Resource Use Dynamics and Land-Cover Change in Ang Nhai Village and Phou Phanang National Reserve Forest, Lao PDR

This study integrated aerial photographs from 1952, 1981, and 1998, and a satellite image from 2000 with oral histories and socioeconomic surveys to assess changes in forest and land cover in Ang Nhai village, Laos. The study documents the history of resource use and changes in household access to resources in the village. Three distinctive trends were observed in terms of forest and land cover—forest degradation, deforestation, and regeneration. Project results suggest that land and forest cover change dynamically under different circumstances. The case study also points out that integration into the market economy can induce intensification of unused lowland areas, while removing pressures from upland areas previously used for supplementing agricultural production. In addition, the creation of a national reserve forest to restrict local access and forest use was an ineffective tool for regulating encroachment and logging activities.     

Changes in Determinants of Deforestation and Forest Degradation in Popa Mountain Park, Central Myanmar

Implementing effective conservation requires an understanding of factors affecting deforestation and forest degradation. Previous studies have investigated factors affecting deforestation, while few studies have examined the determinants of both of deforestation and forest degradation for more than one period. To address this gap, this study examined factors influencing deforestation and forest degradation during 1989–2000 and 2000–2005 in the Popa Mountain Park, Myanmar. We applied multinomial logistic regression (MNL) using land cover maps derived from Landsat images as the dependent variables as well as spatial and biophysical factors as the independent variables. The MNL models revealed influences of the determinants on deforestation and forest degradation changes over time. For example, during 1989–2000, deforestation from closed forest was positively correlated to the distance from the park boundary and was negatively correlated with distance from villages, roads, the park circular road, slope, western aspect and elevation. On the other hand, during 2000–2005, deforestation of closed forest was positively correlated with distance from villages, roads, the park circular road, slope and western aspect, and negatively correlated with distance from the park boundary and elevation. Similar scenarios were observed for the deforestation of open forest and forest degradation of closed forest. The study also found most of the determinants influenced deforestation and forest degradation differently. The changes in determinants of deforestation and forest degradation over time might be attributable to the general decrease in resource availability and to the effect of conservation measures conducted by the park.     

Monitoring Parks Through Remote Sensing: Studies in Nepal and Honduras

The effectiveness of parks as management regimes is hotly contested. Much of the current discussion centered around comparisons of management regimes can be traced to a dearth of cross-site quantitative evaluations. Remote sensing provides a particularly effective tool for this purpose, yet analysis of remotely sensed data requires fieldwork to interpret human activities and the socioeconomic and political contexts that relate to land cover change. This paper examines the effect of establishment of the Celaque National Park, Honduras, and the Royal Chitwan National Park buffer zone, Nepal, on limiting deforestation. In Celaque, the park itself has been largely successful in maintaining forest cover. However, recent changes in land use patterns have led to increasing pressure on the park boundaries, exacerbated by the lack of involvement of local residents. In the Royal Chitwan National Park, in contrast, participatory approaches towards co-management have been implemented over the past decade in the park buffer zone. With significant incomes derived from ecotourism, complete protection of the buffer zone forest has been adopted, leading to significant regrowth of tree cover. However, local decision-making power is limited, and buffer zone management has largely proven successful due to the investment and support provided by international donor agencies. These two case studies demonstrate the utility of remote sensing and Geographical Information Systems analysis in providing a spatiotemporal perspective for assessing management policies. They also demonstrate the importance of fieldwork to provide a nuanced understanding of the socioeconomic and institutional conditions affecting the outcomes of forest management regimes.     

Effects of climate and land use changes on groundwater resources in coastal aquifers

To estimate the freshwater loss in coastal aquifers due to salinisation, a numerical model based on the sharp interface assumption has been introduced. The developed methodology will be useful in areas where limited hydrological data are available. This model will elaborate on the changes in fresh groundwater loss with respect to climate change, land use pattern and hydrologic soil condition. The aridity index has been introduced to represent the variations in precipitation and temperature. The interesting finding is that the deforestation leads to increase groundwater recharge in arid areas, because deforestation leads to reduce evapotranspiration even though it favors runoff. The combined climate and land use scenarios show that when the aridity index is less than 60, the agricultural lands give higher groundwater recharge than other land use patterns for all hydrologic soil conditions. The calculated recharge was then used to estimate the freshwater-saltwater interface and percentage of freshwater loss due to salinity intrusion. We found that in arid areas, the fresh groundwater loss increases as the percentage of forest cover increases. The combined effects of deforestation and aridity index on fresh groundwater loss show that deforestation causes an increase in the recharge and existing fresh groundwater resource in areas having low precipitation and high temperature (arid climates).     

