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1.
Rapid land use/land cover changes have taken place in many cities of Turkey. Land use and land cover changes are essential for wide range of applications. In this study, Landsat TM satellite imageries date from 1987, 1993, 2000 and 2010 were used to analyse temporal and spatial changes in the Western Black Sea Region of Turkey. Zonguldak and Eregli two largest and economic important cities which have been active coal mining and iron fabric areas. Maximum Likelihood Classification technique was implemented and the results were represented in classes of open area, forest, agricultural, water, mining, urban and pollution in the sea. Urban areas on both cities increased from 1987 to 2010. The agricultural and open areas from 1987 to 2010 decreased in parallel to land use and land cover change in both cities. Meanwhile, forest areas increased continuously with about 20 % from 1987 to 2010 in both cities. As industrial activity, the coal fields doubled from 1987 to 2010.  相似文献   

2.
In this study, we assessed land cover land use (LCLU) changes and their potential environmental drivers (i.e., precipitation, temperature) in five countries in Eastern & Southern (E&S) Africa (Rwanda, Botswana, Tanzania, Malawi and Namibia) between 2000 and 2010. Landsat-derived LCLU products developed by the Regional Centre for Mapping of Resources for Development (RCMRD) through the SERVIR (Spanish for “to serve”) program, a joint initiative of NASA and USAID, and NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to evaluate and quantify the LCLU changes in these five countries. Given that the original development of the MODIS land cover type standard products included limited training sites in Africa, we performed a two-level verification/validation of the MODIS land cover product in these five countries. Precipitation data from CHIRPS dataset were used to evaluate and quantify the precipitation changes in these countries and see if it was a significant driver behind some of these LCLU changes. MODIS Land Surface Temperature (LST) data were also used to see if temperature was a main driver too.Our validation analysis revealed that the overall accuracies of the regional MODIS LCLU product for this African region alone were lower than that of the global MODIS LCLU product overall accuracy (63–66% vs. 75%). However, for countries with uniform or homogenous land cover, the overall accuracy was much higher than the global accuracy and as high as 87% and 78% for Botswana and Namibia, respectively. In addition, the wetland and grassland classes had the highest user’s accuracies in most of the countries (89%–99%), which are the ones with the highest number of MODIS land cover classification algorithm training sites.Our LCLU change analysis revealed that Botswana’s most significant changes were the net reforestation, net grass loss and net wetland expansion. For Rwanda, although there have been significant forest, grass and crop expansions in some areas, there also have been significant forest, grass and crop loss in other areas that resulted in very minimal net changes. As for Tanzania, its most significant changes were the net deforestation and net crop expansion. Malawi’s most significant changes were the net deforestation, net crop expansion, net grass expansion and net wetland loss. Finally, Namibia’s most significant changes were the net deforestation and net grass expansion.The only noticeable environmental driver was in Malawi, which had a significant net wetland loss and could be due to the fact that it was the only country that had a reduction in total precipitation between the periods when the LCLU maps were developed. Not only that, but Malawi also happened to have a slight increase in temperature, which would cause more evaporation and net decrease in wetlands if the precipitation didn’t increase as was the case in that country. In addition, within our studied countries, forestland expansion and loss as well as crop expansion and loss were happening in the same country almost equally in some cases. All of that implies that non-environmental factors, such as socioeconomics and governmental policies, could have been the main drivers of these LCLU changes in many of these countries in E&S Africa. It will be important to further study in the future the detailed effects of such drivers on these LCLU changes in this part of the world.  相似文献   

3.
In coastal areas, environmental monitoring is an important tool in acquiring data to achieve the goal of sustainable usage relating to the character of changes in quantity and quality of land cover / land use. Studies can reveal the diversity of species and the natural factors and human influence affecting this diversity, occurring as a result of habitat fragmentation or destruction. As well as comparing the past and current state of environmental resources, monitoring helps to determine trends in the use and changes of resources. It was in this context that Kad?rga Bay, located on the northwest coast of Canakkale province, Turkey was studied. Also situated in this location is Assos, a significant site in ancient history with great tourism potential. This study determined changes in land cover / land use by means of photogrammetrical interpretation of data from 1957 to 2002. The research further aimed to determine pressure on the components of the ecological structure of the area. Based on the data obtained, projections can be made to protect the future, and will provide an important source for management of the area. Within the 45-year study period, it was determined that agriculture and secondary housing construction exerted the most pressure on the habitat of the area. In the main, an increase in agricultural activities and secondary house construction emerged as the cause of a decrease in wetlands and forest areas.  相似文献   

