Photo-interpretation of land facets as a soil mapping techniqueDie photointerpretation von landschaftsfliesen als methode der bodenkartierungPhoto-interprétation de land facets /3- une technique de cartographie de sol

In Montgomeryshire, Wales, UK, a study was carried out to test the validity of a soil mapping technique based on the photo-interpretation of land facets. Land facets were used as the means for extrapolating, using aerial photographs, soil properties between widely separated parts of the county. Statistical techniques such as coefficient of variation, analysis of variance and discriminant analysis, were used in testing the validity of land unit classifications of the terrain and of the predictions of soil-land attributes from aerial photographs.The results show that the land facets are uniform soil areas with a considerable degree of homogeneity in those soil properties which are genetically and morphologically important, such as particle size distribution, colour, stòne content, p^H and free iron oxide. The facets are, however, highly variable notably in the distribution of exchangeable cations and organic carbon. The similarity between analogous facets based on individual soil parameters is not very great and there are significant differences within groups related to ground drainage and parent material lithology. When all parameters are considered simultaneously, however, the similarity between them is proven.     

Assessing space–time variations of denudation processes and related soil loss from 1955 to 2016 in southern Italy (Calabria region)

Studies on denudation processes and soil loss rates can provide insight into the landscape evolution, climate change, and human activities, as well as on land degradation risk. The aims of this study were to analyze the space–time distribution of denudation processes and evaluate the soil loss changes occurred during the period 1955–2016 by using an approach integrating geomorphological, geospatial and modeling analysis. The study area is a representative stream catchment of the Crati Valley (Calabria, southern Italy), which is affected by severe erosion processes. The combined use of aerial photographs interpretation, field survey, geostatistics, and GIS processing has allowed to characterize the types of denudation processes and land use change in space and time. Revised universal soil loss equation implemented in GIS environment was used to estimate the space–time pattern of soil loss and the soil erosion rates for each investigated year. The results showed that from 1955 to 2016, the study area was highly affected by denudation processes, mainly related to landslides and water erosion (slope wash erosion and gully erosion). Comparison of denudation processes maps showed that the total area affected by erosion processes has increased by about 31% and the distribution of geomorphic processes and their space–time evolution resulted from the complex interrelation between geoenvironmental features and human activities. The main land use changes concerned a decrease in areas covered by woodland, scrubland and pasture and an increase in croplands and barren lands that favored erosion processes. The most susceptible areas to soil loss in both years were mapped, and the mean soil loss rates for the study area were 6.33 Mg ha^?1 y^?1 in 1955 and 10.38 Mg ha^?1 y^?1 in 2016. Furthermore, the soil loss in 2016 has increased by about 64% compared to 1955. Finally, the results showed that integrating multi-temporal analysis of denudation processes, land use changes and soil loss rates might provide significant information on landscape evolution which supports decision makers in defining soil management and conservation practices.     

基于数字图像处理技术的砂土颗粒级配分析研究

砂土颗粒级配是影响砂土工程性质的重要参数之一,传统的颗分试验方法由于试验原理不同而具有不同的适用范 围。为更加方便、准确地获取砂土颗粒级配,提出了一种基于数字图像处理技术来获取SEM照片中的砂颗粒粒径参数及级 配特征的新方法。将准备好的砂土样品打磨成薄片放在扫描电镜下拍照,然后利用Photoshop软件对照片进行拼接,并采用 自主研发的SMAS数字图像分析系统对拼接好的照片进行定量分析处理,获取样品的微观结构参数,将获得的“土颗粒等 效直径”和“土颗粒面积”分别等效为实际土颗粒粒径和土颗粒质量,进而换算得到砂土的颗粒级配曲线;然后将通过数 字图像技术获得的砂土颗粒级配曲线与通过传统筛分法和激光粒度分析法得到的颗粒级配曲线进行对比,验证了提出的数 字图像处理方法的有效性和可靠性,同时分析了两种方法之间存在的差异及其原因,并对数字图像处理方法和传统颗分方 法各自的优缺点进行了讨论。     

