ecological impact leading to risks and challenges for future urban planning and land use policies.     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

Assessment for Salinized Wasteland Expansion and Land Use Change Using GIS and Remote Sensing in the West Part of Northeast China

Due to human impact under climatic variations, western part of Northeast China has suffered substantial land degradation during past decades. This paper presents an integrated study of expansion process of salinized wasteland in Da’an County, a typical salt-affected area in Northeast China, by using Geographic Information Systems (GIS) and remote sensing. The study explores the temporal and spatial characteristics of salinized wasteland expansion from 1954 to 2004, and land use/cover changes during this period. During the past 50 years, the salinized wasteland in study area have increased by 135,995 ha, and in 2004 covers 32.31% of the total area, in the meantime grassland has decreased by 104,697 ha and in 2004 covers only 13.15% of the study area. Grasslands, croplands and swamplands were found the three main land use types converted into salinized wasteland. Land use/cover changes shows that between 1954 and 2004, 48.6% of grasslands, 42.5% of swamplands, and 14.1% of croplands were transformed into salinized wasteland, respectively. Lastly, the major factors influencing salinized wasteland expansion and land use/cover changes were also explored. In general, climatic factors supplied a potential environment for soil salinization. Human-related factors, such as policy, population, overgrazing, and intensified and unreasonable utilization of land and water resources are the main causes of salinized wasteland expansion.     

A land use regression model for predicting ambient fine particulate matter across Los Angeles, CA

Land use regression (LUR) models have been used successfully for predicting local variation in traffic pollution, but few studies have explored this method for deriving fine particle exposure surfaces. The primary purpose of this method is to develop a LUR model for predicting fine particle or PM(2.5) mass over the five county metropolitan statistical area (MSA) of Los Angeles. PM(2.5) includes all particles with diameter less than or equal to 2.5 microns. In the Los Angeles MSA, 23 monitors of PM(2.5) were available in the year 2000. This study uses GIS to integrate data regarding land use, transportation and physical geography to derive a PM(2.5) dataset covering Los Angeles. Multiple linear regression was used to create the model for predicting the PM(2.5) surface. Our parsimonious model explained 69% of the variance in PM(2.5) with three predictors: (1) traffic density within 300 m, (2) industrial land area within 5000 m, and (3) government land area within 5000 m of the monitoring site. These results suggest the LUR method can refine exposure models for epidemiologic studies in a North American context.     

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.