卫星遥感技术在永定河流域（河北）土壤侵蚀调查评价中的应用研究

利用Landsat-5TM图像,在分析土壤侵蚀影响因素的基础上,首先进行与土壤侵蚀相关密切的各单项要素的解译;其次,以土壤侵蚀在TM图像上的综合反映为标志进行基本侵蚀图斑的综合解译;第三步通过选定的的土壤侵蚀强度评判模型,对每个基本侵蚀图,由不同权重的各单项要素给出其分值,最后根据综合分值确定每个图斑的土壤侵蚀强度等级。研究结果表明,冀西北地区土壤侵蚀是非常严重的,以轻度侵蚀为下限的侵蚀区面积占全区面积的65％。两大地貌单元区相比,盆地区更严重于山地区。但多时相对比研究也表明,近十几年的治理工作取得了明显成效,土壤蚀的总趋势是向减缓方向发展。     

Geological controls of land degradation as detected by remote sensing: A case study in Los Monegros,north-east Spain

The focus of the work reported in this paper is on the way in which land degradation processes affecting semi-arid Mediterranean environments are enhanced by the operation of external (human-induced) factors. A study of landscape change in the Los Monegros area of Aragon, north-east Spain, over the period 1984-1997 has been undertaken in order to evaluate the effects of the extension of irrigation on the expansion of arable agriculture, and to estimate the consequential effects on the landscape. Radiometrically-calibrated Landsat TM data were combined with ground-based observations (soil and geology maps, plus hydrogeological data) with the aim of analysing temporal change in land cover. A combination of remote sensing methods (linear spectral unmixing and principal components analysis) was used to determine the proportions of individual soil types. Change detection techniques were employed to pick out areas at risk from land degradation processes (increased soil erosion and soil salinization) and to explain the ways in which agricultural land-use practices interact with the geological and hydrogeological characteristics of the study area.     

基于COM的土壤信息系统

应用组件技术建立了开放式的土壤信息系统。提出了适合于土壤信息处理的基于COM的地理信息系统与专业应用软件的接口标准。建立了土壤信息处理组件，内建了土壤质量评价、土地适宜性评价、土壤侵蚀强度评价和土壤侵蚀危险度分级等专业应用模型，并将建成的上壤信息系统在咸宁市进行了系统应用。     

Development of a landslide component for a sediment budget model

Most erosion models focus on overland-flow erosion with fewer incorporating landslide erosion although it is common on hillslopes. Landslide models are typically dynamic, spatially distributed simulations with large data requirements for parameterisation and are often computationally intensive. The Australian SedNet model represents a middle ground between process-based and empirical models and is being modified for New Zealand conditions by incorporating shallow landsliding.We describe a method for implementing a model within SedNetNZ to provide the long-term annual average sediment contribution from shallow landsliding and its spatial distribution. The mass of soil eroded over a defined period is calculated from the landslide probability for each slope class, slope class area, failure depth, soil bulk density, and sediment delivery ratio. Landslide probability is derived from mapping a time series of landslides intersected with DEM-derived slope. The conceptual approach and methodology for parameterisation are suitable for landslide modelling where rainfall-triggered shallow landslides occur.     

Environmental cost of soil erosion in Sri Lanka: tax/subsidy policy options

The on-site and off-site impacts of land degradation, particularly in the form of soil erosion, pose a serious problem in many developing countries. In Sri Lanka, the implementation of wide-ranging policy reforms and institutional changes designed to move the country toward an outward oriented market economy, have strengthened concerns about environmental degradation and the sustainability of the country's natural resource base. The environmental impact of many of the policy reforms and economic changes are determined by complex economy-wide, inter-sectoral interactions. A computable general equilibrium model incorporating soil erosion is developed to analyse the impacts of various policy reforms in Sri Lanka. Our analysis establishes three important results. First, economic losses from soil erosion in Sri Lanka are substantial. Second, trade liberalisation reforms increase national income and marginally reduce soil erosion. Third, while trade liberalisation has a positive impact on soil erosion, complementary policies which directly target soil erosion, such as tax/subsidy incentives, are needed to minimise social losses from soil erosion.     

