Remote sensing and geoinformation processing in the assessment and monitoring of land degradation and desertification, Trier, Germany, 2005 Session 2: Remote sensing based monitoring of land degradation and desertification page 119 Remote sensing and geoinformation processing in the assessment and monitoring of land degradation and desertification, Trier, Germany, 2005 Monitoring of land degradation and desertification dynamics using coarse-scale satellite data C.J. Tuckera, A. Anyambaa and P. Gonzalesb a Code 614.0, NASA/Goddard Space Flight Center, Greenbelt, Maryland 20771 USA b The Nature Conservancy, 4245 North Fairfax Drive, Arlington, VA 22203-1606 USA ABSTRACT The analyses of coarse-resolution remote sensing data at scales of 250 m to 4 km provides an excellent tool for studying arid and semi-arid areas, their primary productivity, and effects of climate upon vegetation in these dry zones. Starting in 1981 with the launch of NOAA-7, 4-km data from the advanced very high resolution radiometer have been available from several satellites in the NOAA-series of polar orbiting meteorological satellites for almost 25 years. These 4-km data have been complimented by 1-km data from the same instruments in regional areas, where they were received and maintained. SeaWiFS 4-km data have been available globally since late 1997 and SPOT Vegetation data have been available globally since May 1998. Data from the MODIS instruments have been available globally at 500 m since 2000 and 2002 from the Terra and Aqua platforms, respectively, and have been available regionally in many areas at 250 m. The uses and limitations of these data will be discussed and a new dry season application of these data from highly-calibrated instruments like SeaWiFS will also be presented. In addition, an example of the use of ~1 m satellite and aerial photography data for counting trees and bushes will be presented as a compliment to course-resolution satellite data. 1 INTRODUCTION A consistent, continuous, and long record of remote sensing data is crucial for desertification studies. Arid and semi-arid areas, where most desertification is thought to occur, have highly variable climatic conditions, and thus data from only a few years are not informative. However, coarse-resolution data over several years and at frequent intervals within each year are necessary to gain a representation of climatic variation in these locales. Simultaneously, ~ 1 m high spatial resolution data are very important for counting trees and bushes, as this information is also extremely important in desertification studies. This paper deals primarily with coarse-resolution time series data but will also touch upon hyper-spatial resolution data for counting trees and bushes. We restrict our paper to the south side of the Sahara Desert but acknowledge there are many other areas of our planet where climatic and/or human degradation influences are of topical concern. Although significant improvements have been made with new, global, land vegetation-sensing instruments (table 1), the existing July 1981 to the present 4-km archive of data from the advanced very high resolution radiometer (AVHRR) instrument is an invaluable and irreplaceable archive of historical land surface information. This archive of global 4-km AVHRR data results from five different AVHRR instruments on five different NOAA polar-orbiting meteorological satellites [1, 2]. The 1981-2005 record of AVHRR data has been processed in a consistent and quantitatively comparable manner [3] with the new generation of sensors to bring the global land surface satellite climate data record an additional ~20 years to compliment the 5+ years of data presently in hand from the improved sensors listed in table 1. New improved coarse-resolution global land surface satellite data are available from SeaWiFS (October 1997 – present), SPOT-4’s Vegetation Sensor (May 1998 – present), and NASA’s moderate resolution imaging spectrometers (MODIS) on the Terra and Aqua platforms (January 2000 – present and December 2002 - present, respectively) (table 1). 