Modeling pedestrian shopping behavior using principles of bounded rationality: model comparison and validation

Models of geographical choice behavior have been dominantly based on rational choice models, which assume that decision makers are utility-maximizers. Rational choice models may be less appropriate as behavioral models when modeling decisions in complex environments in which decision makers may simplify the decision problem using heuristics. Pedestrian behavior in shopping streets is an example. We therefore propose a modeling framework for pedestrian shopping behavior incorporating principles of bounded rationality. We extend three classical heuristic rules (conjunctive, disjunctive and lexicographic rule) by introducing threshold heterogeneity. The proposed models are implemented using data on pedestrian behavior in Wang Fujing Street, the city center of Beijing, China. The models are estimated and compared with multinomial logit models and mixed logit models. Results show that the heuristic models are the best for all the decisions that are modeled. Validation tests are carried out through multi-agent simulation by comparing simulated spatio-temporal agent behavior with the observed pedestrian behavior. The predictions of heuristic models are slightly better than those of the multinomial logit models.     

The measurement of mangrove characteristics in southwest Florida using spot multispectral data

An intensive in situ sampling program near Marco Island, Florida during 19–23 October 1988 collected information on mangrove type, maximum canopy height, and percent canopy closure. These data were correlated with selected vegetation index information derived from analysis of SPOT multispectral (XS) data obtained on 21 October 1988. The Normalized Difference (ND) vegetation index information was the most highly correlated index with percent canopy closure (r=0.91). Percent canopy closure information can be used as a surrogate for mangrove density which is of great value when predicting which parts of the mangrove ecosystem are at greatest risk after an oil spill occurs. Such information is very valuable when constructing oil spill Environmental Sensitivity Index (ESI) Maps for tropical regions of the world.     

山区地形效应对微波辐射特征与土壤水分反演的影响—以青藏高原地区为例

采用星载微波辐射计AMSR-E的低频C波段(6.925GHz),改进了山区微波辐射传输方程,以中国青藏高原地区为例,研究山区可能产生的多种地形效应对微波辐射特征以及土壤水分反演的影响。结果表明,地形效应使得垂直极化亮温最多衰减达到16K,水平极化的亮温最大增强了18K,土壤水分在地形的影响下将被高估超过最大允许误差4%。最后,利用地形效应模拟模型计算的山区地表有效发射率,为山区土壤水分的反演提出了可行的地形校正方法。     

Derivation of crop phenological parameters using multi-date SPOT-VGT-NDVI data: A case study for Punjab

Crop phenological parameters, such as the start and end time of the crop growth, the total length of the growing season, time of peak vegetation and rate of greening and senescence are important for planning crop management and crop diversification/intensification. Multi-temporal remote sensing data provides opportunity to characterize the crop phenology at regional level. This study was conducted during the kharif season of the year 2001–02 for Punjab. The ten-day Normalised Difference Vegetation Index (NDVI) composite products, with 1 km spatial resolution, available from the Vegetation sensor onboard SPOT4 were used for the study. Twenty-one temporal datasets from May 1, 2001 to November 21, 2001 were used. Logical modelling approach was followed to compute the minimum and maximum NDVI, the amplitude of NDVI, the threshold NDVI during sowing and harvest, the crop duration, integrated NDVI and skewness of profile. The analysis showed that before July beginning, in the whole of Punjab, sowing/planting was over. It was found that the crop emergence in the eastern part of the state started earlier than the western region. The maximum NDVI, which represented peak vegetative stage, was above 0.7 and occurred mostly during August. The duration of crops ranged between 90–140 days, with majority between 110–120 days. Total integrated NDVI in Punjab was generally above 60. Using principal component analysis and divergence analysis seven best metrics were selected for crop discrimination.     

室内位置地图数据模型构建与应用

室内位置地图是实现位置服务的基础,不仅包含室内空间对象的几何信息,而且还包含对象之间的位置关联关系和语义特征。现有的地图数据模型缺少从位置服务的角度对室内空间的全面分析和描述,难以满足多样化的应用需求。采用面向对象方法构建了室内位置地图概念模型和逻辑模型,实现室内空间几何形态、位置关系和语义特征的统一描述,并通过位置和语义关联提供精准化、适人化的信息服务。结合商场室内个性化推荐与路径导航等位置服务实验,初步验证数据模型的有效性。     

Methane emission modelling using MODIS thermal and optical data: A case study on Gujarat