Impacts of changes in land use and fragmentation patterns on Atlantic coastal forests in northern Spain

Changes in forested landscapes may have important consequences for ecosystem services and biodiversity conservation. In northern Spain, major changes in land use occurred during the second half of the 20th century, but their impacts on forests have not been quantified. We evaluated the dynamics of landscape and forest distribution patterns between 1957 and 2003 in Fragas do Eume Natural Park (northwestern Spain). We used orthoimages and a set of standard landscape metrics to determine transitions between land cover classes and to examine forest distribution patterns. Eucalypt plantations showed the greatest increase in area (197%) over time. Furthermore, transitions to eucalypt plantations were found in all major land cover classes. Forest showed a net decline of 20% in total area and represented 30% of the landscape area in 2003. Forest losses were mainly due to eucalypt plantations and the building of a water reservoir, while forest gains were due to increases in shrubland, meadows and cultivated fields which had been recolonised. Forest patch size and core area decreased, and edge length increased over time. In turn, increases were obtained in mean distance between forest patches, and in adjacency to eucalypt plantations and to a water reservoir. These results suggest an increase in forest fragmentation from 1957 to 2003, as well as a change in the nature of the habitat surrounding forest patches. This study shows that land use changes, mostly from eucalypt plantation intensification, negatively affected forested habitats, although some regeneration was ongoing through ecological succession from land abandonment.     

Change in vegetation cover in East Timor, 1989–1999

Forest resources play a key role and provide many basic needs to communities in developing economies. To assess the patterns of vegetation cover change, as a corollary of resource utilization, satellite imagery, ground truth data, and image processing techniques can be useful. This article is concerned with identifying change in major vegetation types in East Timor between 1989 and 1999, using Landsat Thematic Mapper data. The results highlight a significant level of deforestation and decline in foliage cover. All major vegetation cover types declined from 1989 to 1999, and there was a sizeable increase in degraded woodlands. This decline has had considerable impact on the livelihoods of rural and urban communities. Causes for these changes include: economic exploitation of abundant resources; and implications of transmigration policies implemented during Indonesian rule, resulting in increased competition for land and woodland resources. As the new nation of Timor‐Leste establishes itself, it must consider its current stock and distribution of natural capital to ensure that development efforts are geared towards sustainable outcomes. Without the knowledge of historical patterns of resource consumption, development efforts may, unwittingly, lead to continuing decline in forest resources.     

Regionalization of Landscape Pattern Indices Using Multivariate Cluster Analysis

Regionalization, or the grouping of objects in space, is a useful tool for organizing, visualizing, and synthesizing the information contained in multivariate spatial data. Landscape pattern indices can be used to quantify the spatial pattern (composition and configuration) of land cover features. Observable patterns can be linked to underlying processes affecting the generation of landscape patterns (e.g., forest harvesting). The objective of this research is to develop an approach for investigating the spatial distribution of forest pattern across a study area where forest harvesting, other anthropogenic activities, and topography, are all influencing forest pattern. We generate spatial pattern regions (SPR) that describe forest pattern with a regionalization approach. Analysis is performed using a 2006 land cover dataset covering the Prince George and Quesnel Forest Districts, 5.5 million ha of primarily forested land base situated within the interior plateau of British Columbia, Canada. Multivariate cluster analysis (with the CLARA algorithm) is used to group landscape objects containing forest pattern information into SPR. Of the six generated SPR, the second cluster (SPR2) is the most prevalent covering 22% of the study area. On average, landscapes in SPR2 are comprised of 55.5% forest cover, and contain the highest number of patches, and forest/non-forest joins, indicating highly fragmented landscapes. Regionalization of landscape pattern metrics provides a useful approach for examining the spatial distribution of forest pattern. Where forest patterns are associated with positive or negative environmental conditions, SPR can be used to identify similar regions for conservation or management activities.     

