Radiant Software, Inc.

April 27, 2010

Re: Personal Statement to Support My Immigration Petition

Applicant:       Dr. Xingtang Hu

Employer:        Radiant Software, Inc.

Field of Expertise:      Geospatial data analyze and visualization, Geographic information system (GIS); Hyperspectral remote sensing data mining; Remote sensing image processing and its applications; Environmental data inverse modeling; Bio-optical modeling for water quality parameters retrieving; Development of innovative, state-of-the-art solutions for the appraisal, assessment, tax collection and GIS industries.

Dear Sir/Madam:

This is a detailed statement of my significant pioneering research findings and the international impact of my achievements in the field of spatial data mining, management, analyzing and mapping and geospatial system integration, emphasized on GIS and Remote sensing system integration, modeling and spatial data analysis, which are supported by documentary evidence listed as references.  I will explain in plain language that: 1) I have made original research contributions of major significance to the development of Geographic Information System, Remote sensing technologies and its applications focusing on spatial data management, analyzing and mapping. I was the principal investigator of Hyper-spectral Remote Sensing Image Processing and Analysis System (HIPAS V1.0) and Remote-sensing Environmental Monitoring System (REMS V1.0). My research also received the Outstanding Remote Sensing Processing Software Platform Award presented by the Ministry of Science and Technology of China in 2003. Additionally I designed and implemented the land, rocks and minerals hyperspectral database information system in order to provide expertise support for land resource management;  2) I was granted government funding from the National Science Foundation (National 863 High Technique Plan) in China as a Co-Principal Investigator and gained patent approval; 3) I gained national/international recognition by my peers for my innovative discoveries and contributions in the form of peer review invitations, publications, and presentations in international venues; 4) I was honored as a member of a notable scientific professional society; and 5) I play a critical role in the ongoing GIS-intrinsic user-friendly computer assisted mass appraisal (CAMA), assessment administration (AA), tangible personal property (TPP), and tax collection (TAX) software platform research projects at Radiant Software, Inc., and my current work and future research serve very important national interests of the United States.

1. I have made innovative original research findings that are of major significance in the area of Geo-informatics sciences, including Geospatial data mining, Design and Development of Geospatial Software and Geographic Information System Integration.

From 2006 to 2008, I was a crucial and contributive research group member in the Earth Sciences Department at Indiana University Purdue University Indianapolis. I have been a Postdoctoral fellow in the projects supported by the National Science Foundation (Project ID: 2003AA131060) and made important original research discoveries on the development of REMS, HIPAS and Sakai platform. I was retained and hired by Indiana University at Indianapolis, India, right after I graduated from the Graduate University of the Chinese Academy of Sciences with a Ph.D. degree in GIS. I am now a key geo-informatics engineer in the GIS oriented research projects of Radiant Software, Inc. I present my major research accomplishments in three areas and describe them in details below.

Area 1: Geospatial data mining

(1) I am the first scientist who successfully applied an independent component analysis (ICA) techniques to identify different kinds of objects, i.e., mineral, soil, vegetation and water substances.

Previous knowledge: The traditional methodology of spectral unmixing was viewed as a specific case of the blind source separation problem where data consist of mixed signals (i.e., minerals) and the goal is to determine the contribution of each material to the mix without prior knowledge of the materials in the mix. The independent component analysis ICA mixture model however, views the observed data as a mixture of several mutually exclusive classes. Each of these classes is described by a linear combination of independent sources with non-Gaussian densities. The algorithm finds independent components (e.g., minerals, water constituents and vegetation types) and the mixing matrix for each class using an extend infomax learning algorithm and also computes the class membership probability for each pixel. Existing ICA mixture models cannot achieve both accuracy and optimal computational cost. In a word, no efficient and accurate analysis tool available for researchers to spectral unmixing.

My Contribution and Significance:  I innovatively applied the application of fast fixed-point independent component analysis algorithm (also named FastICA) to imaging spectroscopy.  Based on my research, I took imaging spectroscopy as a tool to spectrally identify and spatially map materials based on their specific chemical bonds. FastICA can be used to remotely sense hyperspectral image classification, mineral identification, land cover & land use mapping and water quality concentration estimation. The major advantage of using ICA is its ability to classify objects with unknown spectral signatures in an unknown image scene.

In my research, I focused on the ability of ICA to identify on different kinds of objects, i.e., mineral, soil, vegetation and water substances.  My novel theory accounted for using Minimum Noise Fraction (MNF) to eliminate hyperspectral image noise enhanced the FastICA performance. My research results demonstrate that the FastICA significantly outperforms the traditional ISODATA algorithm for land cover classification, and has perfect possibilities for mineral identification and water concentration mapping. Hence, the MNF transform based FastICA offered better adaptability on low signal/noise ratio hyperspectral image (i.e. the noise of the instrument in airborne sensor image).  In addition, my innovation of MNF based ICA model presented the potential ability to be applied to several fields such as Land Cover Classification, Mineral Endermember Extraction, and water parameters inversion.

I applied the independent component analysis (ICA) algorithm to retrieve the physical and chemical water parameters in an Indiana reservoir under the support of the in-situ spectra measurements of the central Indiana reservoirs including upwelling radiance, down welling irradiance above water surface, water physical and chemical parameters.  For the first time, I generated the central Indiana reservoir drink water quality parameters distribution map. These parameters include chlorophyll-a, phycocyanin, color dissolved organic matter (CDOM) and total suspended matter (TSM).

Additionally, I made significant breakthroughs in the development of geospatial data mining algorithms in image processing with independent component analysis (ICA), support vector machine (SVM), wavelet, partial least squares (PLS), and neural networks (NN).  These algorithms could be used widely in areas of Bio-optical parameters extraction, Linear Systems prediction, Regression, and classification.

(2) I am the first scientist who successfully applied fractal-based image compression algorithm supported by wavelet transformation (AWFC) to hyper-spectral image compression.