4.
In the present study, parameters derived from Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System (GLAS) full waveform were used for land cover classification in western part of Doon valley, Uttarakhand, India. Three parameters, viz, height, front slope angle (afslope) and canopy return ratio (rCanopy) were extracted from the returned full waveform signals. k-means (KM), partitioning around medoids (PAM), and fuzzy c-means (FCM) with different cluster sizes were used for classifying the land cover types with the help of GLAS-derived parameters. Among the clustering methods, KM performed the best. The overall accuracy (89.41 %) of all methods were quite significant with cluster size three i.e. with three classes forest, mango orchard and other class including agriculture, barren/fallow land, settlement, dry river bed, etc. The accuracy of the PAM (60 %) and the FCM (68.4 %) decreased drastically at four clusters with the separation of agriculture from barren/fallow land. The accuracy of the PAM and the FCM further decreased with increase in the number of clusters whereas KM showed reliable results for all clusters. KM with five clusters was able to distinguish five different land covers, viz, forest, mango orchard, agriculture and barren/fallow land and other class including settlement, dry river bed, etc. with an overall classification accuracy of 72.93 %. The study presents a method for classifying land cover types using GLAS full waveform data.  相似文献   

5.
Effective quantification of land cover changes remains a challenge in Himalayan hills and mountains, and has a colossal value addition for natural resource management. Here we present a new robust method for classifying land cover vegetation at physiognomic scale along steep elevational gradients from ~?200 to ~?7000 masl in the Kailash Sacred Landscape, Western Himalaya, India along with four decades of land use and land cover changes (1976–2011) using remote sensing techniques coupled with intensive ground surveys. Results show that forest cover loss was minimum ca 7.14% of existing forest in 1976; but, however forest fragmentation is high especially in montane broad-leaved and subtropical needle leaved forests. This change largely impacted the quality of valuable tree species such as Quercus spp. Post 1976, continuous migration forced conversion of high altitude agricultural lands into grasslands and scrublands. Human settlement expansion was high especially in low altitudinal range valleys between 1000 and 2000 masl and has increased 6.76 fold since 1976, leading to high forest fragmentation in spite of reduced agriculture area in the landscape. Our physiognomic level classified land cover map will be a key for forest managers to prioritize conservation zones for protecting this unique forest land.  相似文献   

6.
Rajaji National Park in U.P. is a protected area where large number of nomad population live within the park area. Their dependence on the forest for cattle rearing and firewood has caused degradation of the forests. Proximity to settlements outside the park further adds to the problems. In the present study, forest cover and river, bed changes have been attempted by using temporal aerospace data of the year 1960 and 1993. Subsequently, PAMAP GIS package has been used for the change detection analysis. The study indicates that the land cover changes are mainly due to biotic factors. Some of the important changes in forest cover are: (i) transformation of mixed forest to scrub forest in 67 ha (ii) the sal mixed and mixed sal forest categories have replaced sal forest in 262 ha (iii) significant increase in forest plantation i.e. 2075 ha in the year 1960 to 3793 ha in 1993 (iv) eighteen times increase in Chirpine area, it increased from 13 ha in 1960 to 230 ha in 1993. The land cover changes in 6663 ha (45%) out of 14962 ha of the study area. The consequential changes in the river beds due to the change in the forest cover was also analyzed. During this period river beds with boulders have increased by 87 ha. These river bed changes include lengthening and broadening of river and change in river course.  相似文献   

7.
Land is one of the prime natural resources. A city grows not only by population but also by changes in spatial dimensions. Urban population growth and urban sprawl induced land use changes and land transformation. The land transformation is a natural process and cannot be stopped but it can be regulated. Many geographical changes at the urban periphery are associated with the transfer of land from rural to urban purpose. There is an urgent need for fast growing areas like Delhi, which can be easily done by high-resolution remote sensing data. Land use/land cover of North West of Delhi has been analyzed for the time period of 1972?C2003. The remote sensing data used in study is Aster image of 2003 with a spatial resolution of 15?m and other data of 1972 Survey of India (SOI) toposheet at the scale of 1:50,000. Supervised digital classification using maximum likelihood classifier was applied for preparing land use/land cover. A change detection model was applied in ERDAS Imagine to find out the land use/land cover during 1972 to 2003. Eight land use classes was identified but main dominated classes were built up and agricultural land. A drastic change has been recorded during 30 years of time i. e. (1972-2003). In 1972, 92.06% of the land was under agricultural practice, which reduced to 64.71% in 2003. This shows 27.35% decrease in agricultural land in three decades. On the other hand built up area was 6.31% in 1972, which increased to 34% in 2003. One of the main cause of this land use change is the population growth due to the migration in the district from small cities and rural areas of Delhi.  相似文献   