Application of a spatial decision support system (SDSS) to reduce soil erosion in northern Ethiopia

A spatial decision support system (SDSS) based on multi-criteria and multi-objective decision analysis is applied in a case study in Ethiopia to reduce soil erosion on the basis of reallocation of crops according to their capacity to protect the soil. The case study is carried out in the Adwa district. The SDSS has been implemented using the widespread GIS software IDRISI 32 (release 2) and with the direct involvement of local stakeholders in defining factors and constraints. These are based on land cover-land use, altitude, potential erosion, proximity to roads, water and the relative soil protective capacity of each crop species. A reduction of soil loss from an average of 4.5 t ha⁻¹ yr⁻¹ to values below the risk threshold of soil degradation (1 t ha⁻¹ yr⁻¹) would be achieved through the application of the SDSS results. The biggest impediment to the reallocation exercise, however, is the shortage of cultivable land suitable for cultivation.     

Land-cover changes and potential impacts on soil erosion in the Nan watershed,Thailand

The expansion of built environments and agriculture land in the Nan watershed, Thailand, to support the rapid increase of the national population has resulted in deforestation, thus affecting the ecological balance. This deforestation, especially in high mountainous areas, has led to serious environmental degradation. Recent reports reveal an increasing soil-erosion problem in the watershed. This study analyses land-use and land-cover (LULC) changes and their potential impact on soil erosion during a study period between 1995 and 2005. The 1995, 2000 and 2005 Landsat 5 Thematic Mapper (TM) images were acquired and classified using hybrid classification methods. Cross-tabulation methods and the Markov Chain model were then used to analyse current and future LC changes. A soil risk-assessment model was formulated to identify potential risk areas of soil erosion. The LULC data show that the watershed was predominately covered by 40% closed-canopy forests, 25% paddy fields and 10% croplands. There was a major conversion of forests to agricultural lands and urban areas. The predictive model shows that forests are most likely to convert into paddy fields and croplands. The northern and eastern regions of the watershed have a high potential risk of soil erosion. These findings can be a basis for the design and implementation of sustainable resource management plans and geographically targeted conservation measures.     

土壤侵蚀调查中的遥感应用综述

土壤侵蚀引起土壤肥力下降、土地退化及荒漠化和生态环境恶化等一系列区域性和世界性的重大环境问题。中国是土壤侵蚀最严重的国家之一。遥感是进行环境和灾害动态监测的有效技术手段。自从20世纪70年代以来．人们就开始应用遥感技术进行土壤侵蚀的调查。对遥感技术在土壤侵蚀调查中的应用方法进行概括和汇总，分别是影像判读法、指数提取法、图像分类法、光谱分解和正射影像DEM提法等方法，分析不同方法之间的优缺点以及它们各自的适用范围，并结合当前研究的热点问题，指出未来研究的重点及趋势。     

Soil erosion assessment and simulation by means of SGEOS and ancillary digital data

Abstract

Due to soil erosion processes fertile soils are washed out almost anywhere in the world. Soil erosion protection measures are necessary, especially for food security reasons. This study uses the well-known Universal Soil Loss Equation (USLE) to assess the long-term soil erosion in a small catchment area and to simulate various soil protection alternatives. After completion at this test site the techniques can be applied for larger regions to detect areas that are most afTected by soil erosion and to guide precisely the efficient soil erosion prevention measures that proved to be valuable according to the computer simulation results.

This raster-oriented study uses a very accurate multi-temporal land-use classification to determine the land-cover (C-factor). The other input variables have been determined from ancillary data (e.g., digital elevation model and soil data). The compiled data layers of this geographical information system (GIS) allow the calculation of the long-term soil erosion per pixel as well as inquiries about all data layers for every pixel.

In addition to the resulting soil erosion risk map it is possible to simulate soil protection measures with the computer. This ensures that only the most effective ones are introduced to the field.     

