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1.
A set of six Landsat satellite images with 5–9 years apart was used in a post-classification analysis to map changes occurred at Rosetta promontory between 1973 and 2008 due to coastal erosion. Spectral information were extracted from two multi-spectral scanner (MSS) images (1973 and 1978), three thematic mapper (TM) images (1984, 1990, and 1999), and one enhanced thematic mapper plus (ETM+) image (2008). To estimate the quantity of land loss in terms of coastal erosion, a supervised classification scheme was applied to each image to highlight only two classes: seawater and land. The area of each class was then estimated from the number of pixels pertaining to this class in every image. In addition, the shoreline position was digitized to address retreat/advance pattern throughout the study period. Results showed that Rosetta promontory had lost 12.29 km2 of land between 1973 and 2008 and the shoreline withdrew southward about 3.5 km due to coastal erosion. Most land loss and shoreline retreat occurred between 1973 and 1978 (0.55 km2/year and 132 m/year, respectively). Coastal protection structures were constructed successively at the promontory. These structures have considerably contributed to reduce coastal erosion; however, they promoted downdrift erosion.  相似文献   

2.
Considerable land cover changes have occurred in the Luvuvhu catchment in northeastern South Africa in the past two decades. These changes are associated with human population growth and may be contributing to observed reductions in winter river baseflows and increased episodes of river drying within Kruger National Park. Six-class land cover maps of the catchment were created from 1978 (MSS) and 2005 (TM) Landsat imagery using an iterative technique. Results indicate a 1,000 km2 (12%) increase in Bare Ground between 1978 and 2005, with a concomitant decrease in shrubland and indigenous forest cover. Overall classification accuracy in the 2005 image was 80%. Classification was most accurate for Water and Pine classes (100 and 92%) and least accurate for Indigenous Forest (46%), primarily due to misclassification as Shrubland. These maps are suitable for land cover change and landscape modeling analyses, and can serve as baseline data for further research.  相似文献   

3.
Sustainable management of land requires regular acquisition of qualitative information regarding the status of its use. It is especially important to track the changes relating to the land’s competitive development needs such as mining. The field-based monitoring of a mine with a wide footprint is expensive and time-consuming. Remote sensing techniques have been developed and demonstrated as cost-effective alternatives for the conventional methods of land use/land cover (LULC) monitoring. In this study, the land cover changes that occurred between the year of 2000 and 2009 in a kaolin mining and processing area in the Kutch region of India are mapped using two Landsat-5 Thematic Mapper (TM) images. For this purpose, the spectral signature of the land covers including vegetation cover and kaolin were determined and matched filtering (MF) method was applied to classify the images. The overall accuracy of the classified 2009 image was estimated for the kaolin and the vegetation cover to 89.5 and 86.0 % respectively. The change in the land use which occurred from 2000 to 2009 were quantified and analysed for both classes. This study provided a practical framework for rapid mapping of the land cover changes around open-cut kaolin mining area using freely available Landsat data.  相似文献   

4.
To facilitate urban planning and management in fast-growing metropolitan areas, it is highly necessary to detect the spatiotemporal changes of different land cover types. This study aimed at identifying Beijing’s land cover types and detecting the characteristics of their spatiotemporal changes using time series remote sensing and GIS techniques from 1978 to 2010. A total of 16 Landsat MSS/TM/ETM+ images were collected during the spring and late summer seasons. After preprocessing the dataset, artificial neural network was used to perform the land cover classification. Consequently, four maps were generated for 1978, 1992, 2000, and 2010, with six classes (agriculture, woodland, grassland, water, urban, and barren land) according to the level I classification scheme. Three transition matrices were constructed to represent all possible changes that occur in the landscape. The results showed that agriculture, barren land, and grassland had an increase in area, while urban, water, and woodland had a reduction within the study area. A total of 2,032.341 km2 agriculture was reduced and 2,359.146 km2 woodland was increased. In the three periods for 1978–1992, 1992–2000, 2000–2010, agriculture had the largest amount of transfer out primarily to urban class around central urban areas and woodland had the most transfer in mainly from barren land in mountainous areas. More importantly, the driving forces analysis including economic development, growth of population and construction areas, and institutional policies was conducted to find out the primary factors inducing the land cover change.  相似文献   

