Complex adaptive blended learning for higher GIS education: A theory-driven pedagogy moving forward after the pandemic

None of the prior studies implementing blended learning (BL) for GIS education has explored pedagogical theories to support BL design, and none coupled blended GIS learning practice with theories. Based on the theoretical framework of complex adaptive blended learning system (CABLS), this article presents a holistic and systematic view of BL for higher GIS education (termed as CABLS-GIS), where its key components are tightly integrated as an integral whole. The framework was implemented for an introductory-level GIS course to empirically evaluate the effectiveness of a BL design from students' perspectives. Most students involved in the implementation agreed that the BL enhanced their learning outcomes. They were mostly positive about the BL and motivated to use the BL materials. Incorporating more BL materials, especially practical ones, and active learning activities were suggested by them. A few negative comments about the BL suggested a thorough consideration of individual learners' characteristics.     

Weak GPS signal tracking using FFT discriminator in open loop receiver

An open loop tracking architecture, which tracks GPS signals under weak and challenging conditions, is analyzed. The in-phase and quadrature-phase integration pair is regarded as a single tone complex signal. An FFT-based method is used as a frequency discriminator to estimate the Doppler frequency residual of the single tone signal. Another FFT-based method applies complex squaring to eliminate the effect of the navigation data bits polarities. The performance of the FFT-based discriminators is assessed in three criteria. Those criteria are the signal strength and dynamic range that can be tracked and the accuracy of the estimated Doppler frequency. In addition, the performance of the discriminators is analyzed to provide the theoretical and simulated peak detection probability. The results indicate that the FFT discriminator can track signals about 5 dB weaker than the signals that can be tracked by the complex squared FFT discriminator. In a quasi-static environment, the Doppler frequency residual can be assumed to be around zero, which can enable the FFT-based discriminators to track signals with approximately 2 dB less power. Moreover, the performance of the FFT-based discriminators is compared with the performance of two other frequency discriminators, namely the fast–slow and power-based. The comparison results indicate that these two frequency discriminators give higher frequency estimation accuracy, but they have a narrower dynamic range.     

Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.     

Validation of MODIS Vegetation Continuous Fields for monitoring deforestation and forest degradation: two cases in Mexico

This study assesses whether MODIS Vegetation Continuous Fields percent tree cover (PTC) data can detect deforestation and forest degradation. To assess the usefulness of PTC for detecting deforestation, we used a data set consisting of eight forest and seven non-forest categories. To evaluate forest degradation, we used data from two temperate forest types in three conservation states: primary (dense), secondary (moderately degraded) and open (heavily degraded) forest. Our results show that PTC can differentiate temperate forest from non-forest categories (p = 0.05) and thus suggests PTC can adequately detect deforestation in temperate forests. In contrast, single-date PTC data does not appear to be adequate to detect forest degradation in temperate forests. As for tropical forest, PTC can partially discriminate between forest and non-forest categories.     

A support vector machine classifier based on a new kernel function model for hyperspectral data

The kernel function is a key factor to determine the performance of a support vector machine (SVM) classifier. Choosing and constructing appropriate kernel function models has been a hot topic in SVM studies. But so far, its implementation can only rely on the experience and the specific sample characteristics without a unified pattern. Thus, this article explored the related theories and research findings of kernel functions, analyzed the classification characteristics of EO-1 Hyperion hyperspectral imagery, and combined a polynomial kernel function with a radial basis kernel function to form a new kernel function model (PRBF). Then, a hyperspectral remote sensing imagery classifier was constructed based on the PRBF model, and a genetic algorithm (GA) was used to optimize the SVM parameters. On the basis of theoretical analysis, this article completed object classification experiments on the Hyperion hyperspectral imagery of experimental areas and verified the high classification accuracy of the model. The experimental results show that the effect of hyperspectral image classification based on this PRBF model is apparently better than the model established by a single global or local kernel function and thus can greatly improve the accuracy of object identification and classification. The highest overall classification accuracy and kappa coefficient reached 93.246% and 0.907, respectively, in all experiments.     

一种改进的GOCE卫星几何法轨道速度确定方法

对目前常用内插方法确定GOCE卫星速度的精度进行深入分析与比较,结果表明:常规方法在GOCE几何法轨道速度确定中精度欠佳。在分析切比雪夫多项式拟合方法基本原理及算法的基础上,提出含有多余观测量的切比雪夫多项式拟合方法,该方法在获取几何法轨道速度时,通过选取合适的内插节点数,内插精度较常规方法有了很大提高,三维精度可达到0.3 mm/s。新方法能为基于GOCE卫星几何法轨道的重力场恢复提供强有力的支撑。     

Android平台下地形图编号查询转换系统的设计实现

首先对国家基本比例尺地形图编号的查询与转换的方法进行了研究与探讨,然后利用JAVA语言编程实现了根据经纬度查询不同比例尺地形图的新、旧编号、根据地形图新、旧编号查询地形图图幅范围、地形图新、旧图幅编号的相互转换等功能,最后利用Eclipse软件生成*.apk文件,将其安装在Android手机中,生成地形图编号查询与转换系统,为相关工作提供了便利条件,大大提高了工作效率。     

低空航测的系统工程问题分析

当前低空航测工程实践中的许多技术问题,仅靠个别研究是不够的,必须运用系统工程学的方法进行研究。低空航测系统由飞行平台、成像传感器和航测处理等技术部分构成,各部分间存在相互关联、相互制约的关系,必须进行系统分析和系统优化的研究。同时,系统还受外部环境的制约,必须研究如何在不可改变的外部制约条件下,优化系统,达到系统目标的方法。     

基于GPS无验潮水深测量在自然河段冲淤变化的精度探讨

无验潮模式已经在相关领域得到成熟的运用,但是在内河用于水文泥沙冲淤分析尚属空白。本文简要介绍了GPS无验潮测量的基本原理及作业方法,结合2014年长江三峡工程库区重庆市主城区河段河道演变观测项目,以九龙坡典型河段为例,对该河段进行了验潮与无验潮模式测量,并对两种方法得出的结果进行了计算与分析。测试结果表明,基于GPS无验潮测量模式进行水文泥沙项目观测,对水文泥沙分析精度有一定的影响,对勘测项目的经济效益上有一定的提高。     

土地利用现状和规划数据建库容差浅析

通过对第二次全国土地调查(以下简称"二调")和土地利用总体规划数据建库过程中误差的产生和传播分析,通过误差理论和容差设置实际研究。提出现行数据建库容许误差(以下简称容差)设置不合理,设置过高引起大量无用的数据处理工作。建议合理设置容差参数,提高数据库建设和更新效率。