A multilayer perceptron model for the correlation between satellite data and soil vulnerability in the Ferlo,Senegal

ABSTRACT

Soil erosion processes which contribute to desertification and land degradation, constitute major environmental and social issues for the coming decades. This is particularly true in arid areas where rural populations mostly depend on soil ability to support crop production. Assessment of soil erosion across large and quite diverse areas is very difficult but crucial for planning and management of the natural resources. The purpose of this paper is to investigate a prediction model for soil vulnerability to erosion based on the use of the information contained in satellite images. Based on neural networks models, the used approach in this paper aims at checking a correlation between the digital content of satellite images and soil vulnerability factors: erosivity (R), the soil erodibility (K), and the slope length and steepness (LS); vulnerability (V) as described in the RUSLE model. Significant results have been obtained for R and K factors. This promising pilot study was conducted in South Ferlo, Senegal, a region with Sahelian environmental characteristics.     

A software coupling approach to assess low-cost soil conservation strategies for highland agriculture in Vietnam

Soil degradation is an environmental process mainly caused by land use decision-makers that has substantial feedback effects on livelihoods and the environment. To capture these feedback effects and the resulting human-environment interactions, we used an agent-based modeling approach to couple two software packages that simulate soil, water and plant dynamics (LUCIA), and farm decision-making (MP-MAS). We show that such a software coupling approach has advantages over hard-coded model integration as applied by most other comparable studies, as it facilitates combining of increasingly sophisticated individual models and can achieve a well-balanced representation of agricultural systems. Using a numerical application for a small mountainous watershed in northwest Vietnam we show the challenges in model coupling, calibration and partial validation, and explore the properties of the coupled model system. Scenario analysis covering the introduction of low-cost soil conservation techniques indicates that some of these techniques would have an impact on soil erosion, maize productivity and household income levels in the study catchment area under current conditions. However, maize yields and the adoption of soil conservation appear to be sensitive to the price of mineral fertilizers, with lower fertilizer prices impeding the adoption of soil conservation measures. The software coupling approach was able to capture interactions between decision-makers and natural resources, as well as the level of spatial variability, in more detail than the individual models. Still, the greater number of endogenous variables and thus degrees of freedom increased the importance of validation and testing parameter sensitivity of the results.     

Numerical modelling of interfacial soil erosion with viscous incompressible flows

The aim of this study is to develop a numerical model for simulating surface erosion occurring at a fluid/soil interface subject to a flow process. Balance equations with jump relations are used. A penalization procedure including a fictitious domain method is used to compute the Stokes flow around obstacles, in order to avoid body-fitted unstructured meshes and instead use fast and efficient finite volume approximations on Cartesian meshes. The evolution of the water/soil interface is described by using a level set function. The ability of the model to predict the interfacial erosion of soils is confirmed by several numerical simulations.     

黄河流域甘肃片土壤侵蚀遥感普查的初步分析

以TM影像为主要信息源,借助GIS(地理信息系统)软件ARC/INFO作技术支撑,对黄河流域甘肃片土壤侵蚀现状进行普查。通过提取影响土壤侵蚀主导因子并综合分析确定甘肃片土壤侵蚀类型、分布及强度。     

遥感和GIS辅助下的祖厉河流域土壤侵蚀空间变化分析

以遥感数据和观测数据为数据源,基于改进的SEMMED土壤侵蚀模型,对祖厉河流域1999年和2001年土壤侵蚀的空间变换进行了模拟和对比。结果表明,流域土壤侵蚀最严重的区域主要集中在葛家岔站点附近、草滩站附近和北部葛家寨和靖远一带,流域中南部的土壤侵蚀通常小于北部。在北部的屈吴山,以及与宁夏交界的月亮山还有华家岭由于植被覆盖度较高,很好的起到了减少径流,抑制土壤侵蚀的作用。降水的年际差异导致本区的土壤侵蚀年际差异较大。     