8.
This study investigates urbanization and its potential environmental consequences in Shanghai and Stockholm metropolitan areas over two decades. Changes in land use/land cover are estimated from support vector machine classifications of Landsat mosaics with grey-level co-occurrence matrix features. Landscape metrics are used to investigate changes in landscape composition and configuration and to draw preliminary conclusions about environmental impacts. Speed and magnitude of urbanization is calculated by urbanization indices and the resulting impacts on the environment are quantified by ecosystem services. Growth of urban areas and urban green spaces occurred at the expense of cropland in both regions. Alongside a decrease in natural land cover, urban areas increased by approximately 120% in Shanghai, nearly ten times as much as in Stockholm, where the most significant land cover change was a 12% urban expansion that mostly replaced agricultural areas. From the landscape metrics results, it appears that fragmentation in both study regions occurred mainly due to the growth of high density built-up areas in previously more natural/agricultural environments, while the expansion of low density built-up areas was for the most part in conjunction with pre-existing patches. Urban growth resulted in ecosystem service value losses of approximately 445 million US dollars in Shanghai, mostly due to the decrease in natural coastal wetlands while in Stockholm the value of ecosystem services changed very little. Total urban growth in Shanghai was 1768 km2 and 100 km2 in Stockholm. The developed methodology is considered a straight-forward low-cost globally applicable approach to quantitatively and qualitatively evaluate urban growth patterns that could help to address spatial, economic and ecological questions in urban and regional planning.  相似文献   

9.
Multitemporal land cover classification over urban areas is challenging, especially when using heterogeneous data sources with variable quality attributes. A prominent challenge is that classes with similar spectral signatures (such as trees and grass) tend to be confused with one another. In this paper, we evaluate the efficacy of image point cloud (IPC) data combined with suitable Bayesian analysis based time-series rectification techniques to improve the classification accuracy in a multitemporal context. The proposed method uses hidden Markov models (HMMs) to rectify land covers that are initially classified by a random forest (RF) algorithm. This land cover classification method is tested using time series of remote sensing data from a heterogeneous and rapidly changing urban landscape (Kuopio city, Finland) observed from 2006 to 2014. The data consisted of aerial images (5 years), Landsat data (all 9 years) and airborne laser scanning data (1 year). The results of the study demonstrate that the addition of three-dimensional image point cloud data derived from aerial stereo images as predictor variables improved overall classification accuracy, around three percentage points. Additionally, HMM-based post processing reduces significantly the number of spurious year-to-year changes. Using a set of 240 validation points, we estimated that this step improved overall classification accuracy by around 3.0 percentage points, and up to 6 to 10 percentage points for some classes. The overall accuracy of the final product was 91% (kappa = 0.88). Our analysis shows that around 1.9% of the area around Kuopio city, representing a total area of approximately 0.61 km2, experienced changes in land cover over the nine years considered.  相似文献   

10.
1975年—2018年白洋淀湿地变化分析   总被引：2，自引：0，他引：2  
白洋淀湿地生态功能重要、战略地位特殊，研究其时空变化规律具有重要意义。本文基于1975年—2018年间10期Landsat卫星遥感影像，辅以2017年—2018年高分二号（GF-2）卫星遥感影像，在野外考察湿地类型及其覆被特征基础上，人机交互解译获取各期土地利用/覆被分类图，从面积变化、类型转化、景观格局变化方面分析了近43年白洋淀湿地变化时空特征，讨论了影响分析结果的不确定性因素以及湿地变化成因。结果表明：1975年—2018年白洋淀湿地面积总体呈减少趋势，净变化-68.20 km2（-24.83%）。其中，1975年—1990年湿地面积波动性小、基本稳定，1990年—2011年湿地面积持续性减少，2011年—2018年湿地面积呈现增加趋势。湿地与非湿地类型相互转换区域主要分布于淀区南部、西部、北部的水体—水生植物—耕地—建设用地过渡区域。近43年白洋淀湿地景观趋于破碎、复杂和异质。遥感影像选取月份、年份，以及土地利用/覆被分类体系、分类方法，是影响分析结果的主要不确定性因素。气候、水文等自然因素变化，叠加工农业及城镇生活用水、上游水利工程蓄水、地下水开采等人为因素变化，是白洋淀湿地面积减少、趋于干化的成因。  相似文献   

