Opportunities of the Low-Cost Satellite Image Reception Station Established at GIS & RS Center of Bahir Dar University, Institute of Technology

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1 Opportunities of the Low-Cost Satellite Image Reception Station Established at GIS & RS Center of Bahir Dar University, Institute of Technology Abeyou W. a, Mengeste A. a, Workaferahu A. b, Mulken M. c, Aemro B. d and Essayas K. a a Bahir Dar University, School of Civil and Water Resource Engineering b Bahir Dar University, Land Administration Institute c Lake Tana Basin Organization d Bahir Dar University, School of Computing and Electrical Engineering Corresponding author: Abeyou Wale.W., abeyou_wale@yahoo.com year 2011 Presented at 2 nd Symposium on biodiversity and Natural Conservation at Arba Minch University, Ethiopia (June 03-05, 2010) ABSTRACT In many countries throughout the world, the use of earth observation data for environmental monitoring or community service still remains underexplored. Sustainable development requires the use of Earth observation data for effective decision making in early warning systems, environmental monitoring, resource optimization and other tasks. In support of this objective the Group on Earth Observation (GEO) is leading a worldwide effort to build a Global Earth Observation System of Systems (GEOSS), providing Earth observations data from a multitude of instruments worldwide These Earth observation data (in-situ, air and space borne) and derived products are (re) distributed via GEONETCast to a broad range of user communities worldwide. In March 2, 2011 a low-cost satellite image (GEONETCast) reception station is established at Bahir Dar University, Institute of Technology in collaboration with Tana Sub-Basin Office and ITC, the Netherlands. The reception system ensures the collection of time series data relevant to environmental, hydrological and meteorological monitoring at a minimum cost. The ground reception system comprises of two computers - one for the reception and another for data processing. The reception station is fitted with a TechnSat SkayStar 2 TV DVB board and to decode and decrypt the DVB signal, EUMETCast Client Software and EUMETCast Key Unit (EKU) are fitted. Freeware tools, like GEONETCast toolbox plug-in and ILWIS software both developed by ITC are installed in the processing computer.. Currently the system is receiving data 24 hours a day and seven days a week from Meteosat Second Generation (MSG) satellite every 15 minutes in 12 spectral bands, from Satellite Application Facilities (SAFs) which comprises of standard meteorological products (such as Albedo, Down-welling Surface Short-wave and long wave Radiation Flux W/m2, Fraction of Vegetation Cover % etc), from Meteorological Product Extraction Facility (MPEF) products like Cloud Analysis Image (CLAI), Cloud Mask (CLM), Clear Sky Radiance (CSR) and from VGT4Africa which distributes vegetation data to Africa through EUMETCast. In this paper efforts are made to demonstrate the use of these products in explaining spatio-temporal inter-relationship between rainfall and vegetation phenology over Lake Tana Basin using a decadal satellite image from VGT4Africa and a rainfall collected by the Ethiopian Meteorological Agency for year The result shows the areal average monthly NDVI value in the basin reaches peak in growing season from August to November. The results showed that correlation of areal monthly average NDVI and rainfall across the basin is weak; the possible explanation of which is a lagged response of the vegetation to rainfall. The comparison of the occurrence of the rainfall maximum (July) to the vegetation peak (September) revealed that this lag is about two months. The temperature and evapotranspiration data analyzed from SAF for every one hour interval in the basin shows a maximum and minimum temperature at 11:00 and 22:00 UTC respectively and evapotranspiration at 9:00 and 18:00 to 23:00 UTC respectively. These results may be used to re-schedule the temperature reading times at meteorological stations. Key words: GEONETCast, EUMETcast, SAF, NDVI, Lake Tana Basin 1

