Estimation of land surface evapotranspiration over complex terrain based on multi‐spectral remote sensing data

Land surface evapotranspiration (ET) plays an important role in energy and water balances. ET can significantly affect the runoff yield of a basin and the available water resources in mountainous areas. The existing models to estimate ET are typically applicable to plains, and excessive data are required to calculate the surface fluxes accurately. This study established a simple and practical model capable of depicting the surface fluxes, while using relatively less parameters. Considering the complex terrain, solar radiation was corrected by importing a series of topographic factors. The water deficit index, a measure of land surface wetness, was calculated by applying the f_c (vegetation fractional cover)‐T_rad (land surface temperature) framework in the two‐source trapezoid model for evapotranspiration model to mountainous areas after corrections of temperature based on altitude variations. The model was successfully applied to the Kaidu River Basin, a basin with few gauges located in the east Tien Shan Mountains of China. Based on the time scale extensions, ET was analyzed at different time scales from 2000 to 2013. The results demonstrated that the corrected solar radiation and water deficit index were reasonably distributed in space and that this model is applicable to ungauged catchments, such as the Kaidu River Basin.     

Verification of land surface evapotranspiration estimation from remote sensing spatial contextual information

Estimation of evapotranspiration (ET) is of great significance in modeling the water and energy interactions between land and atmosphere. Negative correlation of surface temperature (T_s) versus vegetation index (VI) from remote sensing data provides diagnosis on the spatial pattern of surface soil moisture and ET. This study further examined the applicability of T_s–VI triangle method with a newly developed edges determination technique in estimating regional evaporative fraction (EF) and ET at MODIS pixel scale through comparison with large aperture scintillometer (LAS) and high‐level eddy covariance measurements collected at Changwu agro‐ecological experiment station from late June to late October, 2009. An algorithm with merely land and atmosphere products from MODIS onboard Terra satellite was used to estimate the surface net radiation (R_n) and soil heat flux. In most cases, the estimated instantaneous R_n was in good agreement with surface measurement with slight overestimation by 12 W/m². Validation results from LAS measurement showed that the root mean square error is 0.097 for instantaneous EF, 48 W/m² for instantaneous sensible heat flux, and 30 W/m² for daily latent heat flux. This paper successfully presents a miniature of the overall capability of T_s–VI triangle in estimating regional EF and ET from limited number of data. For a thorough interpretation, further comprehensive investigation needs to be done with more integration of remote sensing data and in‐situ surface measurements. Copyright © 2011 John Wiley & Sons, Ltd.     

Continuous land cover change monitoring in the remote sensing big data era

<正>Since the late 20th century,global change issues have attracted lots of attention.As a key component of global changes,land cover and land use information has been increasingly important for improved understanding of global environmental changes and feedbacks between social and environmental systems(Verburg et al.,2015).A set of national and global scale land cover/use products with higher spatial and temporal resolutions have been developed to fill this gap.In China,existing efforts include China’s National     

High-resolution remote sensing mapping of global land water

Land water, one of the important components of land cover, is the indispensable and important basic information for climate change studies, ecological environment assessment, macro-control analysis, etc. This article describes the overall study on land water in the program of global land cover remote sensing mapping. Through collection and processing of Landsat TM/ETM+, China’s HJ-1 satellite image, etc., the program achieves an effective overlay of global multi-spectral image of 30 m resolution for two base years, namely, 2000 and 2010, with the image rectification accuracy meeting the requirements of 1:200000 mapping and the error in registration of images for the two periods being controlled within 1 pixel. The indexes were designed and selected reasonably based on spectral features and geometric shapes of water on the scale of 30 m resolution, the water information was extracted in an elaborate way by combining a simple and easy operation through pixel-based classification method with a comprehensive utilization of various rules and knowledge through the object-oriented classification method, and finally the classification results were further optimized and improved by the human-computer interaction, thus realizing high-resolution remote sensing mapping of global water. The completed global land water data results, including Global Land 30-water 2000 and Global Land 30-water 2010, are the classification results featuring the highest resolution on a global scale, and the overall accuracy of self-assessment is 96%. These data are the important basic data for developing relevant studies, such as analyzing spatial distribution pattern of global land water, revealing regional difference, studying space-time fluctuation law, and diagnosing health of ecological environment.     

