Abstract
The Aral Sea region is a rapidly transforming landscape due to the continuous desiccation process. This study describes the vegetation and landscape dynamics in the lower Amu Darya Delta and adjacent parts of the dried sea bottom using MODIS (Moderate Resolution Imaging Spectroradiometer) surface reflectance data and EVI time series for the years 2001–2011. The potential of MODIS time series for monitoring landscape and vegetation dynamics of the dried sea bottom adjacent to the lower Amu Darya Delta was evaluated concerning data availability and spatial and temporal resolution. Two time series with different quality considerations were generated to subsequently characterize the yearly changes in the dried part of the sea bed, a simple layerstack (LS) of observations and quality-filtered and smoothed time series using a double logistic function (DL). The EVI (Enhanced Vegetation Index) values show a small dynamic inter- and intra-annual range. The majority of the EVI values fluctuate between −0.2 and +0.1, which indicates generally low vegetation dynamics in the desiccated areas. Looking at the inter-annual behavior of the LS/DL time series plots, the noise of the data and data fluctuations seem to become less for areas which have been dry for a longer period. A regional differentiation of the landscape dynamics between the Eastern and the Western basin of the southern Aral Sea could be observed. The observation points for the Western basin show a more stable behavior of the EVI values in comparison to the samples on the Eastern basin as seasonal or inter-annual flooding is less frequent. A typical pattern as a result of clear vegetation dynamics could not be observed in the EVI, LS and DL time series plots.
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References
Breckle SW, Wucherer W (2011) Has the Aral Sea a future. In: Lozán JL, Grassl H, Hupfer P, Menzel L et al (Hrsg) Warnsignal Klima: Genug Wasser fuer alle? Wissenschaftliche Auswertungen in Kooperation mit Geo, 3.Auflage (2011), pp 131–135 (in German)
Breckle SW, Wucherer W, Dimeyeva LA, Ogar NP (eds) (2012) Aralkum – a man-made desert. The desiccated floor of the Aral Sea (Central Asia), vol 218, Ecological studies. Springer, Berlin/Heidelberg. doi:10.1007/978-3-642-21117-16
Chatfield C (2004) The analysis of time series: an introduction. Chapman & Hall, London
Colditz RR, Conrad C, Wehrmann T, Schmidt M et al (2006) Generation and assessment of MODIS time series using quality information. In IEEE international conference on geoscience and remote sensing 2006, IGARSS 2006, July 31st–August 4th 2006, Denver, pp 779–782
Colditz RR, Conrad C, Wehrmann T, Schmidt M et al (2008a) TiSeG – a flexible software tool for time series generation of MODIS data utilizing the quality assessment science data set. IEEE Trans Geosci Remote Sens 46(10):3296–3308
Colditz RR, Conrad C, Wehrmann T, Schmidt M et al (2008b) Analysis of the quality of collection 4 and 5 vegetation index time series from MODIS. In: Stein A, Shi W, Bijker W (eds) Quality aspects in spatial data mining. CRC Press, Boca Raton, pp 161–174 (Also published in ISPRS Spatial Data Quality Symposium, June 13th–15th 2007, Enschede, The Netherlands)
Colditz RR, Conrad C, Dech S (2011) Stepwise automated generation of time series using ranked data quality indicators. IEEE J Sel Top Appl Earth Observ Remote Sens 4(2):272–280
Conrad C, Dech SW, Hafeez M, Lamers J, Martius C, Strunz G (2007) Mapping and assessing water use in a Central Asian irrigation system by utilizing MODIS remote sensing products. Irrig Drain Syst 21:197–218. doi:10.1007/s10795-007-9029-z (Dordrecht: Springer Science + Business Media B.V)
Didan K, Huete AR (2006) MODIS vegetation index product series collection 5 change summary. The University of Arizona, Tucson, June 29th
Gao F, Morisette JT, Wolfe RE, Ederer G et al (2008) An algorithm to produce temporally and spatially continuous MODIS-LAI time series. IEEE Geosci Remote Sens Lett 5(1):60–64
Ginzburg AI, Kostianoy AG, Sheremet NA, Kravtsova VI (2010). Satellite monitoring of the Aral Sea region. In: The Aral Sea Envioronment. Series: The handbook of Environmental Chemistry, Series ISSN 1867-979X, DOI 10.1007/698_2009_15, ISBN: 978-3-540-88276-3, pp. 147–179
Glazovskiy NF (1990) The Aral crisis: causative factors and means of solution. Nauka, Moscow (In Russian)
Hansen MC, DeFries RS, Townshend JRG, Sohlberg RA (2000) Global land cover classification at 1 km spatial resolution using a classification tree approach. Int J Remote Sens 21(6–7):1331–1364
Holben BN (1986) Characterization of maximum value composites from temporal AVHRR data. Int J Remote Sens 7(11):1417–1434
Huete AR, Didan K, Miura T, Rodriguez EP et al (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83(1–2):195–213
Jensen RR (2007) Remote sensing of the environment. Prentice Hall, Upper Saddle River
Jiang Z, Huete AR, Didan K, Miura T (2008) Development of a two-band enhanced vegetation index without a blue band. Remote Sens Environ 112:3833–3845
Jönsson P, Eklundh L (2004) TIMESAT – a program for analyzing time-series of satellite sensor data. Comput Geosci 30:833–845