Previous knowledge:  With more and more satellites launched into space, we are able to capture huge remote sensing image data.  For example, the hyper-spectral sensors can capture hundreds and thousands bands of image data.  However, how to store, analyze and process these increasingly huge data has become a major problem.  As hyperspectral remote sensing technology enable us to obtain multiple spectral bands, how to store and transmit such huge data measured by T bits presents a serious difficulty with regards to the limited electrical communication bandwidth. It is important to compress huge hyperspectral image data acquired by hyperspectral sensors such as MODIS, PHI, and OMIS.  Conventional lossless compression algorithms are unable to reach satisfied compression ratio, while other loss compression methods which are able to obtain high compression ratio transmit poor image fidelity, especially to hyperspectral image data.

My Contribution and Significance:  I innovatively applied a new composition algorithm to solve the abovementioned problem.  As a third generation image compression algorithm, fractal image compression is superior to other traditional compression methods with advantages such as high compression ratio, good image fidelity, and less time complexity.  In order to keep the spectral dimension invariability, we tested two compression algorithms based on the storage file structure of BSQ and BIP separately. For the first time, I improved the HV and quadtree partitioning and the domain-range matching algorithms to accelerate the encode/decode efficiency. Furthermore, I presented a fast fractal image coding based on wavelet decomposition, and the sub-image blocks are improved by Pyramidal Haar transform. Simulation shows that the coding time is saved more than 100 times when the same coding result is kept. I improved the HV and Quadtree partitioning and the domain-range matching algorithms to accelerate encode and decode efficiency.  In addition, as an important part of our Hyperspctral Image Process and Analysis System (HIPAS), I implemented the AWFC algorithm using the VC++6.0 integrated development environment (IDE) and obtained perfect compression ratio. This algorithm is superior to other traditional compression methods with high compression ratio, good image fidelity, and less time complexity.

The above-mentioned achievements strongly support the fact that my research on the modeling and analysis of geospatial data mining and GIS based systems are world-leading and very important for future applications in this field. I discovered and developed advanced modeling techniques to expedite the analysis of spatial data. The development of Land Management and GIS-intrinsic Computer Assisted Mass Appraisal (CAMA) products is beneficial to the national interests of the United States due to its major significance to first responders (fire, police, and emergency medical services), emergency management in advanced preparation, as well as subsequent response to potential disasters, including natural disasters.

Area 2: Geographic Information System Integration

(3) I designed and developed the Hyperspectral Remote Sensing Image Processing and Analysis System (HIPAS) and implemented a novel model for hyperspectral data classification.

Previous Knowledge: Modern hyperspectral sensors extend our ability to capture data with higher spectral resolution. Spatial data collected by hyperspectral sensors contain information that objectively allows researchers to specify extremely complex interpretation tasks, which cannot be easily solved using traditional techniques. However, the impressive achievements in both developing survey methods and creating next generation sensors have not been accompanied by an adequate breakthrough in data analyzing and processing. Hyperspectral image processing and analysis system has become a primary tool for researching those data over the past twenty years. Traditional data processing architecture is not sufficient for large-size data processing and visualization, especially when we have abilities in capturing both high spectral resolution and pixel resolution spatial data. Furthermore, traditional continuum-removed method in the hyperspectral remote sensing is used only to analyze spectrum and extract the feature bands for classification with the spectrum of a single pixel. Based on the continuum-removed algorithm, I innovatively applied this method and used the functions of the continuum removed to the whole hyperspectral image space. This model has been applied in data normalizing and feature space extracting for multidimensional classification.

My Contributions and Significance: In the Chinese High-Technology Developing Plan “Hyperspectral Remote Sensing Image Processing and Analysis System (HIPAS)” (Project ID: 2003AA131060), I was the lead architect and designed a huge, novel storage architecture. I designed a huge pyramid image storage system and implemented a system core module in order to process huge image data (great than10TB) in computers with limited memory (less than 2G). The pyramid data partition algorithm was adopted to process huge remote sensing images. In this manner, it was able to process a huge image by cutting up the full size image to image slices and processing the indexed image slices one by one.  This creative methodology sped up data processing efficiently.  I creatively resolved the question that has plagued this area of high technology for years:  How can a limited PC memory process huge satellite and airborne remote sensing image data? This architecture greatly improves the hyper-spectral data analyzing process.

I led a group of more than 20 scientists and programmers in creating, testing, and deploying the Hyperspectral Image Processing and Analysis System (HIPAS). HIPAS was created for researchers for hyperspectral data analyzing, data visualization and thematic mapping. We designed and developed HIPAS in order to realize and implementation of algorithms for hyperspectral imagery calibration and classification, target detection and identification, multi-temporal and multi-source data analysis and interpretation.

In addition, the traditionally continuum-removed method is used only with the spectrum of a single pixel to analyze spectrum and extract the useful feature bands for classification in hyperspectral remote sensing. I creatively applied this method to the whole hyperspectral image space. It reached better MLC and SAM in classification compared to traditional classification methods.

Under my effective work, my first author paper “A New Architecture for Hyperspectral Image Processing and Analysis System: Design and Implementation” was accepted by the IEEE Conference of Multispectral Image Processing and Pattern Recognition in October 2003.   Another first author paper “Hyperspectral Image Processing and Analysis System：Integration and Applications” was published by the Journal of Remote Sensing (Vol.9.2005).   Furthermore, HIPAS was honored with the Outstanding Remote Sensing Processing Software Award by the Ministry of Science and Technology of China in 2003.

(4) I innovatively adopted the spring inversion of control (Spring IoC) technology to take control of whole system components, resulting in a scalable and maintainable Service Oriented Architecture for the Collaboration and Learning Environment platform.  

