Real-time Satellite Data Research Articles

Space-based technologies and high performance computing in support of environmental sustainability in developing countries

Inspired by recent service on the User Working Group for NASA’s Socio-Economic Data Applications Center (SEDAC), the Science Review Panel for the Arctic Region Supercomputer Center, the Technology Advisory Committee for South Africa’s Center for High Performance Computing and participation in the NATO Pilot Study on Clean Products and Processes over the past four years, our distributed interdisciplinary research collaborators intensified our efforts to address some of the fundamental issues with respect to societal sustainability. We particularly focused on highly vulnerable communities, at risk for an array of immediate and long-term biogenic and anthropogenic disasters. Specifically, we sought to address the question: ‘‘How should state-of-the-science computational capabilities and earth observing satellites be optimally placed in the service of environmental sustainability and sustainable development?’’ In the on-going process of examining this issue, it has been encouraging to observe the technological progress that has recently occurred within Latin America, Asia and Africa. CONAE http://www.conae.gov.ar/eng/aplicaciones/ salud_new.html, the Argentine Space Agency’s SAC-C satellite has been operational since 2000 and its successor, Aquarius (SAC-D) will be launched in 2010; while SABIA (SAC-E), the Argentine-Brazilian Satellite for Information on Food, Water and the Environment, ALSAT-2 (SAC-F) and SAOCOM 1-A, with microwave radar and a thermal infrared camera, are each currently under production. Brazil’s other collaboration with China, the ChineseBrazilian Earth Resources Satellite (CBERS) has been generously offered without licensure fees to developing countries. China, as well, freely offers its Fung Yun 1D MVISR globally to receiving stations. Robust earth observing satellite launch schedules are apparent in China, India, Japan, Korea, Taiwan and Thailand. African engagement in satellite remote sensing has been actively promoted by the African Association for Remote Sensing of Environment (AARSE) and by the 2009 IEEE International Geo-science & Remote Sensing Symposium (IGARSS) held in Cape Town, South Africa. As a follow-on to the NATO Committee on the Challenges to Modern Society’s Pilot Study on Clean Products & Processes, the NATO Science for Peace Program has awarded funding to establish the Kamal Ewida Earth Observatory http://www.itap.purdue.edu/pto/NATO_KEEO/ index_en.html, which will include real-time satellite ground stations in Egypt at Cairo University and Al Azhar University, primarily for early warning and mitigation of disasters, including storms, flooding and epidemics, through identifying and monitoring infectious disease vector habitat, as well as for facilitating natural resource management. This initiative is in collaboration with the Kandilli Observatory and Earthquake Research Institute at Bogazici University in Istanbul, Turkey and with the Purdue Terrestrial Observatory at Purdue University’s Rosen Center for Advanced Computing in West Lafayette, Indiana, USA. Analysis of the real-time satellite data will benefit from a recently installed IBM Blue Gene L Supercomputer at Egypt’s National Authority for Remote Sensing & Space Sciences (NARSS), which has the capability to produce data products in near-real-time, as input to decision support for time-critical events. The other civilian supercomputer facility on the African continent is at South G. L. Rochon (&) Purdue Terrestrial Observatory (PTO), Information Technology at Purdue (ITaP), Rosen Center for Advanced Computing (RCAC), Purdue University, 203 Martin Jischke Drive, Mann Hall 160, West Lafayette, IN 47907, USA e-mail: rochon@purdue.edu

Mapping chlorophyll-a through in-situ measurements and Terra ASTER satellite data

This paper presents an application of water quality mapping through real-time satellite and ground data. The Lake Beysehir which is the largest freshwater lake and drinking water reservoir in Turkey was selected as the study area. Terra ASTER satellite image is used as remote sensing data source for water quality mapping in addition to simultaneously performed in-situ measurements. Ground data is collected simultaneously with the ASTER overpass on June 09, 2005 over the Lake Beysehir. The spatial distribution map is developed by using multiple regression (MR) technique for water quality parameter, which is chlorophyll-a (chl-a). The results indicate that simultaneous ground and satellite remote sensing data are highly correlated (R (2) > 0.86). In the image processing step, geometric correction, image filtering and development of water quality map procedures are performed with the ERDAS Imagine and ArcGIS 9.0 software. The trophic status of Lake Beysehir is considered to be oligotrophic with an average 1.55 microg/l chl-a concentration.