基于数字图像处理技术的砂土颗粒级配分析研究

砂土颗粒级配是影响砂土工程性质的重要参数之一，传统的颗分试验方法由于试验原理不同而具有不同的适用范 围。为更加方便、准确地获取砂土颗粒级配，提出了一种基于数字图像处理技术来获取SEM照片中的砂颗粒粒径参数及级 配特征的新方法。将准备好的砂土样品打磨成薄片放在扫描电镜下拍照，然后利用Photoshop软件对照片进行拼接，并采用 自主研发的SMAS数字图像分析系统对拼接好的照片进行定量分析处理，获取样品的微观结构参数，将获得的“土颗粒等 效直径”和“土颗粒面积”分别等效为实际土颗粒粒径和土颗粒质量，进而换算得到砂土的颗粒级配曲线；然后将通过数 字图像技术获得的砂土颗粒级配曲线与通过传统筛分法和激光粒度分析法得到的颗粒级配曲线进行对比，验证了提出的数 字图像处理方法的有效性和可靠性，同时分析了两种方法之间存在的差异及其原因，并对数字图像处理方法和传统颗分方 法各自的优缺点进行了讨论。     

Optical processing of structural contour maps

Optical processing is a fast, easy, economical, and reliable method of quantifying map patterns. A reduced transparency of a zebra-like pattern, obtained by blackening in alternate contour bands of a map, is used as input to an optical system of a laser source and objective lens to produce Fourier transforms. By sampling the intensity distribution across the transform, information about the spatial frequency (periodicity) and orientation in the original map can be inferred. Parameters used for comparing the map images are the values of intensity distribution in the transform. These intensities are normalized and subjected to comparison using various similarity methods. Cross-multiplication of the intensities is suggested as a measure of vectorial comparison of the orientations. By plotting the directional intensities into a polar coordinate system, rose diagrams are prepared for visual comparison. Optically derived parameters are independent of scale and other restrictive and limiting requirements as demanded in techniques of map analyses based on numerically derived parameters. The technique can be used in analyzing other pictorial data including aerial photographs, rock-fabric diagrams, and thin sections.     

SuperMap(杭州超图)在土地利用现状信息库建设中的应用

福州市国土资源局根据国家土地部门通知精神以及经济建设变化的实际情况，于2000年11月对市辖5区重新航空摄影，采用全数字航空摄影测量方法进行变更调查，并利用SuperMap(杭州超图)软件建立土地利用现状信息库。     

Statistical analysis of landslide susceptibility at Yongin, Korea

The aim of this study is to evaluate the susceptibility of landslides at Yongin, Korea, using a geographic information system (GIS). Landslide locations were identified in the Yongin area from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, timber cover, and geology. These data were collected and constructed into a spatial database using GIS. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, age, diameter, and density of timber were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM satellite image. Landslide susceptibility was analyzed using the landslide occurrence factors by probability and logistic regression methods. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide location. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy. The results can be used to reduce associated hazards, and to plan land use and construction.     

Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong

 Steep terrain and the high frequency of tropical rainstorms make landslide occurrence on natural terrain a common phenomenon in Hong Kong. For example, more than 800 slope failures were triggered by a rainstorm in November 1993 on Lantau Island, Hong Kong. Maps of recent landslides interpreted from aerial photographs, in combination with a geographical information system, were used to evaluate the frequency and distribution of landslides, with particular reference to such physical parameters as lithology, slope gradient, slope aspect, elevation, vegetation cover, and proximity to drainage line, all of which are considered to be influential in the occurrence of landslides. A stepwise logistic regression model was obtained between landslide susceptibility and the above mentioned physical parameters. The study area has been classified into five classes of relative landslide susceptibility, namely, very low, low, moderate, high, and very high, based on this methodology. Received: 17 December 1999 · Accepted: 21 March 2000     

