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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Front Earth Sci    0, Vol. Issue () : 196-205    https://doi.org/10.1007/s11707-012-0313-3
RESEARCH ARTICLE
Regional fire monitoring and characterization using global NASA MODIS fire products in dry lands of Central Asia
Tatiana V. LOBODA(), Louis GIGLIO, Luigi BOSCHETTI, Christopher O. JUSTICE
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
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Abstract

Central Asian dry lands are grass- and desert shrub-dominated ecosystems stretching across Northern Eurasia. This region supports a population of more than 100 million which continues to grow at an average rate of 1.5% annually. Dry steppes are the primary grain and cattle growing zone within Central Asia. Degradation of this ecosystem through burning and overgrazing directly impacts economic growth and food supply in the region. Fire is a recurrent disturbance agent in dry lands contributing to soil erosion and air pollution. Here we provide an overview of inter-annual and seasonal fire dynamics in Central Asia obtained from remotely sensed data. We evaluate the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) global fire products within Central Asian dry lands and use these products to characterize fire occurrence between 2001 and 2009. The results show that on average ~15 million ha of land burns annually across Central Asia with the majority of the area burned in August and September in grasslands. Fire is used as a common crop residue management practice across the region. Nearly 89% of all burning occurs in Kazakhstan, where 5% and 3% of croplands and grasslands, respectively, are burned annually.

Keywords Moderate Resolution Imaging Spectroradiometer (MODIS)      fire      Central Asia      dry lands     
Corresponding Author(s): LOBODA Tatiana V.,Email:loboda@umd.edu   
Issue Date: 05 June 2012
 Cite this article:   
Tatiana V. LOBODA,Louis GIGLIO,Luigi BOSCHETTI, et al. Regional fire monitoring and characterization using global NASA MODIS fire products in dry lands of Central Asia[J]. Front Earth Sci, 0, (): 196-205.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-012-0313-3
https://academic.hep.com.cn/fesci/EN/Y0/V/I/196
Fig.1  Location, extent and land covers of Central Asian dry lands mapped by the MODIS land cover product (MCD12Q1). The exact extent of the study area is outlined in black
Fig.2  Land cover distribution (aggregated classes) in Central Asian dry lands mapped by the MODIS land cover product (MCD12Q1)
MCD45A1
Path RowPre datePost dateClassComm errOmiss errOverall Acc/%KappaR2NSlope
124 0276/27/20018/30/2001burned16.9357.9999.530.560.58290.49
unburned0.410.06
126 0264/12/20035/14/2003burned3.2359.6390.330.530.502990.43
unburned10.130.25
130 026 130 0277/26/20029/12/2002burned46.1438.0199.710.570.81670.99
unburned0.120.17
132 0267/24/20029/10/2002burned25.215498.970.560.761390.68
unburned0.810.23
152 0244/15/20029/22/2002burned15.7920.4191.760.770.928070.95
unburned6.114.54
165 0266/13/20027/31/2002burned23.5659.6595.800.510.633190.49
unburned3.590.77
DB
Path RowPre dateEnd dateClassComm errOmiss errOverall Acc/%KappaR2NSlope
124 0276/27/20018/30/2001burned12.9377.6999.430.350.46290.25
unburned0.550.02
