Assessing reference evapotranspiration at regional scale based on remote sensing,weather forecast and GIS tools

Reference evapotranspiration (ET_o) is a key component in efficient water management, especially in arid and semi-arid environments. However, accurate ET_o assessment at the regional scale is complicated by the limited number of weather stations and the strict requirements in terms of their location and surrounding physical conditions for the collection of valid weather data. In an attempt to overcome this limitation, new approaches based on the use of remote sensing techniques and weather forecast tools have been proposed.Use of the Land Surface Analysis Satellite Application Facility (LSA SAF) tool and Geographic Information Systems (GIS) have allowed the design and development of innovative approaches for ET_o assessment, which are especially useful for areas lacking available weather data from weather stations. Thus, by identifying the best-performing interpolation approaches (such as the Thin Plate Splines, TPS) and by developing new approaches (such as the use of data from the most similar weather station, TS, or spatially distributed correction factors, CITS), errors as low as 1.1% were achieved for ET_o assessment. Spatial and temporal analyses reveal that the generated errors were smaller during spring and summer as well as in homogenous topographic areas.The proposed approaches not only enabled accurate calculations of seasonal and daily ET_o values, but also contributed to the development of a useful methodology for evaluating the optimum number of weather stations to be integrated into a weather station network and the appropriateness of their locations. In addition to ET_o, other variables included in weather forecast datasets (such as temperature or rainfall) could be evaluated using the same innovative methodology proposed in this study.     

“一带一路”倡议下老挝沙湾区土地适宜性评价

为了对老挝沙湾区土地适宜性进行评价,本文选择了地形、土壤、水利、区位和生态5类13项指标,建立了老挝沙湾区土地适宜性评价指标体系;将层次分析法(AHP)与GIS技术相结合,对老挝沙湾区农业用地、林业用地和建设用地进行适宜性评价。研究结果表明:宜农用地占土地面积的30.16%,主要分布在海拔较低、坡度较小的沙湾拿吉大平原以及湄公河沿岸;宜林用地占土地总面积的60.07%,主要分布在东部和北部山区;宜建用地占土地总面积的4.62%,主要分布在平原地区,湄公河沿岸,以及交通较发达地区;不适宜用地占总面积的2.32%,主要分布在甘蒙省西北部以及东部。研究方法和研究结果可以为老挝沙湾拿吉省土地利用规划和相关研究提供科学依据与支持,同时为老挝今后的土地资源开发奠定基础。     

线性参照系在城市交通事故发布系统中的作用及应用

针对城市交通部门事故管理系统中存在道路数据不独立以及发布的事故信息易读性差导致应急部队无法准确定位事故地点进行救援的问题,基于公路的线性特征,结合GIS对地理数据的多样操作功能,提出路段名+特征参考点的一维定位表达方法。将线性参照系理论应用到以综合车道为公路模型的空间数据管理模式中,建立基于线性参照系的城市公路事故信息发布系统,实现二维坐标向一维坐标转换、降低数据冗余、实现事故地点的快速定位以及对定位的事故信息进行发布。     

基于ArcEngine的插件式GIS开发框架设计与应用研究

GIS应用领域越来越广,对传统的GIS开发模式提出了新的要求和挑战。插件开发模式具有易扩展、易重用的特点,可降低GIS开发成本,提高应用灵活性,弥补传统开发模式的不足。本文在分析插件技术和插件式GIS开发框架的基础上,采用ArcEngine组件和.NET反射技术设计实现了插件式GIS开发框架PLGGIS。最后以扩展插件的方式开发了多源遥感影像数据管理应用系统,验证了设计插件式GIS开发框架的可行性和应用灵活性。     

Fuzzy logic and multi-criteria methods for groundwater potentiality mapping at Al Fo’ah area,the United Arab Emirates (UAE): an integrated approach

This study has modified an approach based on fuzzy logic in a GIS and multi-criteria decision making (MCDM) for groundwater potentiality mapping in Al Fo’ah area, the United Arab Emirates. The proposed approach uses nine groundwater conditioning factors recognized by local hydrology experts. Each factor and class of each factor was given a weight and score based on its level of contributions to groundwater accumulation using analytical hierarchy process and MCDM. Our results revealed that the areas of very high harbouring groundwater are located at the foot of the Oman mountains and occupies an area of about 8.46 km² (4%) of the study area. We validated our results using the Relative Operating Characteristics. The area under the curve showed a ratio of 0.8957 (of 89.57%). The modified approach is timely and economically effective and can be applied in semi-arid regions to help hydrologists.     

