基于空间信息多级网格的CA模型研究

具备时空计算特征的元胞自动机(CA)模型与GIS集成极大促进了GIS对地理过程的模拟能力。论文简要介绍了空间信息多级网格(SIMG)——一种既能适合网格计算环境又充分考虑到地球空间的自然特征和社会属性的差异性及经济发展不平衡的特点的空间信息表示新方法。充分研究了SIMG与CA之间的联系,分别讨论了在SIMG上CA元胞及状态的确定、元胞空间的确定、规则的定义、时间粒度确定等,提出了空间信息多级网格元胞自动机模型(SIMGCA),并提出了SIMGCA模型在土地利用/覆被变化中的应用框架。     

基于GIS的城市土地利用分析与建模框架研究

本文针对城市土地利用数据的时空特性,依托地理信息系统(GIS)丰富的空间分析工具以及对海量空间数据的高性能计算优势,围绕城市土地利用研究有关数据的处理、分析、建模等方面问题设计了一个基于GIS的城市土地利用分析与建模框架;框架主体结构中有关城市土地利用变化的驱动力机制建模方法选取逻辑回归模型,对地理数据的空间自相关性处理则根据Getis自相关系数构建滤波模型;具体应用则结合深圳市国土资源局的"城市土地利用虚拟政策实验室"项目,取得良好效果     

基于GEE平台的海岛地表覆盖提取及变化监测——以苏拉威西岛为例

随着海洋在国家政治、经济、资源等方面重要性的提升,对海岛开发利用、管理和保护等具有重要意义的海岛地表覆盖研究逐渐受到关注.针对传统的大范围地表覆盖提取速度慢、效率低的问题,基于Google Earth Engine(GEE)地学大数据平台,以作为生态重点保护区的印度尼西亚的苏拉威西岛为研究区,开展海岛地表覆盖提取及变化...     

Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes

Global warming has obtained more and more attention because the global mean surface temperature has increased since the late 19th century. As more than 50% of the human population lives in cities, urbanization has become an important contributor for global warming. Pearl River Delta (PRD) in Guangdong Province, southern China, is one of the regions experiencing rapid urbanization that has resulted in remarkable Urban Heat Island (UHI) effect, which will be sure to influence the regional climate, environment, and socio-economic development. In this study, Landsat TM and ETM+ images from 1990 to 2000 in the PRD were selected to retrieve the brightness temperatures and land use/cover types. A new index, Normalized Difference Bareness Index (NDBaI), was proposed to extract bare land from the satellite images. Additionally, Shenzhen, which has experienced the fastest urbanization in Guangdong Province, was taken as an example to analyze the temperature distribution and changes within a large city as its size expanded in the past decade. Results show that the UHI effect has become more prominent in areas of rapid urbanization in the PRD region. The spatial distribution of heat islands has been changed from a mixed pattern, where bare land, semi-bare land and land under development were warmer than other surface types, to extensive UHI. Our analysis showed that higher temperature in the UHI was located with a scattered pattern, which was related to certain land-cover types. In order to analyze the relationship between UHI and land-cover changes, this study attempted to employ a quantitative approach in exploring the relationship between temperature and several indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Bareness Index (NDBaI) and Normalized Difference Build-up Index (NDBI). It was found that correlations between NDVI, NDWI, NDBaI and temperature are negative when NDVI is limited in range, but positive correlation is shown between NDBI and temperature.     

Modelling the impacts of land system dynamics on human well-being: Using an agent-based approach to cope with data limitations in Koper,Slovenia

To cope with data limitations and to provide insight into the dynamics of LUCC for local stakeholders in the Municipality of Koper, Slovenia, we constructed an ABM (loosely defined) that integrates utility theory, logistic regression, and cellular automaton-like rules to represent the decision-making strategies of different agents. The model is used to evaluate the impact of LUCC on human well-being, as represented by the provision of highly productive agricultural soil, the extent of noise pollution, and quality-of-life measurements. Results for the Municipality of Koper show that, under a range of model assumptions, (1) high quality agricultural soils are disproportionately affected by urban growth, (2) aggregate resident quality of life increases non-linearly with a change in development density, (3) some drivers of residential settlement produce non-linear preference responses, and (4) clustering industrial development had a beneficial impact on human well-being. Additional novel contributions include the incorporation of noise pollution feedbacks and an approach to empirically inform agent preferences using a conjoint analysis of social survey data.     