Assimilating satellite imagery and visible–near infrared spectroscopy to model and map soil loss by water erosion in Australia

Soil loss causes environmental degradation and reduces agricultural productivity over large areas of the world. Here, we use the latest earth observation data and soil visible–near infrared (vis–NIR) spectroscopy to estimate the factors of the Revised Universal Soil Loss Equation (RUSLE) and to model soil loss by water erosion in Australia. We estimate rainfall erosivity (R) using the Tropical Rainfall Measuring Mission (TRMM); slope length and steepness (L and S) using a 3-arcsec Shuttle Radar Topography Mission (SRTM) digital elevation model; cover management (C) and control practice (P) using the national dynamic land cover dataset (DLCD) of Australia derived from the moderate-resolution imaging spectroradiometer (MODIS); and soil erodibility (K) using vis–NIR estimates of the contents of sand, silt, clay and organic carbon in Australian soil. We model K using a machine-learning algorithm with environmental predictors selected to best capture the factors that influence erodibility and produced a digital map of K. We use the derived RUSLE factors to estimate soil loss at 1-km resolution across the whole of Australia. We found that the potential gross average soil loss by water erosion in Australian is 1.86 t ha⁻¹ y⁻¹ (95% confidence intervals of 1.78 and 1.93 t ha⁻¹ y⁻¹), equivalent to a total of 1242 × 10⁶ tonnes of soil lost annually (95% confidence intervals of 1195 and 1293 t × 10⁶ y⁻¹). Our estimates of erosion are generally smaller than previous continental estimates using the RUSLE, but particularly in croplands, which might indicate that soil conservation practices effectively reduced erosion in Australia. However we also identify localized regions with large erosion in northern Australia and northeastern Queensland. Erosion in these areas carries sediments laden with nitrogen, phosphorus and pollutants from agricultural production into the sea, negatively affecting marine ecosystems. We used the best available data and our results provide better estimates compared to previous assessments. Our approach will be valuable for other large, sparsely sampled areas of the world where assessments of soil erosion are needed.     

Mapping malaria risk in West Africa using a Bayesian nonparametric non-stationary model

Malaria transmission is highly influenced by environmental and climatic conditions but their effects are often not linear. The climate-malaria relation is unlikely to be the same over large areas covered by different agro-ecological zones. Similarly, spatial correlation in malaria transmission arisen mainly due to spatially structured covariates (environmental and human made factors), could vary across the agro-ecological zones, introducing non-stationarity. Malaria prevalence data from West Africa extracted from the “Mapping Malaria Risk in Africa” database were analyzed to produce regional parasitaemia risk maps. A non-stationary geostatistical model was developed assuming that the underlying spatial process is a mixture of separate stationary processes within each zone. Non-linearity in the environmental effects was modeled by separate P-splines in each agro-ecological zone. The model allows smoothing at the borders between the zones. The P-splines approach has better predictive ability than categorizing the covariates as an alternative of modeling non-linearity. Model fit and prediction was handled within a Bayesian framework, using Markov chain Monte Carlo (MCMC) simulations.     

Monitoring desertification and land degradation over sub-Saharan Africa

A desertification monitoring system is developed that uses four indicators derived using continental-scale remotely sensed data: vegetation cover, rain use efficiency (RUE), surface run-off and soil erosion. These indicators were calculated on a dekadal time step for 1996. Vegetation cover was estimated using the Normalized Difference Vegetation Index (NDVI). The estimation of RUE also employed NDVI and, in addition, rainfall derived from Meteosat cold cloud duration data. Surface run-off was modelled using the Soil Conservation Service (SCS) model parametrized using the rainfall estimates, vegetation cover, land cover, and digital soil maps. Soil erosion, one of the most indicative parameters of the desertification process, was estimated using a model parametrized by overland flow, vegetation cover, the digital soil maps and a digital elevation model (DEM). The four indicators were then combined to highlight the areas with the greatest degradation susceptibility. The system has potential for near-real time monitoring and application of the methodology to the remote sensing data archives would allow both spatial and temporal trends in degradation to be determined.     