2 1. Introduction In many countries throughout the world, the use of earth observation data for environmental or societal purposes still remains underexplored, in spite increasing earth observation (EO) data provision (Mannaerts et al 2009). Sustainable development requires coordinated, comprehensive and sustained Earth observations for early warning and for effective decision making. In support of this objective the Group on Earth Observation (GEO) is leading a worldwide effort to build a Global Earth Observation System of Systems (GEOSS), providing Earth observations from a multitude of instruments worldwide It is anticipated that these Earth observation data (in-situ, air and space borne) and derived products are (re) distributed via GEONETCast to a broad range of user communities. GEONETCast is a near real time, global network of satellite-based data dissemination systems designed to distribute space-based, air-borne and in situ data, metadata and products to diverse communities. This low-cost, global, environmental information delivery system currently operates the European, African, Asian and American services. The data stream transmitted by these communication satellites can be received using a simple and cheap ground reception infrastructure. With the ongoing development of GEONETCast, broadcasting (globally) a multitude of satellite observations and associated products in conjunction with cheap ground receiving infrastructure, the data is now at the doorstep of the community anywhere in the world (Maathuis et al 2009). In March 2011, in collaboration with Tana Sub-Basin Office and ITC, the Netherlands a low-cost GEONETCast reception station is established at Bahir Dar University Institute of Technology (BDU-IoT). This paper will briefly discuss the opportunities and the components of the system established Objective The main objective of this paper is to describe the components of a ground reception station at Bahir Dar University, Institute of Technology and demonstrate the opportunities in using the satellite images acquired by the reception system by exploring the spatio-temporal relationship between the Normalized Difference Vegetation Index (NDVI) and rainfall as well as Land Surface Temperature (LST) and Evapotranspiration (ET) over the Lake Tana Basin Study area description The study area, Lake Tana is the source of the Blue Nile River and has a total drainage area of approximately 15,000 km 2, of which the lake covers 3,060 km 2 at elevation 1,786 m amsl (Abeyou 2008). The lake is the largest lake in Ethiopia and the third largest in the Nile Basin. The lake is located in the north-west highlands at 12 o 00 N, 37 o 15 E which is 564 km from the capital Addis Ababa see Figure-2. The lake has more than 40 tributary rivers, but the major rivers feeding the lake are Gilgel Abay from the south, Ribb and Gumara from the east and Magetch River from the north, while there are no large rivers that flow from the western side of the lake. According to Kebede (2006) those four rivers contribute 93% of the lake inflow. 2

3 Figure- 1: Location of Lake Tana Basin north-west highlands of Ethiopia (Left side MSG satellite image on April 12, 2011 at 09:35 UTC and right Landsat 7 ETM+ satellite image on September 12, 1999) 1.3. System overview and Opportunities System overview The EUMETSAT AtlanticBird-3 carries the dissemination service for Africa. The reception station at Bahir Dar University comprises a standard PC with Digital Video Broadcast (DVB) card, a C- band LNB and a 2.5 meter diameter parabolic dish antenna. External hard-disk drive (1 Terabyte) is used to store the images. EUMETCast Client software and EUMETCast Key Unit (EKU) are used to decode and decrypt the digital signals. Table-1 below shows the typical GEONETCast reception station components. Table 1: System components of satellite image (GEONETCast) reception station Hardware requirements Two advanced high speed processing computers One for DVB acquisition, reception station Data processing computer Software requirements Microsoft Windows XP SP2 operating system The EUMETCast client software EUMETCast operates a tq -TELLICAST server DVB PCI card driver software ITC ILWIS (Integrated Land and Water Information System) and the GEONETCast toolbox developed at ITC Other requirement Antenna Requirements: 2.4m diameter dish antenna fitted with digital universal V/H LNB C-band Terabyte external hard disk (every three month) Network interconnecting device and UTP cables 3

