Francisco J. Artigas

An experimental study on content-based image classification for satellite image databases

Current art uses metadata associated with satellite images to facilitate their retrieval from image repositories. Typical metadata are geographic location, time, and data type. Because the metadata do not indicate which regions within an image are obscured by clouds, retrieval with such metadata may produce an image within which the region of interest (ROI) for the user is not visible. We report a system that can automatically determine whether an ROI is visible in the image, and can incorporate this into the metadata for individual images to enhance searching capability. The goal is to annotate each image with metadata regarding a number of ROIs. An experiment with the system annotated 236 advanced very high resolution radiometer (AVHRR) images of the North Atlantic from a five-month viewing period with descriptors that expressed the visibility of an ROI centered on Long Island, NY. For ground truth, we used the classifications of three human subjects to determine visibility of the same region of interest, and labeled the ROI with the majority decision of the three subjects. Partial cloud cover made the human determination subjective, and resulted in disagreements among the subjects. Using randomly selected training subsets of the images, we found the two images whose regions were most like those in images for which the Long Island region was visible.

Customized geospatial workflows for e-government services

The past decade has experienced a phenomenal growth in the electronic delivery of business services. This has led to an elevation in the expectations of citizens for fast and efficient delivery of governmental services. Recently, workflow systems have gained importance as an effective= infrastructure for automating the business processes within and across government agencies. Government services, such as permit processing for the development or preservation of land, can be modeled as workflow. They must consider geographic locations and the geodata that include location-specific data, documents and information. We call such workflows dependent upon locations and their geodata Geospatial workflows. We argue that geospatial workflows vary widely from one case to another, and therefore cannot be represented as a generic workflow. We demonstrate, with concrete examples, that there is a compelling need for customized geospatial workflows and propose a system that is capable of generating such customized workflows by capturing the user requirements and extracting the relevant governmental regulations. Our system also provides users with decision support functionalities comprising of various GIS layers, by which users can evaluate and identify a suitable workflow among various possible scenarios. Geospatial workflows can be used by government agencies to automate the delivery of their services. We present the features of a preliminary prototype.

Visual analytics for open government data

The Open Government Data initiative accelerated publishing and sharing of diverse government data with enterprises, software developers and citizens. The key challenge with this unprecedented amount of government data is to make sense of them in a timely manner i.e. find the meaning of the data to assist in decision making. The analytical tools and apps to filter, sort, aggregate for summary along different spatio-temporal dimensions will help find trends and outliers. The capabilities to combine diverse data from different sources may also help users to understand the information and knowledge embedded in data sets. One of most powerful data exploration and analytics is data visualization. In this tutorial, we present two different tools for visual exploration and analytics for citizens and researchers, making use of diverse data sets from different sources, such as government, social media and enterprise or personal collections. Specifically, we focus on Geographic Information Systems (GIS) for mapping data using ArcGIS Explorer, a cloud based data integration and visualization tool and Google Fusion Tables for tabular data. The tutorial is geared toward social science researchers, students and citizens in general.

Geographic information sharing: A regional approach in northern New Jersey, USA

The New Jersey Meadowlands Commission (NJMC) is a regional planning agency in northern New Jersey with jurisdiction over 14 municipalities. This case study describes a five year effort by this agency to serve geographic knowledge to 14 towns in the region by sharing resources and infrastructure through a centralized Geographical Information System (GIS). Serving this information required funding, convincing towns to participate, specialized staff, software licenses and equipment and follow-up with training and updates. The information being served consists of interactive maps available through a Web browser conveying the spatial arrangement of municipal infrastructure, administrative boundaries and fundamental demographics of each town in maps and tables that show proximity, elevations and distances that would otherwise be impractical to describe using words alone. Systems such as these support local governments by delivering information and services to the community in the form of variance notifications, zoning and land use inventories and updates and emergency management information including Right to Know (RTK) records that inform first responders about hazardous materials stored in industrial facilities. The study details how towns were brought in to share resources and participate in a multi-user GIS, how data was organized around the needs of users, the different implementation phases, roll out of the applications, training, maintenance and finally, how the system was adopted and is currently used.