5.
近30a来若尔盖盆地沙漠化时空演变过程及成因分析   总被引：5，自引：0，他引：5  
在遥感(RS)和地理信息系统(GIS)技术的支持下,采用1975年的MSS影像和2005年的TM影像对若尔盖盆地土地沙漠化的时空演变进行了监测。研究发现,从1975年到2005年的30年间,若尔盖盆地的沙漠化土地以年均70.18 km2的速度发展,共增加了2105.36 km2,其中主要以中、轻度沙漠化土地的增加为主,增加面积分别为957.13和1146.75 km2;重度沙漠化土地变化很小,仅增加了1.48 km2。在1965—2007年,若尔盖盆地年平均气温升高了1.41℃,年平均降水减少了34 mm,人类活动对环境的破坏作用加强,严重过度放牧,因此该地区沙漠化发展是自然环境变化和人类活动共同作用的结果。  相似文献   

6.
Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km2) and 0.3% (86.03 km2) while water, garden and bare land have decreased by 0, 0.01% (3.62 km2) and 0.4% (117.168 km2), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.  相似文献   

7.
Human activities in many parts of the world have greatly changed the natural land cover. This study has been conducted on Pichavaram forest, south east coast of India, famous for its unique mangrove bio-diversity. The main objectives of this study were focused on monitoring land cover changes particularly for the mangrove forest in the Pichavaram area using multi-temporal Landsat images captured in the 1991, 2000, and 2009. The land use/land cover (LULC) estimation was done by a unique hybrid classification approach consisting of unsupervised and support vector machine (SVM)-based supervised classification. Once the vegetation and non-vegetation classes were separated, training site-based classification technology i.e., SVM-based supervised classification technique was used. The agricultural area, forest/plantation, degraded mangrove and mangrove forest layers were separated from the vegetation layer. Mud flat, sand/beach, swamp, sea water/sea, aquaculture pond, and fallow land were separated from non-vegetation layer. Water logged areas were delineated from the area initially considered under swamp and sea water-drowned areas. In this study, the object-based post-classification comparison method was employed for detecting changes. In order to evaluate the performance, an accuracy assessment was carried out using the randomly stratified sampling method, assuring distribution in a rational pattern so that a specific number of observations were assigned to each category on the classified image. The Kappa accuracy of SVM classified image was highest (94.53 %) for the 2000 image and about 94.14 and 89.45 % for the 2009 and 1991 images, respectively. The results indicated that the increased anthropogenic activities in Pichavaram have caused an irreversible loss of forest vegetation. These findings can be used both as a strategic planning tool to address the broad-scale mangrove ecosystem conservation projects and also as a tactical guide to help managers in designing effective restoration measures.  相似文献   

8.
Lake Urmia, located in northwest Iran, contains a number of wetlands significantly affecting the environmental, social, and economic conditions of the region. The ecological condition of Lake Urmia has degraded during the past decade, due to climate change, human activities, and unsustainable management. The poor condition of the lake has also affected the surrounding wetlands. This study analyzes the land cover change of one of the wetlands in the southern part of Lake Urmia, known as Ghara-Gheshlagh wetland, in the period 1989–2015 using post-classification change detection and machine learning image classification. For this analysis, three Landsat images, acquired in 1989 (TM), 2001 (TM), and 2015 (Landsat-8), were used for the classification and change detection. Support vector machine learning algorithm, a supervised learning method, is employed, and images are classified into four main land cover classes namely “water,” ”barren,” “salty land,” and “agriculture and grassland.” Change detection was carried out for pairs of years 1989 to 2001 and 2001 until 2015. The results of this classification show that there is a sharp increase in the area of salt-saturated land as well as a decrease in the area of water resources. Overall classification accuracy obtained were high for the individual years: 1989 (91.48%), 2001 (90.63%), and 2015 (88.6%). Also, the Kappa coefficients for individual maps were high: 1989 (0.89), 2001 (0.8742), and 2015 (0.84). After that, the land cover change map of the study area is obtained between 1989 to 2001 and then 2001 to 2015. The results of this analysis suggest that more efforts should be taken to effectively manage water resources in the region and point to potential locations for focused management actions within the wetland area.  相似文献   