Predicting the distribution of ground beetle species (Coleoptera, Carabidae) in Britain using land cover variables

Predictions of plant and animal species distributions are important for conservation and for the assessment of large-scale ecosystem change. Land cover data are becoming more widely available for use in land management and conservation. We use a logistic regression modelling approach to investigate the utility of these data for modelling. The relationship between the distribution of 137 British ground beetles species and land cover was investigated using data from 1,687 10 km national grid squares. Land cover data were simplified using ordination and the axes used as predictors in logistic regression with presence absence data for individual beetle species as response variables. Significant regression models were generated for all species with first and second axis scores. The amounts of variation explained by models were generally low, but predictions derived from models generally matched the known distributions of the species in Britain. Species with coastal preferences were poorly modelled and predicted to occur throughout lowland Britain whilst a number of species occurring in southern Britain were predicted to occur into Scotland. A validation exercise comparing model predictions with new data from a survey of 59 10 km(2) produced mixed results with the distribution of grassland species being better predicted than riverine species. Jack-knifing was used to assess the robustness of models for four species which differed in their apparent responses to the land cover variables. Methods for improving the predictive power of these models and their potential for use in assessing the impact of global climate change are discussed.     

Socioeconomic Drivers of Deforestation in the Northern Ecuadorian Amazon

Investigations of land use/land cover (LULC) change and forest management are limited by a lack of understanding of how socioeconomic factors affect land use. This lack also constrains the predictions of future deforestation, which is especially important in the Amazon basin, where large tracts of natural forest are being converted to managed uses. Research presented in this article was conducted to address this lack of understanding. Its objectives are (a) to quantify deforestation in the Northern Ecuadorian Amazon (NEA) during the periods 1986–1996 and 1996–2002; and (b) to determine the significance and magnitude of the effects of socioeconomic factors on deforestation rates at both the parroquia (parish) and finca (farm) levels. Annual deforestation rates were quantified via satellite image processing and geographic information systems. Linear spatial lag regression analyses were then used to explore relationships between socioeconomic factors and deforestation. Socioeconomic factors were obtained, at the finca level, from a detailed household survey carried out in 1990 and 1999, and at the parroquia level from data in the 1990 and 2001 Ecuadorian censuses of population. We found that the average annual deforestation rate was 2.5% and 1.8%/year for 1986–1996 and 1996–2002, respectively. At the parroquia level, variables representing demographic factors (i.e., population density) and accessibility factors (i.e., road density), among others, were found to be significantly related to deforestation. At the farm level, the factors related to deforestation were household size, distance by road to main cities, education, and hired labor. The findings of this research demonstrate both the severity of deforestation in the Northern Ecuadorian Amazon and the array of factors affecting deforestation in the tropics.     

Decision Tree Algorithm for Detection of Spatial Processes in Landscape Transformation

The conversion of landscapes by human activities results in widespread changes in landscape spatial structure. Regardless of the type of land conversion, there appears to be a limited number of common spatial configurations that result from such land transformation processes. Some of these configurations are considered optimal or more desirable than others. Based on pattern geometry, we define ten processes responsible for pattern change: aggregation, attrition, creation, deformation, dissection, enlargement, fragmentation, perforation, shift, and shrinkage. A novelty in this contribution is the inclusion of transformation processes causing expansion of the land cover of interest. Consequently, we propose a decision tree algorithm that enables detection of these processes, based on three parameters that have to be determined before and after the transformation of the landscape: area, perimeter length, and number of patches of the focal landscape class. As an example, the decision tree algorithm is applied to determine the transformation processes of three divergent land cover change scenarios: deciduous woodland degradation in Cadiz Township (Wisconsin, USA) 1831–1950, canopy gap formation in a terra firme rain forest at the Tiputini Biodiversity Station (Amazonian Ecuador) 1997–1998, and forest regrowth in Petersham Township (Massachusetts, USA) 1830–1985. The examples signal the importance of the temporal resolution of the data, since long-term pattern conversions can be subdivided in stadia in which particular pattern components are altered by specific transformation processes.     

