地形效应下的区域蒸散遥感估算

在地表起伏地区,由于受到坡度、坡向等的影响,地表能量通量表现出与水平地表不一样的特征,为了定量表征起伏地表条件下的蒸散格局,以位于陕甘宁交界区的华池县、庆城县、镇原县、西峰区和合水县为研究区,从能量平衡原理入手,对各能量通量进行了量化计算,并着重考虑了蒸散的能量来源即地表净辐射的地形效应;同时,针对研究区地表特征,确定了土壤热通量的计算方案和感热通量的参数化方案,如零平面位移、动量粗糙长度、热量粗糙长度、动量和热量的稳定度校正项等算法;在此基础上,计算了研究区的瞬时蒸散,计算结果表明采用的蒸散遥感估算方案     

Future directions for advanced evapotranspiration modeling: Assimilation of remote sensing data into crop simulation models and SVAT models

Soil-Vegetation-Atmosphere Transfer Models (SVAT) and Crop Simulation Models describe physical and physiological processes occurring in crop canopies. Remote sensing data may be used through assimilation procedures for constraining or driving SVAT and crop models. These models provide continuous simulation of processes such as evapotranspiration and, thus, direct means for interpolating evapotranspiration between remote sensing data acquisitions (which is not the case for classical evapotranspiration mapping methods). They also give access to variables other than evapotranspiration, such as soil moisture and crop production. We developed the coupling between crop, SVAT and radiative transfer models in order to implement assimilation procedures in various wavelength domains (solar, thermal and microwave). Such coupling makes it possible to transfer information from one model to another and then to use remote sensing information for retrieving model parameters which are not directly related to remote sensing data (such as soil initial water content, plant growth parameters, physical properties of soil and so on). Simple assimilation tests are presented to illustrate the main techniques that may be used for monitoring crop processes and evapotranspiration. An application to a small agricultural area is also performed showing the potential of such techniques for retrieving evapotranspiration and information on irrigation practices over wheat fields.     

基于遥感数据和气象数据的水旱地冬小麦产量估测

研究利用遥感数据进行了运城地区冬小麦不同生育时期归一化差值植被指数和产量关系的研究,利用气象数据和光谱数据构建了冬小麦光谱产量模型、气象产量模型以及光谱气象产量模型。结果表明：运城地区水旱地冬小麦均以5月8日左右的NDVI值与产量相关性最好,且达极显著水平,因此该时期为建立冬小麦遥感估产模型的最佳时相。通过对冬小麦光谱产量模型、气象产量模型以及光谱气象产量模型预测效果进行的F检验,表明各模型均达到极显著水平。与其他两种模型相比,光谱气象产量模型的决定系数（R2）有明显的提高,并且相对均方根误差（RRMSE     

遥感技术在农业塑料大棚识别中的应用

农业塑料大棚的使用对农业生产至关重要,但若使用不当会对农业生产和生态环境带来不利影响。因此,运用遥感技术监测农业塑料大棚的数量与规模对于农业的可持续发展具有重要意义。首先,分析及对比了不同分类原理、遥感数据源、分类器在农业塑料大棚识别中的具体应用,然后,简要阐述了遥感技术在大棚识别领域的发展前景,以期为相关研究提供参考。     

The use of remote sensing for estimating ET of irrigated wheat and cotton in Northwest Mexico

