Spatiotemporal changes of landscape pattern in response to deforestation in Northeastern Turkey: a case study in Rize

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzes spatial and temporal changes in land use and forest cover patterns in a typical mountain forest area in Rize Forest Enterprise of the Northeastern part of Turkey. The area is investigated by evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1984 and 2007 using GIS and FRAGSTATS. The quantative evidences presented here showed that there were drastic changes in the temporal and spatial dynamics of land use/forest cover. As an overall change between 1984 and 2007, there was a net decrease of 2.30% in total forested areas. On one hand, productive forest areas decreased 12,506 ha, on the other hand, degraded forest areas increased 14,805 ha. In examining the changes of crown closure and development stages of forest ecosystem during the study period, the forest stand area with medium crown closures increased. Regenerated area increased while the other development stages were left to grow to mature development stages in the period. These results regarding to crown closure and development stage showed that forest quality has increased but total forest areas decreased. This is partially due to out-migration of rural population in Rize and Cayeli towns. In terms of spatial configuration, analysis of the metrics revealed that landscape structure in Study area had changed substantially over the 23-year study period, resulting in fragmentation of the landscape as indicated by the large patch numbers and the smaller mean patch sizes due to heavy timber subtraction, illegal cutting, and uncontrolled stand treatments.     

Analysing land cover changes for understanding of forest dynamics using temporal forest management plans

This study analyses forest dynamics and land use/land cover change over a 43-year period using spatial-stand-type maps of temporal forest management plans of Karaisal? Forest Enterprise in the Eastern Mediterranean Region of Turkey. Stand parameters (tree species, crown closures and developmental stages) of the dynamics and changes caused by natural or artificial intervention were introduced and mapped in a Geographic Information System (GIS) and subjected to fragmentation analysis using FRAGSTATS. The Karaisal? Forest Enterprise was first planned in 1969 and then the study area was planned under the Mediterranean Forest Use project in 1991 and five-term forest management plans were made. In this study, we analysed only four periods (excluding 1982 revision plans): 1969, 1991, 2002 and 2012. Between 1969 and 2012, overall changes included a net increase of 3,026 ha in forested areas. Cumulative forest improvement accounted for 2.12 % and the annual rate of total forest improvement averaged 0.08 %. In addition, productive forest areas increased from 36,174 to 70,205 ha between 1969 and 2012. This translates into an average annual productive forest improvement rate of 1.54 %. At the same time, fully covered forest areas with crown closure of “3” (>70 %) increased about 21,321 ha, and young forest areas in developmental stage of “a” (diameter at breast height (dbh)?<?8 cm) increased from 716 to 13,305 ha over the 43-year study period. Overall changes show that productive and fully covered forest areas have increased egregiously with a focus on regenerated and young developmental stages. A spatial analysis of metrics over the 43-year study period indicated a more fragmented landscape resulting in a susceptible forest to harsh disturbances.     

Spatial and temporal dynamics of land use pattern in Eastern Turkey: a case study in Gümüşhane

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzed spatial and temporal changes in land use and land cover patterns in a typical mountain watershed in the Gumushane district along the Northeastern part of Turkey. The area is investigated by comparing LANDSAT images from 1987 to 2000 and evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1971 and 1987 using GIS and FRAGSTATS™. The results show a general decreasing trend in area of natural land cover types including broadleaf and conifer forests as well as coppice between 1971 and 1987 (0.54%, respectively). In contrast, between 1987 and 2000 this natural land cover types show increasing trend (1.6%). In parallel with forest dynamics, the area of managed land including lowland and upland agricultural areas, rangelands and grasslands increased during the first period and decreased during second period. In terms of spatial configuration, Gümüşhane forests aren’t generally fragmented by intensive forest utilization in the latter periods. This is partially due to out-migration of rural population in Gümüşhane. Nevertheless, land use pattern significantly changed over time depending on a few factors such as unregulated management actions, social pressure and demographic movements. The study revealed that demographic movements have a major effect on landscape dynamics.     

