Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.     

A Method for Ensemble Wildland Fire Simulation

An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis is used to characterize the seasonal trend in ERC, autocorrelation of residuals, and daily standard deviation and stochastically generate artificial time series of afternoon fuel moisture. Daily wind speed and direction are sampled stochastically from joint probabilities of historical wind speed and direction for the date range of the fire simulation period. Hundreds or thousands of fire growth simulations are then performed using the synthetic fire weather sequences. The performance of these methods is evaluated in terms of the number of ensemble member simulations, one- versus two-dimensional fire spread simulations, and comparison with results from 91 fires occurring from 2007 to 2009. Simulations were found to be in consistent agreement with observations, but trends indicate that the ensemble average of simulated fire sizes were consistently larger than actual fires whereas the farthest extent burned by fires was underestimated.     

中国秸秆焚烧的遥感监测与分析

用最近四年的MODIS火点数据,通过相关处理和分析,得出了全国秸秆焚烧状况的时空分布规律。结果表明,秸秆焚烧最严重的区域一直分布在淮河流域和陕西关中平原,这是秸秆禁烧工作的重点;南部各省秸秆焚烧点密度较小,比较分散,造成的危害相对较小。秸秆焚烧的主要时间,北方集中在夏秋季节,主要是小麦、玉米、油菜等的秸秆;南方集中在冬春季节,主要是水稻、甘蔗、油菜等的秸秆。秸秆焚烧的时空分布规律在最近几年基本无大的变化,秸秆焚烧面积在2002年~2005年期间逐年上升。文章结论反映了各地执行秸秆禁烧政策的效果,可为相关政府部门进行秸秆禁烧工作提供依据。     

Land use pattern, socio-economic development, and assessment of their impacts on ecosystem service value: study on natural wetlands distribution area (NWDA) in Fuzhou city, southeastern China

This paper quantifies the allocation of ecosystem services value (ESV) associated with land use pattern and qualitatively examined impacts of land use changes and socio-economic factors on spatiotemporal variation of ESV in the Natural Wetland Distribution Area (NWDA), Fuzhou city, China. The results showed that total ESV of the study area decreased from 4,332.16?×?10⁶ RMB Yuan in 1989 to 3,697.42?×?10⁶ RMB Yuan in 2009, mainly due to the remarkable decreases in cropland (decreased by 55.3 %) and wetland (decreased by 74.2 %). Forest, water, and wetland played major roles in providing ecosystem services, accounting for over 90 % of the total ESV. Based on time series Landsat TM/ETM+ imagery, geographic information system, and historical data, analysis of the spatiotemporal variation of ESV from 1989 to 2009 was performed. It indicated that rapid expansion of urban areas along the Minjiang River resulted in significant changes in land use types, leading to a dramatic decline in ecosystem services. Meanwhile, because of land scarcity and unique ecosystem functions, the emergency of wetland and cropland protection in built-up area has become an urgent task of local authorities to the local government. Furthermore, there was still a significant negative correlation between ESV of cropland and wetland and the GDP. The results suggest that future planning of land use pattern should control encroachment of urban areas into cropland and wetland in addition to scientific and rational policies towards minimizing the adverse effects of urbanization.     

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.     

Analyzing riparian forest cover changes along the Firniz River in the Mediterranean City of Kahramanmaras in Turkey

Riparian forests adjacent to surface water are important transitional zones which maintain and enrich biodiversity and ensure the sustainability in a forest ecosystem. Also, riparian forests maintain water quality, reduce sediment delivery, enhance habitat areas for aquatic life and wildlife, and provide ecological corridors between the upland and the downstream. However, the riparian ecosystems have been degraded mainly due to human development, forest operations, and agricultural activities. In order to evaluate the impacts of these factors on riparian forests, it is necessary to estimate trends in forest cover changes. This study aims to analyze riparian forest cover changes along the Firniz River located in Mediterranean city of Kahramanmaras in Turkey. Changes in riparian forest cover from 1989 to 2010 have been determined by implementing supervised classification method on a series of Landsat TM imagery of the study area. The results indicated that the classification process applied on 1989 and 2010 images provided overall accuracy of 80.08 and 75 %, respectively. It was found that the most common land use class within the riparian zone was productive forest, followed by degraded forest, agricultural areas, and other land use classes. The results also indicated that the areas of degraded forest and forest openings increased, while productive forest and agricultural areas decreased between the years of 1989 and 2010. The amount of agricultural areas decreased due to the reduction in the population of rural people. According to these results, it can be concluded that special forest management and operation techniques should be implemented to restore the forest ecosystem in riparian areas.     