Components of a satellite-based system for estimating the crop water requirements of irrigated vegetation have been combined, applied, and tested against field data in the Yaqui Valley, northwest Mexico. Frequent satellite observations have the potential to provide snap shots of cloud variability at the high spatial and temporal resolutions that are needed for making simple, near real-time estimates of incoming solar radiation and, thus, daytime evaporation required for irrigation scheduling. Less frequent polar orbiting satellites offer the capacity of following the vegetation development at higher spatial resolution. The operational framework for obtaining cloud cover has been developed and applied using hourly sampled, 1 km resolution, GOES-10 data received in real-time. The high-resolution, cloud-screening algorithm has proved to be efficient and reliable and has been used to provide high-resolution (4 km) estimates of solar radiation. Relationships between vegetation indices (NDVI and SAVI) and crop coefficients (the ratio of measured to reference evapotranspiration) have been derived with four different models (Shuttleworth, Penman, Priestley–Taylor and Makkink), using ground-based surface reflectance measured over the crop. Continuous measurements of surface fluxes and other meteorological variables were made following almost the entire vegetative cycle of the plant using a station equipped with standard meteorological instruments and an eddy-correlation system. Actual evapotranspiration was computed as the product of the estimated crop coefficients, derived from field radiometer measurements, and reference evapotranspiration. In comparison with ground data, RMSE values are on the order of 1 mm per day. Finally the opportunity to use high-resolution satellite data to make near real-time estimates of crop evaporation is discussed.     

基于无人机遥感图像提取农田微地形特征

近年来极端暴雨天气与自然灾害频发,导致农田损毁,影响耕作。该研究利用高精度农田数字地形模型（FDTM, Farmland Digital Terrain Model),基于地形因子综合属性提出一种识别农田微地形特征（凸起特征及洼地特征）的方法。首先,基于SfM（Structure from Motion）技术处理试验田的航拍图像,获取高精度农田FDTM。分析FDTM的高程方差随局部窗口尺度的变化趋势,确定分析窗口的尺度区间为31×31至51×51像素。其次,选择高程、地形起伏度和坡度综合评价在51×51像素窗口下提取的315个高程极值点,获取多窗口地形因子综合隶属度。最终,根据斯特吉斯公式确定阈值为0.627,提取16个农田凸起特征顶点,并结合等高线图识别凸起特征的外形轮廓。类似地,建立反转数字地形模型（RFDTM, Reverse-FDTM）,将FDTM中的洼地特征转变为RFDTM中的凸起特征,识别9个农田洼地特征。研究结果可为农田复垦及精准土地平整作业提供理论依据与方法支持。     

Diagnosis of regional evaporation by remote sensing to support irrigation performance assessment

The success of water management in large irrigation schemes with composites of soil, crop, wetness and micro-meteorological conditions is difficult to quantify. Performance assessment indicators, being among others a function of evaporation, are useful tools to evaluate the actual functioning of an irrigation system. The inevitable spatial variability of evaporation in large irrigation schemes makes its determination with conventional point measurements almost impossible. A new remote sensing evaporation parameterization algorithm has been tested with high resolution Landsat Thematic Mapper data for the Eastern Nile Delta, Egypt. Although the implementation of such an algorithm requires assumptions to be made, the current case study shows that these assumptions do not hamper the estimation of actual and potential evaporation at regional scale. The actual evaporation has been used to express the uniformity of crop water use which is related to the equity of irrigation water distribution. The coefficient of variance in actual evaporation between 53 differenent irrigation districts is 10% on average. The relative evaporation was considered to determine whether the crop was adequately irrigated. The relative evaporation was more than 75% for 48 out of 53 irrigation districts. It is concluded, that improved information on actual crop growth conditions through remote sensing provides an essential insight into the planning of real-time and seasonal irrigation water deliveries.     

基于无人机遥感数据的生态渠系信息提取

针对河套灌区引水灌溉中存在粗放型灌溉,且当地为提高产量,仅注重扩大种植面积的问题,提出了一种渠系信息精准提取的方法.基于无人机遥感图像,运用ENVI 5.1软件,对遥感图像进行预处理,对图像RGB3个通道分别进行拉伸显示,经组合以增强其对比度;运用面向对象法进行图像分割,用基于规则的分类方法,基于不同规则进行单独及组合分析,确定了“光谱平均值小于98、最小包围矩形长宽比处于其最小值与0.85之间、延长线大于1 m”的最优组合规则,提取了内蒙古河套灌区某部分生态渠系信息,对于生态渠道的识别精度达到毛沟级,并对提取结果进行了评价,其中组合辅助解译正确率达96.4%,为精准灌溉运行管理提供了较准确的渠系信息.     