9.
The Chinese Loess Plateau is suffering from severe soil erosion. The eco-environmental changes of the plateau are believed to have an important influence on global eco-environmental sustainability; hence, this problem has attracted considerable attention from scientists around the world. This study has two purposes; application of remote sensing (RS) and geographic information system (GIS) techniques in the dynamic analysis of eco-environmental changes in the semiarid zone; and using the Longdong region of the Chinese Loess Plateau as an example, to make dynamic analysis of the eco-environmental changes of the region during the 1986–2004 period and identify controlling factors. Landsat Thematic Mapper (TM) data at a spatial resolution of 30 m were used for analysis. Two training areas were selected in Jingning and Qingcheng counties for analysis using 10-m resolution SPOT and Landsat TM data. The satellite RS images were obtained from the Institute of Remote Sensing Application (IRSA), Chinese Academy of Sciences (CAS). Each images was rectified by Albers Equal Area Conic projection based on 1:50,000 scale topographic maps after spectrum preparation of the images. To make the precision within 1 or 2 pixels, the accurate coordinative control points of the two systems were identified. Then the interpretation key was established based on the land use/cover survey in the study area. The images were classified into six primary environmental types (farmland, forest, grassland, water, construction area, and desert) and 25 sub-types using a visual image interactive interpretation method to obtain vector and attribute data. The resultant accuracy of the land use/cover classification reached 95%. Finally, the transformation areas and ratios of various eco-environmental types in the region were calculated to obtain the transition matrixes of eco-environmental types in the two training areas, Jingning and Qingcheng. This study demonstrates that satellite RS and GIS techniques are effective tools to monitor and analyze the eco-environmental changes in the semiarid region. Visual image interactive interpretation based on GIS technique provides comprehensive information on the direction, rate, and location of eco-environmental changes. The transition matrix model can be used to precisely analyze the variation and rates of the eco-environmental types and their spatial distribution. Great land use changes have taken place Longdong during the 1986–2004 period. These eco-environmental changes were driven by natural and human factors. Natural factors influencing the Longdong region of the Chinese Loess Plateau mainly include temperature, water condition, terrain, soil, and erosion; while human activities include over-cultivation, overgrazing, and fuelwood cutting. As viewed from the extent and severity of the influences, human activities play a very important role in altering the eco-environment of the semiarid region. The study results indicate a need for future research and observation in the semiarid region.  相似文献   

10.
卫星图像处理技术在蒙阴地区金刚石找矿预测中的应用   总被引：1，自引：0，他引：1  
文章针对研究区内金伯利岩的特征,运用OIF系数确定最佳季相波段,用最小二乘法设计的大气散射校正、比值—分段线性扩展等处理程序,使处理后图像增大了对比度,展宽了与金伯利岩有关的地质体的光谱范围,提取出了与金伯利岩有关地质体的波谱信息。经处理后图像及不同比例尺的遥感图像对应分析,圈定了区内优选靶区,其中在两县色形图像异常内发现的碳酸角砾岩脉,经野外工作和室内重砂、岩石化学、REE、碳氧同位素分析表明,可能是后期碳酸岩化的角砾金伯利岩脉。两县色形异常是寻找金刚石原生矿床的有利靶区。  相似文献   

11.
This paper introduces how to use remote sensing images including Landsat (MSS and TM) andairborne radioactivity images to identify the type of rocks in the areas covered by vegetation. The relationship between light spectrum (Landsat MSS and TM) and energy spectrum (U, Th and K) is discussed on the basis of correlation analysis, and it is proven that there are correlations between the Landsat MSS or TM data and the U, Th and K. data. By using the fusion technique, new images were generated, which contain both the light spectrum and the energy spectrum information.Taking the Lucong basin as the study area, the present paper demonstrates the successful identification of various types of rocks using the fusion technique. Different types of rocks are represented by different colours on the new light-energy spectrum images, so that volcanic rocks of the Jurassic and Cretaceous periods can be discriminated. Another example, in the Lingquan basin in Northeast China, not only the different types of rocks are su  相似文献   

12.
The aim of this paper was to investigate the suitability of the pixel-level and product-level image fusion approaches to detect surface water changes. In doing so, firstly, the principal component analysis technique was applied to Landsat TM 2010 multispectral image to generate the PC components. Several pixel-level image fusion techniques were then performed to merge the Landsat ETM+ 2000 panchromatic with the PC1PC2PC3 band combination of Landsat TM 2010 imagery to highlight the surface water changes between the two images. The suitability of the resulting fused images for surface water change detection was evaluated quantitatively and visually. Finally, the support vector machine (SVM) technique was applied to the qualified fused images to map the highlighted changes. Furthermore, a product level fusion (PLF) approach based on various satellite-derived indices was employed to detect the surface water changes between ETM+ 2000 and TM 2010 images. The accuracy of the resulting change maps was assessed based on a reference change map produced using visual interpretation. The results demonstrated the effectiveness of the proposed approaches for surface water change detection, especially using the Gram Schmidt-SVM, PLF-NDWI, and PLF-NDVI methods which improved the accuracy of change detection over 99.70 %.  相似文献   

