GIS支持下基于遗传优化神经网络的溃坝生命损失评估

针对溃坝生命损失评估涉及众多地理空间对象且影响因素多而复杂的特点,提出了GIS支持下基于遗传优化神经网络的溃坝生命损失评估方法。引入GIS与空间信息格网,提出了基于GIS空间信息格网模型的溃坝生命损失评估计算模型。分析了溃坝生命损失的影响因素,通过灰色关联度模型评判,建立了评估指标体系。开发了GIS支持下的溃坝生命损失快速评估系统,分析了系统的集成方案以及GIS空间信息格网模型的实现方法。应用表明,该评估方法精度较高,效果较好。     

基于SPEI的黑龙江省小兴安岭地区干旱影响因子分析

干旱指数是反映气候干旱程度的指标,也是监测和评估干旱事件的有效工具。本文以黑龙江省小兴安岭地区为研究区,基于FAO Penman-Monteith方法估算潜在蒸散,计算了2000—2018年3个时间尺度标准化降水蒸散指数(SPEI)逐月数据;从气象因子、水循环因子、地形因子和地表覆盖变化的4个方面,分析了多时间尺度下干旱和影响因子的关系。结果表明：干旱和降水、相对湿度、水分盈缺呈负相关,干旱和日照时数、风速、潜在蒸散呈正相关;干旱和地形因子的相关性较为复杂;不同地表覆盖类型的干旱差异不明显,但干湿年份之间差异明显。本研究成果将为旱情监测和评估,以及复杂地形的干旱研究提供科学参考。     

基于矢量评估单元的模糊综合评价在GIS中的实现

模糊综合评价与GIS空间分析功能的融合应用,使基于GIS的模糊综合评价显示出强大的优势。由于栅格模型计算方便,目前GIS模糊综合评价中基本采用栅格评估单元,但栅格单元由人为指定单元大小,其单元大小和形状不一、边界复杂、空间运算时隶属度与权重等属性结构设计较难实现,大大限制了其在模糊综合评价中的应用。本文介绍了在GIS中采用矢量评估单元实现模糊综合评价的基本方法,探讨了在矢量评估单元的属性结构中设计单元的隶属度和权重等属性的关键技术,为矢量评估单元在GIS模糊综合评价中的应用提供了经验。     

基于GIS的土壤重金属污染分析与模拟系统设计

作为环境质量评估的重要指标之一,土壤重金属污染程度对环境质量具有重要影响。为了了解土壤重金属污染现状以及评价重金属污染对环境的影响,利用GIS平台、MySQL数据库、空间分析方法、土壤重金属污染扩散模型等关键技术和方法,设计并开发了基于GIS的土壤重金属污染分析与模拟系统。系统实现了重金属污染分析、二维扩散模拟等功能,可为大面积土壤重金属污染的预防与治理提供技术支持。     

基于几何代数的GIS计算模型研究

正空间分析是地理信息系统(GIS)的核心功能,也是GIS深化应用与服务的重要支撑。现有空间数据分析方法在多维对象的自适应表达、空间数据的统一分析以及多维统一分析框架的构建方面仍显不足,无法满足海量、高维度、多要素的密集型GIS空间数据的分析需求。引入几何代数的多维表达结构及统一运算结构,从底层理论上对现有表达与计算方法进行创新,设计面向多维度、多要素复杂数据的计算模型,是突破传统GIS分析方法     

基于小波的不规则三角网(WTIN)

因特网和个人计算机的普及使地理信息系统(GIS)进入了人们的日常生活。在网络环境中,“互操作”是GIS产品需要重视的特性,这也是OpenGIS组织在其OpenGIS模型中强调的重要概念。分布式GIS的服务应该是变比例的,因为实际用户会有不同的连接带宽、显示设备和使用需求。为了适应这一要求,海量GIS数据管理的好坏显得非常关键。GIS数据中最复杂的数据是三维地形数据,现有数据格式有DEM、TIN,DEM数据量巨大且具有不变性,TIN没有自然     

一种面向角色任务分解的网格三维GIS处理模型

讨论了一种新型的网格任务分配模型.该模型将网格计算思想和三维GIS漫游技术有机地结合在一起,将复杂的三维GIS计算任务分解成小块并分交给多台实验机协同完成,从而使原先只能单机上运行的三维GIS漫游功能,现在能由多台机器同时处理,有效地解决了传统三维GIS漫游中由于三维数据量太大和处理复杂而产生的诸如三维漫游速度慢、要求服务器配置高、漫游时停顿等问题.     