基于Cokriging插值修正冬小麦面积遥感监测

在研究区内冬小麦种植区选取149个地面样方,筛选样方内反映种植结构、地块破碎程度、地形因素的参数并利用差分GPS测量,对3个参数量化并确定插值的主辅变量。探讨和比较了利用普通克里格和协同克里格2种插值方法对研究区的冬小麦种植面积比例的插值结果。结果表明,相同采样数量下,协同克里格法相对于普通克里格法的均方根误差降低1.48%,预测值与实测值之间的相关系数提高了6.82%,利用COK插值获取研究区内冬小麦种植面积比例分布状况,可以分区域对大尺度冬小麦面积遥感提取结果进行修正。     

Managing scarce water resources in Asia: The nature of the problem and can remote sensing help?

Water demands are outstripping supplies in many parts of Asia and causing conflicts, especially as rapidly urbanizing and industrializing areas compete with more traditional agriculture on alluvial plains near expanding metropolises. The environment is increasingly being seen as a legitimate and important user of water, often in competition with irrigation, domestic, industrial, hydropower and community uses of water. Any future scenario requires an improvement in water productivity, especially in agriculture. Surface and ground water supplies are not well regulated owing primarily to a weak knowledge base, analytical capacity in addition to a number of traditional institutional, governance, political and other factors. Water policy makers have, therefore, to work out strategies for integrated water and environmental management, which rely on a proper knowledge base of the basin hydrological and pollution conditions. Examples from various countries in Asia are elaborated in this paper to demonstrate how spatially distributed evapotranspiration data from remote sensing, in conjunction with other key data, can help to build the knowledge base for integrated basin scale water management. Remote sensing is not a solution, but it provides key data that is difficult to access by conventional data collection methods.     

A New Simple Method to Determine Crop Coefficients for Water Allocation Planning from Satellites: Results from Kenya

Crop coefficient K_c is defined as theratio of crop potential and grass referenceevapotranspiration. This paper discussesthe estimation of crop potentialevapotranspiration from remote sensing datato deduce spatial variable and regionalscale crop coefficients. Maps of cropcoefficients avoid the need to frequentlyuse remote sensing data because grassreference evapotranspiration obtained fromroutine weather data describe the shorterterm day-to-day variation. The new methodis based on the simplified Priestley &Taylor equation for cropevapotranspiration. It is argued that thisis justified for humid conditions and thecalculation procedure is validated withfield data collected from irrigatedvegetables in Kenya. The method isthereafter applied to Landsat-TM satellitedata covering the Lake Naivasha Basin,Kenya, and the spatially variable cropcoefficients are determined. This simpletechnique improves the planning ofirrigation water resources because K_cestimations based on satellite imagesreveal the real agricultural practicesbetter than expected acreage data andtabulated K_c-values published in theinternational literature.     

基于语义分割模型和遥感的柑橘园空间信息提取

为应用高分辨率遥感影像和卷积神经网络模型快速提取柑橘园空间信息,选择四川省柑橘重点产区蒲江县为研究区,以高分辨率Google earth图像为数据源,构建3类不同树龄的柑橘园样本数据集,训练U-net和DeepLabv3+语义分割模型,提取柑橘园空间信息。通过验证,具有不同神经网络结构的U-net和DeepLabv3+模型提取柑橘园信息总体精度分别为88.30%和86.79%,Kappa系数为0.75和0.72,二者精度相当;通过分析小地块的果园遥感识别精度,测试区最小识别图斑面积约为120 m²,大于该面积的果园遥感面积平均精度在85%以上。该研究可为经营者、农业部门使用高分辨率遥感影像和开源的深度学习分类工具快速获取果园空间信息提供参考。     