Previous background: Traditional homegrown courseware systems are built based on either J2EE/EJB or ASP/COM architecture. Both architectures are hard for test, extensible and maintains. I participated in the Sakai project as a key architect to design and build a new courseware system based on the modern Service Oriented Architecture (SOA). The Sakai Project began when Stanford University, University of Michigan, Indiana University,  Massachusetts Institute of Technology (MIT), and the University of California, Berkeley  began building a common Courseware Management System rather than continuing their homegrown systems or licensing software from a commercial vendor. This platform was designed to be the most adaptable, interoperable, reliable, and scalable platform for learning and collaboration. The new SOA based courseware should tackle the problem of too much cost and redundancy in traditional enterprise IT systems. Today, the Sakai Collaboration and Learning Environment (CLE) is the enterprise system of choice at over 100 institutions, in production settings ranging from 200 to 200,000 users. The Sakai CLE is open source software that is freely available to everyone and it will continually benefit higher education both in the United States and worldwide. 

My Contribution and Significance:  As the Oncourse specialist and system architect, I participated in the SAKAI open source project and innovatively adopted the spring inversion of control (Spring IoC) technology to take control of the whole java bean component. This makes our platform maintainable. By minimizing the dependency of application code on the lightweight spring IoC container, we can improve productivity, maximize the opportunity for code reuse, and improve testability. Our IoC based container (named Component Manager) is non-invasive and was implemented via configuration through inversion of control (known as the dependency injection pattern). The IoC container takes care of plumbing and leaving application to concentrate on business logic. The lightweight inversion of the control container (Component Manager) has huge benefits for implementing J2EE applications. Comparable to traditional J2EE/EJB architecture, this container, along with Aspect Oriented Programming (AOP), provides the basis for the next generation J2EE architecture of Service Oriented Architecture (SOA).  SOA also solved the problem of burdensome expense and redundancy in traditional enterprise information technologies systems.

I also implemented the forum and message tools for the Oncourse course management and collaboration system. In addition, I resolved several system block bugs such as the anonymous user support problem in system authentication and authorization services.  Based on the excellent job I did while working with the Sakai and Oncourse systems, I have been invited to present unique technical methods at an hour-long session at the First Sakai Chinese workshop.  My reports on “Design and Implementation of Sakai: a Component based and Services Oriented Architecture (SOA) (Xingtang Hu (Hu2@iupui.edu), Lance Speelmon (lance@indiana.edu), Michael Korcuska (mkorcuska@gmail.com))” gained high recognition and contributed to the successful approval of applications on SOA-based architecture. Today, we believe Sakai to be the most adaptable, interoperable, reliable, and scalable platform for learning and collaboration both in the United States and worldwide.

Area 3: Design and Development of Geospatial Software and its applications to Land resource management

 (5) I developed a novel bio-optical analytical model to extract water resource parameters and integrate it with Remote-sensing Environmental Monitoring System REMS.

Previous background:  How to protect environmental resource and reduce disasters effectively are key issues for regional sustainable development. It is difficult to provide information about global environmental change without modern and advanced spatial information technologies such as Remote Sensing (RS), Geographic Information System (GIS), Global Positioning System (GPS) and their integration technologies. These technologies should be integrated to provide useful perspectives while traditional systems are built solely for academic and specific users. In order to meet the requirements of regional water quality monitoring, we should integrate modern technologies (remote sensing and geographic information system) to break the information islands.  We need a system to provide dynamic water pollutions information and broadcast pollution distribution maps to the residents, scientists and governors.

Additionally, in order to improve the precision of water parameters, bio-optical algorithms should be tested and implemented under support of in situ data. These data include multi-temporal, multi-dimensional, multi-source data captured by satellite, airborne sensors and ground measurement data. One of the difficulties in building such a system is that we need to build innovate nonlinear bio-optical model to inverse water parameters (chlorophyll content, total suspended matter and yellow substance etc) with high precision.

My Contribution and Significance:  In the State 863 Project (Project ID: 2004AA131060) of the Chinese High-Technology Developing Plan “Remote-sensing Environmental Monitoring System REMS“, I conducted research as the principal investigator and project manager, and innovatively  designed and developed the four tiers and five subsystems architecture in order to meet the specifications of the Browse/Server and Client/Server.  The four-tier architecture includes: the REMS application server, the middle data server, the web server, and the Clients.  I creatively designed the REMS workflow architecture, wherein the professional workflow module of REMS is composed of two professional modules (1) atmosphere correction and (2) water quality parameters inversion.  By using analytical bio-chemical method, I innovatively built the nonlinear bio-optical models to dynamically monitor inland water pollution and extract major water characters such as Chlorophyll content, Total Suspended Matter (TSM), Yellow Substance, etc.  REMS provides the ability to professionally extract major characteristics of water resources and enable us to estimate water pollution from regional to global scale.

I led a group of 20 scientists, programmers, and clients in creating a Remote-sensing Environmental Monitoring System (REMS). REMS is the first integrated system in China developed to meet the demands of multi-resource, multi-temporal and multi-thematic data processing, analyzing and products distributing. This system is currently used by the National Environmental Protection Administration to create real-time maps of China’s thousands of water resources.

The professional REMS tools enable users to speed up inland water resource pollution processing and monitoring. The most important components of REMS includes tools for multi-resource data input/output, preprocessing, data visualization and mapping, environment information extraction, conventional image analysis, advanced tools for eco-environment modeling, and integrated interface to connect with general spatial and spectral database and water quality monitoring database.

In order to improve the precision of water parameters, I integrated some new algorithms and functions into REMS.  In order to retrieve and predict the blue algae distribution and water quality evolution, a group of statistical algorithms have been integrated to analyze and extract the major characteristics of water resources such as Chlorophyll content, Total Suspended Matter (TSM), Yellow Substance or CDOM etc. In addition, I selected Lake Tai, the third largest lake located in East Central China, as the representative research area and constructed several field applications based on this system.  The remote sensing data captured by sensors such as TM, SPOT, MODIS OMIS, and PHI (two hyperspectral sensors developed in China) had been used to retrieve the regional water information. Furthermore, the ground measurement of water quality and spectral data was also adapted as auxiliary data to supplement my research.

