Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (9): 1307-1328.doi: 10.1007/s11442-018-1527-4
• Orginal Article • Previous Articles Next Articles
Peng LI1,2(), Zhiming FENG1,2(
), Chiwei XIAO1,2, Khampheng BOUDMYXAY1,2, Yu LIU1
Received:
2017-06-07
Accepted:
2018-01-21
Online:
2018-09-25
Published:
2018-09-25
About author:
Author: Li Peng (1984-), PhD and Associate Professor, specialized in remote sensing of natural resources, land use and cover changes. E-mail:
Supported by:
Peng LI, Zhiming FENG, Chiwei XIAO, Khampheng BOUDMYXAY, Yu LIU. Detecting and mapping annual newly-burned plots (NBP) of swiddening using historical Landsat data in Montane Mainland Southeast Asia (MMSEA) during 1988-2016[J].Journal of Geographical Sciences, 2018, 28(9): 1307-1328.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
Table 1
The maximum and minimum area sizes of the newly-burned plots (NBP) of swiddening and the corresponding proportions of total land area and the related occurrence years in Cambodia, Laos, Myanmar, Thailand, Vietnam and MSEA (104 km2 and %)"
Maximum area | Minimum area | |||||
---|---|---|---|---|---|---|
Quantity | Proportion | Year | Quantity | Proportion | Year | |
MSEA | 9.19 | 4.75 | 2007 | 3.94 | 2.04 | 2011 |
Cambodia | 0.01 | 0.07 | 2004 | - | - | 2012* |
Laos | 1.05 | 4.42 | 2004 | 0.19 | 0.81 | 1993 |
Myanmar | 6.08 | 9.00 | 1999 | 2.64 | 3.90 | 1996 |
Thailand | 1.38 | 2.70 | 1998 | 0.29 | 0.57 | 2003 |
Vietnam | 1.18 | 3.59 | 2007 | 0.25 | 0.75 | 1988 |
Table 2
The (quasi-) decadal average area and the related area proportions of the newly-burned plots (NBP) of swidden agriculture in Cambodia, Laos, Myanmar, Thailand, Vietnam and MSEA (104 km2 and %)"
(Quasi-) Decadal average area | Annual average area | Proportion of total land area | ||||
---|---|---|---|---|---|---|
1980s | 1990s | 2000s | 2010s | 1988-2016 | % | |
MSEA | 6.08 | 6.24 | 6.52 | 5.23 | 6.08 | 3.15 |
Cambodia | - | - | - | - | - | 0.02 |
Laos | 0.48 | 0.51 | 0.55 | 0.43 | 0.50 | 2.12 |
Myanmar | 4.39 | 4.15 | 4.42 | 3.52 | 4.11 | 6.08 |
Thailand | 0.78 | 0.94 | 0.78 | 0.67 | 0.81 | 1.57 |
Vietnam | 0.43 | 0.63 | 0.77 | 0.60 | 0.66 | 2.00 |
Figure 4
Temporal variations in annual average area of the newly-burned plots (NBP) of swidden agriculture for the top ten provinces in Cambodia during 1988-2016 Note: The province (i.e., Mondulkiri) with the largest NBP area was plotted with histogram (empty), the second to fifth provinces with line (e.g., solid, dashes, dots and dash dot), and the remaining five provinces with scatter in different symbols, respectively."
Figure 5
Temporal variations in annual average area of the newly-burned plots (NBP) of swidden agriculture for the top ten provinces in Laos during 1988-2016^Note: The province (i.e., Louang Phrabang) with the largest NBP area was plotted with histogram (empty), the second to fifth provinces with line (e.g., solid, dashes, dots and dash dot), and the remaining five provinces with scatter in different symbols, respectively."
Figure 6
Temporal variations in annual average area of the newly-burned plots (NBP) of swidden agriculture for the top ten provinces in Myanmar during 1988-2016^Note: The state (i.e., Shan) with the largest NBP area was plotted with histogram (empty), the second to fifth provinces with line (e.g. solid, dashes, dots and dash dot), and the remaining five provinces with scatter in different symbols, respectively."