天津滨海新区-曹妃甸典型地区土地利用演变分析

根据1984、2000、2006和2009年4期Landsat影像,运用分类后比较法以及土地利用演变的时空分析方法,探讨和分析天津滨海新区和河北曹妃甸地区近30 a的土地利用变化特征和规律,阐明了研究区土地利用变化的区域特点,为土地可持续利用提供有效的决策支持。结果表明：坑塘水面是两个区域最主要的土地利用类型,尤其在曹妃甸地区,坑塘水面占用比例达60%~70%。1984~2009年两地区围海造地面积呈增加趋势,有“向海洋要土地”的发展趋势。土地利用变化的主要特征为耕地减少和建设用地、坑塘水面增加,2000年以后土地利用变化趋势尤为显著。滨海新区建设用地重心有西南方向移动的趋势,其他土地利用类型重心均有向东向北迁移的趋势,曹妃甸地区各土地类型均有明显的南移趋势。     

基于NDVI序列影像的植被覆盖变化研究

归一化植被指数NDVI是地表植被覆盖特征的重要指标之一。以新疆石河子地区2003~2006年MODIS遥感数据反演的NDVI时间序列影像为例,分析研究了植被长势的年内和年际变化,将植被长势的年内变化和年际变化分为比前一年(月)好、比前一年(月)稍好、与前一年(月)持平、比前一年(月)稍差和比前一年(月)差5个等级,得到年内和年际间植被长势的动态分布图,从植被长势分布图中NDVI的变化可以看出年际和年内植被长势的变化。并应用变化矢量分析法对2003~2006年石河子地区NDVI的变化强度进行了分析,获得了植被覆盖变化强度分布情况,研究结果表明4 a内石河子地区植被覆盖未发生大的变化,植被系统基本稳定。     

The Spatial Transformation and Hotspot Detection of Land Use and Cover in Arid Basin：A Case of the Middle Reaches of Heihe River

Based on the data of land use/cover change in the middle reaches of the Heihe River in 1987,2001 and 2016,with the support of remote sensing technology,the Markov transfer matrix and land use dynamic estimation model were used to simulate the land use transformation direction and spatial distribution characteristics,detect hotspots of land use/cover change,analyze the relevant driving factors,and propose the countermeasures for development bottlenecks during the study period in the middle reaches of the Heihe River between 1987~2001 and 2001~2016.Its main findings are as follows：the main changes of land use in the middle reaches of Heihe River as the land of human activities gradually increasing,the ecological land decreasing continuously.The areas with sharp changes in land use are mainly concentrated on both sides of the river,the types of transformation are mainly in the conversion of waters into grassland,grassland into cultivated land,and the unused land to construction land;The scope of land use transformation in the study area have obvious spatial differences,the frequency and expansion are significantly higher than the previous period;as a whole,the hot region are located in the oasis area of agriculture in Zhangye,but the early hot region is more dispersed,small,no benefit,the later is concentrated,and has more central tendency in the larger space.     

土地利用与土地覆盖变化信息的图谱研究——以大福州为例

本论文应用RS和GIS复合技术提取大福州城土地利用信息图谱,从现状结构、发展变化(净变化与相互转化)等方面对大福州城的土地利用信息进行定性和定量的分析,并建立了实验区土地利用演变过程和空间扩展图谱,其研究和建立的土地利用斑块形态与扩展图谱,在一定程度上反映了地学信息图谱的“形-数-理结合”和“系列化”、“谱系化”、“模型数值化”的特征,本工作是地学信息图谱在LUCC中的应用尝试,对区域土地可持续利用有指导意义。     