Based on my creative work, my first author paper titled “Quantitative Remote Sensing of Water Constituents in Taihu Reservoir” was published by the journal, British Hydrobiologia, and published in a book by Kluwer Academic Publishers in 2004.  Another first author paper titled “A New Architecture for Remote-sensing Environmental Monitoring System REMS: Design and Implementation” was published by the IEEE International Geosciences and Remote Sensing Symposium Proceedings in 2004.  My work gained great attention by many scientists in the similar fields.

(6) I provided the novel RESTful web based solution for the CAMA/GIS tax and property management platform under the support of Dojo Ajax and the Windows Communication Framework (WCF).

I currently hold a leading role as a Lead GIS Architect at Radiant Software, Inc., and I play a critical role as the key scientist in several projects involving application of GIS and RS (remote sensing) to the TerraSketch^TM tool and developing a first-of-its-kind GIS-intrinsic CAMA system.  My research and analysis skills will also be able to resolve the difficulty of qualifying the intrinsic value of a property’s spatial location in a GIS/Property Tax platform for the Alachua County, Florida. 

As the Lead GIS Architect, I provided the innovative RESTful web based solution for the CAMA/GIS tax and property management platform under the support of Dojo Ajax and Windows Communication Framework (WCF).  This creative design resolved the difficult requirements of the large scale on distributed systems immersion and huge spatial data processing ability. In order to effectively provide the most comprehensive benefits, accurate information and highest level of customer service, assessors need to advance beyond traditional integration to total immersion. Our RESTful architecture provided the total immersion solution which allows the assessor to maximize GIS, workflow, data integration, and information sharing within the assessor's office, across departments, and to the public to more effectively meet his or her appraisal and assessment needs. This RESTful architecture also offers a paradigm shift in the way assessors search for geospatial information. It brings the stages of using geospatial technology as a platform for search. Under the development of a GIS-intrinsic building sketching function, users can take advantage of GIS technology to streamline the process of gathering building information efficiently.

2.  I am a recipient of a highly competitive national award, the Outstanding Remote Sensing Data Processing Software Platform Award, bestowed by the Ministry of Science and Technology of China, 2003;

In 2003, I won the “Outstanding Remote Sensing Data Processing Software Platform Award” bestowed by the Ministry of Science and Technology of China, 2003.

The Ministry of Science and Technology (MOST, Chinese: 科学技术部), formerly the State Science and Technology Commission, is a ministry of the government of the People's Republic of China which coordinates science and technology activities in the country.  According to its mission statement:

1. MOST takes the lead in drawing up S&T development plans and policies, drafting related laws, regulations and department rules, and guaranteeing the implementation.

2. MOST is responsible for drafting the National Basic Research Program, the National High-tech R&D Program and the S&T Enabling Program. MOST aims to serve socio-economic growth by coordinating basic research, frontier technology research, research on social service, key technology and common technology. […]

10.  MOST is responsible for appraising the National S&T Award, drawing plans on S&T talents team-building and making proposals on policies.  […]

13. MOST undertakes other tasks assigned by the State Council.

The 2003 domestic spatial information system software evaluation was the 8th year software evaluation since 1996, organized and supported by the National Remote Sensing Center, the Ministry of Science and Technology of China. The spatial information system evaluation expert committees (http://www.chinagsec.com/) with 61 professional experts have authorities and certification accredited by the China National Accreditation Service for Conformity Assessment (CNAS), which is the national accreditation body of China unitarily responsible for the accreditation of certification bodies, laboratories and inspection bodies, which is established under the approval of the Certification and Accreditation Administration of the People’s Republic of China. CNAS was the accreditation body member of International Accreditation Forum (IAF) and International Laboratory Accreditation Cooperation (ILAC) ，as well as the member of Asia Pacific Laboratory Accreditation Cooperation (APLAC) and Pacific Accreditation Cooperation (PAC). 

The 2003 spatial information system evaluation was commissioned by the Department of High-tech Development and Industrialization, Ministry of Science and Technology, and was jointly organized by the National Remote Sensing Center, Chinese Association of GIS, and overseas Chinese Association of GIS with a total of 67 platforms from 99 organizations and institutes included in this competition.

Forty-eight software products participated in the GIS annual evaluation which involved 32 enterprises and companies, an evaluation expert committee of 41 people including 2 overseas experts. At the same time, the “Information acquisition and processing” expert committees of the “863 High Technology Plan” held the “Remote sensing data processing and application platform evaluation” on September 16-18, 2003 in Beijing.

Nineteen competitive works participated in the evaluation of the Remote sensing processing software which involved 67 companies and institutions. In addition, 24 projects took part in the application assessment including 19 frontier exchanges.  The evaluation expert committee consisted of 20 leading authorities and professionals. This was the first overall remote sensing platform assessment and evaluation in China with fully proprietary intellectual property rights.

This evaluation was reported by enormous media, including the China Association for Geographic Information System Portal at  http://www.cagis.org.cn/ruanjianceping/; GIS Era Portal at http://www.gisera.com/(S(5mrnou55eck5dr45kxu1hfjc))/MainForm/product/text.aspx?ID=737 and the China Byte Portal at http://www.chinabyte.com/Enterprise/218709381208866816/20031128/1748846.shtml.

I have been leading the design and development of HIPAS since 2001 which was honored as the best professional remote sensing platform of China in 2003. I was the lead architect and creatively designed a huge data processing, storage architecture for HIPAS. I designed a huge pyramid image storage system and implemented the system core module in order to process huge image data (great than10TB) in computers with a limited memory of less than 2 gigabytes.