卫星遥感数据评估黄土高原陆面干湿程度研究

卫星遥感数据具有估算时空尺度上地表参量的优势,在陆地环境状况评估和监测等方面有很大的应用潜力.本文利用美国地球观测系统卫星搭载中等分辨率成像光谱仪（EOS/MODIS）在黄土高原2002-2010年期间获取的每16天归一化植被指数（NDVI）和每日地表温度（LST）数据,分析了黄土高原地区LST-NDVI空间的基本特征.结果发现：当研究区域足够大且遥感数据时间序列足够长时,LST-NDVI空间中（NDVI,LST）散点并非呈三角形或梯形分布.为了能够利用EOS/MODIS的NDVI和LST数据正确地评估陆面的干湿状况,本文给出了利用数据集合法确定LST-NDVI空间中干边和湿边的数值,即在LST-NDVI空间中,利用NDVI等值区间内LST最大值和最小值的集合代表干边和湿边的数值,并进一步证明了在LST-NDVI空间中干边和湿边数值并非呈线性关系.在分析LST-NDVI空间特征的基础上,通过构建地表温度-植被干旱指数（TVDI）,探讨其在评估黄土高原地区陆面的干湿状况的应用潜力.结果表明：由TVDI距平表征的陆面的干湿程度与局地降水距平有很好的关联性,二者在时空分布上有较好的对应关系.在我国陇东黄土高原塬区,TDVI数值与地面观测的表层土壤湿度有很好的相关性,相关系数在0.67以上,并通过显著性为1%的检验.由此说明：如果合理选取干边和湿边的数值,TDVI可应用于区域陆面干湿程度的客观评估.     

Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications

Numerous models had been developed to predict the annual evapotranspiration (ET) in vegetated lands across various spatial scales. Fu's (Scientia Atmospherica Sinica, 5, 23–31) and Zhang's (Water Resources Research, 37, 701–708) ET simulation models have emerged as highly effective and have been widely used. However, both formulas have the non-quantitative parameters (m in Fu's model and w in Zhang's model). Based on the collected 1789 samples from global long-term hydrological studies, this study discovered significant relations between m (or w) and vegetation coverage or greenness in collected catchments. Then, we used these relations to qualify the parameters in both Zhang's and Fu's models. Results show that the ET estimation accuracies of Fu's (or Zhang's) model are significantly improved by about 13.49 mm (or 6.74 mm) for grassland and cropland, 38.52 mm (or 29.84 mm) for forest and shrub land (coverage<40%), 19.74 mm (or 16.17 mm) for mixed land (coverage<40%), respectively. However, Zhang's model shows higher errors compared with Fu's model, especially in regions with high m (or w) values, such as those with dense vegetations or P/E₀ (annual precipitation to annual potential ET) smaller than 1.0. Additionally, this study also reveals that for regions with vegetation cover less than 40%, the annual ET is not only determined by vegetation types, but also relates to the sizes of vegetation-covered areas. Conversely, for regions with vegetation cover more than 40%, the annual ET is mainly determined by the vegetation density rather than vegetation types or vegetation coverage. Thus, linking m (or w) parameters with vegetation greenness allows leveraging remote sensing for forest management in data-scarce areas, safeguarding regional water resources. This study pioneers integrating vegetation-related indices with basin parameters, advocating for their crucial role in more effective hydrological modelling.     

Recent remote sensing applications for hydro and morphodynamic monitoring and modelling

It is not new to recognize that data from remote sensing platforms is transforming the way we characterize and analyse our environment. The ability to collect continuous data spanning spatial scales now allows geomorphological research in a data rich environment and this special issue [coming just eight years after the 2010 special issue of Earth Surface Processes and Landforms (ESPL) associated with the remote sensing of rivers] highlights the considerable research effort being made to exploit this information, for studies of geomorphic form and process. The 2010 special issue on the remote sensing of rivers noted that fluvial remote sensing articles made up some 14% of the total river related articles in ESPL. A similar review of articles up to 2017 reveals that this figure has increased to around 25% with a recent proliferation of articles utilizing satellite‐based data and structure from motion photogrammetry derived data. It is interesting to note, however that many studies published to date are proof of concept, concentrating on confirming the accuracy of the remotely sensed data at the expense of generating new insights and ideas on fluvial form and function. Data is becoming ever more precise and researchers should now be concentrating on analysing these early data sets to develop increased geomorphic insight, to challenge existing paradigms and to advance geomorphic science. The prospect of this occurring is increased by the fact that many of the new remote sensed platforms allow accurate spatial data to be collected cheaply and efficiently, reducing the need for substantial research funding to advance river science. Fluvial geomorphologists have never before been in such a liberated position. As techniques and analytical skills continue to improve it is inevitable that the prediction that remotely sensed data will revolutionize our understanding of geomorphological form and process will prove true, altering our ideas on the very nature of system functioning in the process. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Estimation of annual actual evapotranspiration from nonsaturated land surfaces with conventional meteorological data