Wildfire-induced reduction in the carbon storage of Mediterranean ecosystems: An application to brush and forest fires impacts assessment

Wildfire is one of the most dangerous and harmful phenomena in the world. Hence, fire impacts assessment could become very important in forest areas according to its environmental and landscape values. This paper suggests an approach to identify fire effects on biomass, in consonance with the potential carbon storage of each area used, and its biomass consumption based on fire behavior.Dense mature forests were the most vulnerable landscapes based on its aboveground biomass, mainly tree stem biomass. A significant correlation was found between fire intensity and biomass consumption. Biomass consumption ranged from 16.59% to 98.75% from the two studied wildfires. It is necessary to provide a scenario analysis according to the uncertain CO₂ market. As an example, carbon storage impacts in one fire were between 100,340.66 € (using the minimum price of CO₂) and 741,057.44 € (using the maximum price of CO₂). Differences between scenarios ranged from 35.30% to 46.51% of the total carbon storage impacts. This approach might be a solution to identify and prioritize areas for restoration activities and optimize the allocation of the resources.     

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve,India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004–2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km². There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km² (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km² is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km²) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.     

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.     

Soil Erosion Potential after Fire and Rehabilitation Treatments in Greece

Wildland fires are one of the more severe disturbances for natural ecosystems in the Mediterranean basin and can become a critical factor in the process of soil erosion. A quantitative assessment of soil erosion is needed in order to form an assessment on the extent and magnitude of post-fire soil erosion potential and to assess the effectiveness of the rehabilitation treatment. On 21 August 2006, a large wildland fire occurred in the Kassandra Peninsula in northern Greece, which burned one fifth of the Peninsula. After the fire, in order to protect the soil against erosion, the Forest Services applied a hillslope rehabilitation treatment of contour-felled logs and branch piles. In this paper, we report quantitative estimation of the wildland fire and erosion control treatment on soil erosion potential. The coupling of the Universal Soil Loss Equation and the Geographical Information Systems was implemented and the erosion potential was found to be 2.8 t/ha/year pre-fire, 29.5 t/ha/year post-fire, and 21.3 t/ha/year after rehabilitation treatment. The model can successfully contribute in the planning of the rehabilitation treatment but it cannot be used in the quantification of the soil loss after the application of the erosion control measures. The comparisons between the results of the three cases indicate the importance of the immediate erosion control measures in order to mitigate soil loss and restore the natural environment.     

Pre- and post-fire pollutant loads in an urban fringe watershed in Southern California

Post-fire runoff has the potential to be a large source of contaminants to downstream areas. However, the magnitude of this effect in urban fringe watersheds adjacent to large sources of airborne contaminants is not well documented. The current study investigates the impacts of wildfire on stormwater contaminant loading from the upper Arroyo Seco watershed, burned in 2009. This watershed is adjacent to the Greater Los Angeles, CA, USA area and has not burned in over 60 years. Consequently, it acts as a sink for regional urban pollutants and presents an opportunity to study the impacts of wildfire. Pre- and post-fire storm samples were collected and analyzed for basic cations, trace metals, and total suspended solids. The loss of vegetation and changes in soil properties from the fire greatly increased the magnitude of storm runoff, resulting in sediment-laden floods carrying high concentrations of particulate-bound constituents. Post-fire concentrations and loads were up to three orders of magnitude greater than pre-fire values for many trace metals, including lead and cadmium. A shift was also observed in the timing of chemical delivery, where maximum suspended sediment, trace metal, and cation concentrations coincided with, rather than preceded, peak discharge in the post-fire runoff, amplifying the fire’s impacts on mass loading. The results emphasize the importance of sediment delivery as a primary mechanism for post-fire contaminant transport and suggest that traditional management practices that focus on treating only the early portion of storm runoff may be less effective following wildfire. We also advocate that watersheds impacted by regional urban pollutants have the potential to pose significant risk for downstream communities and ecosystems after fire.     