Carbon storage and emissions offset potential in an African dry forest, the Arabuko-Sokoke Forest, Kenya

Concerns about rapid tropical deforestation, and its contribution to rising atmospheric concentrations of greenhouse gases, increase the importance of monitoring terrestrial carbon storage in changing landscapes. Emerging markets for carbon emission offsets may offer developing nations needed incentives for reforestation, rehabilitation, and avoided deforestation. However, relatively little empirical data exists regarding carbon storage in African tropical forests, particularly for those in arid or semi-arid regions. Kenya's 416 km(2) Arabuko-Sokoke Forest (ASF) is the largest remaining fragment of East African coastal dry forest and is considered a global biodiversity hotspot (Myers et al. 2000), but has been significantly altered by past commercial logging and ongoing extraction. Forest carbon storage for ASF was estimated using allometric equations for tree biomass, destructive techniques for litter and herbaceous vegetation biomass, and spectroscopy for soils. Satellite imagery was used to assess land cover changes from 1992 to 2004. Forest and thicket types (Cynometra webberi dominated, Brachystegia spiciformis dominated, and mixed species forest) had carbon densities ranging from 58 to 94 Mg C/ha. The ASF area supported a 2.8-3.0 Tg C carbon stock. Although total forested area in ASF did not change over the analyzed time period, ongoing disturbances, quantified by the basal area of cut tree stumps per sample plot, correlated with decreased carbon densities. Madunguni Forest, an adjoining forest patch, lost 86% of its forest cover and at least 76% of its terrestrial carbon stock in the time period. Improved management of wood harvesting in ASF and rehabilitation of Madunguni Forest could substantially increase terrestrial carbon sequestration in the region.     

Monitoring the urban green spaces and landscape fragmentation using remote sensing: a case study in Osmaniye,Turkey

Urban green spaces play a significant role in management of physical activity, psychological well-being, and public health of urban residents. With the expansion of urban areas in Turkey during the past decades, urban green spaces have been fragmented and dispersed causing impairment and environmental degradation. The purpose of this study is to model urban green space distribution by focusing on the landscape fragmentation in city of Osmaniye using remote sensing and geographic information system technology. Normalized difference vegetation index (NDVI) and urban landscape ratio (ULR) were used to assess the proximity and spatial arrangement of urban green spaces within the neighbor landscapes to quantify the urban land use effect. The geospatial analysis results showed that increase in total built-up area and population has significantly decreased the urban green space cover because of high levels of landscape fragmentation in urban city center. Also, due to high levels of landscape fragmentation, approximately 45% of the Osmaniye city is estimated to become urbanized by 2030. This study demonstrated the benefits of directional vegetation index application with geospatial analyses in characterizing the environmental quality for planning and management of urban green spaces. This approach could be used for determining the future urban land development scenarios correlating with regional planning procedures.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Using landsat data to determine land use/land cover changes in Samsun, Turkey

The rapid industrialization and urbanization of an area require quick preparation of actual land use/land cover (LU/LC) maps in order to detect and avoid overuse and damage of the landscape beyond sustainable development limits. Remote sensing technology fits well for long-term monitoring and assessment of such effects. The aim of this study was to analyze LU/LC changes between 1980 and 1999 in Samsun, Turkey, using satellite images. Three Landsat images from 1980, 1987 and 1999 were used to determine changes. A post classification technique was used based on a hybrid classification approach (unsupervised and supervised). Images were classified into six LU/LC types; urban, agriculture, dense forest, open forest-hazelnut, barren land and water area. It is found that significant changes in land cover occurred over the study period. The results showed an increase in urban, open forest/hazelnut, barren land and water area and a decrease in agriculture and dense forest in between 1980 and 1999. In this period, urban land increased from 0.77% to 2.47% of the total area, primarily due to conversions from agricultural land and forest to a lesser degree. While the area of dense forest decreased from 41.09% to 29.64% of the total area, the area of open forest and hazelnut increased from 6.73% to 11.88%.     

Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale

Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.     

Effects of Scale and Logging on Landscape Structure in a Forest Mosaic

Landscape structure in a forest mosaic changes with spatial scale (i.e. spatial extent) and thresholds may occur where structure changes markedly. Forest management alters landscapestructure and may affect the intensity and location of thresholds. Our purpose was to examine landscape structure at different scales to determine thresholds where landscape structure changes markedly in managed forest mosaics of the Appalachian Mountains in the eastern United States. We also investigated how logging influences landscape structure and whether these management activities change threshold values. Using threshold and autocorrelation analyses, we found that thresholds in landscape indices exist at 400, 500, and 800 m intervals from the outer edge of management units in our studyregion. For landscape indices that consider all landcovercategories, such as dominance and contagion, landscape structureand thresholds did not change after logging occurred. Measurements for these overall landscape indices were stronglyinfluenced by midsuccessional deciduous forest, the most commonlandcover category in the landscape. When restricting analysesfor mean patch size and percent cover to individual forest types,thresholds for early-successional forests changed after logging. However, logging changed the landscape structure at small spatialscale, but did not alter the structure of the entire forestmosaic. Previous forest management may already have increasedthe heterogeneity of the landscape beyond the point whereadditional small cuts alter the overall structure of the forest. Because measurements for landscape indices yield very differentresults at different spatial scales, it is important first toidentify thresholds in order to determine the appropriate scalesfor landscape ecological studies. We found that threshold andautocorrelation analyses were simple but powerful tools for thedetection of appropriate scales in the managed forest mosaicunder study.     

