Mapping soil erosion risk in Rondônia,Brazilian Amazonia: using RUSLE,remote sensing and GIS

This article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover‐management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall–runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0·2, LS values of less than 2·5, and C values of less than 0·25. A soil erosion risk map with five classes (very low, low, medium, medium‐high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia. Copyright © 2004 John Wiley & Sons, Ltd.     

水土流失区生态变化的遥感评估

水土流失是世界面临的一个严峻问题,它已给全球的生态造成了严重的威胁,及时快速地监测水土流失区的生态变化已显得尤为重要。为此,该文提出遥感生态指数(RSEI)来监测水土流失区的生态变化。该指数选取了绿度、湿度、热度和干度作为四大生态指标,并分别以遥感植被指数、湿度分量、地表温度和土壤-建筑指数为代表。同时采用主成分变换技术来集成各个指标,使各指标的权重是由数据本身的性质来决定,而不是人为的设定。将RSEI应用于福建长汀水土流失区的结果表明,RSEI指数可以定量地评价水土流失区生态修复的效果。数据显示,该区经过20多年的水土流失治理,RSEI生态指数值上升了17%,生态为优良的等级所占的面积比例从33.9%上升到52.3%,总体反映了该区的生态质量有了较明显的提高。     

无人机遥感技术在生产建设项目水土保持监测中的应用——以鄂北水资源配置工程为例

无人机遥感技术在水土保持监测工作中的应用尚未形成统一有效的方法与标准,针对这一问题,笔者以鄂北地区水资源配置工程为例,从遥感基础数据获取、基本监测信息提取、监测信息应用3个方面,开展水土保持监测实例分析.首先,针对案例工程的几个典型区,在航拍的基础上,利用Agisoft Photoscan Professional软件处理原始影像,获取各区域的DOM和DEM成果,其水平精度分别可达0.05和0.2m.然后,基于DOM和DEM提取监测对象的土地利用类型、位置、面积、体积等信息,构建三维虚拟模型.结果表明计算机自动识别更加快速,但存在将监测对象的阴影、苫盖误判为植被的问题.最后,将提取的信息逐一应用于案例工程的水土保持监测工作,直接获取各典型区扰动土地面积、弃渣体积、苫盖与否、苫盖面积等监测结果.无人机监测结果与运用传统方法监测的结果对比表明,2种方法的监测结果均满足相关技术要求,但无人机监测效率是传统人工监测效率的3～5倍.成果可为无人机遥感技术在水土保持监测中的应用提供有效的方法借鉴.     

Relating soil electrical conductivity to remote sensing and other soil properties for assessing soil salinity in northeast Thailand

Mapping and monitoring of soil salinity is required to establish its areal extent and also to keep track of changes in salinity in order to formulate appropriate and timely management strategies for reclamation and rehabilitation of such soils. Remote sensing data have been increasingly used in soil‐salinity studies as they are not only quicker but are also useful for making realistic predictions. A study was conducted in northeast Thailand to understand the relationship of spectral reflectance and physico‐chemical soil properties to electrical conductivity (EC) by using remote sensing data (Landsat® ETM+) and laboratory analysis of soil sample data. Multiple regression analysis was used to examine the relationships between EC and spectral/soil properties and to generate several models. In the case of spectral properties, mid‐infrared band (Landsat® band 7) and near‐infrared (band 4) were found to be most correlated with the observed EC values of the surface layer of the soil. For the soil properties, chloride (Cl), sodium (Na), phosphorus (P), and sodium adsorption ratio (SAR) were found to be most correlated with observed EC values. Similarly, for the subsurface layer, Cl and P were found to be significant predictors of observed EC values. Copyright © 2006 John Wiley & Sons, Ltd.     

