遥感技术在小流域水土流失快速调查中的应用——以老高川地区为例

以SPOT与TM融合图像为遥感信息源,对孤山川流域老高川地区进行1:5万比例尺水土流失遥感调查,分析了小流域水土流失的主要影响因素,指出了遥感技术与地理信息系统结合是遥感技术在小流域水土流失快速调查的发展方向.     

张家界市水土流失遥感调查与监测

以1975年MSS、2000年TM/ETM和2007年SPOT 5共3个时相卫星遥感数据为主要数据源,利用遥感图像处理和信息提取技术,结合土地利用和地形图等资料,提取张家界市水土流失状况信息,分析近32 a水土流失动态变化特征和规律,并提出治理水土流失措施的建议.     

遥感卫星数据产品分类分级规则研究

随着遥感卫星应用的发展,多源、多时相、多尺度以及不同类型遥感卫星的数据综合集成应用以及与地面观测信息集成,对遥感信息产品进行深度开发利用正在成为遥感应用的重要趋势。目前不同国家和地区、不同系列的遥感卫星数据产品分别采用不同的分类分级方案,难以适应多源、多系列地理空间信息整合应用的需求。本文从遥感应用对遥感卫星数据产品分类分级的需求出发,分析了目前主要遥感卫星的产品系列及其数据产品分类分级规则,参考了正在研究的相关国际标准,遵循系统性、科学性、完整性、兼容性、可操作性和可扩充性原则,研究提出了中国遥感卫星数据产品分类分级的规则。该规则以卫星载荷采用的遥感探测光谱特征及其数据获取方式作为分类依据,以卫星遥感数据的处理水平作为分级依据,建立统一的遥感卫星数据产品的分类分级体系。该规则与正在研究制订的相关国际标准保持一致,不但覆盖目前广泛应用的各类遥感卫星数据产品,而且能方便地建立与现有遥感卫星数据产品分类分级方案的映射关系,并且对未来的数据产品的分类分级留有比较充分的可扩充性,为遥感卫星数据产品分类分级指标体系的研究和相关国家标准的研制提供了依据。     

长江中下游流域水土流失特征及相关地质因子分析

以"长江流域水土流失遥感凋查与监测"项目部分研究成果为依据,选择经济活力较强、经济发展较快的长江中下游地区,分析了该区水土流失的分布特征,研究了诱发水土流失的人类不合理活动,探讨了相关地质因子与水土流失的成因关系,总结了水土流失的主要类型及其变化趋势,并提出了合理防治的建议.     

资源三号影像在矿山开发遥感调查中的应用

针对目前矿山开发遥感调查多是依赖国外影像且监管手段滞后的问题,本文在矿产资源开发遥感调查基础上,以四川省攀枝花市红格钒钛磁铁矿区为例,基于资源三号卫星影像,研究了国产高分辨率卫星影像在矿山开发遥感调查中应用的可行性。同时,利用C#语言,研发了矿山开发动态监测系统,提高了矿山开发遥感调查的实时性与可靠性,提升了矿山开发监管工作的效率。     

雅鲁藏布江中游流域水土流失动态变化

以雅鲁藏布江中游流域作为研究区域,运用遥感和地理信息系统技术对2000年、2005年、2009年3个时期的遥感影像处理并提取水土流失因子,通过转移概率矩阵对雅鲁藏布江中游流域的水土流失动态变化进行深入研究,并运用马尔科夫模型预测了2010年-2020年雅鲁藏布江中游流域水土流失变化情况。研究发现：2000年-2005年...     

京九铁路赣南段沿线地区水土流失特征遥感分析

京九铁路赣南段沿线地区是我国南方水土流失最严重地区之一,也是我国南方一个典型的水土流失区。本文根据遥感调查结果,较详细地论述了该区水土流失的类型、分布特征、发展趋势,并分析了水土流失产生的原因及其造成的危害,以便为京九铁路沿线地区的经济开发、国土整治和环境评价提供科学依据。     

基于坡谱和信息熵的水土保持研究——以湖南省三个县为例

湖南省是我国水土流失较严重的地区,而地形、地貌是造成水土流失的重要因素之一。本文针对不同地形地貌特征对水土流失情况影响进行定量分析研究,从县域尺度选取了湘阴县、桃江县、桂东县三县不同典型地貌特征,通过Arc GIS软件利用ASTER和SRTM数字高程数据提取坡度值,分别按照间距为1°的等差分级方法和湖南省水土保持临界坡度的分级方法,绘制了地面坡谱图,进一步计算获得了坡谱信息熵。结果表明:湘阴县、桃江县、桂东县地貌坡度1°分级信息熵由小变大,体现了地貌形态在空间的变化特征;而各县临界坡度分级信息熵的大小反映了各地水土流失情况,有效地证实了坡谱信息熵参数能够定量分析和反映不同区域地貌起伏复杂程度及水土保持情况。     

从遥感地质环境角度研究长江流域水土流失状况及成因

利用2000年前后获取的TM/ETM遥感影像,结合其他资料,提取长江流域水土流失状况信息(包括水土流失的类型、面积和强度),总结该流域内水土流失分布规律,从地质环境角度研究水土流失的现状和变化原因,从地学角度提出水土流失治理建议.     