Landscape approach for quantifying land use land cover change (1972–2006) and habitat diversity in a mining area in Central India (Bokaro, Jharkhand)

The rate and intensity of land use land cover (LULC) change has increased considerably during the past couple of decades. Mining brings significant alterations in LULC specifically due to its impact on forests. Parts of Central India are well endowed with both forests and minerals. Here, the conflict between human interests and nature has intensified over time. Monitoring and assessment of such conflicts are important for land management and policy making. Remote sensing and Geographical Information System have the potential to serve as accurate tools for environmental monitoring. Understanding the importance of landscape metrics in land use planning is challenging but important. These metrics calculated at landscape, class, and patch level provide an insight into changing spatiotemporal distribution of LULC and ecological connectedness. In the present study, geospatial tools in conjunction with landscape metrics have been used to assess the impact of coal mining on habitat diversity. LULC maps, change detection analysis, and landscape metrics have been computed for the four time periods (1972, 1992, 2001, and 2006). There has been a significant decline in forest cover especially of the Sal-mixed forests, both in area as well as quality, due to flouted mining regulations. Reclamation of mined lands has also been observed in some of the areas since 2001.     

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.     

1982—2022年黄土高原归一化植被指数变化的时空特征

长时间地表植被指数变化序列构建与分析是生态环境监测领域的重要内容。以我国生态工程建设重点地区——黄土高原为研究区，采用时间序列的方差匹配方法，融合了2套卫星遥感的归一化植被指数(NDVI)数据产品(GIMMS 3g和MODIS),建立了覆盖1982—2022年的黄土高原暖季(5—9月)NDVI数据集，揭示了其间黄土高原植被覆盖变化的时空特征。研究发现：黄土高原暖季NDVI呈现“先慢后快”的增加趋势，转折点大致出现在2002年，1982—2002年暖季NDVI增速仅为0.01/(10 a),2003—2022年增速高达0.06/(10 a),其中十八大以来增速尤为显著；暖季NDVI快速增加区域主要位于黄土高原中部，并向东北、西南方向延展，与“退耕还林(草)”重点区域范围基本一致；在黄土高原南部、东部和青海省东部一带，暖季NDVI呈缓慢下降趋势。过去40年间黄土高原NDVI增加与生态工程建设关系密切。     

The spatiotemporal dynamics of urbanisation and local climate: A case study of Islamabad,Pakistan

Rapid and unplanned urbanisation, together with climate change, are increasingly affecting the local climatic conditions of urban settlements. Spatiotemporal analysis using land use/land cover (LULC), land surface temperature (LST), and local climatic zone (LCZ) assessments have been helpful in understanding the urbanisation characteristics and morphology. Islamabad, the capital and the only planned city of Pakistan, has witnessed a consistent rise in local temperatures, increased built-up areas, and reduced vegetation cover during the past decades. This study explores the spatiotemporal dynamics of LULC, LST, and LCZ in Islamabad using satellite remote sensing data and spectral indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results indicate a whopping increase in a built-up area in the city (113% during 2013 and 2019). A positive correlation between LST and NDBI, whereas a negative correlation between LST and NDVI clearly indicates how urbanisation (and reduction in vegetation cover) are impacting the local temperatures. Assessment and analysis of LCZs helped to understand the variations and deviations of current LULC from the master plan. It was observed that compact low-rise urban development is the most prevalent. The outcomes of this study are expected to inform the urban planners, climatologists, and policymakers with the knowledge helpful for devising climate-resilient development policies that could reduce thermal stresses in the capital cities.     