Changes in the soil erosion status in the middle and lower reaches of the Yangtze River basin from 2001 to 2014 and the impacts of erosion on the water quality of lakes and reservoirs

ABSTRACT

The revised universal soil loss equation (RUSLE) was used to obtain the soil erosion intensity distribution in the middle and lower reaches of the Yangtze River basin (MLYB), where the input data included a digital elevation model (DEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing products. Changes in the soil erosion intensity throughout the MLYB were analysed from 2001 to 2014, and the potential influences of these changes on the local water quality of lakes and reservoirs were revealed. This investigation is the first to reveal the spatial and temporal changes in soil erosion throughout the MLYB. The results indicated that from 2001 to 2014, most of the MLYB was characterized by slight and light soil erosion levels, whereas relatively few areas exhibited intensive to severe soil erosion. Soil erosion in the MLYB displayed a decreasing trend from 2001 to 2014; over 80% of the region displayed a decreasing soil erosion intensity change rate, indicating that soil conservation in most of the MLYB has improved over the past 14 years. However, 12.8% of the area presented an increasing change rate, and the region with the maximum increasing change rate was located mainly in the lower Yangtze basin. Furthermore, spatial heterogeneities were found in the soil erosion intensities throughout the MLYB: soil erosion improved in the upper and middle regions of the MLYB, whereas soil erosion worsened in the lower regions of the MLYB. Among the sub-basins of the MLYB, obvious soil erosion occurred most frequently in the Hanjiang basin and least frequently in the Taihu basin. A driving force analysis showed that the influence of precipitation on soil erosion is more evident than that of human activities in all sub-basins except the Dongting basin. A correlation analysis between soil erosion and water turbidity/water transparency showed that 45.9% of the decreasing water turbidity is correlated with decreasing soil erosion and that 42.5% of the increasing water turbidity might be influenced by increasing soil erosion. Decreased soil erosion might be responsible for the improved water transparency for 50% of the lakes, whereas increased soil erosion is correlated with a decrease in water transparency for over 50% of the lakes.     

基于遥感和GIS技术的土壤侵蚀量估算研究——以澄江太阳山地区为例

土壤侵蚀量的估算是土壤侵蚀研究的核心问题之一。本文以云南省I类淡水湖抚仙湖东岸的太阳山地区为研究对象,在GIS和遥感技术的支持下,利用土壤类型分布图、土地利用、遥感影像、DEM等数据,探讨了侵蚀模型的选择过程,最终利用修正后的通用土壤侵蚀方程(RUSLE),建立各因子的数据库,对该区域近100km2的土壤侵蚀现状和潜在土壤侵蚀量进行模拟估算,并分析了主要的影响因子。     

An erosion model for evaluating regional land-use scenarios

The conversion to pasture of indigenous forest on New Zealand hill country has led to increased mass-movement erosion and consequently increased sedimentation of waterways. Effective soil conservation requires a model that can evaluate erosion and sedimentation for different land-use scenarios. In this paper, we develop a model of mean sediment discharge related to mean erosion rates through a sediment delivery ratio. Mean erosion rate in a particular terrain (“erosion terrain”) is the product of (i) the square of mean annual rainfall with (ii) a cover factor and (iii) an erosion coefficient that depends on erosion terrain. Measurements of mean sediment discharge are used to estimate erosion coefficients for each erosion terrain. The model can be used to predict mean sediment discharge in response to land-cover/land-use scenarios. It is easy to execute and uses input data readily available in GIS layers in New Zealand. This makes it suitable for widespread management application, in contrast to physically based models which are presently only suitable for research catchments. We demonstrate the utility of the model for three different applications: evaluating land-use scenarios in the Motueka catchment; setting priorities for soil conservation in the Manawatu catchment; and determining national trends in agricultural erosion over a 30-year period. The general methodology is applicable to countries dominated by mountains and steep hills with high erosion rates.