黑龙江省干旱及植被分布的时空变化分析

干旱是影响社会经济系统和自然生态系统的重要气象灾害.本研究基于多时间序列的SPEI和NDVI栅格数据,利用GIS空间分析方法和统计分析方法,对比分析了2000—2018年黑龙江省干旱和植被分布的时空变化特征,从而揭示了干旱对植被分布的影响.研究表明:1)干旱具有明显的年际和季节特征,以及干湿变化的阶段性和趋势性,呈东—西干湿反向变化空间分布;2)植被分布具有明显季节特征,但年际特征不明显,呈西北、北部和东南部高,东北、西南部低的空间分布;3)干旱对植被分布影响具有复杂性.研究结果可为干旱防灾减灾和影响评估以及区域生态恢复提供参考依据.     

2000-2018年黑龙江省干旱时空特征分析

干旱指数是反映气候干旱程度的指标,其是监测和评估干旱事件的有效工具。文中以黑龙江省为研究区,采用标准化降水蒸散指数(SPEI),结合干旱面积比、干旱频率和单位面积干旱强度,利用M-K检验方法、GIS空间分析方法和统计分析方法,从多角度分析研究区干旱的时空特征,揭示2000-2018年黑龙江省干旱的时空变化规律。研究结果可为区域干旱防灾减灾风险评估提供参考依据。     

地理信息系统支持下的降雨时空统计分析

将地理信息系统（GIS）技术与3维虚拟现实（VR）技术引用到防讯工作中，研究并建立GIS支持下的降雨时空统计模型；该模型为早期防汛预报调度提供了先决条件，是防汛信息系统的一个核心评估计算模型。     

在GIS支持下用NOAA/AVHRR数据进行旱情监测

旱灾是影响农作物生产的一种重大自然灾害,它对中国北方春小麦生产的影响极大。本文介绍了一个应用遥感、ＧＩＳ技术对黄淮海平原春小麦的旱情进行监测的系统及其方法。它综合使用的ＮＯＡＡ／ＡＶＨＲＲ数据、地面气象资料和地图,选用作物缺水指数（ＣＷＳＩ）模型和热惯理模型对旱情进行监测。监测结果分别用分县的旱情等级分布图和相应不同等级的旱情面积、面积比例数统计表来表示。该系统自１９９４年起投入运行３年,监测结果     

Comparison of three remotely sensed drought indices for assessing the impact of drought on winter wheat yield

ABSTRACT

Agricultural drought threatens food security. Numerous remote-sensing drought indices have been developed, but their different principles, assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas. Here, we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces, northern China (predominantly rain-fed and irrigated agriculture, respectively): vegetation health index (VHI), temperature vegetation dryness index (TVDI) and drought severity index (DSI). We compared the agreement between these indices and the standardized precipitation index (SPI), soil moisture, winter wheat yield and National Meteorological Drought Monitoring (NMDM) maps. On average, DSI outperformed the other indices, with stronger correlations with SPI and soil moisture. DSI also corresponded better with soil moisture and NMDM maps. The jointing and grain-filling stages of winter wheat are more sensitive to water stress, indicating that winter wheat required more water during these stages. Moreover, the correlations between the drought indices and SPI, soil moisture, and winter wheat yield were generally stronger in Shaanxi province than in Henan province, suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas.     