126 0264/12/20035/14/2003burned2.2733.6894.410.760.812990.71
unburned5.990.29
130 026 130 0277/26/20029/12/2002burned22.0238.8399.820.680.92670.90
unburned0.120.05
132 0267/24/20029/10/2002burnedMissing data
unburned
152 0244/15/20029/22/2002burned15.0522.0391.630.760.947960.96
unburned6.554.21
165 0266/13/20027/31/2002burned21.4628.797.180.730.892980.93
unburned1.771.21
Tab.1  Landsat-based validation sample scenes (Path Row, Pre-burn Date, Post-burn Date) and validation results for the MODIS burned area products MCD45A1 and DB including a confusion matrix assessment (Commission error, Omission error, Overall Accuracy, Kappa) and regression of burned areas within 5km grid cells (, , and Slope)
Fig.3  Annual amount of area burned in Central Asian dry lands between 2001 and 2009 estimated by the MODIS burned area product (MCD45A1)
Fig.4  Mean monthly fire occurrence as shown by (a) area burned from (MCD45A1), (b) number of fire detections (from MOD/MYD14A1)
Fig.5  Fire occurrence (number of fire detections MOD/MYD14A1) and area burned (MCD45A1) as a function of land cover type in Central Asian dry lands
Fig.6  Mean monthly proportions of burned area by land cover types
Class200120022003200420052006200720082009
Bare0.010.020.010.020.010.010.040.010.02
Crop and crop mosaic1.957.334.236.003.254.654.716.622.41
Forest0.210.650.390.270.281.191.441.081.85
Grass1.465.182.372.642.513.211.882.241.06
Shrub0.160.550.340.400.240.320.410.270.22
Urban0.060.130.050.140.030.040.030.020.14
Water0.400.270.250.270.180.430.210.540.41
Wetlands2.041.360.232.270.792.380.231.700.68
All area0.752.691.311.551.281.691.191.430.67
Tab.2  Annual amount of area burned within land cover types relative to the total amount of the land cover available in the region between 2001 and 2009 (unit:%)
Fig.7  Contributions of Central Asian countries to the total amount of area burned in dry land ecosystems between 2001 and 2009 as shown by the MODIS burned area product (MCD45A1).
1 Batima P, Natsagdorj L, Gombluudev P, Erdenetsetseg B (2005) Observed climate change in Mongolia. Assessment of Impacts and Adaptations to Climate Change (AIACC) working paper 12 , www.aiaccproject.org, accessed April4, 2012
2 Boschetti L, Roy D, Barbosa P, Boca R, Justice C (2008). A MODIS assessment of the summer 2007 extent burned in Greece. Int J Remote Sens , 29(8): 2433-2436
doi: 10.1080/01431160701874561
3 Boschetti L, Roy D, Justice C, Giglio L (2012) Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product. International Journal of Wildland Fire (in press)
4 Cardoso M E, Nobre C A, Lapola D M, Oyama M D, Sampaio G (2008). Long-term potential for fires in estimates of the occurrence of savannas in the tropics. Glob Ecol Biogeogr , 17(2): 222-235
doi: 10.1111/j.1466-8238.2007.00356.x
5 Carroll M, Townshend J, DiMiceli C, Noojipady P, Sohlberg R (2009) A new global raster water mask at 250 Meter Resolution. International Journal of Digital Earth . 2(4): 291-308
6 Chibilyov A (2002) Steppe and forest-steppe. In: Shahgedanova M, ed. Physical Geography of Northern Eurasia . New York: Oxford University Press
7 Feng X M, Zhao Y S (2009) Grazing intensity monitoring in Northern China steppe: Integrating CENTURY model and MODIS data. Ecological Inidcators ,
doi: 10.1016/j.ecolind.2009.07.002.
