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基于SPOT 5和北京一号小卫星数据的北京北部山区土壤侵蚀变化研究 总被引：2，自引：0，他引：2
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
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《地理空间信息》2016,(4)
基于修正的土壤流失方程(RUSLE),运用RS和GIS技术对葫芦岛市的土壤侵蚀状况进行分析。结果表明,葫芦岛市年均土壤侵蚀量17 867 598.32 t,年均土壤侵蚀模数为16.13 t/(hm2×a),属于轻度侵蚀。葫芦岛市中度侵蚀以上的土壤侵蚀面积占总侵蚀面积的11.31%,土壤侵蚀模数占总侵蚀量的40.17%。中度侵蚀以下的土壤侵蚀面积占总侵蚀面积的88.96%,土壤侵蚀量占总侵蚀量的59.83%,研究区土壤侵蚀空间差异性大。分析土壤侵蚀与坡度和土地利用之间的关系表明,6°~25°为研究区主要侵蚀坡度段,裸土地、旱地、林地和草地是研究区土壤侵蚀的主要发生区,葫芦岛市应将其列为水土保持重点治理对象,采取有效措施,改善土壤侵蚀现状。 相似文献
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黄河三角洲盐碱地遥感调查研究 总被引：85，自引：1，他引：85
土壤盐渍化是干旱、半干旱农业的主要的土地退化问题，有关盐碱地的性质、范围、面积、地理分布及盐渍程度等方面的实时、可靠的信息，对治理盐碱地防止其进一步退化和进行农业可持续发展规划至关重要，提出运用Landsat TM遥感数据来获取这些信息。基于地物光谱特征、野外调查建立的地物与影像之间的关系以及土壤和地下水监测数据的辅助，将常规监督分类法和改进的图像分类法两种方法相结合，提取了不同盐渍程度的盐碱地，即光板地14477．67hm^2，重度盐碱地52086．33hm^2，中度盐碱地86699．61hm^2，轻度盐碱地215001.7hm^2，占黄河三角洲总面积的近二分之一（47．4％），除此之外，水体，滩涂，非盐碱地等也作了区分。 相似文献
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江淮生态经济区拥有独特的生态资源优势,是江苏省"1+3"重点功能区战略的重要组成部分,且在新时期,江苏发展中的地位不断凸显,作为省级生态重点建设区,了解区域内的水土流失状况至关重要.本文基于修正通用水土流失方程RULSE,结合地理国情数据,从时空视角对2015—2018年江淮生态经济区的水土流失情况进行评估分析,得到以下主要结论:1)近几年来,江淮生态经济区西部地区水土流失强度高于东部地区,但整体上处于微度和轻度侵蚀状态;2)2015—2018年,江淮生态经济区微度侵蚀水土流失面积增加,轻度侵蚀以上水土流失面积减少,除宿豫区外,其他区县中度侵蚀以上水土流失面积均呈减少状态,总体上呈现好转的趋势. 相似文献
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针对神东矿区土壤侵蚀生态破坏及煤炭开采对矿井采区土壤侵蚀的影响问题,该文基于RUSLE模型,提出一种基于矿区和矿井尺度探究矿区土壤侵蚀演变特征并结合地理探测器进行驱动力分析的研究方法。结果表明:(1)矿区尺度上土壤侵蚀呈加重趋势,1989—2019年土壤侵蚀量增加30.28×10~5 t,空间上以微度和轻度侵蚀散布全区,中度和强度侵蚀次之,极强度和剧烈侵蚀最少;(2)矿井尺度上,补连塔、榆家梁矿井受到采矿的负面影响,大柳塔矿井受到生态措施的正面影响,活鸡兔、石圪台矿井受到的负面影响被正面影响消除;(3)各因子对土壤侵蚀的解释力为:坡度>土地利用类型>降雨量>植被覆盖度,因子交互作用的解释力强于单因子,坡度>35°,降雨为416.10～420.69 mm、植被覆盖度为0.5～0.6及未利用地的区域为土壤侵蚀高风险区。该研究方法可摸清矿区的土壤侵蚀变化规律以及矿井受采矿活动的干扰,为矿区实行生态管理提供决策支持。 相似文献
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以松花江流域为例,在RS,GIS技术的支持下,借助不同时期Landsat TM影像数据,研究1995,2005年土壤侵蚀时空格局及其动态变化。结果表明:水力侵蚀是松花江流域土壤侵蚀的主要形式,研究区域以微度侵蚀为主,所占比例分别为68.98%和68.32%,研究区域总体水土保持良好;微度侵蚀保留率最大,强度侵蚀的转出率最大;研究土壤侵蚀动态变化有助于开展流域水土流失治理和生态安全保护。 相似文献
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Sanjay K Gupta M Hussain M Ahmed A S Pandey P Singh K M Saini S N Das 《Journal of the Indian Society of Remote Sensing》1998,26(4):161-168
In this study, an attempt has keen made for the identification, categorisation and mapping of degraded lands in Palamau district of Bihar using remotely sensed data (IRS-1A, raise colour composite, on 1:50,000 scale), It was observed that water erosion is the main cause of land degradation affecting 6.27 per cent area of the district, of which 5.22 per cent is subjected to severe to very severe erosion and remaining 1.05 per cent is moderately to severely gulleid land Degradation due to rock quarries, mine spoils and dumps accounted for only 0.01 per cent of the district area. Degraded lands were mostly confined to agricultural areas (4.76%) follwed by forest lands (1.10%) and opert-scrub/pastures (0.42%), respectively, Subdivision-wise categorisation of degraded lands was also attempted for efficient location-speeific reclamation planning and easy monitoring. 相似文献
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Gopal Krishan S. P. S. Kushwaha A. Velmurugan 《Journal of the Indian Society of Remote Sensing》2009,37(1):119-128
A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the
Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area,
which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status
were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded
area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection
measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the
catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these
measures will reduce the silt load in the river Tons and eventually, in river Yamuna. 相似文献