裸露地表土壤水分的L波段被动微波最佳角度反演算法

该文阐述了中纬度地区春季裸露耕地土壤水分监测的重要性,对比分析了目前几种主要的土壤水分反演方法。为提高裸露耕地土壤水分的监测精度,在分析AIEM土壤发射率模拟数据库的基础上,提出了一种基于L波段单角度双极化被动微波遥感数据的土壤湿度和土壤粗糙度的反演算法,并对新反演算法的创新性和可行性进行了基于仿真数据的论证。该反演算法以地表温度作为辅助数据,利用L波段47°双极化的微波亮温数据进行土壤湿度和粗糙度的反演。仿真数据的验证结果表明,在充分考虑土壤温度、土壤质地等辅助数据测量误差的条件下,算法对土壤湿度和土壤     

基于无人机多光谱遥感的夏玉米冠层叶绿素含量估计

为探讨利用无人机多光谱遥感影像监测夏玉米冠层叶绿素含量的可行性,基于2019年不同施氮水平下(0,105,210,315 kg·N/hm²)夏玉米多光谱遥感影像和田间实测冠层叶绿素含量数据,分析了不同施氮水平下夏玉米冠层叶绿素含量的变化规律,同时选取10种常用光谱植被指数与实测冠层叶绿素含量进行相关性分析,采用与实测叶绿素含量极显著相关的9种植被指数,构建了基于遥感光谱指数的夏玉米冠层叶绿素含量遥感监测模型,并通过精度检验确定最优估测模型.结果表明,施用氮肥能够提高夏玉米冠层叶绿素含量,过量氮肥不能持续提高叶绿素含量,同一施氮水平下不同追肥处理之间叶绿素含量没有明显差异.绿色归一化植被指数与叶绿素含量的相关性系数最高,达到了0.892.采用逐步回归分析方法建立的模型表现最优,决定系数为0.87,均方根误差及相对误差分别为0.15和2.68%.因此,无人机多光谱遥感结合逐步回归模型可以实现田间尺度的夏玉米冠层叶绿素含量的实时监测.     

基于遥感数据的大尺度区域水田空间格局及生态服务价值变化分析

受经济和气候驱动,长江经济带水田空间格局发生了显著变化,影响区域粮食安全与生态安全。本研究基于1990-2015年土地利用遥感监测数据,利用GIS的空间分析功能,探究长江经济带水田空间格局动态变化特征,采用当量因子法计算生态系统服务价值（ESV）,分析了水田变化的综合影响。结果表明：1）1990-2015年长江经济带水田规模持续缩减,共减少了17390km²,减幅呈增长态势具有显著地域差异,长江中上游与下游的水田减幅相差约为9.56%。其中下游减幅较大,水田占区域比例随之降低,中上游恰好相反。2）由于经济建设及水产养殖的发展,水田主要转化为建设用地和水系,水田主要由水系、旱地和湿地等转化而来。长江三角洲城市群、长江中游及成渝城市群的水田变化最为剧烈,建设用地侵占水田扩张的现象分布广泛,水田转为水系主要在两湖平原局部地区。3）水田与其他生态系统的转化对ESV是正影响,水田转为水系对此贡献最大,其转化规模决定了不同时期ESV净增量的大小,水系转化为水田损失的价值最多,建设用地侵占水田次之。不同市域的水田变化情况不一致,因此ESV增减情况具有明显差异。4）生态系统服务中水文调节、水资源供给增强的同时,食物生产、气体调节受到严重损害,与水资源规模扩大和水田资源大量流失有直接关系。研究结果有助于揭示长江流域水田的时空变化过程及其对各项生态系统服务的影响,可为区域土地利用规划、农业政策与生态可持续发展提供理论支持。     

基于SEBS模型反演凌河流域尺度地表蒸散发量

利用NOAA/AVHRR数据和气象资料,结合反演陆面蒸发较为准确的SEBS(Surface Energy Balance System)模型,反演了2011年我国辽宁西部地区凌河流域蒸散发量的时空分布。研究表明,凌河流域各月的蒸散发量变化范围在0~7mm之间,少数地区超过7mm。研究为大面积获取我国辽西北干旱地区的蒸散发情况奠定了基础。     