Wetlands are one of the most important sources of atmospheric methane (CH₄) contributing about 22% to the global methane budget. But to improve estimates of CH₄ emission at regional and global scales there is a need to observe the sources such as wetlands frequently and develop process-based models. In this regard, wetland inventory using satellite remote sensing data has conventionally been carried out by analysis of optical data. Due to thermal inertia differences emittive thermal channels data has shown promise to provide highly critical information about wetlands such as water spread, aquatic vegetation and mud flats etc. Thermal channels data of MODIS (Moderate Resolution Imaging Spectroradiometer) sensor with a spatial resolution of 1km and swath of 2330 km is emerging as the key source of remote sensing data for global/ regional wetland estimation and assessment of green house gas emission. In the present study MODIS thermal channels (31 and 32) and optical channels (1,2, and 3) data have been used for evaluating methane emission from wetlands in Gujarat. An empirical model based on temperature and productivity has been used to investigate the response of methane emission from different sources. Model has the potential to estimate country level methane emission based on satellite remote sensing in conjunction with collateral data/information. In this study. MODIS data of two dates pertaining to Gujarat have been analyzed and results compared with respect to methane emission.     

A study on the polarimetric properties of various features using SIR-C data

Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference (PPD) gives good information about the vegetation parameters.     

利用Sentinel-1A数据监测地表形变案例分析

雷达卫星结合InSAR技术已广泛应用于高精度地表形变监测领域。本文选取2017年九寨沟地震为研究案例,利用Sentinel-1A地震前后的单视复数影像,基于D-InSAR技术获取该次地震的同震形变场。结果显示:震中西北侧表现出相对均匀的下沉现象,沉降漏斗区雷达视线向最大沉降量达25.1 cm;东南侧呈现不均匀抬升状态,地表破碎较为明显,最大抬升量为11.6 cm。研究表明基于Sentinel-1A数据的D-InSAR技术可以为地震形变场的定量分析提供一种快速有效的手段,为阐释地震发震机理及评估受灾情况提供必要的数据支撑,具有广阔的应用前景。     

多角度遥感估算稀疏团粒分布型土壤表面粗糙度方法初探

表面粗糙度是影响土壤在微波波段发射和散射辐射的主要因素之一,也是微波遥感研究与应用的重要参量。由于微波后向散射还受介电特性、穿透深度等因素的影响,在微波遥感应用中往往难以单独考虑介质表面粗糙度,给参数估算与反演带来了一定困难。在可见光、近红外波段,粗糙度作为土壤表面重要的结构参数之一,直接影响着土壤的二向反射分布特征。因此,本文尝试利用光学多角度观测信息,反演土壤表面粗糙度。基于地表二向反射几何光学模型,假设裸土像元由随机分布于平坦表面的土壤团粒组成,将团粒近似为半椭球体,建立裸露土壤表面二向反射模型,模拟不同粗糙度条件下土壤表面像元的二向反射分布特征。进一步尝试采用多角度观测数据反演模型,估算土壤团粒的几何结构参数,进而计算土壤表面均方根高度,作为表面粗糙度的衡量指标。地面实测多角度数据的初步验证结果表明,多角度光学遥感估算土壤表面粗糙度的方法是可行的。     

A comprehensive framework for exploratory spatial data analysis: Moran location and variance scatterplots

Abstract

A significant Geographic Information Science (GIS) issue is closely related to spatial autocorrelation, a burning question in the phase of information extraction from the statistical analysis of georeferenced data. At present, spatial autocorrelation presents two types of measures: continuous and discrete. Is it possible to use Moran's I and the Moran scatterplot with continuous data? Is it possible to use the same methodology with discrete data? A particular and cumbersome problem is the choice of the spatial-neighborhood matrix (W) for points data. This paper addresses these issues by introducing the concept of covariogram contiguity, where each weight is based on the variogram model for that particular dataset: (1) the variogram, whose range equals the distance with the highest Moran I value, defines the weights for points separated by less than the estimated range and (2) weights equal zero for points widely separated from the variogram range considered. After the W matrix is computed, the Moran location scatterplot is created in an iterative process. In accordance with various lag distances, Moran's I is presented as a good search factor for the optimal neighborhood area. Uncertainty/transition regions are also emphasized. At the same time, a new Exploratory Spatial Data Analysis (ESDA) tool is developed, the Moran variance scatterplot, since the conventional Moran scatterplot is not sensitive to neighbor variance. This computer-mapping framework allows the study of spatial patterns, outliers, changeover areas, and trends in an ESDA process. All these tools were implemented in a free web e-Learning program for quantitative geographers called SAKWeb© (or, in the near future, myGeooffice.org).     