Data warehousing in environmental digital libraries

The purpose of this article is to present what we view as a new application of data warehousing in non-traditional domains such as environmental monitoring and research, biomedical applications, and other types of digital libraries (DL). While the work we present here focuses on an environmental data warehouse, the ideas are equally applicable to other DL environments. Data warehousing has been embraced by the professional IT community with many successful implementations reported in the retail, insurance, finance, and other industries [7]. For the most part, traditional data warehouses share the following common features. First, virtually all the data propagated from the operational systems and data sources to the data warehouse is either numeric or character-based. The data warehouse database contains mostly aggregated and summarized data in numeric format. Next, operational systems and data sources are identified early on in the warehouse development cycle. Once the warehouse is operational, new data sources are often difficult to integrate into the data warehouse schema. Quite often the warehouse database is designed around a core set of business needs that are decided upon in advance. The set of queries that can be addressed by the warehouse might therefore be fixed. By contrast, data warehouses to support DLs must contend with a variety of multimedia data types from a collection of component systems that may grow over time.

Tide gate sensor network as a forensic tool: establishing facts during superstorm sandy

This study presents a Sensor Network based Tide Gate Monitoring System (SensorTGMS) that automatically collects the real-time water levels at tide gates in the New Jersey Meadowlands District where ninety percent of which lies within two feet of the high water mark. We report our experience of developing the SensorTGMS, and how the real-time water level data from the sensor-enabled tide gates provide water level alerts for government officials and citizens for planning evacuations and allocating resources by identifying risk areas in timely manner. The data, augmented with the social media data shared by citizens on their flood incident episodes can provide real-time situation awareness and promote community-based incident management during and after a disaster. Additionally, the SensorTGMS data supports the objective unbiased account of the progression of flood events. The animated visualization of the water levels over a time line can be a powerful tool for understanding where and how residents and infrastructure were affected by a high energy rain event and/or a tidal surge. This objective data captured by the system can be used as a forensic tool for understanding the weak points of coastal defenses and to assess the magnitude of the flood damages.

Spatial analytics for open government data

Information from the Census is tied to a State, County or Township boundaries and is dated to when the information was collected. Similarly, water quality, electricity consumption, and sociolinguistic accents are tied to geography and dated to when they were measured. Any attribute that is spatially explicit can be explored using Geographical Information Systems (GIS). GIS is a tool to find relationships and visualize trends and patterns between datasets that share the same geography. Researchers may be familiar with GISs visually appealing results and its analytical powers and may even have ideas on how to apply this tool to their own research questions but have never had the chance to actually use this tool to generate tangible results on their own. These compressed hands on tutorial exercises on spatial analytics for open government data are designed to expose participants to levels of complexity that build on each other and explore an increasing range of functionalities offered by modern GIS. As a result, participants walk away having experienced the entire cycle of spatial analysis from identifying and importing data, performing overlays for spatial analysis and preparing map layouts and presentations to communicate the findings. Through this tutorial, participants should gain a basic understanding and practice of GIS to utilize this tool and address research problems in their own fields of expertise.

Constituent-centric municipal government coalition portal

Businesses have used Customer Relationship Management (CRM) to gain strategic advantages by understanding and satisfying customer needs and creating short and long-term values. Similarly, governments face increased demands from citizens for better citizen-oriented one-stop services and more efficient and responsive government. Municipal governments started to introduce CRM to address these demands [2]. The key functionalities of CRM include (1) Citizen Segmentation into groups, such as individual taxpayers, corporate taxpayers, at-risk non-compliers; (2) Assess and monitor activities of certain segments of the population; (3) Provide tools, such as surveys, to uncover special needs and to measure service satisfaction levels; (4) Develop targeted offerings and outreach campaigns to meet specific population segment requirements, including education and notification of changes in tax laws.