Post-classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmaraş, Turkey

This study assessed land cover (LC) changes in Kahramanmara? (K.Mara?) and its environs by using multitemporal Landsat and ASTER imagery, respectively belong to 1989, 2000 and 2004. A priori defined nine land cover classes in the classification scheme were urban and built-up, forest, sparsely vegetated areas, grassland, vegetated stream beds, unvegetated stream beds, bare areas, crop fields, and water bodies. Individual classifications were employed using the combination of both unsupervised and supervised classification methods. Iterative Self Organizing Data Analysis (ISODATA) was used to reduce spectral variation in the scenes arising from complex pattern of crop fields. Maximum Likelihood classifier was used in the LC classification of the individual images. Image pairs of consecutive dates were compared by overlaying the thematic LC maps and cross-tabulating the LC statistics. Urbanization and expansion of agriculture were the major reasons for the dramatic LC conversions. The amount of conversion from crop fields to water occurred as large as 927.67 ha, accounting for 73% of the total land-to-water conversion. Conversions to agriculture have mainly been occurred from grasslands and sparsely vegetated areas as large as 1,314.95 and 1,325.84 ha, respectively. Urban coverage doubled in this period as a result of 1,443.45 ha of increase. Urban area increased in the second period from 2,920 to 3,526 ha. Conversions to agriculture occurred at high amounts. A total of 1,075.79 ha area changed from sparsely vegetated areas to crop fields. A landscape-level environmental monitoring scheme based on satellite remote sensing was proposed for effective environmental resource management.     

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.     

Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks

China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R ²) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R ² values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.     

Nutrient Export from Watersheds on Mt. Desert Island, Maine, as a Function of Land Use and Fire History

A study of 13 small (less than 7.5 km²) watersheds on Mt. Desert Island, Maine, was conducted from January 1999 to September 2000 to determine nutrient export delivery to coastal waters around the island, and to determine whether a series of wildfires in 1947 have affected nutrient export in burned watersheds. Nutrient export (nitrate–nitrogen, total nitrogen, total phosphorus) was determined for each watershed during the study period, and was normalized by watershed area. The yield of nitrate–nitrogen (N) ranged from 10 to 140 kg/km²/year. Total N yield ranged from 42 to 250 kg/km²/year. Total phosphorus (P) yield ranged from 1.4 to 7.9 kg/km²/year. Watersheds entirely within Acadia National Park (lacking human land-based nutrient sources) exported significantly less total N and total P than watersheds that were partly or entirely outside the park boundary. Nitrate–N export was not significantly different in these two groups of watersheds, perhaps because atmospheric deposition is a dominant source of nitrate in the study area. No relation was observed between burn history and nutrient export. Any effect of burn history may be masked by other landscape-level factors related to nutrient export.     