基于云平台的中哈干旱区典型城市地表覆盖变化遥感监测与比较

城市地表覆盖组分是影响人居生存环境和城市生态系统服务的关键因素。基于Google Earth Engine平台,利用Landsat 5/8遥感影像数据,采用改进的“植被—不透水面—土壤”模型及线性光谱混合分解方法,提取地处干旱区的中国西部大城市乌鲁木齐市与邻国哈萨克斯坦首都城市努尔–苏丹市、大城市阿拉木图市的地表覆盖信息,对比分析1990~2015年3个城市地表覆盖的变化特征。结果表明：1990~2015年间乌鲁木齐市城市建成区扩张面积最大,扩张了349.81 km²;其次为努尔-苏丹市,城市扩张面积为158.16 km²;由于哈萨克斯坦首都由阿拉木图市迁往努尔-苏丹市,整个时段阿拉木图市城市扩张最慢,总计扩张了126.23 km²。在城市建成区内,1990年到2015年间乌鲁木齐市城市地表不透水组分增加了7.10%,努尔—苏丹市和阿拉木图市分别减少了14.9%、4.49%。建成区内绿地组分努尔—苏丹市从1990年到2015年增加了6.68%;乌鲁木齐市和阿拉木图市分别减少了6.65%和2.75%。城市所表现出来的不同地表覆盖特征乌鲁木齐市主要受国家政策支持,阿拉木图市由于其历史背景和城市规划,努尔—苏丹市城市的快速发展则受哈萨克斯坦迁都的影响。     

青藏高原地表温度时空变化分析

使用MODIS地表温度(LST)产品对青藏高原地表温度的空间分布和年际变化进行分析。通过一种融合时空信息的方法对LST缺失像元进行重建恢复,重建后有效像元比例达到97%以上。用正弦和线性分段函数法将4个瞬时时刻的LST观测值拟合为日平均LST,经地面0cm土壤温度观测数据验证,拟合后的均方根误差(RMSE)在1K以内。建立以年为周期的余弦函数模型,刻画了LST在一年内的季节波动,并得到LST的年平均值、振幅和峰值日期3个参数。分析了各参数在空间上的分布和多年的变化趋势。结果显示:LST年平均值与海拔高度、纬度和下垫面类型相关性较大;年内振幅从青藏高原东南部到西北部呈升高趋势;水体的峰值日期相比其他地物类型有明显的延迟。多年变化斜率分析显示,整个青藏高原的年平均LST以每年0.015K的速度升高,振幅以每年0.076K的速度增长,反映出受气候变化的影响,极端气候出现的概率明显增大,而峰值日期有所提前。     

基于关键成功因子的ERP项目实施过程模型

鉴于ERP实施项目周期长、成本高、失败风险大的现实情况,本文以“关键成功因子”为核心建立ERP实施过程模型,模型包括“关键成功因子的识别”、“以关键成功因子评价为基础的实施过程改进”和“以变更管理为基础的实施过程改进”三个要素。应用该模型使得在ERP项目实施前能预测到项目可能的风险,缩短实施周期,使整个实施过程得到有效监督、测量,提高ERP实施成功率。     

A logistic regression framework for information technology outsourcing lifecycle management

We present a methodology for managing outsourcing projects from the vendor's perspective, designed to maximize the value to both the vendor and its clients. The methodology is applicable across the outsourcing lifecycle, providing the capability to select and target new clients, manage the existing client portfolio and quantify the realized benefits to the client resulting from the outsourcing agreement. Specifically, we develop a statistical analysis framework to model client behavior at each stage of the outsourcing lifecycle, including: (1) a predictive model and tool for white space client targeting and selection—opportunity identification (2) a model and tool for client risk assessment and project portfolio management—client tracking, and (3) a systematic analysis of outsourcing results, impact analysis, to gain insights into potential benefits of IT outsourcing as a part of a successful management strategy. Our analysis is formulated in a logistic regression framework, modified to allow for non-linear input–output relationships, auxiliary variables, and small sample sizes. We provide examples to illustrate how the methodology has been successfully implemented for targeting, tracking, and assessing outsourcing clients within IBM global services division.Scope and purposeThe predominant literature on IT outsourcing often examines various aspects of vendor–client relationship, strategies for successful outsourcing from the client perspective, and key sources of risk to the client, generally ignoring the risk to the vendor. However, in the rapidly changing market, a significant share of risks and responsibilities falls on vendor, as outsourcing contracts are often renegotiated, providers replaced, or services brought back in house. With the transformation of outsourcing engagements, the risk on the vendor's side has increased substantially, driving the vendor's financial and business performance and eventually impacting the value delivery to the client. As a result, only well-ran vendor firms with robust processes and tools that allow identification and active management of risk at all stages of the outsourcing lifecycle are able to deliver value to the client. This paper presents a framework and methodology for managing a portfolio of outsourcing projects from the vendor's perspective, throughout the entire outsourcing lifecycle. We address three key stages of the outsourcing process: (1) opportunity identification and qualification (i.e. selection of the most likely new clients), (2) client portfolio risk management during engagement and delivery, and (3) quantification of benefits to the client throughout the life of the deal.     

Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data

The overarching goal of this study was to map irrigated areas in the Ganges and Indus river basins using near-continuous time-series (8-day), 500-m resolution, 7-band MODIS land data for 2001-2002. A multitemporal analysis was conducted, based on a mega file of 294 wavebands, made from 42 MODIS images each of 7 bands. Complementary field data were gathered from 196 locations. The study began with the development of two cloud removal algorithms (CRAs) for MODIS 7-band reflectivity data, named: (a) blue-band minimum reflectivity threshold and (b) visible-band minimum reflectivity threshold.A series of innovative methods and approaches were introduced to analyze time-series MODIS data and consisted of: (a) brightness-greenness-wetness (BGW) RED-NIR 2-dimensional feature space (2-d FS) plots for each of the 42 dates, (b) end-member (spectral angle) analysis using RED-NIR single date (RN-SD) plots, (c) combining several RN-SDs in a single plot to develop RED-NIR multidate (RN-MDs) plots in order to help track changes in magnitude and direction of spectral classes in 2-d FS, (d) introduction of a unique concept of space-time spiral curves (ST-SCs) to continuously track class dynamics over time and space and to determine class separability at various time periods within and across seasons, and (e) to establish unique class signatures based on NDVI (CS-NDVI) and/or multiband reflectivity (CS-MBR), for each class, and demonstrate their intra- and inter-seasonal and intra- and inter-year characteristics. The results from these techniques and methods enabled us to gather precise information on onset-peak-senescence-duration of each irrigated and rainfed classes.The resulting 29 land use/land cover (LULC) map consisted of 6 unique irrigated area classes in the total study area of 133,021,156 ha within the Ganges and Indus basins. Of this, the net irrigated area was estimated as 33.08 million hectares—26.6% by canals and 73.4z5 by groundwater. Of the 33.08 Mha, 98.4% of the area was irrigated during khariff (Southwest monsoonal rainy season during June-October), 92.5% irrigated during Rabi (Northeast monsoonal rainy season during November-February), and only 3.5% continuously through the year.Quantitative Fuzzy Classification Accuracy Assessment (QFCAA) showed that the accuracies of the 29 classes varied from 56% to 100%—with 17 classes above 80% accurate and 23 classes above 70% accurate.The MODIS band 5 centered at 1240 nm provided the best separability in mapping irrigated area classes, followed by bands 2 (centered at 859 nm), 7 (2130 nm) and 6 (1640 nm).     

结合编码-解码网络和条件随机场的全极化合成孔径雷达土地覆盖分类

针对多极化合成孔径雷达影像地物分类特征表征性较弱及全卷积网络分类精度较低的问题,文中提出结合编码-解码网络(E-D-Net)和条件随机场(CRF)的全极化合成孔径雷达(SAR)土地覆盖分类算法.首先,利用Freeman分解和Pauli分解建模全极化SAR影像,提取各分解对应的散射特征.再借鉴语义分割网络模型的建模思想和多尺度卷积单元构建对称网络模型,将多尺度非对称卷积单元嵌入中层,设计E-D-Net网络模型.通过E-D-Net网络模型对PolSAR影像Freeman分解散射特征进行多层自主学习,获得初始分类结果.最后,利用全连接CRF结合Pauli相干分解伪彩色图信息,对初始分类结果再进行降噪和平滑优化,得到最终分类结果.在两地区PolSAR影像上的实验验证文中算法的有效性和可行性.