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Tongyu County in Northeast China is highly prone to land degradation due to its fragile physical settings characterized by a flat topography, a semi-arid climate, and a shallow groundwater table. This study aims to determine the causes of land degradation through detecting the long-term trend of land cover changes. Degraded lands were mapped from satellite images recorded in 1992 and 2002. These land cover maps revealed that the area subject to land degradation in the form of soil salinization, waterlogging and desertification increased from 2400 to 4214 km2, in sharp contrast to most severely degraded land that decreased by 122.5 km2. Newly degraded land stems from productive farmland (263 km2), harvested farmland (551 km2), and grassland (468 km2). Therefore, the worsened degradation situation is attributed to excessive reclamation of grassland for farming, over cultivation, overgrazing, and deforestation. Mechanical, biological, ecological and engineering means should be adopted to rehabilitate the degraded land. 相似文献
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G P OBI Reddy A K Maji C V Srinivas M Velayutham 《Journal of the Indian Society of Remote Sensing》2002,30(1-2):15-31
In recent years, the use of remotely sensed data and Geographic Information System (GIS) applications has been found increasing in a wide range of resources inventory, mapping, analysis, monitoring and environmental management. Remote sensing data provides an opportunity for better observation and systematic analysis of terrain conditions following the synoptic and multi-spectral coverage. In the present study, the geomorphological analysis reveals that various denudational and depositional landforms have been analysed and mapped. The soil depth ranges from extremely shallow in isolated mounds to very deep in the pediplains. Based on the slope gradient, morphometry, soil depth, vegetation cover and image characteristics of standard FCC imagery of IRS-1D LISS-III data, four categories of eroded lands i.e., very severe, severe, moderate and nil to slight have been identified and mapped. The integrated analysis of slope, geomorphology and degraded lands layers in GIS revealed that the pediplains, rolling plains and subdued plateau are associated with very severe land degradation and accounts for 6.05%, 3.85% and 3.47% of total area respectively. The analysis of percentage of degraded lands at geomorphic sub unit level indicates that severe land degradation process is dominant in the dissected ridges, isolated mounds, escarpments and plateau spurs. The remote sensing data and GIS based detailed geomorphological and degraded lands analysis ensure better understanding of landform-eroded lands relationship and distribution to assess the status of land degradation at micro geomorphic unit for reclamation, geo-environmental planning and management. Similar study also helps in the areas of natural resource management, environmental planning and management, watershed management and hazards monitoring and mitigation. 相似文献
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Degraded lands in Vidarbha region of Maharashtra were assessed using remote sensing technique. District wise land degradation maps were generated on 1:25,0000 scale through visual interpretation of lRS 1A data supported by limited ground survey. It was observed that degraded lands occupy nearly 2.1 million ha or 21.5 per cent of the total geographical area. The analysis of district wise land degradation statistics indicate that. Yavatmal and Akola districts are graded as having most problematic lands in the region. Nagpur, Amravati, Buldana and Wardha districts are categorised as moderately problematic, whereas Gadchiroli, Chandrapur and Bhandara are districts having least problem of degradation. Among the major land forms, the largest degraded area is associated with undifferentiated plain accounting for 1.1 million ha or 12 per cent of the total area of region, which is mostly under cultivation. It thus follows that problem of degradation is more rampant in agricultural land than forest/waste lands. 相似文献