Land surface evapotranspiration is an important component both in earth surface heat and water bal-ance, on whose budgets weather and climate depend, to a great extent, for their changes are responsible for the formation and variation of vegetation features on the globe. Besides, the evapotranspiration is an im-portant topic of short-term flood forecasting and the estimation of runoff from mountainous sides. As a result, the problem as to the evapotranspiration has been one of the concerns in …     

卫星遥感技术在火山监测中的应用

作为一门新兴技术，卫星遥感已被有效地应用于火山活动监测、通过SAR(合成孔径雷达)和InSAR(合成孔径雷达干涉成像)资料可以监测火山地表形变、使用热辐射数据以及将遥感与其它技术相结合能够研究火山区的热活动和火山喷发物。在我国的火山监测中，广泛地应用卫星遥感技术是非常必要的。     

Object-oriented land cover classification using HJ-1 remote sensing imagery

The object-oriented information extraction technique was used to improve classification accuracy, and addressed the problem that HJ-1 CCD remote sensing images have only four spectral bands with moderate spatial resolution. We used two key techniques: the selection of optimum image segmentation scale and the development of an appropriate object-oriented information extraction strategy. With the principle of minimizing merge cost of merging neighboring pixels/objects, we used spatial autocorrelation index Moran’s I and the variance index to select the optimum segmentation scale. The Nearest Neighborhood (NN) classifier based on sampling and a knowledge-based fuzzy classifier were used in the object-oriented information extraction strategy. In this classification step, feature optimization was used to improve information extraction accuracy using reduced data dimension. These two techniques were applied to land cover information extraction for Shanghai city using a HJ-1 CCD image. Results indicate that the information extraction accuracy of the object-oriented method was much higher than that of the pixel-based method.     

太湖蓝藻水华遥感监测方法

利用遥感技术监测太湖蓝藻水华具有重要的现实意义.基于不同遥感数据,包括MODIS/Terra、CBERS-2 CCD、ETM和IRS.P6 LISS3,结合蓝藻水华光谱特征,采用单波段、波段差值、波段比值等方法,提取不同历史时期太湖蓝藻水华.结果表明:MODIS/Terra数据可以利用判别式Band2＞0.1和Band2/Band4＞1提取蓝藻水华;CBERS-2 CCD、ETM和IRS-P6 LISS3数据可以利用Band4大于一定阈值和Band4/Band3＞1提取蓝藻水华;波段比值(近红外,红光＞1)算法稳定,可以发展成为蓝藻水华遥感提取普适模式.同时,本文成功利用ETM和IRS.P6 LISS3数据Band4波段对蓝藻水华空间分布强度进行了五级划分.这为今后利用遥感技术,建立太湖蓝藻水华监测和预警系统莫定了基础.     

Modeling the land surface reflectance for optical remote sensing data in rugged terrain

A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented.Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively,the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model.A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper.The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.     

Temporal dynamics of evapotranspiration in semiarid native forests in Brazil and Spain using remote sensing