Figure 7
Temporal variations in annual average area of the newly-burned plots (NBP) of swidden agriculture for the top ten provinces in Thailand during 1988-2016 Note: The province (i.e., Chiang Mai) with the largest NBP area was plotted with histogram (empty), the second to fifth provinces with line (e.g., solid, dashes, dots and dash dot), and the remaining five provinces with scatter in different symbols, respectively."
Figure 8
Temporal variations in annual average area of the newly-burned plots (NBP) of swidden agriculture for the top ten provinces in Vietnam during 1988-2016^Note: The province (i.e., Son La) with the largest NBP area was plotted with histogram (empty), the second to fifth provinces with line (e.g., solid, dashes, dots and dash dot), and the remaining five provinces with scatter in different symbols, respectively."
Figure 9
Temporal changes in decadal annual average area of newly-burned plots (NBP) of swidden agriculture at provincial, national and regional levels during 1988-2016 Note: (a) MSEA and the five countries; (b)-(f) refers to the top ten provinces of MSEA countries in an alphabetical order."
[2] |
Achard F, Beuchle R, Mayaux Pet al., 2014. Determination of tropical deforestation rates and related carbon losses from 1990 to 2010.Global Change Biology, 20(8): 2540-2554.
doi: 10.1111/gcb.12605 pmid: 4312855 |
[3] |
Achard F, Eva H D, Stibig H Jet al., 2002. Determination of deforestation rates of the world's humid tropical forests.Science, 297(5583): 999-1002.
doi: 10.1126/science.1078714 pmid: 12586926 |
[4] |
Brady N C, 1996. Alternatives to slash-and-burn: A global imperative.Agriculture, Ecosystems & Environment, 58(1): 3-11.
doi: 10.1016/0167-8809(96)00650-0 |
[5] |
Bruun T B, de Neergaard A, Lawrence Det al., 2009. Environmental consequences of the demise in swidden cultivation in Southeast Asia: Carbon storage and soil quality.Human Ecology, 37(3): 375-388.
doi: 10.1007/s10745-009-9257-y |
[6] | Cairns M F, 2015. Shifting Cultivation and Environmental Change: Indigenous People, Agriculture and Forest Conservation. New York: Routledge, 1057. |
[7] | Chuan G K, 2005. The climate of Southeast Asia. In: Gupta A (ed.). The Physical Geography of Southeast Asia.Oxford, UK:Oxford University Press, 80-93. |
[8] |
Cohen P T, 2009. The post-opium scenario and rubber in northern Laos: Alternative Western and Chinese models of development.International Journal of Drug Policy, 20(5): 424-430.
doi: 10.1016/j.drugpo.2008.12.005 pmid: 19231150 |
[9] | Corlett R T, 2005. Vegetation. In: Gupta A (ed.). The Physical Geography of Southeast Asia. Oxford, UK: Oxford University Press, 105-119. |
[10] |
Cummings A R, Karale Y, Cummings G Ret al., 2017. UAV-derived data for mapping change on a swidden agriculture plot: Preliminary results from a pilot study.International Journal of Remote Sensing, 38(8-10): 2066-2082.
doi: 10.1080/01431161.2017.1295487 |
[11] |
Dong J, Xiao X, Menarguez M Aet al., 2016. Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine.Remote Sensing of Environment, 185: 142-154.
doi: 10.1016/j.rse.2016.02.016 pmid: 5181848 |
[12] |
Dressler W H, Wilson D, Clendenning Jet al., 2016. The impact of swidden decline on livelihoods and ecosystem services in Southeast Asia: A review of the evidence from 1990 to 2015.Ambio, 46(3): 291-310.
doi: 10.1007/s13280-016-0836-z pmid: 27854070 |
[13] |
Dressler W, Wilson D, Clendenning Jet al., 2015. Examining how long fallow swidden systems impact upon livelihood and ecosystem services outcomes compared with alternative land-uses in the uplands of Southeast Asia.Journal of Development Effectiveness, 7(2): 210-229.
doi: 10.1080/19439342.2014.991799 |
[14] | Dudal R, 2005. Soil of Southeast Asia. Gupta A (ed.). The Physical Geography of Southeast Asia. Oxford, UK: Oxford University Press, 94-104. |
[15] |
Dutrieux L P, Jakovac C C, Latifah S Het al., 2016. Reconstructing land use history from Landsat time-series: Case study of a swidden agriculture system in Brazil.International Journal of Applied Earth Observation and Geoinformation, 47: 112-124.