应用遥感技术对中国亚热带地区坡地利用及土壤侵蚀的研究

This paper introduces briefly two remote sensing case studies on land use in the subtropic region of China. One is on slope land use in the Yangtze River Three Gorges area. This is a large area of 60497 km². First of all, geometric correction and supervised classification were conducted for ten scenes of Landsat-5 TM or MSS images. The resolution of the processed images is 50 m × 50 m on ground. By the classification the land use/cover categories in this area were discriminated. Then the croplands including rice fields and upland fields were extracted from the land use/cover maps. Simultaneously the slope grade maps were prepared based on the topographic maps. Overlaying the slope grade maps and the cropland maps, the area and percentage of the croplands in different slope grades were determined. This case study indicated that 71.5% of the uplands was situated on the slope above 150 and 25% on the slope above 250 in this area. It is dangerous, and urgent cultivation or engineering measures should be taken. Another case study is on soil erosion in Linshan County of Guangxi Province. Airphoto interpretation and supervised classification of a Landsat TM image were carried out for discriminating land cover/use categories in an area of 3 557.8 km². And the soil erosion intensity grades were determined according to the land cover/use maps and slope maps. It wad discovered that the land suffering soil erosion accounted for 2404.0 km², 67.6% of the total area of the county. Necessary measures to control soil erosion should be taken also.     

区域土壤侵蚀遥感与核素示踪联合评价技术

土壤侵蚀遥感调查具有宏观、快速、信息量大等优点,但是实际应用中有3大制约因素：1）廉价高分辨率影像的获取;2）科学准确的判读和解译方法;3）成熟的土壤侵蚀评价模型或系统的观测数据。我国普遍缺乏土壤侵蚀评价模型和长期观测数据,技术问题比较突出。土壤侵蚀遥感调查中,采用经验分级指标法得出土壤侵蚀现状或强度,影响了土壤侵蚀评价的精度、准确性和应用范围。利用土壤侵蚀核素示踪技术测算不同土地利用单元的土壤侵蚀量,能够突破了遥感土壤侵蚀调查依赖模型和观测数据的限制,实现土壤侵蚀评价的宏观与微观、点与面、估算与实测的结合,为区域土壤侵蚀快速评价提供一条高效途径。     

应用于遥感监测土壤流失的GIS航片像素地形因素的一个新软件

Based on the new algorithm for GIS image pixel topographic factors in remote sensing monitoring of soil losses,a software was developed for microcomputer to carry out computation at a medium river basin (County),This paper lays its emphasis on algorithmic skills and programming techniques as well as application of the software.     

基于多源遥感数据的浙江省水土流失遥感监测

 通过浙江省土壤侵蚀强度判别模型,确定影响浙江省水土流失的主导因子;以TM数据和航摄1:1万DOM数据为遥感数据源,利用浙江省数字化地形图,结合样地调查,进行2009年浙江省水土流失遥感监测;以基于约束三角网技术的坡度因子提取方法、基于植被指数和像元二分模型的植被覆盖度因子提取方法以及土地利用因子提取方法,通过叠置分析实现土壤侵蚀信息提取。结果表明：浙江省水土流宍面积呈逐年减少的趋势;经过野外调査验证,研究成果准确度高。     

半干旱沙区土类/亚类的遥感调查制图方法

传统土壤调查制图存在低时效性、低精度等问题。为了解决半干旱沙区土壤遥感调查制图问题,该文以科尔沁左翼后旗为例,基于野外实地调查和专家知识分析了半干旱沙区土壤类型分布特征与环境因素之间的关系,并探讨了基于多时相Landsat8 OLI影像数据的半干旱沙区土类/亚类遥感调查制图方法。结果表明:利用多时相Landsat8 OLI影像数据提取的归一化差异水体指数(modified normalized difference water index,MNDWI)、盐分指数(salt index,SI)、归一化差异湿度指数(normalized difference moisture index,NDMI)、归一化差异植被指数(normalized difference vegetation index,NDVI)等环境信息,可实现对沼泽土、盐碱土、草甸土、风沙土及其亚类等半干旱沙区主要土壤类型的遥感调查制图。应用本文提出的半干旱区土类/亚类遥感调查制图方法对科左后旗进行土壤遥感调查制图和精度验证,总体精度约为72.84%,Kappa系数为0.667 8。该方法可为半干旱沙区数字土壤调查制图提供思路和参考。     