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The Tibetan Plateau in Western China is the world’s largest alpine landscape, sheltering a rich diversity of native flora and fauna. In the past few decades, the Tibetan Plateau was found to suffer from grassland degradation processes. Grassland degradation is assumed to not only endanger biodiversity but also to increase the risk for natural hazards in other parts of the country which are ecologically and hydrologically connected to the area. However, the mechanisms behind the degradation processes remain poorly understood due to scarce baseline data and insufficient scientific research.We argue that remote sensing data can help to better understand degradation processes and patterns by: (1) identifying the distribution of severely degraded areas and (2) comparing the patterns of key spatial attributes of the identified areas (altitude above sea level, aspect, slope, administrative districts) with existing theories on degradation drivers. Therefore, we applied four Landsat 8 images covering large portions of the three counties Jigzhi, Baima and Darlag in the Eastern Tibetan Plateau. The dates of the Landsat scenes were selected to cover differing phenological stages of the ecosystem. Reference data were collected with a remotely piloted aircraft and a standard consumer RGB camera. To exploit the phenological information in the Landsat data as well as deal with the problem of cloud cover in multiple images, we developed a straightforward PCA-based procedure to merge the Landsat scenes. The merged Landsat data served as input to a supervised support vector machine classification which was validated with an iterative bootstrap procedure and an additional independent validation set. The considered classes were “high-cover grassland”, “grassland (including several stages of grassland vitality)”, “(severely) degraded grassland”, “green shrubland”, “grey shrubland”, “urban areas” and “water bodies”. Kappa accuracies ranged between 0.84 and 0.93 in the iterative procedure, while the independent validation led to a kappa accuracy of 0.76. Mean producer’s and user’s accuracies for all classes were higher than 80%, and confusion mainly occurred between the two shrubland classes and between the three grassland classes.Analysis of the slope, aspect and altitude values of the vegetation classes revealed that the degraded areas mostly occurred at the higher altitudes of the study area (4300–4600 m), with no strong connection to any specific slope or aspect. High-cover grassland was mostly located on sunny slopes at lower altitudes (less than 4300 m), while shrubland preferred shady, relatively steep slopes across all altitudes. These observations proved to be stable across the examined counties, while the proportions of land-cover classes differed between the examined regions. Most counties showed 5–7% severely degraded land cover. Darlag, the county located at the edge of the permafrost zone, and featuring the highest average altitude and lowest annual temperature and precipitation, was found to suffer from larger areas of severe degradation (14%).Therefore, our findings support a strong connection between degradation patterns and climatic as well as altitudinal gradients, with an increased degradation risk for high altitude areas and areas in colder and drier climatic zones. This is relevant information for pastoral management to avoid further degradation of high altitude pastures. 相似文献