doi: 10.1016/j.jag.2015.11.018 |
[16] |
Fernández-Manso A, Fernández-Manso O, Quintano C, 2016. SENTINEL-2A red-edge spectral indices suitability for discriminating burn severity.International Journal of Applied Earth Observation and Geoinformation, 50: 170-175.
doi: 10.1016/j.jag.2016.03.005 |
[17] |
Fox J, Castella J, Ziegler A D, 2014. Swidden, rubber and carbon: Can REDD+ work for people and the environment in Montane Mainland Southeast Asia?Global Environmental Change, 29: 318-326.
doi: 10.1016/j.gloenvcha.2013.05.011 |
[18] |
Fox J, Vogler J B, 2005. Land-use and land-cover change in Montane Mainland Southeast Asia.Environmental Management, 36(3): 394-403.
doi: 10.1007/s00267-003-0288-7 pmid: 16132447 |
[19] | Gamon J A, Field C B, Goulden M Let al., 1995. Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types.Ecological Applications, 5(1): 28-41. |
[20] |
García M L, Caselles V, 1991. Mapping burns and natural reforestation using Thematic Mapper data.Geocarto International, 6(1): 31-37.
doi: 10.1080/10106049109354290 |
[21] |
Goldammer J G, 1988. Rural land-use and wildland fires in the tropics.Agroforestry Systems, 6(3): 235-252.
doi: 10.1007/BF02220124 |
[22] | Gupta A, 2005. Accelerated erosion and sedimentation in Southeast Asia. In: Gupta A (ed.), The Physical Geography of Southeast Asia. Oxford, UK: Oxford University Press, 239-249. |
[23] | Gupta A, 2005. Landforms of Southeast Asia. In: Gupta A (ed.). The Physical Geography of Southeast Asia.Oxford, UK: Oxford University Press, 38-64. |
[24] | Hansen P K, 1998. Shifting cultivation development in northern Laos. In: Chapman E C, Bouaham B, Hansen P K. Upland Farming System in the Laos PDR: Problems and Opportunities for Livestock. Vientiane, Laos, Australian Centre for International Agricultural Research (ACIAR): 34-42. |
[25] |
Hett C, Castella J C, Heinimann Aet al., 2012. A landscape mosaics approach for characterizing swidden systems from a REDD plus perspective.Applied Geography, 32(2): 608-618.
doi: 10.1016/j.apgeog.2011.07.011 |
[26] |
Huang H, Chen Y, Clinton Net al., 2017. Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine.Remote Sensing of Environment, 202: 166-176.
doi: 10.1016/j.rse.2017.02.021 |
[27] |
Huete A R, 1988. A soil-adjusted vegetation index (SAVI).Remote Sensing of Environment, 25(3): 295-309.
doi: 10.1016/0034-4257(88)90106-X |
[28] | Huete A R, Liu H, Van Leeuwen W J, 1997. The use of vegetation indices in forested regions: Issues of linearity and saturation. In: IGARSS. Remote Sensing: A Scientific Vision for Sustainable Development. Singapore, IEEE: 1966-1968. |
[29] | Hurni K, Hett C, Epprecht Met al., 2013. A texture-based land cover classification for the delineation of a shifting cultivation landscape in the Lao PDR using landscape metrics.Remote Sensing, 5(7): 3377-3396. |
[30] |
Hurni K, Hett C, Heinimann Aet al., 2013. Dynamics of shifting cultivation landscapes in Northern Lao PDR between 2000 and 2009 based on an analysis of MODIS time series and Landsat images.Human Ecology, 41(1): 21-36.
doi: 10.1007/s10745-012-9551-y |
[31] |
Jackson T J, Chen D, Cosh Met al., 2004. Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans.Remote Sensing of Environment, 92(4): 475-482.