利用遥感和GIS研究兴国县土壤侵蚀的变化

The spatial and temporal dynamics of soil erosion in Xingguo County, Jiangxi Province, China were studied using multi-period remote sensing images and GIS. The results indicated that the soil erosion status of the region has been improving, particularly since the 1980s, with the erosion rate showing an evident decline over the past 30 years. The improvement showed not only in the decline of eroded soil area, but also with the reduction in the extent of erosion. The extent of erosion mainly changed by one level, and the change primarily occurred with the severely or moderately eroded soil types. However, in general, soil erosion was still an overriding problem in the region with some areas becoming more serious, especially those with large quantities of granite.     

Assessment of SoilGrids data for soil erosion estimation at watershed scale: A case study in northern Thailand

Soil erosion has been identified as one of the most destructive forms of land degradation, posing a threat to the sustainability of global economic, social and environmental systems. This underscores the need for sustainable land management that takes erosion control and prevention into consideration. This requires the use of state-of-the-art erosion prediction models. The models often require extensive input of detailed spatial and temporal data, some of which are not readily available in many developing countries, particularly detailed soil data. The soil dataset Global Gridded Soil Information (SoilGrids) could potentially fill the data gap. Nevertheless, its value and accuracy for soil erosion modelling in the humid tropics is still unknown, necessitating the need to assess its value vis-à-vis field-based data. The major objective of this study was to conduct a comparative assessment of the value of SoilGrids and field-based soil data for estimating soil loss. Soil samples were collected from five physiographic positions (summit, shoulder, back slope, foot slope, and toe slope) using the soil catena approach. Samples were collected using a 5-cm steel sample ring (undisturbed) and a spade (disturbed). Data of the landform, predominant vegetation types, canopy cover, average plant height, land use, soil depth, shear strength, and soil color were recorded for each site. The soil samples were subjected to laboratory analysis for saturated hydraulic conductivity, bulk density, particle size distribution, and organic matter content. Pedotransfer functions were applied on the SoilGrids and field-based data to generate soil hydrological properties. The resultant field-based data were compared with the SoilGrids data for corresponding points/areas to determine the potential similarities of the two datasets. Both datasets were then used as inputs for soil erosion assessment using the revised Morgan-Morgan-Finney model. The results from both datasets were again compared to determine the degree of similarity. The results showed that with respect to point-based comparison, both datasets were significantly different. At the hillslope delineation level, the field-based data still consistently had a greater degree of variability, but the hillslope averages were not significantly different for both datasets. Similar results were recorded with the soil loss parameters generated from both datasets; point-based comparison showed that both datasets were significantly different, whereas the reverse was true for parcel/area-based comparison. SoilGrids data are certainly useful, especially where soil data are lacking; the utility of this dataset is, however, dependent on the scale of operation or the extent of detail required. When detailed, site-specific data are required, SoilGrids may not be a good alternative to soil survey data in the humid tropics. On the other hand, if the average soil properties of a region, area, or land parcel are required for the implementation of a particular project, plan, or program, SoilGrids data can be a very valuable alternative to soil survey data.     

无人机遥感技术在生产建设项目水土保持监测中的应用——方法构建

无人机遥感为水土保持监测提供了新的技术支撑手段,但这一技术在水土保持监测工作中的应用尚处于起步阶段,还未形成统一、有效的方法与标准.研究将无人机遥感技术与水土保持监测现行的规范规程相结合,从基础数据获取、监测信息提取及信息在水土保持监测中的应用等3方面,构建基于无人机遥感的生产建设项目水土保持监测方法,并将其应用于工程实例.基础数据获取包括飞行规划设计、原始数据获取及原始数据处理3个步骤,最终生成DEM和DOM成果;监测信息提取可在DEM或DOM成果的基础上进行,通常包括土地利用类型、监测对象位置、长度、面积及体积等;信息应用主要是结合相关规程规范,将提取出的有效信息,逐一应用到生产建设项目水土保持监测工作中.应用结果表明,研究构建的方法简单实用,可提高无人机遥感在水土保持监测中应用的技术水平,为生产建设项目水土流失防治提供技术支撑.     