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M. S. S. Nagaraju G. P. Obi Reddy A. K. Maji Rajeev Srivastava P. Raja A. K. Barthwal 《Journal of the Indian Society of Remote Sensing》2011,39(1):51-61
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
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G. P. Obi Reddy M. S. S. Nagaraju I. K. Ramteke Dipak Sarkar 《Journal of the Indian Society of Remote Sensing》2013,41(2):331-343
In the present study, landforms and soils have been characterized in Borgaon Manju watershed of basaltic terrain located in Akola district, Maharashtra, Central India. Terrain characterization using Shuttle Radar Topography Mission (SRTM) elevation data (90 m) and IRS-P6 LISS IV data in conjunction with adequate field surveys shows nine distinct landforms. Soil resource inventory shows fourteen soil series in the study area. Soils formed on gently sloping (3–8 %) subdued plateau are very shallow (23 cm), moderately well drained, moderate (15–40 %) surface stoniness, severely eroded, clayey and slightly alkaline in reaction, whereas, the soils formed on level to nearly level (0–1 %) slope in the main valley are very deep (>150 cm), well drained, very slight (<3 %) surface stoniness, moderately eroded with clayey surface and moderately alkaline in reaction. Soils in the watershed are grouped into Lithic Ustorthents, Vertic Haplustepts, Calcic Haplustepts, Typic Haplustepts, Typic Haplusterts and Sodic Calciusterts. The study demonstrates that the analysis of SRTM elevation data and IRS P6–IV data in Geographic Information System (GIS) with adequate field surveys helps in characterization of landforms and soils in analysis of landscape-soil relationship. 相似文献
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K M Saini T K Deb P P Mitra S G Ghatol A K Sen N C Saha S N Das 《Journal of the Indian Society of Remote Sensing》1999,27(1):23-30
Land degradation in Puruliya district, West Bengal was assessed using remote sensing techniques. Analysis of satellite data (False Colour Composite in 1:50,000 scale) was carried out visually and subsequent ground verification and translation of imgae interpretation units into various categories of degraded lands. The results indicate that 31.8 per cent area of the district suffers from one or the other kind of land degradation. Water induced soil erosion is the major problem which accounts for 31.3 per cent area of the district. Land degradation due to waterlogging is limited to only 0.3 per cent area whereas 0.2 per cent area is degraded due to rock quarries, brick kiln and indus-trial effluents. 相似文献
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The Landsat (MSS and TM), SPOT (PLA and MLA) and IRS (LISS-I and LISS-II) images of crop free period (April, May), rainfed crop (October) and rabi irrigated crop (January, February) have been evaluated for their capabilities of mapping (1) primary salt affected soils: (slightly, moderately and severely) (2) saline water irrigated saline soils, (3) sodic water irrigated sodic soils and (4) salt affected soils due to tank seepage in the arid region of Rajasthan. The moderately and severe salt affected soils could be mapped with Landsat, (IRS LISS-I) and SPOT, images of any season. However, the summer season imagery provided maximum extent of salt affected soils. The LISS-II imagery also provided delineation of slightly salt affected soils in addition to the moderate and severely salt affected soils. The delineation of saline and sodic water irrigated areas was possible by using Landsat False Colour Composite for the January month by their characteristic reflectance, existing cropping pattern and the quality of irrigation water being used in the area. The IRS (LISS-II) and SPOT PLA images for the May month were also used for mapping of saline and sodic water irrigated soils. 相似文献