Jamaica's disappearing forests: physical and human aspects

Jamaica is a small island that is losing its forest cover at a rapid rate. Due to the dependency of its largely poor population on the many services and functions its forests provide, this loss threatens to have substantial socioeconomic and ecological consequences for the country. Despite these basic facts, the problem of Jamaican deforestation has received very little attention from the scientific community. This article presents results of an island-wide, satellite-based study of forest change for Jamaica for the period 1987–1992, which was supplemented by a field trip to the island in 1999 to assess the overall accuracy of the estimate. Landsat MSS images, which are available only up until 1992, have proved to be an invaluable and cost-effective resource for mapping forest change in the tropics, particularly in large areas. A supervised classification indicates that Jamaica experienced an average annual deforestation rate of 3.9% for this period, a figure higher than existing estimates based on partial ground surveys but lower than the FAO's 1990 Tropical Forest Assessment of 5.3% for 1981–1990. Deforestation estimates for Jamaica's 14 parishes are also presented, based on the integration of satellite-derived forest classification maps with a parish administrative boundaries map of the island in a GIS. A correlation analysis between parish deforestation estimates and socioeconomic and land use/quality indicators derived from official sources suggests that deforestation is occurring most rapidly in highly populated areas possessing large numbers of small farmers who live and work under resource-poor conditions. By providing a sense of the magnitude of and main forest loss hotspots, it is hoped that these national and subnational level forest estimates will draw scientific attention to the problem of deforestation on the island. In addition, the socioeconomic analysis may provide policy-makers and planners with some sense of the relative contribution of underlying driving process in this deforestation as a first step toward the creation of effective social programs to combat the problem.     

Forecasting the Effects of Land-Use Change on Forest Rodents in Indiana

Forest cover in the upper Wabash River basin in Indiana was fragmented due to agricultural conversion beginning more than 175 years ago. Currently, urban expansion is an important driver of land-use change in the basin. A land transformation model was applied to the basin to forecast land use from 2000 to 2020. We assessed the effect of this projected land-use change scenario on five forest rodent species at three scales: using occupancy models at the patch level, proportional occupancy models at the landscape level, and ecologically scaled landscape indices to assess the change in connectivity at the watershed level. At the patch and landscape scales, occupancy models had low predictability but suggest that gray squirrels are most susceptible to land-use change. At the watershed scale, declines in connectivity did not correspond with the decline of forest. This study highlights the importance of map resolution and consideration of matrix elements in constructing forecast models. Unforeseen drivers of land use, such as changing economic incentives, may also have important ramifications.     

Projecting Land-Use Change and Its Consequences for Biodiversity in Northern Thailand

Rapid deforestation has occurred in northern Thailand over the last few decades and it is expected to continue. The government has implemented conservation policies aimed at maintaining forest cover of 50% or more and promoting agribusiness, forestry, and tourism development in the region. The goal of this paper was to analyze the likely effects of various directions of development on the region. Specific objectives were (1) to forecast land-use change and land-use patterns across the region based on three scenarios, (2) to analyze the consequences for biodiversity, and (3) to identify areas most susceptible to future deforestation and high biodiversity loss. The study combined a dynamic land-use change model (Dyna-CLUE) with a model for biodiversity assessment (GLOBIO3). The Dyna-CLUE model was used to determine the spatial patterns of land-use change for the three scenarios. The methodology developed for the Global Biodiversity Assessment Model framework (GLOBIO 3) was used to estimate biodiversity intactness expressed as the remaining relative mean species abundance (MSA) of the original species relative to their abundance in the primary vegetation. The results revealed that forest cover in 2050 would mainly persist in the west and upper north of the region, which is rugged and not easily accessible. In contrast, the highest deforestation was expected to occur in the lower north. MSA values decreased from 0.52 in 2002 to 0.45, 0.46, and 0.48, respectively, for the three scenarios in 2050. In addition, the estimated area with a high threat to biodiversity (an MSA decrease >0.5) derived from the simulated land-use maps in 2050 was approximately 2.8% of the region for the trend scenario. In contrast, the high-threat areas covered 1.6 and 0.3% of the region for the integrated-management and conservation-oriented scenarios, respectively. Based on the model outcomes, conservation measures were recommended to minimize the impacts of deforestation on biodiversity. The model results indicated that only establishing a fixed percentage of forest was not efficient in conserving biodiversity. Measures aimed at the conservation of locations with high biodiversity values, limited fragmentation, and careful consideration of road expansion in pristine forest areas may be more efficient to achieve biodiversity conservation.     