Evapotranspiration (ET) plays an important role in integrated water resource planning, development and management. This process is particularly relevant in semiarid regions. The aim of this study is, hence, to compare spatial and temporal patterns of actual ET, as well as the temporal trends in two different semiarid forests, Caatinga (Brazil) and Tierra de Pinares (Spain). We used the surface energy balance algorithm for land (SEBAL) to assess actual evapotranspiration (ET_a) in both areas. In the Brazilian semiarid forest, Caatinga is the main vegetation, while it is Pinares in Spain. For this purpose, 69 Landsat-5 and 42 Landsat-8 images (1995–2019) were used. The Mann–Kendall test was applied to assess the occurrence of trends in precipitation, temperature and potential ET data; and the Temporal Stability Index (TSI) to know which areas have greater seasonal ET_a. The annual amplitude of the potential evapotranspiration (ET₀) is the same in both areas, however, the Caatinga values are higher. In the Caatinga forest, when ET₀ presents its highest values throughout the year, ET_a presents the lowest, and vice versa. In the Pinares forest, ET_a follows the ET₀ dynamics during the year, and the difference between ET₀ and ET_a is maximum during the summer. The Caatinga forest showed a greater spatial variation of ET_a than the Pinares forest as well as a greater extension with lower temporal stability of ET_a than the Pinares forest. Both the Caatinga forest and the Pinares forest showed significant positive trends in annual ET₀ and ET_a. We estimate that the value of ET_a increases more rapidly in Pinares than in the Brazilian Caatinga. Taking Caatinga as a hydrological mirror, some consequences are expected to Pinares, such as significant changes in the water balance, increase of biodiversity vulnerability, and reduction of water availability in soil and reservoirs.     

基于星载被动微波遥感的青藏高原湖冰物候监测方法

湖冰物候影响着区域及全球气候,是全球变化的敏感因子,青藏高原湖泊众多,冻融现场监测数据缺乏,而微波具有对冰水相变敏感、时间分辨率高、历史存档数据长等特点,这对于长时间序列湖冰物候研究具有重要意义.然而,被动微波遥感空间分辨率低、湖泊亮温的精准定位难.论文通过获取AMSR-E/Aqua和AMSR-2/Gcom-W1的亮温数据,构建了基于轨道亮温数据的阈值判别法,通过对青藏高原不同区域和不同大小的青海湖、色林错、哈拉湖以及阿其克库勒湖进行测试研究:与青海湖现场观测对比,湖泊完全冻结日期与开始融化日期最大误差小于3天;与无云光学遥感判别结果相比,4个湖泊的冻融参数误差为2~4天.结果表明,被动微波轨道亮温数据可实现青藏高原地区亚像元级中大型湖泊冻融信息的获取,历史卫星资料可为湖冰物候的监测提供重要的支撑.     

Synergy of satellite remote sensing and numerical modeling for monitoring of suspended particulate matter

Monitoring and modeling of the distribution of suspended particulate matter (SPM) is an important task, especially in coastal environments. Several SPM models have been developed for the North Sea. However, due to waves in shallow water and strong tidal currents in the southern part of the North Sea, this is still a challenging task. In general there is a lack of measurements to determine initial distributions of SPM in the bottom sediment and essential model parameters, e.g., appropriate exchange coefficients. In many satellite-borne ocean color images of the North Sea a plume is visible, which is caused by the scattering of light at SPM in the upper ocean layer. The intensity and length of the plume depends on the wave and current climate. It is well known that the SPM plume is especially obvious shortly after strong storm events. In this paper a quasi-3-D and a 3-D SPM transport model are presented. Utilizing the synergy of satellite-borne ocean color data with numerical models, the vertical exchange coefficients due to currents and waves are derived. This results in models that for the first time are able to reproduce the temporal and spatial evolution of the plume intensity. The SPM models consist of several modules to compute ocean dynamics, the vertical and horizontal exchange of SPM in the water column, and exchange processes with the seabed such as erosion, sedimentation, and resuspension. In the bottom layer, bioturbation via benthos and diffusion processes is taken into account.Responsible Editor: Jörg-Olaf Wolff     

富营养化水体浮游植物遥感监测研究进展

随着湖泊流域经济的快速发展,蓝藻水华频繁暴发的现象越来越严重,水体富营养化已经成为国内外重大环境问题.浮游植物是水体的初级生产者,是衡量水体富营养化程度的主要指标之一,遥感技术则是探测水体浮游植物时空分布的重要手段.在收集整理近千篇国内外水体浮游植物遥感研究论文的基础上,从卫星数据源、研究内容及研究方法等角度,总结了遥感技术在富营养化湖泊浮游植物监测应用的历史进展、研究重点及发展趋势.研究表明,现有的富营养化水体浮游植物遥感研究,以湖泊蓝藻水华问题为切入点,研究视角由水体表层(藻华面积、色素浓度)转至水下三维(藻总量),研究方法从定性识别转向定量反演,研究内容从监测蓝藻水华推进到探测不同类群蓝藻,逐渐形成了以应用为导向,"MODIS/VIIRS大中型湖泊日常监测—GF/Sentinel2小型湖泊针对性监测—无人机应急监测"的浮游植物遥感综合监测体系.上述研究梳理了富营养化水体浮游植物遥感监测湖泊水环境学科的发展动向,以期为从事蓝藻水华生态灾害监测和预警人员提供重要的技术支撑和理论参考.     