基于被动微波遥感的地表粗糙度及土壤水分反演研究

被动微波遥感具有监测面积大、重复周期短、对土壤水分更为敏感等优点,成为反演土壤水分最有潜力的方式.论文针对地表粗糙度和植被覆盖变化对土壤水分反演过程中带来的误差和不确定性展开研究,发展更适合大区域土壤水分反演的算法.     

Mapping wetland characteristics using temporally dense Sentinel-1 and Sentinel-2 data: A case study in the St. Lucia wetlands,South Africa

Wetlands have been determined as one of the most valuable ecosystems on Earth and are currently being lost at alarming rates. Large-scale monitoring of wetlands is of high importance, but also challenging. The Sentinel-1 and -2 satellite missions for the first time provide radar and optical data at high spatial and temporal detail, and with this a unique opportunity for more accurate wetland mapping from space arises. Recent studies already used Sentinel-1 and -2 data to map specific wetland types or characteristics, but for comprehensive wetland characterisations the potential of the data has not been researched yet. The aim of our research was to study the use of the high-resolution and temporally dense Sentinel-1 and -2 data for wetland mapping in multiple levels of characterisation. The use of the data was assessed by applying Random Forests for multiple classification levels including general wetland delineation, wetland vegetation types and surface water dynamics. The results for the St. Lucia wetlands in South Africa showed that combining Sentinel-1 and -2 led to significantly higher classification accuracies than for using the systems separately. Accuracies were relatively poor for classifications in high-vegetated wetlands, as subcanopy flooding could not be detected with Sentinel-1’s C-band sensors operating in VV/VH mode. When excluding high-vegetated areas, overall accuracies were reached of 88.5% for general wetland delineation, 90.7% for mapping wetland vegetation types and 87.1% for mapping surface water dynamics. Sentinel-2 was particularly of value for general wetland delineation, while Sentinel-1 showed more value for mapping wetland vegetation types. Overlaid maps of all classification levels obtained overall accuracies of 69.1% and 76.4% for classifying ten and seven wetland classes respectively.     

Geological study of sedimentary basins using SPOT data

This paper illustrates the benefits of DTMs created from SPOT images for the exploration of sedimentary basins. We chose an example located in the Ebro sedimentary basin in Spain, characterized by good outcropping conditions and slight deformations. The data used consist of a pair of SPOT panchromatic images and a SPOT XS image. The work consists of making up a 3D database, followed by interpretation of stereo pairs computed from orthoimages and the DTM. This interpretation is made on a stereoscopic desk and results in a digital file containing in the form of vectors all the observed faults and lithology. These vectors are then used to make calculations on the geometry of the objects they represent: we demonstrate that we can accurately measure layer directions and dips, sediment thicknesses and fault throws. Synthesis of perspective views made at the same time provide a good understanding of the structures and help to test their geometric consistency. Thus knowledge about relief given by DTMs helps to interpret remote detection images in 3D space, and particularly to accurately quantify the results of this interpretation.     

Earthquake-induced built-up damage identification using IRS-P6 data: a comparative study using fuzzy-based classifiers

The 8 October 2005 earthquake caused widespread destruction in both the state of Jammu and Kashmir of India and Northern Pakistan. Due to poor accessibility in the hazardous and difficult mountainous terrain, a proper and comprehensive ground-based survey was not possible. However, with the help of remote sensing data and its analysis techniques, it is feasible to undertake both earthquake-related damage identification and assessment. This study attempts to document and identify built-up damaged (BD) areas using spectral indices taking temporal multispectral images from IRS-P6 LISS-IV. Five spectral indices have been used to identify BD areas using supervised possibilistic c-means (PCM) and noise cluster (NC) classifiers, to analyse the satellite data. The result indicates that Class Based Sensor Independent (CBSI) based Transformed Normalized Difference Vegetation Index (TNDVI) temporal indices provide the best results for identifying BD areas, while Simple Ratio (SR) index gives the best results for built-up undamaged area identification. Further, it observed that PCM classifier performed better in comparison to NC classifier.     