黑土区田块尺度土壤有机质含量遥感反演模型

为了对田块尺度土壤有机质进行空间反演并提高模型精度和稳定性,该文以黑龙江省黑土带41.3 hm~2田块为例,获取2016年5月中下旬两期(受限于拍摄周期和天气原因而选择不同卫星影像,2016年5月17日Landsat 8影像和5月25日Sentinel-2A影像)裸土时期遥感影像和4 m分辨率DEM数据;分析单期影像与土壤有机质(soil organic matter,SOM)的关系,两期影像所包含的土壤含水量变化信息与地形因素对SOM预测模型精度的影响,建立基于BP神经网络的SOM遥感反演模型。结果表明:该田块内SOM含量差异较大;利用单期影像预测SOM时,基于红波段和785~899 nm波段建立的预测模型精度(建模均方根误差RMSE 1.033,检验RMSE 1.079)和稳定性(建模决定系数R2 0.677,检验R20.644)较高;两期影像时,基于红波段和1 570~1 650 nm波段建立的预测模型精度(建模RMSE 0.855,检验RMSE 0.898)和稳定性(建模R2 0.792,检验R2 0.797)显著提高;在两期影像模型基础上,加入地形因子作为输入量,模型精度(建模RMSE 0.492,检验RMSE 0.499)和稳定性(建模R2 0.917,检验R2 0.928)进一步提高。研究成果可为土壤碳库估算和农田精准施肥提供理论与技术支持。     

区域蒸散和表层土壤含水量遥感模拟及影响因子

以甘肃省武威市为研究区域,应用灌溉前后两景Landsat TM-5卫星遥感数据,采用SEBAL模型进行了区域蒸散估算,综合应用归一化植被指数(NDVI)和地表温度(Ts),计算了该区域的条件植被温度指数(VTCI),并估算了表层土壤含水量(0～20 cm)。在获得区域净辐射通量、地表温度以及植被覆盖度空间分布的基础上,进一步对灌溉前后两景影像中日蒸散和表层土壤含水量的影响因素进行了分析。结果表明,区域蒸散和表层土壤含水量的遥感估算与地面同步观测值比较,能较好地反映研究区域的蒸散和地表含水量的空间变异特征。当土壤较干时,区域蒸散的空间分布变异较大,而表层土壤含水量的空间变异较小。在灌溉前后两景影像中,日蒸散与净辐射通量、地表温度和覆盖度之间都有极显著的相关性,决定系数均在0.90以上,而日蒸散量与表层土壤含水量的相关性以灌溉后较高。此外,表层土壤含水量与地表温度、覆盖度都呈显著的相关性,但比较而言,地表温度指数关系的离散性较小,相关系数也大。但地表温度、覆盖度与表层土壤含水量的相关性都依赖于土壤干湿程度,通常土壤越湿,相关性也越高。     

Land suitability assessment for perennial crops using remote sensing and Geographic Information Systems: A case study in northwestern Egypt

Abstract

The main objective of this study was to develop a Geographic Information Systems-based model for land suitability assessment for guava, olive and date palm in the North-western coast of Egypt. Soil, climatic and landscape database as well as satellite image have been integrated through Geographic Information Systems (GIS). A Landsat ETM+ image dated 2001, was classified using maximum likelihood classifier to produce land use/land cover map. Physical and chemical analyses of 57 soil profiles were interpolated to produce continuous land characteristic maps that are relevant to the requirement of the considered crops. These maps with climate and land cover map were integrated using GIS to produce land suitability maps for guava, olive and date palm. Two types of land suitability maps were produced in this study namely: Continuous land suitability maps and conventional land suitability classified maps. For each of them six land suitability maps were produced for the three crops in which three are for actual land suitability and the other three for potential land suitability. It was found that the suitability was higher for date palm followed by olive and the lowest suitability was assigned for guava.     