Real-time agrometeorological crop yield monitoring in Eastern Africa

The Joint Research Centre (JRC), in collaboration with the Food Agriculture Organization (FAO), has developed for East Africa an operational crop yield monitoring and forecasting system (CYMFS). The CYMFS integrates into a Geographical Information System (GIS): the meteorological information of the European Centre for Medium-Range Weather Forecast (ECMWF), the Crop-Specific Water Balance (CSWB) model, and the Crop Production System Zones database (CPSZ). Additional and independent real-time satellite data from SPOT VEGETATION were analyzed using a specific crop mask to concentrate the analysis only on agricultural areas. This approach gives to the food analyst a qualitative picture of crop yield expectation for rain-fed crops at different stages of the growing season. The proposed methodology was applied to the first crop season of 2001 and 2002 and demonstrated a clear potential in crop monitoring and yield forecasting. The results obtained during the extremely dry year of 2002 proved that the crop monitoring system was timely and geographically precise. A new crop cycle progress index (CCPI) was developed to take into consideration the agro-ecological heterogeneity of the region.

Introducing Real-Time AVHRR-APT Satellite Imagery in the Classroom Environment

A low-cost (US$350) satellite receiving station was assembled and operated within a classroom environment in Gainesville (Florida) on October 2001 for acquiring satellite data directly from the Advanced Very High Resolution Radiometer (AVHRR) satellites. The simplicity of the satellite signal makes this source of real-time satellite data readily accessible to the K-16 educational community. The educational strategy of this program sought to achieve pedagogical effectiveness within the sciences, mathematics, and technology through the cultivation of applied, critical, and analytical skills. The applied hands-on laboratory and lecture experiences aimed at enabling students to visualize and integrate the various concepts presented in the classroom. The characteristics of the satellite data provide students and educators with “live” visible and infrared images that allow for the visualization and exploration of dynamic scientific concepts, making the AHVRR-APT system a suitable educational tool for complementing the K-16 curricula. This educational experience relied on inexpensive radio equipment for accessing satellite data through the exploration of modern space technology. When compared to Internet-based sources of AVHRR data, the virtual nature of Internet portals cannot provide students with a “live” satellite data acquisition experience, such as that available through a classroom-based AVHRR-APT satellite receiving station.

Integrated satellite observations of the 2001 eruption of Mt. Cleveland, Alaska

Satellite data were the primary source of information for the eruption of Mt. Cleveland, Alaska on 19 February, and 11 and 19 March 2001. Multiple data sets were used pre-, syn- and post-eruption to mitigate the hazard and determine an eruption chronology. The 19 February eruption was the largest of the three, resulting in a volcanic cloud that formed an arc over 1000 km long, moved to the NE across Alaska and was tracked using satellite data over more than a 50-h period. The volcanic cloud was “concurrently” detected on the GOES, AVHRR and MODIS data at various times and their respective signals compared. All three sensors detected a cloud that had a very similar shape and position but there were differences in their areal extent and internal structural detail. GOES data showed the largest volcanic cloud in terms of area, probably due to its oblique geometry. MODIS bands 31 and 32, which are comparable to GOES and AVHRR thermal infrared wavelengths, were the least effective single channels at detecting the volcanic cloud of those investigated (MODIS bands 28, 29, 31 and 32). MODIS bands 28 and 29 detected the largest volcanic clouds that could easily be distinguished from weather clouds. Of the split-window data, MODIS bands 29 minus band 32 detected the largest cloud, but the band 31 minus band 32 data showed the volcanic cloud with the most internal structural detail. The Puff tracking model accurately tracked the movement, and predicted the extent and shape of this complex cloud even into areas beyond satellite detection. Numerous thermal anomalies were also observed during the eruption on the twice-daily AVHRR data and the high spatial-resolution Landsat data. The high-resolution Radarsat data showed that the AVHRR thermal anomalies were due to lava and debris flow features and a newly formed fan along the west coast of the island. Field observations and images from a hand-held Forward Looking Infrared Radiometer (FLIR) showed that the flow features were ′a′a lava, debris flows and a warm debris fan along the west coast. Real-time satellite data were the primary tool used to monitor the eruption, track changes and to mitigate hazards. High-resolution data, even though coverage is infrequent, were critical in helping to identify volcanic processes and to compile an eruption chronology.

Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data

An operational crop yield model was developed by introducing realtime satellite imagery into a Geographical Information System (GIS) and the Crop Specific Water Balance (CSWB) model of the Food and Agriculture Organization (FAO). Input databases were developed with three different resolutions; agro-ecological zone (AEZ) polygons, 7.6 km and 1.1 km pixels; from archived satellite data commonly used by Early Warning Systems (EWS) to simulate maize yield and production in Kenya from 1989 to 1997. Simulated production results from the GIS-based CSWB model were compared to historical maize production reports from two Government of Kenya (GoK) agencies. The coefficients of determination (r 2) between the model and GoK district reports ranged from 0.86 to 0.89. The results indicated the 7.6 km pixel-by-pixel analysis was the most favorable method due to the Rainfall Estimate (RFE) input data having the same resolution. The GIS-based CSWB model developed by this study could also be easily expanded for use in other countries, extended for other crops, and improved in the future as satellite technologies improve.

Agricultural Management Decision Aids Driven by Real-Time Satellite Data

Abstract In a NASA-sponsored program entitled Use of Earth and Space Science Data Over the Internet, scientists at the University of Wisconsin—Madison have developed a suite of products for agriculture that are based in satellite and conventional observations, as well as state-of-the-art forecast models of the atmosphere and soil_canopy environments. These products include an irrigation scheduling product based in satellite estimates of daily solar energy, a frost protection product that relies on prediction models and satellite estimates of clouds, and a product for the prediction of foliar disease that is based in satellite net radiation, rainfall measured by NEXRAD, and a detailed model of the soil_canopy environment. During the growing season, the first two products are available in near-real time on the Internet. The last product involving foliar disease depends on a decision support system named WISDOM developed by the University of Wisconsin—Extension, which resides locally on growers' home compu...

The Third Phase of TESS

The U.S. Navy has developed the Tactical Environmental Support System, third generation, TESS(3), a computer workstation to provide environmental information for the Navy's tactical decision makers. With interfaces to real-time satellite data, to commercial weather teletype, and to naval communication broadcasts, the TESS(3) maintains a dynamic environmental database to support meteorological and oceanographic requirements. This article describes the TESS(3) system. With delivery of TESS(3) stations to both ashore and afloat sites, the Navy oceanographer/meteorologist has an updated toolbox for analysis and forecasting. The TESS(3) system allows the forecaster to acquire, assimilate, and disseminate information rapidly for quick utilization—a definite improvement for Navy operational environmental support.

Comments on “A Real-Time Satellite Data Acquisition, Analysis and Display System—A Practical Application of the GOES Network”

Comments on “A Real-Time Satellite Data Acquisition, Analysis and Display System—A Practical Application of the GOES Network”

A Real-Time Satellite Data Acquisition, Analysis and Display System—A Practical Application of the GOES Network

A real-time satellite data acquisition, analysis and display system is described which uses analog data transmitted by telephone line over the GOES network. Results are displayed on the system color video monitor as 'thermal' images which originated from infrared surface radiation sensed by the Geostationary Operational Environmental Satellite (GOES).