4 Figure- 2: Typical components of the reseption station at BDU-ioT A 2.5 meter LNB C-band receiver aligned to the direction of AtlanticBird-3 Satellite to the left, EUMETCast Key Unit (EKU) license and Receiving and processing computers respectively Opportunities of the reception station Real-time environmental data is hardly available in Ethiopia. Nevertheless, the country had experienced various natural (such as drought, flood, landslide and most recently volcanic ash overcast) and manmade (such as human induced forest fires) disasters. These disasters had become more frequent and catastrophic with an increase in population and climate change effects. Thus the use of real or near real-time information is an indispensable tool to mitigate the problem. In this regard the GEONETCast is a highly relevant alternative to collect information for environmental monitoring and provides meaningful information to assess flood, drought and agricultural conditions, all of which are currently major issues in Ethiopia. The various sources of satellite images and processed products available through low-cost satellite image reception station established at BDU-IoT are listed below: Meteosat Second Generation (MSG): Although MSG has a number of communications missions its priority mission is Earth imaging. This is achieved through two specialized instruments; the primary instrument is the Spinning Enhanced Visible and Infrared Imager (SEVIRI), which has the capability to observe the Earth in 12 spectral channels at 15-minute temporal resolution day and night (EUMETSAT 2005). Table-2 shows detail description of the MSG channels. MSG has a wide field of view encompassing not only Africa but also Europe and the Middle East. Table 2: MSG channels available through the reception station every 15 minutes Channel Spatial Resolution (km) Primary Objective Ch01 (VIS0.6) 3 Surface, clouds, wind fields Ch02 (VIS0.8) 3 Surface, clouds, wind fields Ch03 (NIR1.6) 3 Surface, cloud phase Ch04 (IR3.9) 3 Surface, clouds, wind fields Ch05 (WV6.2) 3 Water vapor, high level Ch06 (WV7.3) 3 Water vapor, atmospheric instability Ch07 (IR8.7) 3 Surface, clouds, atmospheric instability Ch08 (IR9.7) 3 Ozone Ch09 (IR10.8) 3 Surface, clouds, wind fields, Ch10 (IR10.8) 3 Surface, clouds, atmospheric instability Ch11 (IR13.4) 3 Cirrus cloud height, atmospheric Broadband Ch12 (HRV) 1 Surface, clouds 4

5 Satellite Application Facilities (SAFs): The SAF network complements the production of standard meteorological products derived centrally in Darmstadt and also distributes user software packages. The overall objective is to provide high-quality products and services for improved applications (EUMETSAT 2005). Table 3 shows various SAF products with their spatial and temporal resolution. Table 3: List of products available from SAF SAF product Temporal Resolution (minute) Spatial Resolution (km) Albedo 60 3 Down-welling Surface Short-wave Radiation Flux (DSSF) Down-welling Surface Long-wave Radiation Flux (DSLF) Land Surface Temperature (LST) 15 3 Fraction of Vegetation Cover (FVC) 60 3 Leaf Area Index (LAI) 60 3 Evapotranspiration (ET) 30 3 Meteorological Product Extraction Facility (MPEF): The MPEF is a part of the MSG Ground Segment; its primary function is the generation of Meteorological Products from the Level 1.5 image data supplied by the Image Processing Facility (IMPF) (EUMETSAT, 2008). Table-4 shows the various products of MPEF with their spatial and temporal resolutions. Table-4: List of products available through MPEF MPEF products Temporal Resolution (minutes) Spatial Resolution (km) Atmospheric Motion Vectors (AMV) 60 Vector file Cloud Analysis Image (CLAI) Cloud Mask (CLM) 15 3 Cloud Top Height (CTH) 60 9 Active Fire Monitoring (FIR) 15 Vector file Global Instability Index (GII) 15 Vector file Multi-Sensor Precipitation Estimate (MPE) 15 3 Clear Sky Radiance (CSR) Tropospheric Humidity (TH) Total Ozone (TOZ) VGT4Africa: The VEGETATION project was developed to provide a land monitoring capacity. This mission is led by France, Belgium, Sweden and Italy. VGT4AFRICA distributes vegetation data to Africa through EUMETCast. Table-5 shows list of products available from VGT4Africa. Where products are derived from the vegetation instrument onboard of SPOT satellites and delivered at a 10 day s interval (Fred B. et al 2006). 5