北京大清河流域生态涵养区富硒土壤资源分布特征和来源解析

北京是典型的硒缺乏地理分布区,但近些年研究成果表明局部地区土壤达到富硒水平,掌握该区富硒分布特征对于开展北京地区的富硒环境研究和开发利用富硒土地资源具有重要意义。本文以北京大清河流域生态涵养区1615km~2地球化学调查数据为基础,采用原子荧光光谱(AFS)等方法测定了研究区1297件表层土壤、25组玉米及对应根系土壤和15件岩石中Se等地球化学指标;利用相关分析、多元统计分析方法,结合GIS技术,研究土壤和农作物中硒含量特征、富硒成因来源以及土壤硒与碳铁磷等其他元素的关系,评价富硒土地的安全性。结果表明:研究区土壤硒含量区间为0.055～0.465mg/kg,背景值为0.257mg/kg,呈现富硒特征,厘定出360.4km~2富硒土地资源。当地种植的玉米硒含量变化范围为0.028～0.70mg/kg,几何均值为0.20mg/kg,80%的玉米样本为富硒农产品,且土壤富硒与作物富硒空间分布一致,指示土壤硒是作物体内硒的重要供给来源。研究认为,地质背景和成土母质是研究区富硒土地资源分布的主控因素,河流相沉积的暗色岩系是重要的土壤硒来源。富硒土地整体环境质量清洁安全,仅3.23km~2(面积占比0.2%)土壤重金属(镉汞铅)含量超风险管控值,在土地开发过程中需重点关注。     

Soil Organic Carbon Storage Changes in Coastal Wetlands of the Liaohe Delta,China, Based on Landscape Patterns

Growing wetland loss along a coastal area in China was examined through shoreline recession and land use changes. Carbon storage or sequestration in coastal wetland soils was based on vertical marsh accretion and aerial change data. Marshes sequester significant amounts of carbon through vertical accretion; however, large amounts of carbon previously sequestered in the soil profile are lost through rapid land use changes and shoreline recessions. The Liaohe Delta (LHD) was divided into nine landscape types based on Landsat TM digital images from 1991 to 2011. The distributed areas and transfer matrices of each landscape type were calculated. Combined with the organic carbon content and bulk density of 202 soil surface samples from field investigations in 2012, the soil organic carbon pools and stocks were estimated. Results showed that the soil organic carbon pools varied from 0.58 to 9.75 kg m^?2, and organic carbon storage in the upper 20 cm of soil was 1935.92 × 10⁴ and 1863.87 × 10⁴ t in 1991 and 2011, respectively. We attributed these large losses of carbon to rapid land use changes. The construction of levees along the shoreline has triggered large instantaneous losses of previously sequestered carbon through the destruction of 278.06 km² of tidal flats. Our results reveal that the LHD wetlands might not serve as a desired sink of carbon if maladministration practices are applied. These results can provide scientific guidance for decision makers in determining an effective way to maintain the soil carbon pool in the wetlands of the LHD.     

Mapping of the soil texture using geostatistical method (a case study of the Shahrekord plain, central Iran)

Soil texture is a key variable that reflect a number of soil properties such as soil permeability, water holding capacity, nutrient storage and availability, and soil erosion. The main objective of this study was to produce the kriged maps of soils of the Shahrekord region, central Iran. One hundred four soil samples were collected on a 375-m² sampling grid from the depths of 0–30, 30–60, and 60–100 centimeter, and their particle sizes were determined using hydrometer method. The results showed a moderately spatial correlation in the soil particles among sampling soil layers and across the study area. Moreover, increasing clay and therewith observation of heavier soil textures is evident from surface to subsurface layers of the soils in the studied area due to rainfall and/or irrigation agriculture. These findings indicated that study of the soil texture variation with depth can be used as a clue for site-specific management and precision agriculture. Moreover, we suggest further analysis by using other data layers like topographical parameters, land use, parent material, soil erosion, and any other information which might influence the spatial distribution of soil texture.     

Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana’a metropolitan city, Yemen

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands.     

Spatial prediction of urban landslide susceptibility based on topographic factors using boosted trees

As global warming accelerates, abnormal weather events are occurring more frequently. In the twenty-first century in particular, hydrological disruption has increased as water flows have changed globally, causing the strength and frequency of hydrological disasters to increase. The damage caused by such disasters in urban areas can be extreme, and the creation of landslide susceptibility maps to predict and analyze the extent of future damage is an urgent necessity. Therefore, in this study, probabilistic and data mining approaches were utilized to identify landslide-susceptible areas using aerial photographs and geographic information systems. Areas where landslides have occurred were located through interpretation of aerial photographs and field survey data. In addition, topographic maps generated from aerial photographs were used to determine the values of topographic factors. A frequency ratio (FR) model was utilized to examine the influences of topographic, soil and vegetation factors on the occurrence of landslides. A total of 23 variables that affect landslide frequency were selected through FR analysis, and a spatial database was constructed. Finally, a boosted tree model was applied to determine the correlations between various factors and landslide occurrence. Correlations among related input variables were calculated as predictor importance values, and sensitivity analysis was performed to quantitatively analyze the impact of each variable. The boosted tree model showed validation accuracies of 77.68 and 78.70% for the classification and regression algorithms using receiver operating characteristic curve, respectively. Reliable accuracy can provide a scientific basis to urban municipalities for policy recommendations in the management of urban landslides.     