Acid soil indicators in forest soils of the Cherry River Watershed, West Virginia

Declining forest health has been observed during the past several decades in several areas of the eastern USA, and some of this decline is attributed to acid deposition. Decreases in soil pH and increases in soil acidity are indicators of potential impacts on tree growth due to acid inputs and Al toxicity. The Cherry River watershed, which lies within the Monongahela National Forest in West Virginia, has some of the highest rates of acid deposition in Appalachia. East and West areas within the watershed, which showed differences in precipitation, stream chemistry, and vegetation composition, were compared to evaluate soil acidity conditions and to assess their degree of risk on tree growth. Thirty-one soil pits in the West area and 36 pits in the East area were dug and described, and soil samples from each horizon were analyzed for chemical parameters. In A horizons, East area soils averaged 3.7 pH with 9.4 cmol_c kg^???1 of acidity compared to pH 4.0 and 6.2 cmol_c kg^???1 of acidity in West area soils. Extractable cations (Ca, Mg, and Al) were significantly higher in the A, transition, and upper B horizons of East versus West soils. However, even with differences in cation concentrations, Ca/Al molar ratios were similar for East and West soils. For both sites using the Ca/Al ratio, a 50% risk of impaired tree growth was found for A horizons, while a 75% risk was found for deeper horizons. Low concentrations of base cations and high extractable Al in these soils translate into a high degree of risk for forest regeneration and tree growth after conventional tree harvesting.     

Use of Satellite Imagery as Environmental Impact Assessment Tool: A case Study from the Nw Egyptian Red Sea Coastal Zone

Knowledge and detecting impacts of human activities on the coastal ecosystem is an essential management requirement and also very important for future and proper planning of coastal areas. Moreover, documentation of these impacts can help in increasing public awareness about side effects of unsustainable practices. Analysis of multidate remote sensing data can be used as an effective tool in environmental impact assessment (EIA). Being synoptic and frequent in coverage, multidate data from Landsat and other satellites provide a reference record and bird’s eye viewing to the environmental situation of the coastal ecosystem and the associated habitats. Furthermore, integration of satellite data with field observations and background information can help in decision if a certain activity has caused deterioration to a specific habitat or not. The present paper is an attempt to utilize remote sensing data for assessment impacts of some human activities on the major sensitive habitats of the NW Egyptian Red Sea coastal zone, definitely between Ras Gemsha and Safaga. Through multidate change analysis of Landsat data (TM & ETM+ sensors), it was possible to depict some of the human infringements in the area and to provide, in some cases, exclusive evidences for the damaging effect of some developmental activities.     

基于Landsat TM/ETM+/OLI遥感大数据分析南京市1984—2015年大气能见度变化趋势

对南京市1984—2015年Landsat 4／5／7／8卫星TM／ETM＋／OLI传感器获取的遥感数据，利用ENVI遥感软件的FLAASH大气校正模块，进行了区域大气能见度（ VIS）遥感反演。结果表明，时间跨度达30余年的Landsat卫星遥感数据影像序列反演的VIS呈明显的下降趋势，20世纪80年代数值较高，“差”能见度（＜10 km）的观测率不到6％，21世纪以来VIS下降明显，“差”能见度的观测率为20％～25％。与2010—2015年南京市PM10、PM2．5监测数据进行了对比，在城市空气清洁及污染较轻时，星地监测结果有较好的一致性，但中到重污染天气时FLAASH算法反演VIS偏高，侧重于代表离主城区距离远的偏远乡野山林地区的能见度状况。     

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

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

Coastal dynamic and shoreline mapping: multi-sources spatial data analysis in Semarang Indonesia

Semarang coastal area has geomorphologically complex processes, such as erosion-sedimentation, land subsidence, and tidal inundation hazard. Multi-years shoreline mapping is considered a valuable task for coastal monitoring and assessment. This paper presents maps illustrating the shoreline dynamic in a coastal area of Semarang-Indonesia using multi-sources spatial data. The segment data has been obtained by visual delineation of the topographic maps Year 1908, 1937, 1992 and Ikonos image Year 2003 as well as digital number (DN) value analysis and masking operation of Landsat MSS Year 1972 and Landsat ETM Year 2001. For the long period of almost 100 year, the shoreline dynamic in Semarang coastal area is dominated by sedimentation process. Shoreline extended to the sea as a result of man-made infrastructure and natural processes. The research's result was satisfactory and the method has proven to be effective considering lack of homogeneous data-series. However, some further improvement regarding geo-processing can be made and the accuracy can be tested in future version.