Applications of generalized additive model (GAM) to satellite-derived variables and fishery data for prediction of fishery resources distributions in the Arabian Sea

This study aims to illustrate how remotely sensed oceanic variables and fishing operations data can be used to predict suitable habitat of fishery resources in Geographic Information System. We used sea surface height anomaly (SSHa), sea surface temperature (SST), chlorophyll concentration (CC), photosynthetically active radiation (PAR) and fishing depth as predictor variables. Fishery data of Indian squid (Loligo spp.) and catfish (Tachysurus spp.) for study period (1998–2004) were segregated randomly to create training and validation. Catch was normalized into Catch per unit Effort (kg h^?1). Generalized additive modelling was performed on training data and then tested on validation data. Suitable ranges of SST, CC, SSHa and PAR for different species distributions were derived and integrated to predict their spatial distributions. Results indicated good match between predicted and actual catch. Monthly probability maps of predicted habitat areas coincide with high catch of the particular month for the study period.     

Applying VGI to collaborative research in the humanities: the case of ARTL@S

ABSTRACT

Using Artl@s as an example of a project that relies on volunteered geographic information (VGI), this article examines the specific challenges that exist, beyond those frequently discussed in general VGI systems (e.g., participants’ motivation and data quality control) in regard to sharing research data in humanities: (1) most data from the humanities is qualitative and collected from multiple data sources which are often inconsistent and unmappable; (2) data is usually interconnected with multiple relationships among different tables which creates challenges for both mapping and query functionality; (3) data is both geographical and historical. Consequently addresses that no longer exist have to be geolocated and visualized on historical basemaps and spaces must be represented diachronically; (4) the design of web map application needs to balance both sophisticated research requirements and a user-friendly interface; (5) finally contributors expect their data to be cited or acknowledged when used in other studies and users need metadata and citation information in order to reuse and repurpose datasets.

In this article, we discuss how Artl@s, a project which developed a georeferenced historical database of exhibition catalogues, addresses these challenges. Artl@s provides a case study for VGI adoption by digital humanities scholars for research data sharing, as it offers features, such as flexible batch data contribution, interrelated spatial query, automatic geolocalization of historical addresses, and data citation mechanisms.     

Context inference and prediction modeling in ubiquitous health GIS

The ever‐increasing population in cities intensifies environmental pollution that increases the number of asthmatic patients. Other factors that may influence the prevalence of asthma are atmospheric parameters, physiographic elements and personal characteristics. These parameters can be incorporated into a model to monitor and predict the health conditions of asthmatic patients in various contexts. Such a model is the base for any asthma early warning system. This article introduces a novel ubiquitous health system to monitor asthmatic patients. Ubiquitous systems can be effective in monitoring asthmatic patients through the use of intelligent frameworks. They can provide powerful reasoning and prediction engines for analyzing various situations. Our proposed model encapsulates several tools for preprocessing, reasoning and prediction of asthma conditions. In the preprocessing phase, outliers in the atmospheric datasets were detected and missing sensor data were estimated using a Kalman filter, while in the reasoning phase, the required information was inferred from the raw data using some rule‐based inference techniques. The asthmatic conditions of patients were predicted accurately by a Graph‐Based Support Vector Machine in a Context Space (GBSVMCS) which functions anywhere, anytime and with any status. GBSVMCS is an improved version of the common Support Vector Machine algorithm with the addition of unlabeled data and graph‐based rules in a context space. Based on the stored value for a patient's condition and his/her location/time, asthmatic patients can be monitored and appropriate alerts will be given. Our proposed model was assessed in Region 3 of Tehran, Iran for monitoring three different types of asthma: allergic, occupational and seasonal asthma. The input data to our system included air pollution data, the patients’ personal information, patients’ locations, weather data and geographical information for 270 different situations. Our results showed that 90% of the system's predictions were correct. The proposed model also improved the estimation accuracy by 15% in comparison to conventional methods.     

Modeling the environmental susceptibility of landfill sites in California

??The proper management of solid waste (SW) is a global environmental challenge. A major issue is the proper disposal of SW while balancing a wide range of criteria and working with different spatial data. In this study, we used geographic information system as a tool to perform multi-criteria decision analysis with an analytical hierarchy process to develop an environmental impact susceptibility model (EISM) for landfills. The model was applied to the state of California, USA and results are presented herein. In particular, the EISM considers factors such as geology, pedology, geomorphology, water resources, and climate as represented by 13 associated environmental indicators. The results of the EISM indicate that more than 75% of California’s territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 25% of the state’s land, 61 landfills are located in the high and very high categories. These results are alarming because during the period from 2000 to 2015, these 61 landfills received approximately 308 million tons of SW, which corresponds to more than 57% of all SW disposed in California. The model results can be used toward mitigating the environmental impacts of these facilities.