基于遥感和蚁群算法的多目标种植结构优化

针对农业种植结构与水资源不匹配的问题,以主要作物不同生育期需水特点和区域降水特点吻合性为基础,建立了考虑灌区节水效益、经济效益和生态效益的多目标种植结构优化模型,并以宝鸡峡五泉灌区为例,利用遥感快速获取灌区种植结构信息,并以不同口粮面积约束为条件建立2种优化方案,采用蚁群算法对模型在不同约束下的2种优化方案进行优化求解.结果表明：方案1,2的灌区需水总量为现状的85.4%和83.4%,纯收入比现状在平水年低5.4%和高7.1%,在干旱年低5.9%和高7.3%,降雨耦合度分别在平水年高12.6%和15.6%,干旱年高17.5%和28.6%,对2种不同约束方案优化结果比较得出,方案2为最优调整方案.该研究在未改变原有灌区种植面积的条件下,经种植结构优化调整后,既可保持灌区生态环境的可持续发展,又使灌区经济收入有很大的提高.这对农业节水规划具有较高的实用价值和理论意义.     

Evaluation of FAO-56 methodology for estimating reference evapotranspiration using limited climatic data: Application to Tunisia

The Food and Agriculture Organization of the United Nations had improved the version of the Penman–Monteith method (FAO-56 PM) which has recently been proposed as the standard for estimating reference evapotranspiration (ET_o). Unfortunately, some weather variables, especially solar radiation, relative humidity and wind speed, are often missing which could impede the estimation of ET_o with the FAO-56 PM method. To overcome the problem of the availability of climatic parameters, procedures to estimate ET_o with missing climate data are proposed as part of the FAO methodology. Therefore, assessing the accuracy of these procedures for different Tunisian locations is important. The comparison of ET_o estimates using limited data to those computed with full data set revealed that the difference between ET_o obtained from full and limited data set is small considering the 8 locations studied. Both the Mean Bias Error (MBE) and the Root Mean Square Error (RMSE) of the comparison were less than 0.6 and 0.8 with a minimum of −0.4 and 0.2 mm day⁻¹, respectively, leading to small errors in the ET_o estimates. The higher deviations occur when the only available information is minimum and maximum air temperature. These deviations were significantly higher when using the Hargreaves equation to calculate ET_o.     

遥感监测土壤含水量方法综述

土壤水分是陆地表面参数化的一个关键变量,土壤水分含量随时空的分布和变化对地—气间的热量平衡、土壤温度及农业墒情等都会产生显著的影响。常规的土壤水分测量方法采样速度慢、代表性差,无法实现大面积土壤水分的实时动态监测。随着农业信息化的发展,利用遥感技术监测土壤水分是目前定量遥感研究的前沿和难题之一。为此,阐述了土壤水分遥感信息模型方法,并对各方法所需要解决的关键问题及其优缺点做了评述。     

Irrigation Performance Indicators Based on Remotely Sensed Data: a Review of Literature

The earlier generation of irrigation performanceindicators was based on canal flow data. Commonly,they quantify performance in a command area downstreamof a discharge measurement device. Remote sensingdeterminants, such as actual evapo-transpiration, soilwater content and crop growth reflect the overallwater utilization at a range of scales, up to fieldlevel. Crop evapo-transpiration includes wateroriginating from irrigation supply, water fromprecipitation, groundwater and water withdrawn fromthe unsaturated zone. Hence, this is a refinement inspatial scale as compared to the classicallycollected flow measurements, and describes moreoverdepletion from all water resources. If thesepossibilities are well implemented, we expect that anew generation of irrigation performance indicatorscan be quantified in a cost-effective manner.Especially, because satellite measurements pave a wayto standardize data collection between differentirrigation schemes and among different countries atcosts which are currently decreasing. These challengescan only turn into a success if irrigation managersare involved in pilot projects and demonstrationstudies exploring satellite data.