首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 593 毫秒
1.
In the present study efforts have been made to identify and map areas affected by various land degradation processes with the aid of Landsat TM imagery data of 1988 and ground truth verification. The kind, extent and degree of land degradation have been mapped. In an area of over 4,124 sq. km. 51% was affected by water erosion and 30% area by wind erosion. Nearly 1.14% area is affected by salinity. Degradation due to combined effect of water and wind erosion and water erosion and salinization has affected 8.20% of the study area. 1.53% area is free from any hazard. Remaining 7.85% area comes under hills and rivers. Nearly 44 percent of the affected area is subjected to moderate and severe degradation which can easily be combatted by techniques referred.  相似文献   

2.
Soil erosion is one of the major causes of land degradation in arid areas. Soil erosion models, e.g. the revised universal soil loss equation (RUSLE), use arithmetical expressions to explore relationships among various processes occurring in the terrain. The established model includes soil parameters, slope, climate and human activities to estimate the water erosion rate and sediment yield. In this study, an approach was adopted to integrate RUSLE model and geographic information system to detect erosion vulnerability and determine the soil erosion risk in the study area. The study area is situated in the Eastern Desert, Egypt. Ground truth data were examined to represent two regions: Luxor-Suhag and Suhag–ElMinya. These regions are exampled by four dry valleys named Sannor, Tarfa, Asyut and Qena, which are planned for agricultural development. The results indicate high risk of water erosion and sediment load discharge into the cultivated land in Luxor–Suhag region. The other region of Suhag–ElMinya is moderately affected by water and sediment load discharge. A higher soil erosion rate was found in Qena wadi followed by Asyut, then Tarfa and Sannur, respectively.  相似文献   

3.
Soil erosion modeling using MMF model -A remote sensing and GIS perspective   总被引：1，自引：0，他引：1  
Hardly any part of the world has remained unchanged since the arrival of the speciesHomo sapiens including the mountain ecosystems. Himalayan physiographic unit of India in due course has become populated and is tolerating all kinds of human interventions. Soil erosion in this region has been identified as a major problem due to both natural and anthropogenic factors. Remote sensing and Geographical Information system (GIS) techniques hold great promises in the assessment and conservation of natural resources including the surface soil. The major objective of the present study was to apply a process based model to quantify soil erosion and to prioritize the sub-watershed on this basis. The sub-watershed located at Jakhan rao area of Western Dun in lower Himalayan belt was taken as the test site for the study at 1: 50,000 scale. Deforestation, unscientific agricultural practices, terrace farming, cattle grazing and land degradation in the sub-watershed are some of the anthropogenic factors causing soil erosion in the area. Here, MMF model was used for estimation of soil erosion by incorporating layers derived from both remote sensing and ancillary data. IRS 1C LISS III satellite data was used for the preparation of land use map that was used to derive RD map, BD map and K map. Digital Elevation Model (DEM) provided slope map, an intermediate layer used in equation 6 to generate G map, and soil map provided MS map, BD map and K map. The above intermediate layers generated were then integrated in GIS domain to estimate the amount of soil erosion in the sub-watershed area. Results show high values 4572.333 kg/m2 for G map, which depicted transport capacity of overland flow. Comparatively lower values 13.15, and 7.98 kg/m2were observed for F map, which depicted soil detachment by raindrop impact. The subtracted image of the aforesaid layers produced the real picture, where in the highest value 3.770 kg/m2 was found in the midland region of the site. The crossed erosion map was then classified into different erosion classes for sub-watershed area. This study illustrates the applications of remote sensing and GIS techniques for soil erosion modeling.  相似文献   