doi: 10.1016/j.rse.2003.10.021 |
[32] | Kapos V, Rhind J, Edwards M et al., 2000. Developing a map of the world's mountain forests. In: Price M F, Butt N (ed.). Forests in Sustainable Mountain Development: A State of Knowledge Report for 2000. Task Force on Forests in Sustainable Mountain Development. Oxford: UK, 4-19. |
[33] |
Laurance W F, Sayer J, Cassman K G, 2014. Agricultural expansion and its impacts on tropical nature.Trends in Ecology & Evolution, 29(2): 107-116.
doi: 10.1016/j.tree.2013.12.001 pmid: 24388286 |
[34] | Li P, Feng Z, 2014. Monitoring phenological stages of swiddening in northern Laos during the dry season. Proc. SPIE 9260, Land Surface Remote Sensing II. Beijing, International Society for Optics and Photonics: 13. |
[35] |
Li P, Feng Z, 2016. Extent and area of swidden in Montane Mainland Southeast Asia: Estimation by multi-step thresholds with Landsat-8 OLI data.Remote Sensing, 8(1): 44.
doi: 10.3390/rs8010044 |
[36] |
Li P, Feng Z, Jiang Let al., 2014. A review of swidden agriculture in Southeast Asia.Remote Sensing, 6(2): 1654-1683.
doi: 10.3390/rs6021654 |
[37] |
Li P, Feng Z, Xiao C, 2018. Acquisition probability differences in cloud coverage of the available Landsat observations over mainland Southeast Asia from 1986 to 2015.International Journal of Digital Earth, 11(5): 437-450.
doi: 10.1080/17538947.2017.1327619 |
[38] |
Liao C, Feng Z, Li Pet al., 2015. Monitoring the spatio-temporal dynamics of swidden agriculture and fallow vegetation recovery using Landsat imagery in northern Laos.Journal of Geographical Sciences, 25(10): 1218-1234.
doi: 10.1007/s11442-015-1229-0 |
[39] |
Manivong V, Cramb R A, 2008. Economics of smallholder rubber expansion in Northern Laos.Agroforestry Systems, 74(2): 113-125.
doi: 10.1007/s10457-008-9136-3 |
[40] |
Masek J G, Vermote E F, Saleous N Eet al., 2006. A Landsat surface reflectance dataset for North America, 1990-2000.IEEE Geoscience and Remote Sensing Letters, 3(1): 68-72.
doi: 10.1109/LGRS.2005.857030 |
[41] |
Mertz O, Leisz S, Heinimann Aet al., 2009. Who counts? Demography of swidden cultivators in Southeast Asia.Human Ecology, 37(3): 281-289.
doi: 10.1007/s10745-009-9249-y |
[42] |
Mertz O, Padoch C, Fox Jet al., 2009. Swidden change in Southeast Asia: Understanding causes and consequences.Human Ecology, 37(3): 259-264.
doi: 10.1007/s10745-009-9245-2 |
[43] |
Messerli P, Heinimann A, Epprecht M, 2009. Finding homogeneity in heterogeneity: A new approach to quantifying landscape mosaics developed for the Lao PDR.Human Ecology, 37(3): 291-304.
doi: 10.1007/s10745-009-9238-1 pmid: 2709899 |
[44] | Michaud J, 2010. Editorial-Zomia and beyond.Journal of Global History, 5(2): 187-214. |
[45] |
Padoch C, Coffey K, Mertz Oet al., 2007. The demise of swidden in Southeast Asia? Local realities and regional ambiguities.Geografisk Tidsskrift-Danish Journal of Geography, 107(1): 29-41.
doi: 10.1080/00167223.2007.10801373 |
[46] |
Rerkasem K, Lawrence D, Padoch Cet al., 2009. Consequences of swidden transitions for crop and fallow biodiversity in Southeast Asia.Human Ecology, 37(3): 347-360.
doi: 10.1007/s10745-009-9250-5 |
[47] |
Rerkasem K, Yimyam N, Rerkasem B, 2009. Land use transformation in the mountainous mainland Southeast Asia region and the role of indigenous knowledge and skills in forest management.Forest Ecology and Management, 257(10): 2035-2043.
doi: 10.1016/j.foreco.2008.11.008 |
[48] |
Schmidt-Vogt D, Leisz S J, Mertz Oet al., 2009. An assessment of trends in the extent of swidden in Southeast Asia.Human Ecology, 37(3): 269-280.