A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses

Bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the Cuyahoga River watershed, northeastern Ohio, U.S.A. The relationship between landslides and various instability factors contributing to their occurrence was evaluated using a Geographic Information System (GIS) based investigation. A landslide inventory map was prepared using landslide locations identified from aerial photographs, field checks, and existing literature. Instability factors such as slope angle, soil type, soil erodibility, soil liquidity index, landcover pattern, precipitation, and proximity to stream, responsible for the occurrence of landslides, were imported as raster data layers in ArcGIS, and ranked using a numerical scale corresponding to the physical conditions of the region. In order to investigate the role of each instability factor in controlling the spatial distribution of landslides, both bivariate and multivariate models were used to analyze the digital dataset. The logistic regression approach was used in the multivariate model analysis. Both models helped produce landslide susceptibility maps and the suitability of each model was evaluated by the area under the curve method, and by comparing the maps with the known landslide locations. The multivariate logistic regression model was found to be the better model in predicting landslide susceptibility of this area. The logistic regression model produced a landslide susceptibility map at a scale of 1:24,000 that classified susceptibility into four categories: low, moderate, high, and very high. The results also indicated that slope angle, proximity to stream, soil erodibility, and soil type were statistically significant in controlling the slope movement.     

基于复数傅里叶分析的岩土颗粒细观特征识别与随机重构方法

岩土细观特征的识别与分析是岩土力学研究的重要内容。基于傅里叶变换原理,将任意岩土颗粒的二维轮廓变换为傅里叶描述符与相位进行分析,建立了基于复数傅里叶分析的细观特征表征与重构方法。通过两组不同颗粒的傅里叶细观特征统计,研究了不同阶傅里叶描述符与细观特征参量的对应关系。结果表明：-12～0及16～20阶对应的傅里叶描述符决定颗粒的形状;-23～-11及1～15阶对应的傅里叶描述符与颗粒粗糙度密切联系;傅里叶描述符曲线峰值与颗粒的粒径显著线性相关;高阶傅里叶系数与阶数近似呈对数线性关系,低阶系数则由不同颗粒形状决定。采用建立的傅里叶描述符对应关系进行颗粒相似重构研究,发现重构颗粒的外轮廓及傅里叶统计参量与实际颗粒十分接近,且反映颗粒的粗糙度、纹理等细部特征,其成果可用于大量岩土颗粒与力学特性的相关性研究。     

平原区中大比例尺土壤地球化学调查采样方法--浙江省平湖市试验研究

文章以浙江省平湖市为典型三角洲平原区,开展了多种尺度、不同采样方法的对比试验。结果表明,田块内土壤元素分布较为均匀,小范围内元素的空间分异性较小,而田块之间土壤元素含量差异性明显增加;Hg,Cd等典型污染元素空间分异性较强,而人为污染扰动较弱的元素的空间分布较为均一;不同采样方法取得的区域性资料,其统计值接近,空间分布模式也相似,但有些元素仍有较明显差异。因此,中大比例尺地球化学调查时,应根据调查研究的目标任务,充分考虑地块分布、土壤类型和土地利用方式,选择合理的采样点。土壤样品可采取多坑点采集、多子样组合的方式,以保证样品的代表性,同时减少分析测试工作量。     

Detecting trends in seagrass abundance using aerial photograph interpretation: Problems arising with the evolution of mapping methods