13.
Statistical analysis is conducted to determine the unique value of real- and synthetic-aperture side-looking airborne radar (SLAR) to detect interpreted structural elements. SLAR images were compared to standard and digitally enhanced Landsat multispectral scanner (MSS) images and to aerial photographs. After interpretation of the imagery, data were cumulated by total length in miles and by frequency of counts. Maximum uniqueness is obtained first from real-aperture SLAR, 58.3% of total, and, second, from digitally enhanced Landsat MSS images, 54.1% of total.Publication authorized by the Director, U.S. Geological Survey, on 20 September 1984.  相似文献   

14.
从遥感信息分析入手，分析了抚州地区水土流失区在Landsat TM1,TM2,TM3,TM4,TM5,TM6,TM7各个波段上与其它背景地物的可分性。利用水土流失区光谱特征与其它地物的差异性，建立条件表达式，并建立简单模型，即可把该区的水土流失区提取出来。该区土地利用率不是很高，水土流失比较严重，而且面积大。由于居民地光谱特征与水土流失区比较接近，所以区分居民地与水土流失区成为研究的重点。研究表明，通过建立简单的模型，可以将水土流失区提取出来，并能达到很好的效果。  相似文献   

15.
Wular Lake is the largest freshwater lake of India located in north western Himalayas of Kashmir Valley which has got deteriorated over the period of time due to the enough human interference within its catchment areas. The purpose of the present research study is to identify the changes in land use and land cover in the Wular catchment as well as its transformation into other classes and its impact on the overall water quality of the lake. For the present study Landsat (TM) image of 1992 and Landsat-8 (OLI) of 2015 have been used for assessing the changes in land use/land cover. Supervised classification technique was used to generate LULC maps of different categories pertaining to study area for years 1992 and 2015. Regarding water quality, water samples were collected from five different spots of the lake in four different seasons of the year—from December 2014 to September 2015. The sites from which samples were collected are Vintage Park, Ashtungo, Watlab, Makhdomyari and Ningal as site 1, 2, 3, 4, and 5 respectively. Some parameters of water like temperature, transparency, depth, conductivity and pH were examined on the spot during the sample collection by their respective measuring instruments. The rest of the parameters were examined in hydrological laboratory within 24 h after collection following the standard methods of APHA (Standard methods for the examination of water and wastewater, 21st edn. American Public Health Association, Washington, DC, 2005). The relationship between the LULC classes and water quality parameters has been calculated with the help of SHDI which has shown both positive and as well as negative results.  相似文献   

16.
This research selected water soil erosion indicators (land cover, vegetation cover, slope) to assess the risk of soil erosion, ARCMAP GIS ver.9.0 environments and ERDAS ver.9.0 were used to manage and process satellite images and thematic tabular data. Landsat TM images in 2003 were used to produce land/cover maps of the study area based on visual interpreting method and derived vegetation cover maps, and the relief map at the scale of 1:50,000 to calculate the slope gradient maps. The area of water soil erosion was classified into six grades by an integration of slope gradients, land cover types, and vegetation cover fraction. All the data were integrated into a cross-tabular format to carry out the grid-based analysis of soil erosion risk. Results showed that the upper basin of Miyun Reservoir, in general, is exposed to a moderate risk of soil erosion, there is 715,848 ha of land suffered from water soil erosion in 2003, occupied 46.62% of total area, and most of the soil erosion area is on the slight and moderate risk, occupied 45.60 and 47.58% of soil erosion area, respectively.  相似文献   

17.
Using Landsat data to determine land use changes in Datong basin,China   总被引：1，自引：0，他引：1  
The aim of this study was to determine land use changes in Datong basin using multitemporal Landsat data for the period of 1977–2006. Four dates of Landsat images from 1977, 1990, 2000, and 2006 were selected to classify the study area. Based on the supervised classification method of maximum likelihood algorithm, images were classified into six classes: water, urban, forest, agriculture, wetland, and barren land. A multidate postclassification comparison change detection algorithm was used to determine changes in land use in four intervals. It is found that (1) urban land area increased 213% due to urbanization that resulted from rapid increase of urban population and high-speed economic development, (2) agriculture area increased 34.0% due to land reclamation that resulted from rapid increase of rural population and improvement of irrigation capacity, (3) forest area decreased 20.9% due to deforestation for urban area and agricultural use, (4) barren land area decreased 78.2% due to cultivation for agricultural use, and (5) water and wetland decreased 39.1 and 67.1%, respectively, due to exploitation of surface water and decrease of recharge from groundwater to surface water that resulted from over exploitation of groundwater.  相似文献   