Maintaining the Conservation Value of Shifting Cultivation Landscapes Requires Spatially Explicit Interventions

Fallow vegetation within landscapes dominated by shifting cultivation represents a woody species pool of critical importance with considerable potential for biodiversity conservation. Here, through the analysis of factors that influence the early stages of fallow vegetation regrowth in two contrasting forest margin landscapes in Southern Cameroon, we assessed the impact of current trends of land use intensification and expansion of the cultivated areas, upon the conservation potential of shifting cultivation landscapes. We combined the analysis of plot and landscape scale factors and identified a complex set of variables that influence fallow regrowth processes in particular the characteristics of the agricultural matrix and the distance from forest. Overall we observed a decline in the fallow species pool, with composition becoming increasingly dominated by species adapted to recurrent disturbance. It is clear that without intervention and if present intensification trends continue, the potential of fallow vegetation to contribute to biodiversity conservation declines because of a reduced capacity, (1) to recover forest vegetation with anything like its original species composition, (2) to connect less disturbed forest patches for forest dependent organisms. Strategies to combat biodiversity loss, including promotion of agroforestry practices and the increase of old secondary forest cover, will need not only to operate at a landscape scale but also to be spatially explicit, reflecting the spatial pattern of species reservoirs and dispersal strategies and human usage across landscapes.     

Landscapes of Protection: Forest Change and Fragmentation in Northern West Bengal,India

In the tropics and sub-tropics, where high levels of biodiversity co-exist with some of the greatest levels of population density, achieving complete exclusion in protected area contexts has proved close to impossible. There is a clear need to recognize that parks are significantly impacted by human–environment interactions in the larger landscape within which they are embedded, and to move the frontier of research beyond the boundaries of protected areas in order to examine larger landscapes where multiple forms of ownership and access are embedded. This research evaluates forest change and fragmentation between 1990 and 2000, in a landscape surrounding the Mahananda Wildlife Sanctuary in the Indian state of West Bengal. This protected forest is bounded to the south by a less intensively protected area, the Baikunthapur Reserve Forest, and surrounded by a mosaic of unprotected, largely private land holdings. Results indicate differences in the extent and spatial pattern of forest cover change in these three zones, corresponding to different levels of government protection, access and monitoring. The two protected areas experience a trend toward forest regrowth, relating to the cessation of commercial logging by park management during this period. Yet, there is still substantial clearing toward peripheral areas that are well connected to illegal timber markets by transportation networks. The surrounding landscape, although experiencing some forest regrowth within less intensively cultivated tea plantations, is also becoming increasingly fragmented, with potentially critical impacts on the maintenance of effective wildlife corridors in this ecologically critical region.     

The Influence of Forest Regrowth on the Stream Discharge in the North Carolina Piedmont Watersheds

This study focuses on the relationships of watershed runoff with historical land use/land cover (LULC) and climate trends. Over the 20th Century, LULC in the Southeast United States, particularly the North Carolina Piedmont, has evolved from an agriculture dominated to an extensively forested landscape with more recent localized urbanization. The regrowth of forest has an important influence on the hydrology of the region as it enhances ecosystem interaction with recent climate change. During 1920‐2009, the amount of precipitation in some parts of the North Carolina Piedmont forest regrowth area showed increasing trends without corresponding increments in runoff. We employed the Soil and Water Assessment Tool (SWAT) to backcast long‐term hydrologic behavior of watersheds in North Carolina with different LULC conditions: (1) LULC conversion from agricultural to forested area and (2) long‐term stable forested area. Comparing U.S. Geological Survey‐measured stream discharge with SWAT‐simulated stream discharge under the assumption of constant 2006 LULC, we found significant stream discharge underprediction by SWAT in two LULC conversion watersheds during the early simulation period (1920s) with differences gradually decreasing by the mid‐1970s. This model bias suggests that forest regrowth on abandoned agricultural land was a key factor contributing to mitigate the impact of increased precipitation on runoff due to increasing water consumption driven by changes in vegetation.     

Deforestation Projections for Carbon-Rich Peat Swamp Forests of Central Kalimantan,Indonesia

We evaluated three spatially explicit land use and cover change (LUCC) models to project deforestation from 2005–2020 in the carbon-rich peat swamp forests (PSF) of Central Kalimantan, Indonesia. Such models are increasingly used to evaluate the impact of deforestation on carbon fluxes between the biosphere and the atmosphere. We considered both business-as-usual (BAU) and a forest protection scenario to evaluate each model’s accuracy, sensitivity, and total projected deforestation and landscape-level fragmentation patterns. The three models, Dinamica EGO (DE), GEOMOD and the Land Change Modeler (LCM), projected similar total deforestation amounts by 2020 with a mean of 1.01 million ha (Mha) and standard deviation of 0.17 Mha. The inclusion of a 0.54 Mha strict protected area in the LCM simulations reduced projected loss to 0.77 Mha over 15 years. Calibrated parameterizations of the models using nearly identical input drivers produced very different landscape properties, as measured by the number of forest patches, mean patch area, contagion, and Euclidean nearest neighbor determined using Fragstats software. The average BAU outputs of the models suggests that Central Kalimantan may lose slightly less than half (45.1%) of its 2005 PSF by 2020 if measures are not taken to reduce deforestation there. The relatively small reduction of 0.24 Mha in deforestation found in the 0.54 Mha protection scenario suggests that these models can identify potential leakage effects in which deforestation is forced to occur elsewhere in response to a policy intervention.     