In the late 1970s and early 1980s an inventory of seagrass distribution in southeast Australia was made from multiscale aerial photographs using a simple analog mapping method, referred to here as theCamera lucida technique. Four priority estuaries were remapped in 2003, also using multi-scale aerial photographs, but using a geographic information system (GIS)-based analog mapping technique. We quantified the degree of error that arose when estimates of seagrass distribution were compared for the two techniques be ressessing. with GIS, the same aerial photographs used earlier for four estuaries: Port Hacking, Bermagui River, Merimbula Lake, and St Georges Basin.Camera lucida produced a larger estimate of total seagrass area than GIS in all four locations: 8% of total seagrass area or 12.9 ha in Port Hacking, 15% or 5 ha in Bermagui River, 20% or 38.0 ha in Merimbula Lake, and 243% or 502.2 ha in St Georges Basin. The consistent and moderate discrepancy in Port Hacking, Bermagui River, and Merimbula Lake was attributed mainly to differences betweenCamera lucida and GIS, such as the tendency ofCamera lucida to overestimate seagrass area by amalgamating disjunct seagrass patches into continuous meadows. The large discrepancy at St Georges Basin was attributed to interoperator error; i.e., the operators who mapped photographs taken in 1979 had widely differing interpretations of the aerial photographs. A 20-yr trend was calculated for each estuary using either theCamera lucida or revised GIS value as the start point. Perceived management status of the seagrass depended greatly on the initial data used. In St Georges Basin, a catastrophic decline (65%, 553.9 ha) occurred based on theCamera lucida-GIS comparison but only a small decline (14.7%, 51.8 ha) when all photos were GIS assessed, In view of the technical developments in habitat mapping, evaluation of change in seagrass abundance using remote sensing needs an assessment of intra-operator error, inter-operator error, and systemic error before maps produced by superseded technology are considered useful baselines.     

A numerical terrain classification scheme for off-road terrain trafficability assessments

A numerical terrain classification scheme was developed in which multi-parameter data were used to describe geomorphological units. Parameters important in terrain trafficability studies were selected and data were obtained from soil survey reports, topographic maps, aerial photographs and limited field tests. The method was tested in the Fort St. John area in northeastern British Columbia. In order to account for the dynamic changes introduced by the varying climatic conditions a separate treatment was used for frozen-ground winter conditions and wet and dry summer conditions. An average distance clustering program was used to classify the units in terms of degree of similarity measured in multi-parameter terms. A different combination of parameters was used to establish ground conditions for the three climatic regimes. The numerical procedure has the advantage of treating many physical and environmental parameters simultaneously and is flexible enough to allow the important parameters to be emphasized. With this selective process a good account of all weather-related ground conditions can be given.     

Application of color infrared aerial photography to assess macroalgal distribution in an eutrophic estuary,Upper Newport Bay,California

Newport Bay is a large estuary in southern California that is subject to anthropogenic nutrient loading, eutrophication, and hypoxia. Ground-based methods of assessing algal extent for monitoring and management are limited in that they cannot provide a synoptic view of algal distribution over comparatively large areas. The goal of this study was to explore the application of color infrared aerial photography as an alternative for analyzing the changes in the abundance of exposed macroalgae. Three surveys combining remote sensing (color infrared aerial photography) and ground-based sampling to quantify macroalgal mat coverage were carried out in Upper Newport Bay (UNB) between July and October 2005. Airborne photographs (scale 1:6000) collected during daytime low tides, clear skies, and appropriate sun angle were digitized to 25-cm resolution, orthorectified, georegistered, and combined into three mosaic composite digital images: one for each survey. During each aerial photography survey, macroalgal percent cover was measured on the ground by the pointintercept method in a 6.25-m² area at ca. 30 locations distributed along the water’s edge throughout the intertidal mudflat area. There were three main types of cover:Ulva spp. (green algae),Ceranrium spp. (red algae), and bare surface (mud and mussel beds). To analyze similarities between spectral signatures in the images and cover types, the pixels corresponding to the ground samples from each survey were grouped into clusters based on similarity of their spectral signatures. To establish relationships between spectral signatures in the images and cover as determined from ground data, pixels in each composite image corresponding to ground samples from the same day that were characterized by > 90% of one cover type were attributed to that cover type. Ground samples comprised of a mixture of cover types were used for accuracy assessment. Before classification, each digital image was transformed by the Minimum Noise Fraction Rotation method to remove noise and enhance contrast between the classes. For classification of each composite image, the Spectral Angle Mapper scheme was used: all pixels in each image were attributed to the identified classes and the areal extent of each class was estimated. According to these assessments, the macroalgal coverage in UNB increased from 37% in July to 57% in September to 80% in October, and during this timeUlva spp. replacedCeramium spp. as the dominant alga. This analysis showed that color infrared aerial photography is an effective tool for assessing estuarine, intertidal macroalgal coverage.