6 Table 5: list of products available from VGT4Afria VGT4Afric products Temporal Resolution (days) Spatial Resolution (km) Normalized Difference Vegetation Index (NDVI) 10 1 Albedo(ALBQ) 10 1 Dry Matter Productivity (DMP) 10 1 Fraction of surface covered by vegetation (FCOVER) 10 1 Leaf Area Index (LAI) 10 1 Normalized Difference Water Index (NDWI) 10 1 Vegetation Productivity Index (VPI) 10 1 Phenology (PHENOKS) 10 1 Small Water Bodies (SWB) Methodology In determining the spatial and temporal relationship between vegetation density and rainfall the VGT4Africa decadal NDVI products for the year 2005 were used. The decadal NDVI map is aggregated to a monthly NDVI map using ILWIS 1. The daily rainfall data from Bahir Dar, Gondar, Dangla, Addis Zemen, Enfranze and Debre Tabor meteorological stations for the year 2005 are also used. The daily rainfall data is aggregated to monthly rainfall and interpolated to an aerial average using Thiessen polygon method. The spatial and temporal relationship of monthly NDVI and rainfall for the Lake Tana Basin is drawn from these two raster s. NDVI calculations are based on the principle that actively growing green plants strongly absorb radiation in the visible region of the spectrum while strongly reflecting radiation in the near infrared region of the spectrum (Larry Ryan 1997). NDVI pixel by pixel can be calculated using Equation 1 shown below: NDVI= Equation 1 Where: NDVI: Normalized Vegetation Index NIR: Near infrared channel VIS: Visible part of the electromagnetic spectrum This formula yields a value that ranges from -1 to +1; the two extreme values indicate water body and rainforest respectively. It was also tried to explain the temporal relationship between LST and ET over the Lake Tana Basin using image products archived from SAF. Images of March 15, 2011 are retrieved at an hour interval through the ground reception station. The areal average values of LST and ET are masked for Lake Tana basin and correlations of the parameters are drawn. LST is an operational product of the Land Surface Analysis Satellite Application Facility (LSA- SAF). According to Land SAF (2006) LST is defined as the radiative skin temperature of the land surface. LST is estimated by the Generalized Split-Window (GSW) algorithm, which is a semiempirical algorithm that allows the estimation of LST from top-of-atmosphere brightness temperatures of two adjacent cloud free MSG thermal infrared windows of IR10.8 and IR12.0 channels within the atmospheric window of the spectrum (Trigo S. 2009). 1 ILWIS (Integrated Land and Water Information System) is an open source geo-information tool, Developed by ITC, the Netherlands 6

7 ET accounts for the flux of water evaporated at the Earth-atmosphere interface (from soil, water bodies and interception) and transpired by vegetation through stomata in its leaves as a consequence of photosynthetic processes RMI Team (2008). ET is estimated by a physical model of energy exchange between the surface (soil and canopy) and the atmosphere in mm/hr. The model is driven by input data derived from MSG (A. Arboleda 2004). 3. Result & discussion The monthly areal rainfall of Lake Tana Basin is estimated by Thiessen polygon using data from six stations (Figure-3) Thiessen polygon map of the L. The weights for the stations are shown on Table-6. Aggregated monthly areal rainfall shows a maximum and minimum rainfall of mm and zero in July and December respectively (Table-7). Figure- 3: Thiessen polygon map of the basin Table-6: Weights of rainfall stations on the Lake Tana Basin Station Weight Bahir Dar 0.27 Dangla 0.20 Debre Tabor 0.14 Addis Zemen 0.06 Enfranze 0.16 Gondar 0.18 Table-7: Monthly areal rainfall of Lake Tana Basin for year 2005 Month Rainfall (mm) Jan 0.96 Feb 5.48 Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0.00 The result of areal average NDVI shows a maximum value on month September 0.65 and minimum of 0.23 on April and June (see Table-8 Average monthly areal NDVI value of Lake Tana Basin for year 2005) 7

8 Zegi town Figure-4: Monthly NDVI map aggregated from a decadal data of VGT4Africa for the Lake Tana Basin, year Table-8: Average monthly areal NDVI value of Lake Tana Basin for year 2005 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average NDVI For year 2005 the main rainy season is from June through September which contributes more than 85% of the annual rainfall. The vegetation density reaches peak in growing season from August to November see Figure-5. The correlation of areal monthly NDVI and rainfall over the Lake Tana Basin for year 2005 is very poor aroung 0.1, the analysis showed that for the study period NDVI responded slowely to preciptation by almost two month lag time. The forested area around Zegi Town in the western part of the lake marked with circle in Figure-4 has a consistant high NDVI value throughout the study period and has a very poor with the aerial montly rainfall. 8

9 NDVI NDVI Rainfall Jan Mar May Jul Sep Nov Month Figure 5: Relation between NDVI and Rainfall for year 2005 in the Lake Tana Basin Hourly LST and ET archived from the LSA-SAF for March 15, 2010 through the reception station was analyzed by the ILWIS software (see Figure-6 showing LST and ET map of Lake Tana Basin). The analysis shows that ET and LST are maximum at 9:00 UTC and at 11:00 UTC respectively which indicate a lag time of approximately two hours see Figure-6, those two parameters for the study period have a strong correlation approximately r 2 of Rainfall (mm) Radiative skin temperature of the ground surface LST Evapotranspiration ET Figure-6: LST and ET map of Lake Tana Basin 9