18.
面向对象的遥感图像分类方法研究   总被引：5，自引：2，他引：3  
影响遥感图像分类效果的主要因素之一是空间分辨率。通过融合多分辨率遥感图像,引入面向对象的思想,有效地克服了多光谱图像空间分辨率低的问题。该方法由图像分割和分类等一系列技术组成,首先用基于区域分割法则对正射校正SPOT图像进行分割,然后把它作为参考用最大似然法分类器和其他一些经验规则对TM图像进行分类。对土地覆盖图分类进行精度测试,取得了良好的应用效果。  相似文献   

19.
Object-based image analysis was used to map land use in the Panxie coal mining area, East China, where long-term underground coal mines have been exploited since the 1980s. A rule-based classification approach was developed for a Pleiades image to identify the desired land use classes, and the same rule-based classification strategies, after the threshold values had been modified slightly, were applied to the Landsat series images. Five land use classes were successfully captured with overall accuracies of between 80 and 94%. The classification approach was validated for its flexibility and robustness. Multitemporal classification results indicated that land use changed considerably in the Panxie coal mining area from 1989 to 2013. The urban, coal and coal gangue, and water areas increased rapidly in line with the growth in mine production. Urban areas increased from 9.38 to 20.92% and showed a tendency to increase around the coal mines. From 1989 to 2013 the coal and coal gangue area increased by 40-fold, from 0.02 to 0.58%. Similarly, the water area increased from 2.77 to 7.84% over this time period, mainly attributable to the spread of waterlogged areas. The waterlogged areas increased to about 2900 ha in 2013, which was about 80 times more than their area in 1989. In contrast, the area of cultivated land was negatively related to the increase in mine production and decreased from 73.11 to 57.25%. The results of this study provide a valuable basis for sustainable land management and environmental planning in the Panxie coal mining area.  相似文献   

20.
The present study designed to monitor and predict land cover change (LCC) in addition to characterizing LCC and its dynamics over Al-Baha region, Kingdom of Saudi Arabia, by utilizing remote sensing and GIS-cellular automata model (Markov-CA). Moreover, to determine the effect of rainwater storage reservoirs as a driver to the expansion of irrigated cropland. Eight Landsat 5/7 TM/ETM images from 1975 to 2010 were analyzed and ultimately utilized in categorizing LC. The LC maps classified into four main classes: bare soil, sparsely vegetated, forest and shrub land, and irrigated cropland. The quantification of LCC for the analyzed categories showed that bare soil and sparsely vegetated was the largest classes throughout the study period, followed by forest, shrubland, and irrigated cropland. The processes of LCC in the study area were not constant, and varied from one class to another. There were two stages in bare soil change, an increase stage (1975–1995) and decline stage (1995–2010), and the construction of 25 rainwater-harvesting dams in the region was the turning point in bare soil change. The greatest increase was observed in irrigated cropland after 1995 in the expense of the other three categories as an effect of extensive rainwater harvesting practices. Losses were evident in forest and shrubland and sparsely vegetated land during the first stage (1975–1995) with 5.4 and 25.6 % of total area in 1995, while in 1975, they covered more than 13.8 and 32.7 % of total area. During the second stage (1995–2010), forest and shrubland witnessed a significant increase from 1569.17 km2 in 1975 to 1840.87 km2 in 2010. Irrigated cropland underwent the greatest growth (from 422.766 km2 in 1975 to 1819.931 km2 in 2010) during the entire study period, and this agriculture expansion reached its zenith in the 2000s. Markov-CA simulation in 2050 predicts a continuing upward trend in irrigated cropland and forest and shrubland areas, as well as a downward trend in bare soil and sparsely vegetated areas; the spatial distribution prediction indicates that irrigated cropland will expand around reservoirs and the mountain areas. The validation result showed that the model successfully identified the state of land cover in 2010 with 97 % agreement between the actual and projected cover. The output of this study would be useful for decision makers and LC/land use planners in Saudi Arabia and similar arid regions.  相似文献   

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