2 STUDY AREA To illustrate the use of monitoring land degradation and desertification dynamics using coarse-scale satellite data, we will use the southern boundary of the Sahara and the adjacent semi-arid transition zone known as the “Sahel”. “Sahel”, a word apparently meaning “shoreline” in Arabic [4], is a climatic and vegetation transition zone between the hyper arid Sahara and the more humid savannas to the south. From the Sahara to the south there is an unusual north-south precipitation gradient of ~1 mm yr-1 km-1, extending for over 6,000 km from the Atlantic Ocean to the Red Sea. Associated with this unusual precipitation gradient is an almost imperceptible gradient of vegetation, as page 120 Remote sensing and geoinformation processing in the assessment and monitoring of land degradation and desertification, Trier, Germany, 2005 Table 1. Global coarse-resolution satellite spectral vegetation index data sets. Instrument Dates of Spatial Spectral Global Data References, comments Coverage Resolution Bands Volume (nadir) (gb/day) NOAA [1, 2] AVHRR NOAA-7 07/1981-02/1985 4-km 5 0.6 NOAA-9 02/1985-09/1988 4-km 5 0.6 NOAA-11 09/1988-9/1994 4-km 5 0.6 NOAA-9-d 9/1994-01/1995 4-km 5 0.6 Descending node 09:00 data NOAA-14 01/1995-11/2000 4-km 5/6 0.6 NOAA-16 11/2000-12/2003 4-km 5/6 0.6 NOAA-17 5/2002-now 4-km 5/6 0.6 NOAA-18 7/2005-now 4-km 5/6 0.6 SeaWiFS 9/1997-present 4-km 8 0.4 [5] SPOT-4 05/1998-present 1-km 4 5 [6] Vegetation MODIS 01/2000-present 250-1000 m 32 70 [7] one moves up or down the gradient, from the Sahara to tropical forests and back [4, 8, 9]. We use the following generalized definitions after Le Houreou (1980) [4] and others: Sahara Desert: <100 mm/yr Saharan-Sahelian Transition: 100-200 mm/yr Sahel Zone: 200-400 mm/yr Sahelian-Sudanian Transition: 400-600 mm/yr Sudan Zone: 600-800 mm/yr Since the 1970s international interest has frequently focused on the south side of the Sahara Desert, upon the Sahel Zone, the semi-arid grassland or steppe area immediately to the south of the Sahara. A prevalent suggestion in the 1970s and 1980s was the continuous expansion of the Sahara Desert to the south into the semi-arid Sahelian Zone, via the process of “desertification” or “desert creep”. Desertification has been defined as the process by which more productive arid and semi-arid lands become less productive or more "desert like" (reviewed in [10, 11]). This can result from many causes, but generally is associated with over-use by man that then results in reinforcing climatic tendencies toward dryer climates. The occurrence of a period of successive wet years (1950 to 1960), followed by a period of successive dry years (1969 to 1997), has also contributed to the controversy in the location of the southern Sahara boundary [12]. Lamprey [13] estimated the southern Saharan boundary had shifted southward in western Sudan 90 to 100 km between 1958 (a wet year) and 1975 (a dry year). Hellden [14], working in the same western Sudan area, found no evidence to support a southern Saharan expansion from 1958 to the early 1980s. Disagreement on the location of the southern Saharan boundary is not new--it has occurred since the early part of the 20th century [15, 16, 17, 18]. We expand upon previous work [19] and extend to 2004 a satellite-derived vegetation index to map inter-annual changes in vegetative cover and, by inference, rainfall, along the Saharan-Sahelian boundary from the Atlantic Ocean to the Red Sea. Our use of satellite data for mapping annual variations through corresponding changes in the density of green vegetation cover is based on precipitation being the principal determinant of primary production below ~800 mm/yr in the Sahel and Sudan Zones of Africa [20, 21, 22, 23]. page 121 Remote sensing and geoinformation processing in the assessment and monitoring of land degradation and desertification, Trier, Germany, 2005 3 REMOTE SENSING INDICES We will discuss the use of 3 very different remote sensing indices for studying arid and semi-arid lands: surface reflectance data from the dry season, after the work of Charney et al. [25]; spectral vegetation indices to define arid boundaries by their less arid adjacent semi-arid zones (after [19]); and Ikonos and Quickbird hyper spatial ~ 1 m data to count trees and bushes to infer aridity and climatic effects in arid and semi-arid areas as these are expressed in tree and bush cover. 3.1 Dry Season Surface Reflectance Charney et al. [25] proposed a “feedback” situation, where degradation of arid and semi-arid lands resulted in a reduced vegetation cover and a higher surface reflectance or albedo. The higher the reflectance, the lower the amount of absorbed energy, the lower the temperature of the surface, a lower degree of convection, and less rainfall, thus “locking in” drier conditions. Although the existence of this positive feedback remains to be seen, the tool of using satellite data to infer land degradation by the means of albedo or surface reflectance variations can be a useful tool in arid and semi-arid land research and desertification studies. We have been investigating the use of SeaWiFS land data for a variety of applications, including studying arid and semi-arid land degradation. One of the features of SeaWiFS data is a high degree of calibration accuracy through time because this is extremely important for ocean primary productivity studies. To achieve a high degree of sensor calibration, the SeaWiFS platform “flips” and images the lunar disk every full moon.