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.     

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.     

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.     

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).     

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.     

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.     

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.     

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。     

Glacial mapping using landsat thematic mapper data: A case study in parts of gangotri glacier, NW himalaya

Glacial mapping is difficult and hazardous because of the remoteness and inaccessibility of the terrain. In this context, remotely-sensed data from satellites provide valuable information on glaciers and the associated landforms. It is important to note that judicious selection of spectral bands is critical in mapping the glacial features. Glacial landforms in parts of Gangotri glacier, NW Himalaya, have been delineated using selected bands of Landsat Thematic Mapper Data. Digital image processing of Landsat data has helped in identifying the major features of the Gangotri glacier such as accumulation and ablation zones, and glacial moraines. The study shows that Thematic Mapper bands 4, 5 and 7 are more useful in snow mapping because of their distinct spectral discriminability in identifying the glacial features.     

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.     

Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.     

Diurnal and seasonal impacts of urbanization on the urban thermal environment: A case study of Beijing using MODIS data

Beijing has experienced rapid urbanization and associated urban heat island effects and air pollution. In this study, a contribution index was proposed to explore the effect of urbanization on land surface temperature (LST) using Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived data with high temporal resolution. The analysis indicated that different zones and landscapes make diurnally and seasonally different contributions to the regional thermal environment. The differences in contributions by the three main functional zones resulted from differences in their landscape compositions. The roles of landscapes in this process varied diurnally and seasonally. Urban land was the most important contributor to increases in regional LSTs. The contributions of cropland and forest varied distinctly between daytime and nighttime owing to differences in their thermal inertias. Vegetation had a notable cooling effect as the normalized vegetation difference index (NDVI) increased during summer. However, when the NDVI reached a certain value, the nighttime LST shifted markedly in other seasons. The results suggest that urban design based on vegetation partitions would be effective for regulating the thermal environment.     

无气象要素的GPS对流层延迟推算可降水量的研究

本文针对武汉地区GPS气象网资料,进行了GPS对流层延迟直接推算可降水量的研究。在武汉东湖站GPS对流层延迟与无线电探空可降水量的比较中,两者具有很好的相关性,相关系数达到了0.93;推导了对流层延迟直接推算可降水量的模型,对模型结果进行了检验,在武汉东湖站的对流层延迟转换的可降水量与无线电探空可降水量的比较中,均方根为7.8mm,相关性为0.91,这说明了在没有气象数据的地区对流层延迟直接推算的可降水量可以作为气象短期预报的参考。     

Moraine-Dammed Lakes study in the chenab and The Satluj River Basins using IRS data

Moraine-dammed lakes are normally formed near glacier terminus. These lakes can burst due to excessive melting and can cause floods in the valleys. Many such floods have been reported in the Himalayas and other parts of the World. In this paper, an inventory of these lakes in the Satluj and the Chenab basins has been reported. During the investigation, 22 lakes in the Satluj and 31 lakes in the Chenab basin were mapped. In the Chenab basin, two lakes are of very large size, their areal extent is 105 and 55 ha, located in toposheet number 52 HI 1 and 52H02, respectively. These lakes were selected for detail monitoring. The lake near the Geepang glacier, is located in toposheet number 52H 02 and its area was 27 ha in 1976. Using the satellite data, areal extent of the lake was monitored. The lake area was almost doubled to 55 ha in 2001. This suggested that, lake size is constantly increasing and it can cause outburst flood. The maximum possible depth of lake was estimated by taking the average difference of maximum and minimum height of moraine dam from the Survey of India toposheet. By considering the average depth, the volume of the lake water and the instantaneous discharge of 350 mVsec were estimated. This is large discharge for a small stream like the Geepang Gath and it can damage many civilian and defense establishments. Therefore, further detail field investigations of this lake are needed to assess threat potential and to develop strategy to avoid this flash flood.     

关于总体最小二乘方法适应性实验研究

总体最小二乘是近年来发展起来的较最小二乘方法更为严密的平差方法,总体最小二乘能够顾及系数矩阵和观测值矩阵同时存在偶然误差并加以改正。然而对于总体最小二乘方法的适用性以及在根据实际数据建立模型时总体最小二乘方法改正系数矩阵和观测值矩阵误差的能力问题还没有深入研究,针对一元线性回归模型,讨论总体最小二乘方法的灵敏性,利用仿真实验数据验证总体最小二乘方法在线性回归模型中的改正能力和优越性。     

利用GRACE卫星Level-1B数据反演陆地水储量变化的方法研究

卫星重力探测技术为监测陆地水储量变化提供了新的技术手段。对利用GRACE卫星Level-1B数据反演地球陆地水储量变化的重力位差法和Mascon方法的数学模型作了详细推导分析,总结两种方法的特点和解算处理步骤。推导过程表明:重力位差法和Mascon方法在反演时只采用卫星飞临研究区域上空时的观测数据,能够提高反演结果的空间分辨率,比传统的球谐系数法更具优势;Mascon方法在解算时还引入了时空约束方程,进一步提高了反演结果的时空分辨率。     

GIS-based geomorphological mapping using remote sensing data and supplementary geoinformation: A case study of the Dhaka city area,Bangladesh

This study aims to prepare a detailed GIS-based geomorphological map accompanied with landfill sites of Dhaka city area which can be used for multipurpose functionality. Attainment of the geomorphological map is based upon interpretation of the oldest available aerial photographs (1:40,000) and contemporary topographic maps (1:8000) which reflect almost pre-urban ground of Dhaka. Randomly distributed 160 boreholes have been used to prepare representative soil profiles (RSP) to identify the near-surface lithology of the geomorphological units. The study reveals that 13 out of 18 low-lying geomorphic units, comprising 65% of the total area demand landfill practices for urban development. Landfill sites have been merged with urban growth on each low-lying geomorphic unit using a spatially enhanced fused image of IRS-1D PAN and ETM+ bands 5, 4 and 3, acquired February 2000 and 2002, respectively. We found that 43% area of the total low-lying geomorphic units experience fill practices so far. The fill sites have been differentiated into four classes based on their relative thickness. Integration of fill classes with geomorphological map shows the urban dynamics of Dhaka city area till 2002. Due to GIS integration, this map can be rapidly updated to demonstrate temporal modifications in urban ground. It can be used effectively in different geomorphological hazard mapping and urban land-use practices.