Morphological analysis of the Sudd region using land survey and remote sensing data

An analysis of the vast wetland of the Sudd swamps in southern Sudan was designed to assess and describe interdependencies between morphology and hydrology. Findings based on field survey and remote sensing data include an assessment of the effect of ground slopes and morphological features on spill and flooding of the seasonally flooded grasslands. Through bathymetric surveys and analysis of Landsat images, depth profiles and cross‐sectional depth and flow distributions were established. Data from remote sensing, field survey and historical sources were correlated and correction factors established; the SRTM was found to be partly unsuitable for further assessments. Further analysis of remote sensing data was used to investigate the Sudd's inland delta as well as the question of spill into the Bahr el Ghazal basin. Copyright © 2008 John Wiley & Sons, Ltd.     

Role of satellite remote sensing for monitoring of surface water resources in an arid environment

Abstract

Water bodies up to 0.9 ha surface area, which are indistinguishable by Landsat Multispectral Scanner (MSS) due to the latter's poor spatial resolution of 80 m, can be identified and mapped reliably and reasonably within ±10% accuracy by Landsat Thematic Mapper (TM) false colour composite because of its higher spectral and spatial resolution of 30 m. Comparative study of Landsat TM and the Survey of India topographical maps revealed reductions in the water surface and drainage basin areas up to 1.8 to 2.4 and 6.0 to 8.0 times, respectively, over a period of 28 years (1958–1986) due to the biotic interference resulting in desertification in the large adjoining areas.     

Temporal monitoring of water level changes in Seyfe Lake using remote sensing

The Earth's water resources are endangered by inconsiderate use, pollution and lack of conservation measures. Temporal monitoring is necessary for the conservation and usage planning of water resources and to make informed decisions. Seyfe Lake and its environs in Turkey is one of the most important water basins in the world, because it is a node on bird migration paths between Europe, Asia and Africa. For this reason, the International Council of Bird Preservation (ICBP) has registered 27 of the bird species living at Seyfe Lake on the conservation list. In this work, the temporal changes in the water surface area of Seyfe Lake and its environs, which are important for ecological, historical and tourism reasons, are investigated. The change of water surface in the lake is examined over a 26 year period using satellite images taken between 1975 and 2001. Landsat images from years 1975, 1987 and 2001 are used. The change is tracked from the images using an unsupervised classification method. A decrease of slightly more than 33% was observed in the water surface area this 26 year period. The temporal change indicated by the images was compared with the related meteorological data between 1975 and 2001. Over this time period, climate conditions (rainfall, temperature and evaporation) in the study area have been changed by approximately 21%. These changes could have affected the Lake surface area, but so also could external human interference around the Lake. Copyright © 2008 John Wiley & Sons, Ltd.     

南极冰盖物质平衡变化的卫星遥感监测现状与发展趋势

南极冰盖物质平衡对全球海平面变化影响巨大,提高南极冰盖物质平衡估算精度对实现全球海平面变化趋势准确预测至关重要.卫星遥感技术的发展,特别是极地卫星对南极冰盖系统监测能力的提升,有助于认识、保护和利用南极,解决极地科学国际前沿难题.揭示南极冰盖对全球气候环境的响应及其反馈机制,对深化人类对南极的科学认知也具有重要意义.本文首先系统总结了用于南极冰盖监测卫星的发展现状及现有的卫星遥感数据产品序列,然后讨论了运用遥感卫星监测南极物质平衡的主要方法和研究进展,并对南极卫星遥感技术的最新进展进行了分析.最后在我国极地遥感卫星发展方面提出了建议,旨在进一步提升我国对极地冰盖变化和全球海平面上升的长期观测及预测能力,为相关应对策略的制定提供有力的科学支撑.