冬小麦旱情遥感监测模型研究

本研究依据土壤水量平衡及能量平衡的原理,提出了一套利用遥感方法监测冬小麦干旱及建模的方法。首先,用热惯性方法建立试区土壤表观热惯量与土壤水分的关系,用其估算初始土壤含水量(W_0);再用NOAA-AVHRR数字图像和气象数据相结合的方法估算冬小麦地的蒸散(E_t);从而根据水量平衡方程获得某一时段(旬)的土壤含水量(W_t);最后,根据冬小麦的需水规律和土壤有效水含量构造干旱指数模型。试验表明,此模型反映了作物干旱的本质,能大范围有效地监测作物旱情。     

On agricultural drought monitoring in Australia using Himawari-8 geostationary thermal infrared observations

Monitoring agricultural drought effectively and timely is important to support drought management and food security. Effective drought monitoring requires a suite of drought indices to capture the evolution process of drought. Thermal infrared signals respond rapidly to vegetation water stress, thus being regarded useful for drought monitoring at the early stage. Several temperature-based drought indices have been developed considering the role of land surface temperature (LST) in surface energy and water balance. Here, we compared the recently proposed Temperature Rise Index (TRI) with several agricultural drought indices that also use thermal infrared observations, including Temperature Condition Index (TCI), Vegetation Health Index (VHI) and satellite-derived evapotranspiration ratio anomaly (Δf_RET) for a better understanding of these thermal infrared drought indices. To do so, we developed a new method for calculating TRI directly from the top-of-atmosphere brightness temperatures in the two split-window channels (centered around ∼11 and 12 μm) rather than from LST. TRI calculated using the Himawari-8 brightness temperatures (TRI_BT) and LST retrievals (TRI_LST), along with the other LST-based indices, were calculated for the growing season (July–October) of 2015−2019 over the Australian wheatbelt. An evaluation was conducted by spatiotemporally comparing the indices with the drought indices used by the Australian Bureau of Meteorology in the official drought reports: the Precipitation Condition Index (PCI) and the Soil Moisture Condition Index (SMCI). All the LST-based drought indices captured the wet conditions in 2016 and dry conditions in 2019 clearly. Ranking of Pearson correlations of the LST-based indices with regards to PCI and SMCI produced very similar results. TRI_BT and TRI_LST showed the best agreement with PCI and SMCI (r > 0.4). TCI and VHI presented lower consistency with PCI and SMCI compared with TRI_BT and TRI_LST. Δf_RET had weaker correlations than the other LST-based indices in this case study, possibly because of outliers affecting the scaling procedure. The capability of drought early warning for TRI was demonstrated by comparing with the monthly time series of the greenness index Vegetation Condition Index (VCI) in a case study of 2018 considering the relatively slow response of the greenness index to drought. TRI_BT and TRI_LST had a lead of one month in showing the changing dryness conditions compared with VCI. In addition, the LST-based indices were correlated with annual wheat yield. Compared to wheat yields, all LST-based indices had a peak correlation in September. TRI_BT and TRI_LST had strong peak and average correlations with wheat yield (r ≥ 0.8). We conclude that TRI has promise for agricultural drought early warning, and TRI_BT appears to be a good candidate for efficient operational drought early warning given the readily accessible inputs and simple calculation approach.     

Winter wheat mapping using a random forest classifier combined with multi-temporal and multi-sensor data

Wheat is a major staple food crop in China. Accurate and cost-effective wheat mapping is exceedingly critical for food production management, food security warnings, and food trade policy-making in China. To reduce confusion between wheat and non-wheat crops for accurate growth stage wheat mapping, we present a novel approach that combines a random forest (RF) classifier with multi-sensor and multi-temporal image data. This study aims to (1) determine whether an RF combined with multi-sensor and multi-temporal imagery can achieve accurate winter wheat mapping, (2) to find out whether the proposed approach can provide improved performance over the traditional classifiers, and (3) examine the feasibility of deriving reliable estimates of winter wheat-growing areas from medium-resolution remotely sensed data. Winter wheat mapping experiments were conducted in Boxing County. The experimental results suggest that the proposed method can achieve good performance, with an overall accuracy of 92.9% and a kappa coefficient (κ) of 0.858. The winter wheat acreage was estimated at 33,895.71?ha with a relative error of only 9.3%. The effectiveness and feasibility of the proposed approach has been evaluated through comparison with other image classification methods. We conclude that the proposed approach can provide accurate delineation of winter wheat areas.     