Supported by the Chinese High-Technology 863 project (2003AA131060), the Hyperspectral Remote Sensing Image Processing and Analyzing System (HIPAS) is the first professional system designed for hyperspectral remote sensing applications in China. HIPAS can be used to analyze enormous hyper-spectral, even super-spectral image with professional modules, integrative data processing and perfect human-machine interaction. HIPAS was developed base on the international standard spectral libraries and designed to meet the requirements of further extension and development for other platforms such as Linux and UNIX system. The most kernel modules of HIPAS include: (1) Multi-source hyper-spectral data importing and processing; (2) Satellite calibration tools for VIS-SWIR-TIR data; (3) Automatic geo-reference and mosaic based on POS/IMU data; (4)Powerful performance of spatial data quantitative analysis, feature extraction and parameter extraction; (5) Automatic/manual endmember extraction and spectrum unmixing; (6) Image classification and target detection based on spectrum matching technologies and (7) Applicative modules aiming at different kinds of application demands.

3.  I played a leading and critical role as a Principal Investigator in some important projects supported by the Central Indiana Water Resources Partnership and the National Science Foundation in China (No. 2003AA131060).

I was a recipient and the principal investigator of a national funding from the Central Indiana Water Resources Partnership (CIWRP) Grant from 2006 to 2007 while working on the project titled “Quantifying blue-green algae of central Indiana reservoirs using hyperspectral reflectance” at Indiana University Purdue University in Indianapolis. The CIWRP is a national Water Quality Research and Development Partnership under the direct administration of the IUPUI Center for Earth and Environmental Science (CEES) and Veolia Water Indianapolis, LLC, and was established primarily to support and promote young researchers and engineers in the fields of water quality and watershed research development focused on resolving water quality issues. 

I was the primary investigator. of a project titled "Popularizing Sakai based course management and collaboration systems to speed up Chinese higher education informationization" from the local government of Jiangsu Province, China, with a grant with 600,000 RMB in 2008.  This project was approved for the grant by a committee composed of professional experts from across China.

More details of my granted projects are listed as follows:

1)      Principal Investigator - Popularizing Sakai based course management and collaboration systems to speed up Chinese higher education informationization, supported by the local government of Jiangsu Province, South China with a grant of 600,000 RMB, 2008-2009.

2)      Key Research Scientist - Quantifying blue-green algae of central Indiana reservoirs using hyperspectral reflectance, Central Indiana Water Resources Partnership (CIWRP) Grant, 2006-2007. $250,000.

3)      Key Research Scientist  - Development of Forecasting Models for Water Consumption in Indianapolis, PI Jose A.Ramos& Lenore P. Tedesco, July 26,2005, Water Consumption Project Grant, 2006-2007.

4)      Principal Investigator - Hyper-spectral Remote Sensing Image Processing and Analysis System HIPAS, National 863 project (2003AA131060), Chinese High-Technology Developing Plan, 2001-2003

5)      Key Research Scientist -  Bio-optical and empirical modeling of hyperspectral remote sensing for improved mapping of water quality parameters in Indianapolis’ Reservoirs, Central Indiana Water Resources Partnership (CIWRP) Grant, 2007-2008. $146,796.

6)      Key Research Scientist - Quantifying blue-green algae of central Indiana reservoirs using hyperspectral reflectance, Central Indiana Water Resources Partnership (CIWRP) Grant, 2006-2007. $250,000.

7)      Key Research Scientist - Remote-sensing Environmental Monitoring System REMS, National 863 project (2004AA131060), Chinese High-Technology Developing Plan, 2003-2005

8)      Principal Investigator - China Typical Land Objects Hyper-spectral Database Information System, National 863 project, Chinese High-Technology Developing Plan, 2003-2005

9)      Key Research Scientist - Software Platform Design and Development for On-orbit Calibration and Validation of China Disaster Monitoring Constellation (DMC) Micro-satellite, National 863 project, Chinese High-Technology Developing Plan, 2004-2006

4.  My research discoveries have resulted in one patents issued by the Ministry of Patents in China (No. 2007SRBJ0549).

In 2003, I produced practical, significant, and original inventions/methods that have been issued patents in China. This is further evidence that I am fully capable of producing industry-leading contributions that have important impact on the field, as well as on society.  The following is detailed information about my approved patent:

·     REMS software registry patent

Title: Remote-sensing Environmental Monitoring System (REMS) and Its Applications

Registry No.:   20060005 BJ

Author:   Xingtang Hu

Reference:  HU, X.-T., B. Zhang, X. Zhang, Q.-X. Tong, L.-F. Zheng, Q. Wang, and J.-L. Yu, A new architecture for remote-sensing environmental monitoring system REMS: Design and implementation. Proc. of IEEE International Geoscience and Remote Sensing Symposium (IGARSS), vol.3, 2115-2118, 2004.

Computer Software Copyright Registration Certificate

No.  Software Registration No. BJ7521

Registration No.:            2007SRBJ0549 

Name of the Software:    Remote Sensing Environment Monitoring System REMS V1.0 

Copyright owner:            Institute of Remote Sensing Applications, Chinese Academy of Sciences

Copyright type:                Original  

Scope of the copyright:    All copyrights granted.  

First publication date:      September 16, 2005 

Pursuant to the < Regulations of Computer Software Protection> and the <Registration of Computer Software Copyright>, the above-described copyright has been registered.

Sealed:   by The National Copyright Administration of the People’s Republic of China.  

Dated:    March 30, 2007.

This patent has been cited by the China Registration Database of Scientific and Technological Achievements at http://dbpub.cnki.net/grid2008/Unis/Detail.aspx?DBName=SNAD&FileName=SNAD000001003844&QueryID=31&CurRec=1.

Supported by the Chinese High-Technology Developing Plan, the National 863 project, we developed the Remote Sensing Environment Monitoring System (REMS V1.0) mainly for water quality in cooperation with Environment Protecting Bureau of China and Jiangsu Environment Monitoring Center.