8 Friedl M A, McIver D K, Hodges J C F, Zhang X Y, Muchoney D, Strahler A H, Woodcock C E, Gopal S, Schneider A, Cooper A, Baccini A, Gao F, Schaaf C (2002). Global land cover mapping from MODIS: algorithms and early results. Remote Sens Environ , 83(1-2): 287-302
doi: 10.1016/S0034-4257(02)00078-0
9 Geerken R, Batikha N, Celis D, Depauw E (2005). Differentiation of rangeland vegetation and assessment of its status: field investigations and MODIS and SPOT VEGETATION data analyses. Int J Remote Sens , 26(20): 4499-4526
doi: 10.1080/01431160500213425
10 Giglio L, Descloitres J, Justice C O, Kaufman Y J (2003). An enhanced contextual fire detection algorithm for MODIS. Remote Sens Environ , 87(2-3): 273-282
doi: 10.1016/S0034-4257(03)00184-6
11 Giglio L, Loboda T, Roy D P, Quayle B, Justice C O (2009). An active-fire based burned area mapping slgorithm for the MODIS sensor. Remote Sens Environ , 113(2): 408-420
doi: 10.1016/j.rse.2008.10.006
12 Giglio L, van der Werf G R, Randerson J T, Collatz G J, Kasibhatla P (2006). Global estimation of burned area using MODIS active fire observations. Atmos Chem Phys , 6(4): 957-974
doi: 10.5194/acp-6-957-2006
13 Hall D O, Ojima D S, Parton W J, Scurlock J M O (1995). Response of temperate and tropical grasslands to CO2 and climate change. J Biogeogr , 22(2/3): 537-547
doi: 10.2307/2845952
14 Justice C O, Vermote E, Townshend J R G, Defries R, Roy D P, Hall D K, Salomonson V V, Privette J L, Riggs G, Strahler A, Lucht W, Myneni R B, Knjazihhin Y, Running S W, Nemani R R, Wan Z, Huete A, van Leeuwen W, Wolfe R (1998). The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research. IEEE Trans Geosci Rem Sens , 36(4): 1228-1249
doi: 10.1109/36.701075
15 Kaufman YJ, Justice CO, Flynn LP, Kendall JD, Prins EM, Giglio L, Ward DE, Menzel WP, Setzer AW (1998) Potential global fire monitoring from EOSMODIS. Journal of Geophysical Research—Atmospheres , 103(D24): 32215-32238
16 Korontzi S, McCarty J, Loboda T, Kumar S, Justice C (2006). Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data. Global Biogeochem Cycles , 20(2): GB2021
doi: 10.1029/2005GB002529
17 Kruse F A, Lefkoff A B, Boardman J W, Heidebrecht K B, Shapiro A T, Barloon J P, Goetz A F H (1993). The spectral image processing system (SIPS)-Interactive visualization and analysis of imaging spectrometer data. Remote Sens Environ , 44(2-3): 145-163
doi: 10.1016/0034-4257(93)90013-N
18 Leptoukh G, Csiszar I, Romanov P, Shen S, Loboda T, Gerasimov I (2007). NASA NEESPI data and services center for satellite remote sensing information. Environ Res Lett , 2(4): 045009
doi: 10.1088/1748-9326/2/4/045009
19 Loboda T (2009). Modeling fire danger in data-poor regions: a case study from the Russian Far East. Int J Wildland Fire , 18(1): 19-35
doi: 10.1071/WF07094
20 McCarty J, Loboda T, Trigg S (2008). A hybrid approach to quantifying crop residue burning in the US based on burned area and active fire data. Appl Eng Agric , 24(4): 515-527
21 McCarty J L, Korontzi S, Justice C O, Loboda T (2009). The spatial and temporal distribution of crop residue burning in the contiguous United States. Sci Total Environ , 407(21): 5701-5712
doi: 10.1016/j.scitotenv.2009.07.009 pmid:19647857
22 National Bureau of Statistics of China (2008) China Statistical Yearbook 2008: Total Population and Birth Rate, Death Rate and Natural Growth Rate by Region (2007). http://www.stats.gov.cn/tjsj/ndsj/2008/indexeh.htm Accessed 05/02/2010.