Maize drought disaster risk assessment of China based on EPIC model

Abstract

Digital Agriculture is one of the important applications of Digital Earth. As the global climate changes and food security becomes an increasingly important issue, agriculture drought comes to the focus of attention. China is a typical monsoon climate country as well as an agricultural country with the world's largest population. The East Asian monsoon has had a tremendous impact upon agricultural production. Therefore, a maize drought disaster risk assessment, in line with the requirements of sustainable development of agriculture, is important for ensuring drought disaster reduction and food security. Meteorology, soil, land use, and agro-meteorological observation information of the research area were collected, and based on the concept framework of ‘hazard-inducing factors assessment (hazard)-vulnerability assessment of hazard-affected body (vulnerability curve)-risk assessment (risk),’ importing crop model EPIC (Erosion-Productivity Impact Calculator), using crop model simulation and digital mapping techniques, quantitative assessment of spatio-temporal distribution of maize drought in China was done. The results showed that: in terms of 2, 5, 10, and 20 year return periods, the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas. With the 20 year return period, high risk value regions (drought loss rate ≥0.5) concentrate in the irrigated maize region of Northwest china, ecotone between agriculture and animal husbandry in Northern China, Hetao Irrigation Area, and north-central area of North China Plain, accounting for 6.41% of the total maize area. These results can provide a scientific basis for the government's decision-making in risk management and drought disaster prevention in China.     

A simple assessment approach for winter wheat loss risk impacted by water stress

In this study, an empirical assessment approach for the risk of crop loss due to water stress was developed and used to evaluate the risk of winter wheat loss in China, the United States, Germany, France and the United Kingdom. We combined statistical and remote sensing data on crop yields with climate data and cropland distribution to model the effect of water stress from 1982 to 2011. The average value of winter wheat loss due to water stress for the three European countries was about ?931 kg/ha, which was higher than that in China (?570 kg/ha) and the United States (?367 kg/ha). Our study has important implications for the operational assessment of crop loss risk at a country or regional scale. Future studies should focus on using higher spatial resolution remote sensing data, combining actual evapotranspiration to estimate water stress, improving the method for downscaling of statistical crop yield data and establishing more sophisticated zoning methods.     

区域可持续发展评价信息系统研究

自然科学、技术与社会科学的有机结合是可持续发展研究中非常重要而有效的途径之一。在研究区域可持续发展指标体系的基础上，探讨基于利用地理信息系统（GIS）技术的可持续发展评价信息系统，提出了系统的设计框架与实现方式。选择四川省攀枝花市作为研究区域，建立该市可持续发展指标体系和可持续发展评价信息系统，将可持续发展信息基础数据库、指标计算、指标的可视化表现、评价报告的自动生成及空间信息查询等集成为一体，并实现了系统的开放性、网络化，是规划方案制定、决策实现和公众参与的有效便捷工具，可以为可持续发展规划、管理决策提供科学依据。     

旱情遥感监测研究进展与应用案例分析

在大范围、长时序的旱情监测中,遥感技术以其快速、经济和大空间范围获取的特点,弥补了基于台站气象数据旱情监测的不足,为防旱和抗旱决策提供了实时、动态、宏观的辅助决策数据。本文对已有旱情遥感监测方法进行分析和整理,将其总结为基于土壤热惯量、基于土壤波谱特征、基于蒸散模型和基于植被指数的旱情监测方法,并对各类方法从监测原理、适用范围和应用进展等方面进行了阐述。在此基础之上,详细介绍一种结合了全球植被水分指数和短波角度归一化指数的优势建立的旱情遥感监测模型和方法。以2010年春季西南地区旱情为应用案例,从监测模型方法、数据处理流程和应用分析等方面,介绍一种基于植被水分指数的旱情监测方法,并对其监测结果进行统计分析与评价。     

基于WebGIS的饮用水水源地水质监测与评价系统设计

随着工业化进程加快,居民饮水安全受到的威胁日趋增多,因而以水源作为核心标准,加强对饮用水水源地水质的监测与评估对确保饮用水安全具有重要意义。本文利用GIS技术具有的空间特性,以城市饮用水的水源地为对象,结合单因子评价法和综合标识指数评价法建立水质评价模型,建立基于WebGIS的水质监测与评价系统,为水源地信息管理工作和保障城市饮用水安全提供技术支撑与数据依据。