I designed a new architecture for Remote-sensing Environmental Monitoring System (REMS). REMS provide professional ability to extract the major characteristics of water resources such as Chlorophyll content, Total Suspended Matter (TSM), Yellow Substance (also named CDROM) etc. In this system, I presented the most important components of REMS including tools for multi-resource data input, output, preprocessing, data visualization and mapping, environment information extraction, conventional image analysis, advanced tools for eco-environment modeling, and integrated user interface to connect with general spatial database, spectral database and water quality monitoring database.

By integrating with WebGIS and Remote sensing technologies, REMS includes four tiers and five subsystems so that it could meet the specification of the browser/server and desktop/server architecture. The four-tier architecture includes the REMS application server, the middle data server, the web server and the client. The REMS application server was composed by two important modules including the atmosphere-correcting module and the water quality parameters inversing module.

REMS was designed to meet the requirements of operational remote sensing monitoring on environment by local government. REMS not only provides the general image processing functionality, but also provides more than 500 band hyperspectral image processing ability. 

REMS has been applied to process multi-resolution, multi-temporal, multi-source remote sensing data in Jiangsu Environmental Monitoring Center (http://www.jsaem.org/jshjjc/default.aspx)  to generate water quality pollution reports by week, season and year. REMS was also applied for satellite data processing and applications of China Disaster Monitoring Constellation (DMC).

The results show that the REMS has excellent practicability and applications in water quality dynamically monitoring and prediction.

5.  My research discoveries have also been published in peer reviewed professional journals and conference proceedings.

My research discoveries and findings in the area of geospatial data mining and system integration have been reduced to scientific papers published in peer-reviewed professional journals, including Advances in Space Research, Journal of Geophysical Research, Journal of Remote Sensing and Science in China Series E: Technological Sciences.  These journals are highly prestigious international journals in their specialized areas with strict peer-review policies.

Advances in Space Research is the Official Journal of the Committee on Space Research (COSPAR), a Scientific Committee of the International Council for Science (ICSU). Materials published has been presented to the international community of space scientists and, following discussions at the meetings, edited by eminent scientists in the field. The policy of the Editorial Board is that only reviewed papers may be considered for publication. Fields covered are: Space Studies of the Earth's Surface, Meteorology and Climate; Space Studies of the Earth-Moon System, Planets and Small Bodies of the Solar System; Space Studies of the Upper Atmospheres of the Earth and Planets, including Reference Atmospheres; Space Plasmas in the Solar System, including Planetary Magnetospheres; Research in Astrophysics from Space; Materials Sciences in Space; and Life Sciences as Related to Space.

Journal of Geophysical Research is a journal of the American Geophysical Union. It is often called by its initials, JGR. JGR publishes original scientific research on the physical, chemical, and biological processes that contribute to the understanding of the Earth, Sun, and solar system and all of their environments and components.

The AGU provides subscribers access to electronic versions of nearly all papers published in the JGR from 1994 to the present. In addition, since 1994, the AGU has provided online e-supplements to JGR articles, allowing data sets to be disseminated and archived along with electronic versions of the published articles.

Science in China Series E: Technological Sciences was Co-published with Science in China Press, Science in China Series E: Technological Sciences is co-sponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China. The journal is committed to publishing high quality, original results in both basic and applied research.

Journal of Remote Sensing is devoted to presenting the important advancements of the science and technology in remote sensing technologies and environmental remote sensing applications. The original research papers published in this journal present concepts, analytical methods, technical knowledge, exploratory developments, and new applications of remote sensing. The field of remote sensing is changing quickly, being impacted by newer platforms, sensors, innovative modeling, and substantial advances in the display, manipulation, and analysis of spatial information.  Every entry of these journals is critically peer-reviewed by several experts in the field, ensuring top-quality research and information.

Additionally, I was invited to write a chapter in a textbook, Hyperspectral Remote Sensing Science-Theory:  Technologies and It’s Applications edited by Q.-X. Tong.  This is a major textbook for graduate student majors in earth sciences in China.

In addition, my works have been published in highly reputable journals and major symposia in Geosciences. My research accomplishments were published as first author papers in conference proceedings such as the IEEE International Geosciences and Remote Sensing Symposium (IGARSS) and IEEE International Society for Optical Engineering Symposium (SPIE). The IGARSS and SPIE are leading professional publications concentrated specifically on geosciences.

The abovementioned work has had a profound impact on scientists and researchers around the world.    According to the Science Citation Index, my papers have been cited more than 20 times by sole- or first-authors in the field.  Prominent scientists from national and international wide cited and discussed my work as authoritative. 

6.  I have made presentations at leading professional conferences.

The national and international impact of my research can be further proved by my frequent presentations at international conferences. In the past twelve years, I have been invited to give presentations at several famous universities and professional Symposiums such as The First Sakai China Workshop 2008; 26th International North American Lake Management Society (NALMS) Symposium, Indianapolis, IN, U.S.A. 2006; The Central Indiana Water Resources Partnership (CIWRP) Science Meeting: Watershed and Reservoir Assessment and Analysis, Indianapolis, IN, U.S.A. 2006; National Symposium on Remote Sensing of China 2005; National Remote Sensing Technology Symposium, Guizhou, China 2005; IEEE International Geosciences and Remote Sensing Symposium 2004; Hyper-spectral Remote Sensing Technology and Applications Symposium, Kunming, Yunnan, China 2004; and the International Society for Optical Engineering Symposium 2003.  Active participation in the above conferences shows the recognition of my expertise by my peers as well as my dedication to geospatial data mining and geoinformatics sciences.

(I)  IEEE International Geoscience & Remote Sensing Symposium (IGARSS): The Geoscience and Remote Sensing Society annually sponsors the International Geoscience and Remote Sensing Symposium (IGARSS), a premier world conference on this topic. Held annually with alternate years in North American and International venues, this prestigious meeting has become an international focus of remote sensing programs, applications and activities. Each year, it draws more than a thousand scientists, engineers and community leaders from around the world to become familiar with current research and technology and to discuss instruments, techniques, models, uses and programs of global interest. IEEE Geoscience and Remote Sensing Symposium to be the excellent tradition of gathering world-class scientists, engineers and educators engaged in the fields of geoscience and remote sensing to meet and present their latest activities.