4.
The study area is characterized by low and fluctuating rainfall pattern, thin soil cover, predominantly rain-fed farming with low productivity coupled with intensive mining activities, urbanization, deforestation, wastelands and unwise utilization of natural resources causing human induced environmental degradation and ecological imbalances, that warrant sustainable development and optimum management of land resources. Spatial information related to existing geology, land use/land cover, physiography, slope and soils has been derived through remote sensing, collateral data and field survey and used as inputs in a widely used erosion model (Universal Soil Loss Equation) in India to compute soil loss (t/ha/yr) in GIS. The study area has been delineated into very slight (<5 t/ha/yr), slight (5–10 t/ha/yr), moderate (10–15 t/ha/yr), moderately severe (15–20 t/ha/yr), severe (20–40 t/ha/yr) and very severe (>40 t/ha/yr) soil erosion classes. The study indicate that 45.4 thousand ha. (13.7% of TGA) is under moderate, moderately severe, severe and very severe soil erosion categories. The physiographic unit wise analysis of soil loss in different landscapes have indicated the sensitive areas, that has helped to prioritize development and management plans for soil and water conservation measures and suitable interventions like afforestation, agro-forestry, agri-horticulture, silvipasture systems which will result in the improvement of productivity of these lands, protect the environment from further degradation and for the ecological sustenance.  相似文献   

5.
永定河治理区土壤侵蚀时空变化分析   总被引：1，自引：0，他引：1  
本文利用“北京一号”小卫星32 m多光谱数据提取研究区的植被覆盖信息与土地利用信息,利用1∶50 000DEM数据提取研究区坡度信息,采用中华人民共和国水利部部颁标准“土壤侵蚀分类分级标准SL 190-96”,评价研究区的水蚀风险等级;并结合全国第二次土壤侵蚀遥感(LandsatTM)调查数据,进行土壤侵蚀时空变化分析...  相似文献   

6.
This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km2, respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km2, respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km2. Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha?1 year?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha?1 year?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.  相似文献   

7.
The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16 t ha−1 a−1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.  相似文献   

8.
缅甸中部干旱地区土壤侵蚀的分析   总被引：3，自引：0，他引：3  
李红旮  崔伟宏 《遥感学报》2000,4(3):233-238246
伊落瓦底江中游是缅甸中部著名的干热地带,地壤流失严重。在研究中,首先利用遥感图像（１９９５年的ＴＭ图像,１９９８年的ＴＭ和ＳＰＯＴ图像）进行判读和土壤侵蚀地面实况的野外验证。同时,根据影响封侵蚀的生态环境因子,建立实验区的数字高程模型和窨数据库。然后,在地理信息系统（ＧＩＳ）中进行土壤侵蚀测定以及生态环境因子相关分析。影响土壤侵镅的生态环境因子很多,但植被和耕作方式是人们可以控制的因子。在此基础上  相似文献   

9.
通过利用Terra/Aqua卫星上搭载的MODIS传感器计算获取的16d合成植被指数产品(MOD13A2),进一步按照最大值合成法计算月合成光谱植被指数,按照USLE模型月模式评价江西省2005年土壤侵蚀,并与传统的USLE模型年模式计算的结果进行了比较。  相似文献   

10.
利用2004年10月SPOT 5卫星影像及2007年9月北京一号小卫星多光谱和全色影像,以植被覆盖度、坡度、土壤可蚀性和土地利用4种影响因子作为辅助数据,进行土壤侵蚀信息提取。利用所提取的信息,分析2004~2007年北京北部山区土壤侵蚀在空间、面积上的变化状况、强度类型转化状况以及变化的驱动力。分析结果表明,北京北部山区土壤侵蚀主要为轻度侵蚀与中度侵蚀,以轻度侵蚀为主; 2004~2007年北京北部山区虽然局部地区土壤侵蚀强度增强,但土壤侵蚀总面积减少,大体上呈中度→轻度→微度发展趋势,总体状况得到明显改善。  相似文献   

11.
A comparative study of soil erosion modelling by MMF,USLE and RUSLE   总被引：1，自引：0，他引：1  
The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area.  相似文献   

12.
Soil is an integral part of ecosystem nurturing the biological system. Sustainable management of soil resources based on the consideration of constraints is the key to check land degradation and maintain productivity of biological system. To meet the objective remote sensing and GIS technology has been employed for identification of soil constraints in resource potential Bhilwara district. IRS LISS-III FCC images were interpreted for soil constraints using physiography soil approach, verified through field checking and laboratory analysis. On IRS LISS-III FCC images the salt affected soils of Kotri and Taswaria appeared in bright white to light grey tone, smooth texture with white mottles. These were also verified during ground truth and soil analysis for salinity (EC 2.90–3.32 dS m−1) and sodicity (pH 9.50–9.86 and ESP 17.60–19.05). Similarly on the LISS III FCC, constraints due to water erosion near Bir, Sareri and Vijaypura soil series were apparent in light grey to whitish tone, intercepted by medium grey streaks indicating streams and exposed sub-soil. The constraints due to shallow depth associated with rock out crops and hilly areas of Balda and Delwara series appeared in greenish grey tone and coarse texture. There was close relationship between image characteristics, field observation and analytical data.  相似文献   