10 LST o C LST oc ET mm/hr Hour (UTC) Figure-6: Relation between LST and ET in the Lake Tana Basin ET mm/hr 4. Conclusion In this study we have demonstrated the relationships between NDVI and rainfall and also LST and ET using images archived from a low cost satellite image reception system established at Bahir Dar University, Institute of Technology. The availability of the reception system had made possible the collection of time series data s relevant for environmental, hydrological and meteorological monitoring which would have been impossible through downloading from public domains at current internet connection speed. This archived image data can be utilized for further researches so as to get a better insight in the changing conditions of the environment and to assist the policy making process. The study found that correlation of areal average monthly NDVI and rainfall across Lake Tana Basin is weak for the period. As per the results the NDVI response lags by two months to the rainfall peak. The vegetation density peaks in September where as rainfall peaks in July. While more vegetal activity is anticipated during the rainy season a lag in the peak of the NDVI may be explained through the unavailability of the moisture for plant intake as the soil storage is taking some time to fillup. More over, while NDVI retains certain favorable ratioing properties that reduce noise and uncertainty associated with the sensor instrument and external sources of noise, there are certain disadvantages with it, including nonlinearity, scaling problems and sensitivity to exposed soil backgrounds with sparse vegetation (Justice et. al., 1998) at the beginning of the growing period. Further refinement in the method used may yield in a better explanation of the rainfall vegetation phenology inter-relationship. The analsis shows a strong correlation between LST and ET with a two hour lag time. 10

11 References Arboleda, N. Ghilain, F. Gellens-Meulenberghs (2004)THE LSA-SAF EVAPOTRANSPIRATION PRODUCT: FIRST RESULTS WITH MSG Royal Meteorological Institute of Belgium, Avenue Circulaire 3, B-1180 Brussels, Belgium Ben Maathuis, Chris Mannaerts and Bas Retsios. (2009). The ITC GEONETCast-toolbox approach for less developed countries. International Institute for Geo Information Science and Earth Observation (ITC) ISPRS 2008: TC 7 / WG 7.7 Innovative methodologies for less developed countries EUMETSAT (2005), MSG Meteosat Second Generation in Orbit - In Use, EUMETSAT Am Kavalleriesand 31 D Darmstadt Germany. ISBN MSG.02 Version 1 EUMETSAT (2008), MSG Meteorological Products Extraction Facility Algorithm Specification Document. EUMETSAT Am Kavalleriesand 31, D Darmstadt, Germany. v4, 16 May 2008 Fred B., Etienne B., Patrice B., Geert B., Lieven B., Bruno C., and J. (2006) VGT4Africa user manual, First edition. VGT4AFRIC. Joint Research Centre Ispra (VA) Italy. European Communities Justice, C. O., The Moderate Resolution Imaging Spectroradiometer (MODIS): Land Remote Sensing For Global Change Research, IEEE Transactions On Geoscience And Remote Sensing, 36, 4, Kebede, S., Y. Travi, et al. (2006). "Water balance of Lake Tana and its sensitivity to fluctuations in rainfall, Blue Nile basin, Ethiopia." Journal of Hydrology 316(1-4): Larry Ryan (1997) Creating a Normalized Difference Vegetation Index (NDVI) image Using MultiSpec, 161 Morse Hall OPAL/EOS University of New Hampshire Durham, The GLOBE Program Land SAF (2006) Product User Manual PUM LST LAND SURFACE TEMPERATURE Ref. SAF/LAND/IM/ PUM_LST/1.4 Issue: Version 1.4, Date: 18 September 2006 RMI Team (2008) The EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF, Evapotranspiration (ET) Product User Manual PRODUCTS: LSA-16 (MET), LSA-17 (DMET) Trigo, S. Freitas, J. Bioucas-Dias, C. Barroso, I. Monteiro, P. Viterbo (2009) Algorithm Theoretical Basis Document for Land Surface Temperature (LST) PRODUCTS: LSA-4 (MLST) SAF/LAND/IM/ATBD_LST/1.0 Issue 1.0 Last Change: 19/06/