Use of object-oriented classification and fragmentation analysis (1985�C2008) to identify important areas for conservation in Cockpit Country, Jamaica

Forest fragmentation is one of the most important threats to global biodiversity, particularly in tropical developing countries. Identifying priority areas for conservation within these forests is essential to their effective management. However, this requires current, accurate environmental information that is often lacking in developing countries. The Cockpit Country, Jamaica, contains forests of international importance in terms of levels of endemism and overall diversity. These forests are under severe threat from the prospect of bauxite mining and other anthropogenic disturbances. In the absence of adequate, up-to-date ecological information, we used satellite remote sensing data and fragmentation analysis to identify interior forested areas that have experienced little or no change as priority conservation sites. We classified Landsat images from 1985, 1989, 1995, 2002, and 2008, using an object-oriented method, which allowed for the inclusion of roads. We conducted our fragmentation analysis using metrics to quantify changes in forest patch number, area, shape, and aggregation. Deforestation and fragmentation fluctuated within the 23-year period but were mostly confined to the periphery of the forest, close to roads and access trails. An area of core forest that remained intact over the period of study was identified within the largest forest patch, most of which was located within the boundaries of a forest reserve and included the last remaining patches of closed-broadleaf forest. These areas should be given highest priority for conservation, as they constitute important refuges for endemic or threatened biodiversity. Minimizing and controlling access will be important in maintaining this core.     

A comparative assessment of land cover dynamics of three protected forest areas in tropical eastern Africa

Processes of deforestation, known to threaten tropical forest biodiversity, have not yet been studied sufficiently in East Africa. To shed light on the patterns and causes of human influences on protected forest ecosystems, comparisons of different study areas regarding land cover dynamics and potential drivers are needed. We analyze the development of land cover since the early 1970s for three protected East African rainforests and their surrounding farmlands and assess the relationship between the observed changes in the context of the protection status of the forests. Processing of Landsat satellite imagery of eight or seven time steps in regular intervals results in 12 land cover classes for the Kakamega–Nandi forests (Kenya) and Budongo Forest (Uganda) whereas ten are distinguished for Mabira Forest (Uganda). The overall classification accuracy assessed for the year 2001 or 2003 is similarly high for all three study areas (81% to 85%). The time series reveal that, despite their protection status, Kakamega–Nandi forests and Mabira Forest experienced major forest decrease, the first a continuous forest loss of 31% between 1972/1973 and 2001, the latter an abrupt loss of 24% in the late 1970s/early 1980s. For both forests, the temporally dense time series show short-term fluctuations in forest classes (e.g., areas of forest regrowth since the 1980s or exotic secondary bushland species from the 1990s onwards). Although selectively logged, Budongo Forest shows a much more stable forest cover extent. A visual overlay with population distribution for all three regions clearly indicates a relationship between forest loss and areas of high population density, suggesting population pressure as a main driver of deforestation. The revealed forest losses due to local and commercial exploitation further demonstrate that weak management impedes effective forest protection in East Africa.     

Assessing implications of land use and land cover changes in forest ecosystems of NE Turkey

Monitoring land use and land cover change (LUCC) and understanding forest cover dynamics is extremely important in sustainable development and management of forest ecosystems. This study analyzed the spatial and temporal pattern of LUCC in the Yaln?zçam and U?urlu forest planning units which are located in the northeast corner of Turkey. The investigation also evaluates the temporal changes of the spatial structure of forest conditions through the spatial analysis of forest-cover type maps from 1972 and 2005 using geographical information systems and FRAGSTATS^TM. As an overall change between 1972 and 2005, there was a net increase of 1,823 ha in forested areas, and cumulative forest improvement accounted for 2.06 %. In terms of spatial configuration, the landscape structure in the study area changed substantially over the 33-year study period, resulting in fragmentation of the landscape as indicated by large patch numbers and smaller mean patch sizes, owing to heavy grazing, illegal cutting, and uncontrolled stand treatments.     

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.     

Estimation of Plant Diversity at Landscape Level: A Methodological Approach Applied to Three Spanish Rural Areas

Approaches linking biodiversity assessment with landscape structure are necessary in the framework of sustainable rural development. The present paper describes a methodology to estimate plant diversity involving landscape structure as a proportional weight associated with different plant communities found in the landscape mosaic. The area occupied by a plant community, its patch number or its spatial distribution of patches are variables that could be expressed in gamma plant diversity of a territory. The methodology applies (1) remote sensing information, to identify land cover and land use types; (2) aspect, to discriminate composition of plant communities in each land cover type; (3) multi-scale field techniques, to asses plant diversity; (4) affinity analysis of plant community composition, to validate the stratified random sampling design and (5) the additive model that partitions gamma diversity into its alpha and beta components. The method was applied to three Spanish rural areas and was able to record 150-260 species per ha. Species richness, Shannon information index and Simpson concentration index were used to measure diversity in each area. The estimation using Shannon diversity index and the product of patch number and patch interspersion as weighting of plant community diversity was found to be the most appropriate method of measuring plant diversity at the landscape level.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.