13.
Soil erosion is a prominent cause of land degradation and desertification in Mediterranean countries. The detrimental effects of soil erosion are exemplified in climate (in particular climate change), topography, human activities, and natural disasters. Forest fires, which are an integral part of Mediterranean ecosystems, are responsible for the destruction of above-and below-ground vegetation that protects against soil erosion. Under this perspective, the estimation of potential soil erosion, especially after fire events, is critical for identifying watersheds that require management to prevent sediment loss, flooding, and increased ecosystem degradation. The objective of this study was to model the potential post-fire soil erosion risk following a large and intensive wildland fire, in order to prioritize protection and management actions at the watershed level in a Mediterranean landscape. Burn severity and preand post-fire land cover/uses were mapped using an ASTER image acquired two years before the fire, air photos acquired shortly after the fire, and a Landsat TM image acquired within one month after-fire. We estimated pre-and post-fire sediment loss using an integrated GIS-based approach, and additionally we analyzed landscape erosion patterns. The overall accuracy of the severity map reached 83%. Severe and heavy potential erosion classes covered approximately 90% of the total area following the fire, compared to 55% before. The fire had a profound effect on the spatial erosion pattern by altering the distribution of the potential erosion classes in 21 out of 24 watersheds, and seven watersheds were identified as being the most vulnerable to post-fire soil erosion. The spatial pattern of the erosion process is important because landscape cover heterogeneity induced especially by fire is a dominant factor controlling runoff generation and erosion rate, and should be considered in post-fire erosion risk assessment.  相似文献   

14.
Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.  相似文献   

15.
长江上游小流域土壤侵蚀动态模拟与分析   总被引：1，自引：0，他引：1  
以长江上游甘肃省尚沟流域为研究区,在遥感影像和GIS空间分析技术支撑下,根据USLE因子算法生成各因子栅格图,借助地图代数运算,估算了尚沟流域1998年和2004年的土壤侵蚀量,并对2004年土壤侵蚀与其环境背景因子进行叠加和空间统计分析。在此基础上,构建了与GIS软件平台集成的地理元胞自动机,模拟了该流域2004年、2010年和2020年土壤侵蚀空间演化情形。结果表明:研究区平均侵蚀量从1998年的6598.1t/km2下降到2004年的5923.3t/km2,侵蚀面积净减少172.3hm2,输沙量减少9.15×104t;1300～1400m的海拔高程带、25～35°坡度带、南坡和旱耕地是发生水土流失的主要区域;经模拟,2010年总侵蚀面积为93.49km2,侵蚀总量73.15×104t,侵蚀模数为5126t/km2,土壤侵蚀状况总体上将有所减缓。  相似文献   

16.
The aim of this study was to map soil erosion on the Mediterranean island of Cyprus. The G2 model, an empirical model for month-time step erosion assessments, was used. Soil losses in Cyprus were mapped at a 100?m cell size, while sediment yields at a sub-basin scale of 0.62?km2 mean size. The results indicated a mean annual erosion rate of 11.75?t?ha?1?y?1, with October and November being the most erosive months. The 34% of the island's surface was found to exceed non-sustainable erosion rates (>10?t?ha?1?y?1), with sclerophyllous vegetation, coniferous forests, and non-irrigated arable land being the most extensive non-sustainable erosive land covers. The mean sediment delivery ratio (SDR) was found to be 0.26, while the mean annual specific sediment yield (SSY) value for Cyprus was found to be 3.32?t?ha?1?y?1. The annual sediment yield of the entire island was found to be 2.746?Mt?y?1. This study was the first to provide complete and detailed erosion figures for Cyprus at a country scale. The geodatabase and all information records of the study are available at the European Soil Data Centre (ESDAC) of the Joint Research Centre (JRC).  相似文献   