doi: 10.1007/s10745-009-9239-0 |
[49] |
Stibig H, Achard F, Carboni Set al., 2014. Change in tropical forest cover of Southeast Asia from 1990 to 2010.Biogeosciences, 11(2): 247.
doi: 10.5194/bg-11-247-2014 |
[50] |
Stibig H J, Achard F, Fritz S, 2004. A new forest cover map of continental southeast Asia derived from SPOT-VEGETATION satellite imagery.Applied Vegetation Science, 7(2): 153-162.
doi: 10.1111/j.1654-109X.2004.tb00606.x |
[51] |
Stibig H J, Belward A S, Roy P Set al., 2007. A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data.Journal of Biogeography, 34(4): 625-637.
doi: 10.1111/j.1365-2699.2006.01637.x |
[52] |
Tian Y, Wu B, Zhang Let al., 2011. Opium poppy monitoring with remote sensing in North Myanmar.International Journal of Drug Policy, 22(4): 278-284.
doi: 10.1016/j.drugpo.2011.02.001 pmid: 21440430 |
[53] |
Tucker C J, Justice C O, Prince S D, 1986. Monitoring the grasslands of the Sahel 1984-1985.International Journal of Remote Sensing, 7(11): 1571-1581.
doi: 10.1080/01431168608948954 |
[54] | U.S. Geological Survey (USGS), 2016. USGS Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA) On Demand Interface (Version 3.3). |
[55] | Van Schendel W, 2002. Geographies of knowing, geographies of ignorance: Jumping scale in Southeast Asia.Environment and Planning D: Society and Space, 20(6): 647-668. |
[56] |
van Vliet N, Mertz O, Birch-Thomsen Tet al., 2013. Is there a continuing rationale for swidden cultivation in the 21st century?Human Ecology, 41(1): 1-5.
doi: 10.1007/s10745-013-9562-3 |
[57] |
van Vliet N, Mertz O, Heinimann Aet al., 2012. Trends, drivers and impacts of changes in swidden cultivation in tropical forest-agriculture frontiers: A global assessment.Global Environmental Change, 22(2): 418-429.
doi: 10.1016/j.gloenvcha.2011.10.009 |
[58] |
Vogelmann J E, Rock B N, 1988. Assessing forest damage in high-elevation coniferous forests in Vermont and New Hampshire using Thematic Mapper data.Remote Sensing of Environment, 24(2): 227-246.
doi: 10.1016/0034-4257(88)90027-2 |
[59] | Woodcock C E, Allen R, Anderson Met al., 2008. Free access to Landsat imagery.Science, 320(5879): 1011-1012. |
[60] |
Xiao C W, Li P, Feng Z Met al., 2018. Spatio-temporal differences in cloud cover of Landsat-8 OLI observations across China during 2013-2016.Journal of Geographical Sciences, 28(4): 429-444.
doi: 10.1007/s11442-018-1482-0 |
[61] |
Zhu Z, Woodcock C E, 2012. Object-based cloud and cloud shadow detection in Landsat imagery.Remote Sensing of Environment, 118: 83-94.
doi: 10.1016/j.rse.2011.10.028 |
[62] |
Ziegler A D, Bruun T B, Guardiola-Claramonte Met al., 2009. Environmental consequences of the demise in swidden cultivation in Montane Mainland Southeast Asia: Hydrology and deomorphology.Human Ecology, 37(3): 361-373.
doi: 10.1007/s10745-009-9258-x |
[63] |
Ziegler A D, Fox J M, Webb E Let al., 2011. Recognizing contemporary roles of swidden agriculture in transforming landscapes of Southeast Asia.Conservation Biology, 25(4): 846-848.
doi: 10.1111/j.1523-1739.2011.01664.x pmid: 21453366 |
[64] |
Zwartendijk B W, van Meerveld H J, Ghimire C Pet al., 2017. Rebuilding soil hydrological functioning after swidden agriculture in eastern Madagascar.Agriculture, Ecosystems & Environment, 239: 101-111.