区域生态遥感的发展与未来

结合生态遥感应用技术的发展, 介绍了中国科学院遥感应用研究所农业与生态遥感研究室在区域生态遥感研究领域的发展现状与未来。研究室重点开展植被结构、蒸散发、降水量、土壤湿度、水土流失和热环境等生态因子的遥感监测技术研究, 以三峡库区、海河流域、三北地区为研究区, 开展生态遥感的综合应用。研究室以全球变化条件下的水生态管理、工程生态效应评估、区域人地关系等作为未来区域生态遥感应用的重点发展方向。     

土壤水力侵蚀的遥感信息模型研究——以江西省为例

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。     

基于遥感和GIS的环境敏感性分区研究

文章在对邹城区域生态环境状况进行分析和判别的基础上,确定了邹城环境敏感性单因子及分级依据。利用SRTM3数据,提取了邹城区域高程分级和坡度数据;利用TM遥感影像,通过监督分类和和人机交互解译方法提取植被要素和土地利用/覆被数据。结合收集到的矿产资源、自然保护及风景区及采煤塌陷风险分布专题信息建立敏感性分析数据库,使用ARCGIS平台进行空间叠加分析,得到邹城区域环境敏感性分区图。发现邹城区域重度敏感区主要分布在坡度较大、易发生水土流失地区以及山地;中度敏感区主要包括地下水源地、贡献较大的水体、自然保护区和部分塌陷风险较大的区域;轻度敏感区多为天然及人工林地。对于不同敏感级别的地区应有针对性地采取保护性开发,并在土地利用中尽量避免对重度及中度敏感区的干预。最后指出了应用RS和GIS空间信息技术进行敏感性分区的作用和意义。     

区域尺度海河流域水土流失风险评估

借鉴USLE的因子选择及综合方法,在遥感和GIS的支撑下对海河流域的水土流失风险进行评估,并对其空间分布特征进行分析.结果表明:海河流域山区水土流失风险显著高于平原地区,北三河山区水土流失风险最低,太行山区最高,永定河上游介于两者之间;水土流失风险"很低"等级主要分布在小于5°的平坦地区,"中"、"高"水土流失风险面积...     

An integrated approach for prioritization of reservoir catchment using remote sensing and geographic information system techniques

This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning.     

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

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.     

Soil erosion assessment in Rangit catchment,India through a process-based model in the geospatial environment

The accurate assessment of soil erosion in the spatial environment can give valuable input in designing reservoirs and for preparing watershed management action plans. Rangit River in northeastern India is affected by severe soil erosion, causing reduction in its reservoir capacity. The main aim of the paper is to estimate the soil erosion in the Rangit catchment, India through a process-based soil erosion model that integrates remote sensing and field data in the geospatial domain, and also to identify the problem areas for further watershed management action plans. Various topographic parameters that were derived from land use, soil texture and a digital elevation model were used for the estimation of soil erosion. The Morgan, Morgan and Finny model was used to compute soil erosion. Based on the drainage pattern, the catchment was divided into eight sub-catchments for detailed study. Annual soil erosion was estimated for four years from 2002 to 2005 using the corresponding year’s meteorological data. Estimated soil erosion was compared with the field data in each year and found very good correlation.     

Prediction of soil loss differences and sediment accumulation at the Nilufer creek watershed,Turkey, using multiyear satellite data in a GIS

This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km^?2 y^?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area.     

近30年来密云水库上游水土流失动态监测

使用修正的通用土壤流失方程RUSLE,综合考虑降雨、土壤可蚀性、地形、土地覆盖和水土保持措施等因素,计算得密云水库上游地区1990年、2000年和2008年3期的土壤侵蚀数据,并对土壤侵蚀变化结果及其原因进行分析,发现：①研究区近20年水土流失状况经历由加剧到减轻的过程,但总体来说是减轻的,1990～2008年减轻区面积和加剧区面积分别为3083．11km。和2287．71km2;②研究区水土流失变化的原因主要为以土地利用类型变化为特征的人为因素,降雨也有影响,而与坡度没有关系。     

中国北方沙尘灾害特点及其下垫面状况的遥感监测

2000年春季,中国北方地区多次受到沙尘灾害的影响,对生产、生活活动造成了多方面的不利影响。采用遥感和GIS技术进行沙尘灾害的过程监测、空间特点分析和下垫面状况分析是一个有效的技术方法,通过对沙尘灾害发生、发展的环境条件的了解,可以减轻沙尘天气的危害、防治等一系列决策措施的制定、实施提供客观、及时的空间信息,有助于制定和实施区域生态环境保护措施,以便减少沙尘天气的次数和减轻灾害性天气的危害程度。