17.
ABSTRACT

To assess the effects of the Grain for Green Program (GGP) on soil erosion is essential to support better land management policies in the Chinese Loess Plateau. Studies on the evaluation of the effects of the GGP on soil erosion have garnered heightened attention. However, few studies examined the efficiency of GGP on soil erosion control through spatial relationship analysis. Thus, this study focuses on analyzing the spatial variation relationship between soil erosion and GGP in northern Shaanxi, Chinese Loess Plateau, from 1988 to 2015. The Universal Soil Loss Equation was used to quantify changes in soil erosion at the regional and watershed scales, and the Geographically Weighted Regression model was used to analyze the spatial relationships between land use and land cover (LULC) and soil erosion. Our results indicated that the major characteristic of LULC change during the GGP was a rapid increase of vegetation area and a rapid decrease of cropland. Bare lands contributed to the most serious soil loss, followed by croplands and sparse grasslands. The GGP had a globally positive influence on the decrease in soil erosion over the study area, but the amount of soil erosion in western and northern regions maintained a severe level. Spatial heterogeneity in the nature of the relationships among different vegetation, croplands, and soil erosion was also observed. The change rate of wood and the change rate of soil erosion in northern sub-watershed represented a negative relationship, while the change rate of sparse grassland was negatively correlated to the change rate of soil erosion in 21 sub-watersheds, account for 72% of the study area. The GGP implemented in northern sub-watersheds were more effective for soil erosion control than southern sub-watersheds. We propose that current areas of vegetation can support soil erosion control in the whole northern Shaanxi, but local-scale ecological restoration can be considered in northern sub-watersheds.  相似文献   

18.
Soil is a suitable place for vegetation and plant growth. When this valuable resource is not preserved, shortage of food, erosion and damage of natural resources will be respected. Soil is a heterogeneous, diverse and dynamic system and investigation of its temporal and spatial changes is essential. In this paper spatial variability of some chemical and physical soil were investigated. Three hundred fifty eight soil samples were collected by systematic sampling strategy at 20 cm depth on a regular grid spacing of 500 × 500 m2 under different vegetation cover and processed for analysis in the laboratory. Soil chemical and physical parameters including pH, electrical conductivity, organic carbon, available phosphorus, available nitrogen, available potassium, sulphur, calcium, magnesium and sodium were measured. After data normalization, classical statistical analysis was used to describe soil properties and geo-statistical analysis was used to illustrate spatial correlation of soil characteristics. By using interpolating techniques, spatial distribution of these properties were prepared. Results indicated that calcium and phosphorus had strong and weak spatial dependence, respectively.  相似文献   

19.
安徽省大别山区江子河小流域的水文模拟与分析   总被引：1，自引：0，他引：1  
目前,许多发达国家的研究已经证实,农业非点源污染是导致水环境恶化的主要原因之一。土壤侵蚀与非点源污染是一对密不可分的共生现象,特别在农业非点源污染中,土壤侵蚀是主要的发生形式,是一种重要的非点源污染。本文主要应用目前使用较广泛的非点源污染模型—SWAT模型对淮河流域安徽省大别山区水土流失较严重的江子河小流域进行径流量和泥沙量的模拟,并得到该小流域径流量和泥沙流失量的空间分布图。  相似文献   

20.
Soil erosion which occurs at spatially varying rate is a widespread threat to sustainable resource management at watershed scale. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. The present study focuses application of most widely used Universal Soil Loss Equation (USLE) to determine soil erosion and prioritization of micro-watersheds of Upper Damodar Valley Catchment (UDVC) of India. Annual average soil loss for the entire basin is 23.17 t/ha/yr; for micro-watersheds. High soil loss is observed in 345 micro-watersheds, medium in 159 micro-watersheds and low soil loss is observed in 201 micro-watersheds. It is found that, out of 705 micro-watersheds of UDVC, 453 micro-watersheds are in agreement with AISLUS suggested priority which is based on observed sediment yield, 116 micro-watersheds under predict and 136 micro-watersheds over predict the priority. Geographic Information System (GIS) is applied to prepare various layers of USLE parameters which interactively estimate soil erosion at micro-watershed level. The main advantage of the GIS methodology is in providing quick information on the estimated value of soil loss for any part of the investigated area.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号