(II)  IEEE SPIE - The International Society for Optical Engineering:  SPIE is a non-profit professional society dedicated to the advancement of research, engineering, and applications in optics, photonics, imaging, and electronics. The mission of SPIE is to serve scientists and engineers in industry, academia, and government, as well as companies producing leading-edge products. SPIE constituents work in a wide variety of fields that utilize some aspect of optics and photonics, which is the science and application of light.

Individuals involved with SPIE conduct research and apply new techniques to the design and development of technologies such as semiconductor manufacturing, robotics, medical imaging, next-generation displays, battlefield technologies, entertainment, biometric security, image processing, communications, astronomy, and much more. SPIE attracts Members from around the world, including North and South America, Europe, Africa, and Asia, and supports them from offices in North America and Europe.

(III) National Symposium on Remote Sensing of China NSRSC: The NSRSC is well-known as the largest conference in the area of remote sensing and its applications in China.  The NSRSC conference reports most up-to-date research and development in the area of geospatial data mining and advanced geosciences technologies such as GIS, RS and GPS.

7.  I am a member of the International Association of Assessing Officers IAAO, Indiana Lakes Management Society ILMS and China Association of Remote Sensing Application, among other professional organizations, which require extraordinary achievements.

I am currently a member or was formerly a member of the following:

·     (1) International Association of Assessing Officers IAAO, 2010: I was invited to become a member of the International Association of Assessing Officers due to my leadership and extraordinary academic performance in the development of CAMA/GIS tax and property management platform. The International Association of Assessing Officers is a professional membership organization of government assessment officials and others interested in the administration of the property tax. The IAAO was founded in 1934, and now has a membership of more than 8,000 members worldwide from governmental, business, and academic communities. The mission of IAAO is to promote innovation and excellence in property appraisal, assessment administration, and property tax policy through professional development, education, research, and technical assistance.  IAAO is the internationally recognized leader and preeminent source for innovation, education and research in property appraisal, assessment administration and property tax policy. 

(2) Indiana Lakes Management Society (ILMS), 2006:  I was approved to be a Member of the Indiana Lakes Management Society by the Committee on Qualifications.  Indiana Lakes Management Society, more commonly known as “ILMS”, was incorporated as a not-for-profit corporation in the State of Indiana in 1991 by a group of individuals with a common interest in protecting and saving Indiana lakes for future generations. ILMS is a nationwide honor scientific research society, and selected membership is comprised of scientists, researchers, and engineers who have reached a high level of proficiency and achievements in their professional endeavors. The nature of the society is to encourage original investigation and research in science and engineering, and promotes the public’s understanding of science for the objective of improving the human condition. The approval of nomination as a member of this international honor society demonstrated my excellence and prominent accomplishments in my particular field.

(3)  China Association of Remote Sensing Application (CARSA), 2003: Moreover, I was invited to become a member of the China Association of Remote Sensing Application due to my extraordinary academic performance at the Graduate University of Chinese Academic of Sciences, in which I was placed among the top 5% in my class. Members in China Association of Remote Sensing Application are highly regarded and sought after by many prestigious employers and institutions.  China Association of Remote Sensing Application (CARSA) was founded on August 26, 1992. Affiliated with the China National Space Administration (CNSA), the Association is formed by institutions and individuals of whole country, which dealing with geographic information system, remote sensing information technologies and related subjects. It is a professional and scientific, nonprofit social organization in the field of geographic information system and remote sensing information technologies of China.

The objectives of the CARSA is to unite all the remote sensing information technical forces of the nation to abide by the constitution, lows and government regulations; conform to the morality and ethics of the society; to standard the remote sensing technical, market and to promote technical applications and development. The scope of activities of CARSA includes technical exchange, theoretical study, technical training, and literature editing, consulting and international cooperation.

(4) Notably, I have been the President of Wuxi Hanphon Limited Corporation since October 2008. This leadership position was bestowed upon me by the Wuxi Hanphon Limited Corporation after a two-tiered nomination and review process.  I was in charge of the research and development of Sakai based collaboration and learning applications.

8.  I was invited and served as an expert reviewer/referee for leading professional journals.

I have been a reviewer for the Journal of Remote Sensing in the special field of geographic information systems and remote sensing due to my remarkable achievements in geospatial data mining and system integration. As noted above, the Journal of Remote Sensing is very well respected in the scientific community, with strict standards for both publication and review. My invitation as a sufficient expert to judge the works of others in these journals clearly shows that my scientific reputation in the field is distinguished and impressive.

9. My works have garnered major international media reports.

My achievements on geosciences and information system integration gained wide attention and were reported by several famous national and international media, as follows:

(1) Portal of the Ministry of Science and Technology of the People’s Republic of China:  “Domestic GIS and RS Software Platform Reached a New Epoch” (12/03) -  This media article discussed my research on the Hyper-spectral Image Processing and Analysis System (HIPAS), which led to my receipt of the Outstanding Remote Sensing Data Processing Software Platform by the China Association of Remote Sensing Application and the National Remote Sensing Center, Ministry of Science and Technology of the People’s Republic of China.  For further details, please refer to:  http://www.most.cn/xwzx/xwfb/200312/t20031212_8672.htm.

The Portal of the Ministry of Science and Technology of the People’s Republic of China is the official web portal for the Ministry of Science and Technology (MOST) of China. This information portal is dedicated to providing comprehensive information of organization, international cooperation, policies and regulations, S&T programmers, S&T statistics and S&T Newsletters for the Ministry of Science and Technology (MOST) of China to users including governors, scientists and residents as well as international cooperation with researchers from around the world. MOST aims to serve socio-economic growth by coordinating with basic research, pioneer technology research, social service research, key and common technologies as well as tasks assigned by the State Council.