Projecting Large-Scale Area Changes in Land Use and Land Cover for Terrestrial Carbon Analyses

One of the largest changes in US forest type areas over the last half-century has involved pine types in the South. The area of planted pine has increased more than 10-fold since 1950, mostly on private lands. Private landowners have responded to market incentives and government programs, including subsidized afforestation on marginal agricultural land. Timber harvest is a crucial disturbance affecting planted pine area, as other forest types are converted to planted pine after harvest. Conversely, however, many harvested pine plantations revert to other forest types, mainly due to passive regeneration behavior on nonindustrial private timberlands. We model land use and land cover changes as a basis for projecting future changes in planted pine area, to aid policy analysts concerned with mitigation activities for global climate change. Projections are prepared in two stages. Projected land use changes include deforestation due to pressures to develop rural land as the human population expands, which is a larger area than that converted from other rural lands (e.g., agriculture) to forestry. In the second stage, transitions among forest types are projected on land allocated to forestry. We consider reforestation, influences of timber harvest, and natural succession and disturbance processes. Baseline projections indicate a net increase of about 5.6 million ha in planted pine area in the South over the next 50 years, with a notable increase in sequestered carbon. Additional opportunities to expand pine plantation area warrant study of landowner behavior to aid in designing more effective incentives for inducing land use and land cover changes to help mitigate climate change and attain other goals.     

Spatial Modeling and Habitat Quantification for Two Diadromous Fish in New Zealand Streams: A GIS-Based Approach with Application for Conservation Management

We developed logistic regression models from data on biotic and abiotic variables for 172 sites on Banks Peninsula, New Zealand, to predict the probability of occurrence of two diadromous fish, banded kokopu (Galaxias fasciatus) and koaro (G. brevipinnis). Banded kokopu occurrence was positively associated with small streams and low-intensity land uses (e.g., sheep grazing or forested), whereas intensive land uses (e.g., mixed sheep and cattle farming) and lack of riparian forest cover impacted negatively on occurrence at sampled sites. Also, if forests were positioned predominantly in lowland areas, banded kokopu occurrence declined with increasing distance to stream mouth. Koaro occurrence was positively influenced by catchment forest cover, high stream altitudes, and areas of no farming activity or mixed land uses. Intensive land uses, distance to stream mouth, and presence of banded kokopu negatively influenced koaro occupancy of stream reaches. Banded kokopu and koaro presence was predicted in 86.0% and 83.7% agreement, respectively, with field observations. We used the models to quantify the amount of stream reaches that would be of good, moderate, and poor quality, based on the probability of occurrences of the fish being greater than 0.75, between 0.75 and 0.5, or less than 0.5, respectively. Hindcasting using historical data on vegetation cover undertaken for one catchment, Pigeon Bay, showed they would have occupied most of the waterway before anthropogenic modification. We also modeled potential future scenarios to project potential fish distribution.     

Land Use and Land Cover Change Analysis and Prediction in the Upper Reaches of the Minjiang River,China

Scientists have aimed at exploring land use and land cover change (LUCC) and modeling future landscape pattern in order to improve our understanding of the causes and consequences of these phenomena. This study addresses LUCC in the upper reaches of Minjiang River, China, from 1974 to 2000. Based on remotely sensed images, LUCC and landscape pattern change were assessed using cross-tabulation and landscape metrics. Then, using the CLUE-S model, changes in area of four types of land cover were predicted for two scenarios considering forest polices over the next 20 years. Results showed that forestland decreased from 1974 to 2000 due to continuous deforestation, while grassland and shrubland increased correspondingly. At the same time, the farmland and settlement land increased dramatically. Landscape fragmentation in the study area accompanied these changes. Forestland, grassland, and farmland take opposite trajectories in the two scenarios, as does landscape fragmentation. LUCC has led to ecological consequences, such as biodiversity loss and lowering of ecological carrying capacity.