11.
Landsat MSS (1982) and IRS LISS-II (1989) data have been used to study the land use/land cover changes in Dalli-Rajhara iron ore mine area. Supervised classification has been performed on the temporal data to generate land use/land cover maps. Land use/land cover categories generated from IRS LISS-II data of 36 m resolution has been resampled to 80 m and areal statistics have been computed for 2, 4, 8 and 10 km wide strips around Dalli-Rajhara iron ore mine. The environmental impact due to on-going mining activities in the area has been analysed. The results of this study indicate that due to increase in mine-related and agricultural activities, forests have been degraded and also forest areas have been reduced considerably.  相似文献   

12.
Assessment of area under agroforestry in Tehri district of North Western Himalaya, Uttarakhand, India has been done using GIS and remote sensing technology. The study district characterized by hilly terrain with varying elevations from 288 m to more than 2800 m and generally gentle slopes, valleys, flat land covers and agricultural terraces. High-resolution satellite imageries (spatial resolution 5.8 m) were used in this study for land uses and land covers classification. According to unsupervised classification, highest area was found under forest class (65.22%) followed by cropland (20.41%). Considerable area was also found under snow cover (9.45%) in the district. Area under agroforestry was estimated to be 5572.26 ha (1.53%) by this method, whereas it was estimated to be 7029.06 ha (1.93%) by supervised classification. Estimated cropland area comes out to be about 20.0%. An accuracy of 86.5% was found in this classification for agroforestry class. Highest area under agroforestry of 3707.36 ha was obtained in 1200–2000 m elevations followed by 2231.26 ha in 288–1200 m elevations. Negligible area was found on high elevation zones of more than 2800 m. The major agroforestry systems of dominated by Grewia oppositifolia (Bhimal), Celtis australis (Kharik) and Quercus leucotrichophora (Banj) were identified and mapped and remaining systems were grouped as others class. Estimated area under G. oppositifolia, C. australis and Q. leucotrichophora based systems come out to be 2330.82, 1456.80 and 1129.10 ha, respectively. These systems are multiple usufructs are food, fuelwood, fodder, fiber and small timber. It has been observed from the accuracy assessment that the estimates of area under agroforestry obtained under this study are reliable.  相似文献   

13.
Land use and land cover change are of prime concern due to their impacts on CO2 emissions, climate change and ecological services. New global land cover products at 300 m resolution from the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI LC) project for epochs centered around 2000, 2005 and 2010 were analyzed to investigate forest area change and land cover transitions. Plant functional types (PFTs) fractions were derived from these land cover products according to a conversion table. The gross global forest loss between 2000 and 2010 is 172,171 km2, accounting for 0.6% of the global forest area in year 2000. The forest changes are mainly distributed in tropical areas such as Brazil and Indonesia. Forest gains were only observed between 2005 and 2010 with a global area of 9844 km2, mostly from crops in Southeast Asia and South America. The predominant PFT transition is deforestation from forest to crop, accounting for four-fifths of the total increase of cropland area between 2000 and 2010. The transitions from forest to bare soil, shrub, and grass also contributed strongly to the total areal change in PFTs. Different PFT transition matrices and composition patterns were found in different regions. The highest fractions of forest to bare soil transitions were found in the United States and Canada, reflecting forest management practices. Most of the degradation from grassland and shrubland to bare soil occurred in boreal regions. The areal percentage of forest loss and land cover transitions generally decreased from 2000–2005 to 2005–2010. Different data sources and uncertainty in the conversion factors (converting from original LC classes to PFTs) contribute to the discrepancy in the values of change in absolute forest area.  相似文献   

14.
To prevent soil loss and achieve better ecological environments, soil conservation measures have been taken during the past decades in the western Loess Plateau of China. In this paper, a case study was taken in Luoyu valley and Lver valley, two sub-watersheds of Xihe watershed and comparison was carried out between them. The main object of this study is to monitor land use/cover changes in the two similar small watersheds utilizing SPOT5 imageries by object-oriented human–computer interactive classification method, further develop the method of spatio-temporal analysis of land use/cover change by using pattern metrics of change trajectories and relative land use suitability index (R) in smaller watersheds, and make comparisons between the two similar small watersheds, taking water and soil conservation measures into consideration. Results show that combining GIS and RS, this method can be perfectly applied to make comparisons between different small watersheds with similar geographical backgrounds. And land use/cover spatiotemporal dynamic change characteristics can be preferably expressed by pattern metrics of change trajectories and R values based on topographical data. Different emphases have been laid according to their own geological backgrounds in the two watersheds and human activities have different effects on the landscapes of the two watersheds. The main change pattern is from slope farmland to terrace (322, the largest in Luoyu valley) or to economic fruit forest (344, the largest in Lver valley). R value of every slope grade in both of the two watersheds drops with the rising of slope degree on the whole and it shows that there is still much to do for people in the two watersheds in consideration that all the R values are still lower than 0.7.  相似文献   