This site is the official portal to publish and renew national important polices including policies to encourage the synergy of enterprise, university and research institute, promote application and demonstration of scientific discovery and technological invention, and improve innovation capacity of enterprises.  It is authorized and managed by the Science and Technology of the People’s Republic of China and presently serving more than 1,000 universities, scientific research institutions and academic organizations.  It is available to an international audience and can be accessed worldwide.

(2) The China Science-Meeting Online: “The First Sakai Day in China has been held successfully by HuaZhong Normal University” (3/10/08) –  This article discussed the fine points of the Sakai presentation conducted by scientists at HuaZhong Normal University, including my own research on the design and implementation of the Component based and Services Oriented Architecture (SOA).  The above article can be found at:

http://www.meeting.edu.cn/webmedia/oemui/newsinfo/newsshow.asp?news_id=4805&news_type_id=3

The China Science-Meeting Online is dedicated to providing comprehensive information of International Academic Events (including conferences, meetings, symposiums, workshops, summer schools, etc) to a Chinese audience, including scientific research personnel, teachers, and students in school. It is authorized by the Ministry of Education of China and managed by the Science and Technology Development Centre under the Ministry of Education. It is presently serving more than 1,000 universities, scientific research institutions, and academic organizations with over 100,000 registered members in China.  It is available to an international audience and can be accessed worldwide.

10. My research position requires me to apply geospatial data mining theory and GIS/RS integration technologies to design and develop land management, property tax and field data collection systems. My current work and future research plan will continue to serve important national interests of the United States.

I have been a leading scientist in the Remote-sensing Environmental Monitoring System, Hyperspectral Remote Sensing Image Processing and Analysis System and the Sakai Collaboration and Learning projects. Essentially, I played a leading role in the design and development of a novel HIPAS Software funded by the National Science Foundation.  My contribution to the preparation of the HIPAS project is significant.  With a solid background and comprehensive knowledge in GIS and Remote Sensing and in-depth experience of Geospatial data mining and modeling techniques acquired through numerous research projects, I was offered a Lead GIS Architect position at Radiant Software, Inc. Corporation in 2008. In this position, I am responsible for infrastructure development, design, deployment, and implementation of land management, property tax and field data collection systems and support for the customers.  This includes system analysis, design, development, debugging, maintenance, enhancements, custom programming, and configuration management. 

I am currently conducting cutting edge research on the design and development of innovative pen computing software to state/province and local government for more effective field data collection.  My current work is to apply my prior research findings and knowledge to the property tax industry with the acquisition of TerraSoft Systems, Inc. assets, including its user-friendly computer assisted mass appraisal (CAMA), assessment administration (AA), tangible personal property (TPP), and tax collection (TAX) software and its experienced staff.  These projects heavily depend on my expertise, as I am one of the first investigators to apply GIS and advanced spatial modeling and analysis techniques to the design of Land management Software, which places me at the very forefront in this subject. I am also the only GIS Architect in the company responsible for integration of GIS, Tax and assessment systems. The successful completion of various tasks of the project cannot be achieved without my professional skills, profound research experiences, and future dedication. Furthermore, as a Lead GIS Architect, my innovative abilities will make me successful in learning new products and supporting the development, marketing and sales of all products including product design, development, capacity planning, installation planning, and project management, planning, and scheduling.

I am playing a critical role as the lead GIS architect in several GIS-oriented projects.  The key projects at this time are the TerraSketch building drawing tool which we are currently marketing.  There will be numerous Geographic Information Systems (GIS) and Remote Sensing (RS) additions to this product.  At the same time we have Spatial Assessor our GIS-intrinsic Computer Assisted Mass Appraisal (CAMA) product in the early stages of development.  The CAMA System will make far more use of GIS/RS.  As it is in the early stages, my input is critical to fully leverage GIS and RS before production is too far along to make corrections or changes.  No one has built a GIS-intrinsic building drawing or CAMA system before, so the possibilities are truly extensive and cutting-edge.  Based on my comprehensive background of geospatial data mining and geospatial systems integration, I am in the very top of a small group who can fully comprehend the possibilities to implement such information platform.

Moreover, I have made significant contributions to Geospatial data mining research projects and my research helped to gain funding from Central Indiana Water Resources Partnership. The geospatial data mining is directly related to Land management Software research project. The Land management Software research project can be described combination of GIS system, assisted mass appraisal (CAMA), assessment administration (AA), tangible personal property (TPP), and tax collection (TAX) software.  The possible utility of these products and my research and development will serve the national interest of the United States to a great degree.  First, the abovementioned products provide valuable location detail relative to both building structures and what they contain.  This kind of information is valuable to first responders (fire, police, and emergency medical services) since they are available to use data immediately.  This information is also valuable for emergency management in advanced preparation for, and subsequent response to, potential natural and man-made disasters. 

In summary, I believe I am qualified for all of the requirements provided by Immigration Regulations for the classification of EB1: An alien of extraordinary ability.  I have established a track record of success in my area of expertise. I have made important original research contributions of major significance to modeling and analysis techniques of Geospatial data mining and system integration. I was a  geo-informatics scientist who has risen to the very top of the field of GIS and Remote sensing engineering, as well as distribute information system integration. My research findings were published in prestigious international journals and had significant major impacts on the work of other experts in my field of endeavor. I have been a leading scientist in important government-funded projects. My future research will continue my current exploration in GIS and its application in land management, which requires highly sophisticated novel knowledge, skills, and expertise based on my prior research discoveries and technical developments. My achievements and research, both previous and current, have benefited and will continue to benefit important interests of the United States in a national scope.

I thus respectfully request your favorable adjudication for my permanent residency status in United States.

Thank you for your time and consideration.

Sincerely yours,

Xingtang Hu, Ph.D.

Lead GIS Architect

Radiant Software, Inc.

Clearwater, Florida