基于Skyline的三维空间数据网络发布

三维场景中三维地形模型和建筑模型等结构复杂,纹理丰富,使得三维数据被称为"海量"数据库,给三维场景在IE浏览器中的的快速加载与显示增加了难度。本文在分析评价现今网络三维可视化方面使用较广泛的软件和技术模式的基础上,介绍Skyline系列软件关于提高三维数据的传输效率的关键技术,并针对此问题进行设计实验,对软件的实用性的进行分析和评估。     

Geomorphic evolution of a part of Middle Ganga Plain,Bihar: A case study using remote sensing data

An insight into the geomorphic evolution of any area can be obtained by detailed landform mapping. In the present study, an area in the Middle Ganga Plain has been selected for the study using mainly remote sensing data. Various fluvial landforms have been mapped and the changes in planform of rivers over approximately 50 years have been evaluated. Both fluvial processes and tectonic activities are considered to have collectively influenced the migration of the rivers in this region. Digital enhancements of Landsat MSS and TM data are found to be quite useful in identification and mapping of subtle fluvial palaeofeatures. The present study demonstrates the utility of remote sensing in examining the geomorphic evolution of the area.     

GIS 优化 SRM 储流函数模型变量与参数方法研究

水文模型的结构确定后,模型参数的选择对水文模型整体性能和水文预报结果的好坏有着至关重要的影响。为使得模型的输出值能够尽可能地接近实际值,文中结合数字高程模型(DEM)和流域地质资料,使用GIS方法分别从优化数据源和加入地质因素影响分析优化模型参数两方面入手,对SRM储流函数模型进行优化,并以北海道沙流川流域为例对上述方法进行检验,结果说明了方法的可行性。     

基于TM/ETM和DEM数据的BRDF特征提取

巴丹吉林沙漠地区地物类型单一,地形起伏,形成了天然的二向反射数据集;因此,本研究利用巴丹吉林沙漠地区的ASTER GDEM产品提供的地面高程数据,计算出每个坡元所对应的太阳-观测几何信息(包括太阳天顶角与方位角和观测天顶角与方位角),假设沙丘上每个坡元的表面结构不随其坡度和坡向变化,加上Landsat-TM/ETM+对地观测的信息,就形成了对同一地物的多角度观测数据集,从而可以提取该地区的BRDF特征。为了检验该方法,利用该方法获取的BRDF特征信息模拟了25景Landsat-TM/ETM+数据,并与实际的Landsat-TM/ETM+图像进行对比分析。结果表明, Landsat-TM/ETM+前4个波段的模拟图像与真实图像地表平均反射率相比,平均误差分别为2.80%、1.92%、2.68%和2.32%,高于一般辐射定标中5%—7%的误差要求,因此本研究方法可为高分辨率数据的交叉辐射定标等应用提供参考。     

Analysis of sorghum yield dependence on crop growth characteristics using noaa-avhrr data

Growth profiles of 1987-88 rabi sorghum crop cultivated in spatially extensive sites in six tehsils of Solapur and Ahmadnagar districts in Maharashtra have been generated using multidate NOAA AVHRR data based on crop growth equation suggested by Badhwar (1980). The sensitive parameters for sorghum yield modelling have been identified. The correlation of final grain yield with growth parameters shows that yield relationship is stronger when logarithmic senescence rate and timeintegrated logarithmic senescence rate are considered as the parameters instead of its value on any day during 30 days senescence period after attaining maximum vegetative cover.     

Interplay between urban communities and human‐crowd mobility: A study using contributed geospatial data sources

An intense process of urbanization, witnessed particularly in the last decade, has stressed the need to comprehend human mobility behavior in urban settings. Although the emergence of contributed geospatial data (i.e., pervasive activity‐based data) has contributed to substantial progress toward understanding human activity, the relationship between human‐crowd mobility and the functional structure of a city is not yet well understood. In this context, the present research focuses on the intra‐urban origin–destination matrix modeling founded on a combination of two major crowdsourced datasets as well as the inclusion of urban communities’ structure. Specifically, the well‐known “radiation” and “PWO” models were modified through first, identifying the communities embedded in the cyberspace network then employing the identified hierarchical structure of the spatial‐interaction network for the formulation of the users’ movement network and second, imposing proper input variables including the telecommunication activity volume and check‐in frequency. The results obtained by various empirical analyses suggest that the modified community‐constrained origin–destination flow estimation models exhibit better performance levels than those of alternative conventional mobility models.