23 Norton J, Glenn N, Germino M, Weber K, Seefeldt S (2009). Relative suitability of indices derived from Landsat ETM+ and SPOT 5 for detecting fire severity in sagebrush steppe. Int J Appl Earth Obs Geoinf , 11(5): 360-367
doi: 10.1016/j.jag.2009.06.005
24 Peel M C, Finlayson B L, McMahon T A (2007). Updated world map of the K?ppen–Geiger climate classification. Hydrol Earth Syst Sci , 11(5): 1633-1644
doi: 10.5194/hess-11-1633-2007
25 Randerson JT, van der Werf GR, Giglio L, Collatz GJ, Kasibhatla PS (2007) Global Fire Emissions Database, Version 2 (GFEDv2.1).
doi: 10.3334/ORNLDAAC/849
26 Roy D P, Boschetti L (2009). Southern Africa validation of the MODIS, L3JRC and GlobCarbon burned area products. IEEE Trans Geosci Rem Sens , 47(4): 1032-1044
doi: 10.1109/TGRS.2008.2009000
27 Roy D P, Boschetti L, Justice C O, Ju J (2008). The collection 5 MODIS burned area product-global evaluation by comparison with the MODIS active fire product. Remote Sens Environ , 112(9): 3690-3707
doi: 10.1016/j.rse.2008.05.013
28 Roy D P, Frost P G H, Justice C O, Landmann T, Le Roux J L, Gumbo K, Makungwa S, Dunham K, Du Toit R, Mhwandagara K, Zacarias A, Tacheba B, Dube O P, Pereira J M C, Mushove P, Morisette J T, Santhana Vannan S K, Davies D (2005). The Southern Africa Fire Network (SAFNet) regional burned-area product-validation protocol. Int J Remote Sens , 26(19): 4265-4292
doi: 10.1080/01431160500113096
29 Roy D R, Boschetti L, Trigg S (2006). Remote sensing of fire severity: assessing the performance of the normalized burn ratio. IEEE Transactions on Geoscience and Remote Sensing Letters , 3(1): 112-116
doi: 10.1109/LGRS.2005.858485
30 Scheintaub M R, Derner J D, Kelly E F, Knapp A K (2009). Response of the shortgrass steppe plant community to fire. J Arid Environ , 73(12): 1136-1143
doi: 10.1016/j.jaridenv.2009.05.011
31 Shen S, Leptoukh G, Loboda T, Csiszar I A, Romanov P, Gerasimmov I (2009) The NASA NEESPI data portal to support studies of climate and environmental changes in non-boreal Europe. In: Groisman P Y, Ivanov SV, eds. Regional Aspects of Climate-Terrestrial-Hydrologic Interactions in Non-Boreal Eastern Europe . Dordrecht: Springer
32 Song Y, Chang D, Liu B, Miao W, Zhu L, Zhang Y (2010). A new emission inventory for nonagricutrual open fires in Asia from 2000 to 2009. Environ Res Lett , 5(1): 014014
doi: 10.1088/1748-9326/5/1/014014
33 Streets D G, Yarber K F, Woo J H, Carmichael G R (2003). Biomass burning in Asia: annual and seasonal estimates and atmospheric emissions. Global Biogeochem Cycles , 17(4): 1099
doi: 10.1029/2003GB002040
34 US Department of Agriculture, Foreign Agricultural Service (1999). Crop calendars. http://www.fas.usda.gov/pecad/weather/Crop_calendar/crop_cal.pdf. Accessed 05/03/2010
35 US Department of State (2009) Background notes.<http://www.state.gov/r/pa/ei/bgn/index.htm#mostrecent>. Accessed 05/02/2010
36 Wolfe R, Masek J, Saleous N, Hall F (2004) LEDAPS: mapping North American disturbance from the Landsat record. Geoscience and Remote Sensing Symposium, IGARSS ’04 Proceedings. IEEE International .
doi: 10.1109/IGARSS.2004.1368929
37 Yan X, Ohara T, Akimoto H (2006). Bottom-up estimate of biomass burning in Mainland China. Atmos Environ , 40(27): 5262-5273
doi: 10.1016/j.atmosenv.2006.04.040
38 Yu F, Price K, Ellis J, Shi P (2003). Response of seasonal vegetation development to climatic variations in eastern central Asia. Remote Sens Environ , 87(1): 42-54
doi: 10.1016/S0034-4257(03)00144-5
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