15.
The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R2 = 0.96), shrub cover (adj. R2 = 0.83), grass cover (adj. R2 = 0.71), bare soil (adj. R2 = 0.88), stone cover (adj. R2 = 0.83) and litter cover (adj. R2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land cover assessment and aid in agricultural and ecological studies.  相似文献   

16.
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial–temporal variability is a challenging task.We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain.The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.  相似文献   

17.
Human activities have diverse and profound impacts on ecosystem carbon cycles. The Piedmont ecoregion in the eastern United States has undergone significant land use and land cover change in the past few decades. The purpose of this study was to use newly available land use and land cover change data to quantify carbon changes within the ecoregion. Land use and land cover change data (60-m spatial resolution) derived from sequential remotely sensed Landsat imagery were used to generate 960-m resolution land cover change maps for the Piedmont ecoregion. These maps were used in the Integrated Biosphere Simulator (IBIS) to simulate ecosystem carbon stock and flux changes from 1971 to 2010. Results show that land use change, especially urbanization and forest harvest had significant impacts on carbon sources and sinks. From 1971 to 2010, forest ecosystems sequestered 0.25 Mg C ha?1 yr?1, while agricultural ecosystems sequestered 0.03 Mg C ha?1 yr?1. The total ecosystem C stock increased from 2271 Tg C in 1971 to 2402 Tg C in 2010, with an annual average increase of 3.3 Tg C yr?1. Terrestrial lands in the Piedmont ecoregion were estimated to be weak net carbon sink during the study period. The major factors contributing to the carbon sink were forest growth and afforestation; the major factors contributing to terrestrial emissions were human induced land cover change, especially urbanization and forest harvest. An additional amount of carbon continues to be stored in harvested wood products. If this pool were included the carbon sink would be stronger.  相似文献   

18.
This study reveals the temporal changes in the land use/land cover of district Ludhiana from the years 1970 to 2001 and reports on the change that has occurred in land use/land cover as a result of change in cropping pattern. The changes were analysed through the data obtained from statistical abstract 1969–70, False Colour Composite (FCC) of IRS-IC LISS-III satellite data of March 2001 and ground truth. There has been a decrease in agricultural land by 2100 ha. but still it occupies 83.76% of the total geographical area (TGA). The wasteland shows a declining trend whereas forest cover has increased from 1.07 to 2.71% of TGA. Area under non-agricultural uses has increased from 10.13 to 12.50% of TGA. There has also been a great change in the cropping pattern of the district. Crops such as groundnut, gram and cotton have nearly disappeared and wheat and rice dominate the region. This change has substantially resulted in the decrease of area under wastelands.  相似文献   

19.
基于景观格局分析方法,分别选取8个反映景观格局类型和6个反映景观水平格局指数用于探索土地利用变化状况.实验结果表明:①基于选择合适的训练样本下,对3期遥感影像采用随机森林的监督分类方法,总体精度均在94％以上,kappa系数均为90％以上;②综合来看,研究期内建设用地为优势景观类型.研究区斑块数量增加,破碎化程度有所加...  相似文献   

20.
Land cover types of Hustai National Park (HNP) in Mongolia, a hotspot area with rare species, were classified and their temporal changes were evaluated using Landsat MSS TM/ETM data between 1994 and 2000. Maximum-likelihood classification analysis showed an overall accuracy of 88.0% and 85.0% for the 1994 and 2000 images, respectively. Kappa coefficients associated with the classification were resulted to 0.85 for 1994 and 0.82 for 2000 image. Land cover types revealed significant temporal changes in the classification maps between 1994 and 2000. The area has increased considerably by 166.5 km2 for mountain steppe and by 12 km2 for a sand dune. By contrast, agricultural areas and degraded areas affected by human being activity were decreased by 46.1 km2 and 194.8 km2 over the 6-year span, respectively. These areas were replaced by mountain steppe area. Specifically, forest area was noticeably fragmented, accompanied by the decrease of ∼400 ha. The forest area revealed a pattern with systematic gain and loss associated with the specific phenomenon called as ‘forest free-south slope’. We discussed the potential environmental conditions responsible for the systematic pattern and addressed other biological impacts by outbreaks of forest pests and ungulates.  相似文献   

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