doi: 10.1016/j.agee.2017.01.002 |
[1] | Guofeng XIAO, Xiufang ZHU, Chenyao HOU, Xingsheng XIA. Extraction and analysis of abandoned farmland:A case study of Qingyun and Wudi counties in Shandong Province [J]. Journal of Geographical Sciences, 2019, 29(4): 581-597. |
[2] | Yujie LIU, Ya QIN, Quansheng GE. Spatiotemporal differentiation of changes in maize phenology in China from 1981 to 2010 [J]. Journal of Geographical Sciences, 2019, 29(3): 351-362. |
[3] | Chenzhi WANG, Zhao ZHANG, Jing ZHANG, Fulu TAO, Yi CHEN, Hu DING. The effect of terrain factors on rice production: A case study in Hunan Province [J]. Journal of Geographical Sciences, 2019, 29(2): 287-305. |
[4] | Miaomiao QI, Xiaojun YAO, Xiaofeng LI, Hongyu DUAN, Yongpeng GAO, Juan LIU. Spatiotemporal characteristics of Qinghai Lakeice phenology between 2000 and 2016 [J]. Journal of Geographical Sciences, 2019, 29(1): 115-130. |
[5] | Wenbo ZHU, Xiaodong ZHANG, Jingjing ZHANG, Lianqi ZHU. A comprehensive analysis of phenological changes in forest vegetation of the Funiu Mountains, China [J]. Journal of Geographical Sciences, 2019, 29(1): 131-145. |
[6] | Yang FU, Hui CHEN, Huihui NIU, Siqi ZHANG, Yi YANG. Spatial and temporal variation of vegetation phenology and its response to climate changes in Qaidam Basin from 2000 to 2015 [J]. Journal of Geographical Sciences, 2018, 28(4): 400-414. |
[7] | Abdi OMID, Shirvani ZEINAB, F. Buchroithner MANFRED. Visualization and quantification of significant anthropogenic drivers influencing rangeland degradation trends using Landsat imagery and GIS spatial dependence models: A case study in Northeast Iran [J]. Journal of Geographical Sciences, 2018, 28(12): 1933-1952. |
[8] | Yujie LIU, Ya QIN, Quansheng GE, Junhu DAI, Qiaomin CHEN. Reponses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province, China [J]. Journal of Geographical Sciences, 2017, 27(9): 1072-1084. |
[9] | Fengshan LIU, Ying CHEN, Wenjiao SHI, Shuai ZHANG, Fulu Tao, Quansheng GE. Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback [J]. Journal of Geographical Sciences, 2017, 27(9): 1085-1099. |
[10] | Cristina NOYOLA-MEDRANO, Valeria Abigaíl MARTÍNEZ-SÍAS. Assessing the progress of desertification of the southern edge of Chihuahuan Desert:A case study of San Luis Potosi Plateau [J]. Journal of Geographical Sciences, 2017, 27(4): 420-438. |
[11] |
Samantha HART, Elena MIKHAILOVA, Christopher POST, Patrick McMILLAN, Julia SHARP, William BRIDGES.
Spatio-temporal analysis of flowering using LiDAR topography [J]. Journal of Geographical Sciences, 2017, 27(1): 62-78. |
[12] | Xiaojun YAO, Long LI, Jun ZHAO, Meiping SUN, Jing LI, Peng GONG, Lina AN. Spatial-temporal variations of lake ice phenology in the Hoh Xil region from 2000 to 2011 [J]. Journal of Geographical Sciences, 2016, 26(1): 70-82. |
[13] | Mingjun DING, Lanhui LI, Yili ZHANG, Xiaomin SUN, Linshan LIU, Jungang GAO, Zhaofeng WANG, Yingnian LI. Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data [J]. Journal of Geographical Sciences, 2015, 25(2): 131-148. |
[14] | Baojuan HUAI, Zhongqin LI, Shengjie WANG, Meiping SUN, Ping ZHOU, Yan XIAO. RS analysis of glaciers change in the Heihe River Basin, Northwest China, during the recent decades [J]. Journal of Geographical Sciences, 2014, 24(6): 993-1008. |
[15] | Samuli HELAMA, Jianmin JIANG, Johanna KORHONEN, Jari HOLOPAINEN, Mauri TIMONEN. Quantifying temporal changes in Tornionjoki river ice breakup dates and spring temperatures in Lapland since 1802 [J]. , 2013, 23(6): 1069-1079. |
|