首页|基于星地传感技术的土壤盐渍化监测进展与展望

基于星地传感技术的土壤盐渍化监测进展与展望

扫码查看
土壤盐渍化是全球面临的土壤退化和环境恶化的共性问题.近地传感、卫星遥感与机载遥感等星地传感技术的蓬勃发展使得高效且准确的土壤盐分周期监测成为可能,并为土壤盐渍化研究提供了坚实技术支撑.本文针对土壤盐渍化星地传感监测的发展进程,以"数据—方法—应用"为脉络,详细分析梳理了土壤盐渍化监测的原理、主要数据源及主流方法;随后归纳总结当前技术体系的发展现状和监测数据、监测方法及尺度效应等局限性;最后针对基于星地传感技术的土壤盐渍化监测研究的进一步发展提出了展望和设想,明确了多源星地数据融合的次生土壤盐渍化监测;依托多平台开展土壤盐渍化的多尺度协同监测;借助学科交叉加深土壤盐渍化的探测深度;以及基于云计算的土壤盐渍化共享数据集与平台开发等未来需要重点关注的研究方向.
Monitoring soil salinization on the basis of remote sensing and proximal soil sensing:Progress and perspective
As a global problem of soil degradation,salinization has become a major obstacle to the sustainable development of the ecological environment and agriculture.Moreover,it has become one of the major environmental and socioeconomic issues globally.However,the traditional process of salinity survey is too cumbersome,expensive,and time consuming to meet the mapping needs in a large scale.Remote sensing and proximal soil sensing technology has become important tools for rapid,accurate,and efficient acquisition and monitoring of soil salinization.The appropriate mapping methods are directly related to the spatial scale of interest.The need of regional soil salinity mapping was also one of the first published geostatistical applications.Macroscopic maps of salt affected soils at global scale may roughly illustrate the extent of the environmental problem;however,regional or greater level assessments are based on remote sensing and geographic information systems coupled with ground measurements.Applying remote sensing technology to the monitoring of soil salinization to obtain soil salinization information has become a trend.This article discusses the detection mechanisms,multisource data,and methods for monitoring soil salinization.Multiple sensors installed on different platforms can provide considerable earth observation information with various temporal,spatial,and spectral resolutions.On the basis of height,the observation platforms can be divided into near ground(proximal),airborne,and spaceborne remote sensing.With regard to the operating principle,these sensors can be mainly divided into electromagnetic sensors and optical/radiational sensors.Among them,spectral imaging and thermal infrared sensors are suitable for various observation platforms,while ground penetrating radar and electromagnetic induction are only suitable for near-ground soil salinization monitoring.The mainstream methods can be categorized into(1)thematic information extraction,(2)spectral index development,(3)quantitative retrieval modeling,and(4)digital soil mapping.On the basis of the above,this review summarized and explained the limitations of the current research fields and framework,monitoring data,monitoring methods,and scale effects.The integration of spacebome remote sensing data with ground-based sensor information,complemented by the agile observational capabilities of Unmanned Aerial Vehicles(UAVs),enables us to transcend the limitations of noncoordinated Earth observation techniques.This integration allows for comprehensive coverage from a broad-scale perspective down to specific localized points.In summary,the core of the integration of satellite,UAV,and proximal sensing for soil salinization monitoring lies in the fusion of data from diverse sources,the establishment of quantitative models,and the extension of spatial scales.Finally,for future development and actual application needs,this review discussed the prospect for the further development of soil salinization studies on the basis of remote sensing and proximal soil sensing.To further advance and optimize technology,analysis,and retrieval methods,we identify critical future research needs and directions:(1)secondary soil salinization monitoring based on multisource data fusion,(2)multiscale collaborative monitoring of soil salinization,(3)improving detection depth on the basis of multidisciplinary knowledge,and(4)sharing research data and platform based on cloud computing.

soil salinizationremote sensingproximal soil sensingspatiotemporal variationsdigital soil mapping

王敬哲、丁建丽、葛翔宇、彭杰、胡忠文

展开 >

深圳职业技术大学人工智能学院,深圳 518055

中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101

新疆大学地理与遥感科学学院,乌鲁木齐 830017

新疆大学新疆绿洲生态自治区重点实验室,乌鲁木齐 830017

塔里木大学农学院,阿拉尔 843300

深圳大学自然资源部大湾区地理环境监测重点实验室,深圳 518060

展开 >

土壤盐渍化 遥感 近地传感 时空变化 数字土壤制图

天山创新团队新疆维吾尔自治区自然科学基金重点项目国家自然科学基金广东省基础与应用基础研究基金广东省基础与应用基础研究基金深圳市高等院校稳定支持计划深圳职业技术大学校级科研项目深圳职业技术大学校级科研项目资源与环境信息系统国家重点实验室开放基金

2022TSYCTD00012021D01D06422610162023A15150112732020A1515111142202208111733160016023310031K6023271008K

2024

遥感学报
中国地理学会环境遥感分会 中国科学院遥感应用研究所

遥感学报

CSTPCD北大核心
影响因子:2.921
ISSN:1007-4619
年,卷(期):2024.28(9)