Justice CO, Townshend JRG, Vermote EF, Masuoka E et al (2002) An overview of MODIS land data processing and product status. Remote Sens Environ 83(1–2):3–15
Kidwell KB (1991) NOAA polar orbiter data users guide. National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, Washington, DC
Loew F, Navratil P, Bubenzer O et al (2012) Landscape dynamics in the Southern Aralkum. Using MODIS time series for land cover change analysis. In: Breckle SW (ed) Aralkum a man made desert: the desiccated floor of the Aral Sea (Central Asia), Ecological studies 218. Springer, Berlin/Heidelberg. doi:10.1007/978-3-642-21117-16
Lunetta RS, Knight JF, Ediriwickrema J, Lyon J et al (2006) Land-cover change detection using multi-temporal MODIS NDVI data. Remote Sens Environ 105(2):142–154
Micklin P (2004) The Aral Sea crisis. In: Nihoul CJ, Zavialov P, Micklin P (eds) Dying and dead seas: climatic vs. anthropic causes, NATO science series IV: Earth and environmental sciences, 36th edn. Kluwer, Boston, pp 99–125
Micklin P (2007) The Aral Sea disaster. Annu Rev Earth Planet Sci 35:47–72, Palo Alto: Annual Reviews
Myneni RB, Nemani RR, Running SW (1997) Estimation of global leaf area index and absorbed par using radiative transfer models. IEEE Trans Geosci Remote Sens 35(6):1380–1393
Neteler M (2005) Time series processing of MODIS satellite data for landscape epidemiological applications. Int J Geoinf 1(1):133–138
Novikova N (1996a) The Tugai of the Aral Sea region is dying: can it be restored? Russ Conserv News 6:22–23
Novikova N (1996b) Current changes in the vegetation of the Amu Darya Delta. In: Micklin P, Williams D (eds) The Aral Sea Basin. In Proceedings of the NATO advanced research workshop, Tashkent, Uzbekistan 2–5 May, NATO ASI Series, 2. Environment, vol 12. Springer, New York, pp 69–78
Novikova N (1997) Principles of preserving the botanical diversity of the deltaic plains of the Turan. Dissertation for the degree of Doctor of Geographical Sciences. Moscow (in Russian)
Ptichnikov A (ed) (2002) Bulletin no 3, NATO science for peace project 974101: sustainable development of ecology, land and water use through implementation of a GIS and remote sensing centre in Karakalpakstan (in Russian and English)
Ressl RA (1996) Monitoring of recent area and volume changes of the Aral Sea and development of an optimized land and water use model for the Amu Darya Delta. In: Micklin P, Williams D (eds) The Aral Sea Basin. In Proceedings of the NATO advanced research workshop, Tashkent, Uzbekistan 2–5 May, NATO ASI Series, 2. Environment, vol 12. Springer, New York, pp 149–160
Ressl RA, Dech SW, Ptichnikov A, Novikova NM, Micklin P (1998) Aufbau eines fernerkundungsbasierten geographischen informationssystems zur optimierung der landnutzung im Amu Darya delta. (Development of a remote sensing based geographical information system for optimizing landuse in the Amu Darya delta). GIS Geo Inf Syst 11:25–33 (in German)
Roerink GJ, Menenti M, Verhoef W (2000) Reconstructing cloud free NDVI composites using fourier analysis of time series. Int J Remote Sens 21(9):1911–1917
Roy DP (2000) Investigation of the maximum Normalized Difference Vegetation Index (NDVI) and the maximum surface temperature (Ts) AVHRR compositing procedure for the extraction of NDVI and Ts over forests. Int J Remote Sens 18(11):2383–2401
Roy DP, Borak JS, Devadiga S, Wolfe RE et al (2002) The MODIS land product quality assessment approach. Remote Sens Environ 83(1–2):62–76
Solano R, Didan K, Jacobson A, Huete A (2010) MODIS vegetation index user’s guide (MOD13 series). Version 2.0, (Collection 5)
Thenkabail PS, Schull M, Turral H (2005) Ganges and indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data. Remote Sens Environ 95:317–341
Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8(2):127–150
Tucker CJ, Pinzon JE, Brown ME, Slayback DA et al (2005) An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int J Remote Sens 26(20):4485–4498
Van der Meer F, Bakker W, Scholte K, Skidmore A et al (2000) Vegetation indices, above ground biomass estimates and the red edge from MERIS. Int Arch Photogramm Remote Sens 33(Part B7):1580–1586
Vermote EF, el Saleous NZ, Justice CO (2002) Atmospheric correction of MODIS data in the visible to middle infrared: first results. Remote Sens Environ 83(1–2):97–111
Yuan H, Dai Y, Xiao Z, Ji D et al (2011) Reprocessing the MODIS leaf area index products for land surface and climate modeling. Remote Sens Environ 115:1171–1187
Acknowledgements
We would like to thank F. Loew and C. Conrad, University of Wuerzburg, Department of Geography for the provision of in-situ data for the year 2008 as well as a satellite-based classification for the Amu Darya Delta.
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Ressl, R.A., Colditz, R.R. (2014). Time Series Analysis of Satellite Remote Sensing Data for Monitoring Vegetation and Landscape Dynamics of the Dried Sea Bottom Adjacent to the Lower Amu Darya Delta. In: Micklin, P., Aladin, N., Plotnikov, I. (eds) The Aral Sea. Springer Earth System Sciences, vol 10178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02356-9_10
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