遥感技术在土壤侵蚀研究中的应用述评

[目的]对遥感技术在土壤侵蚀研究中的应用进行述评,探索土壤侵蚀遥感研究的发展方向,并为研究者快速选择适宜的遥感数据源和研究方法提供参考。[方法]通过文献查阅,从不同研究方面开展综述和分析。[结果]针对不同研究区域和主题,总结了土壤侵蚀研究中常用遥感平台和数据源,综述了遥感技术在区域土壤侵蚀特征识别、监测与尺度效应研究中的应用。以及遥感技术在通用土壤流失方程关键因子获取中的应用。同时分析了目前研究中存在的问题并提出相应建议。[结论]遥感技术作为开展大范围、长时间序列土壤侵蚀研究的重要技术手段,在我国土壤侵蚀研究中发挥了巨大作用。但实际应用中也存在基层遥感数据时效性不强、数据源单一和识别因子针对性不强等问题。其高效应用和推广需要技术层面和人员、经济支持层面共同发展与创新。     

遥感与地统计方法在表层土壤有机碳空间格局 研究中的应用比较

土壤有机碳为土壤肥力的核心指标之一,精确、及时、低耗的土壤有机碳空间格局估测对促进精准农业的发展和科学施肥具有重要意义,分别利用地统计方法和遥感技术测定法分析了海伦市表层土壤有机碳的空间分布格局,发现： 1）表层土壤有机碳与遥感影像的TM1波段之间存在着极显著的相关性（p＜0.01）,而与TM2、TM3和NDSVI显著相关（p＜0.05）; 2）通过对两种方法所得结果比较得出在精度基本一致的前提下,遥感技术测定法所需样本量低于地统计法所需样本量,且前者所得结果与当地实际情况更为相符,是一种潜在、高效的表层土壤有机碳空间格局研究方法。     

遥感和GPS支持的高山草甸土草地盖度精确量化研究

The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover densities to their image properties according to their geographic coordinates. The principles and procedures for quantifying grassland cover density from satellite image data were presented with an example from Qinghai Lake, China demonstrating how quantification could be made more accurate through the integrated use of remote sensing and global positioning systems （GPS）. An empirical model was applied to an entire satellite image to convert pixel values into ground cover density. Satellite data based on 68 field samples was used to produce a map of ten cover densities. After calibration a strong linear regression relationship （r^2 = 0.745） between pixel values on the satellite image and in situ measured grassland cover density was established with an 89% accuracy level. However, to minimize positional uncertainty of field samples, integrated use of hyperspatial satellite data and GPS could be utilized. This integration could reduce disparity in ground and space sampling intervals, and improve future quantification accuracy even more.     

基于遥感和地面试验的水分指数与土壤湿度及生理指标关系

为研究作物生长发育早期受干旱影响的作物水分光谱特征,对冬小麦返青期进行水分控制试验。利用野外光谱辐射仪在河北固城试验区测量冬小麦的光谱并分别计算归一化水分指数（NDWI）和简单比值水分指数（SRWI）,同时测定冬小麦的叶绿素浓度（Chl）、叶面积指数（LAI）、株高（H）和叶片相对含水率（LRWC）等冠层生理指标和土壤湿度（SM）。分析结果表明：冬小麦生理指标与土壤湿度之间有着显著的正相关,最大相关系数为0.657,表明土壤水分状况直接影响作物发育早期的光合和生长状况。NDWI/SRWI与SM相关系数均为 0.545,呈现弱的正相关;相反,水分指数与冬小麦生理指标之间的相关不明显,特别是,NDWI/SRWI与LRWC的相关系数仅为0.175。据此得出在作物低覆盖生长阶段,水分指数更多反映的是土壤水分状况而不是作物水分。