A method of characterizing land-cover swap changes in the arid zone of China
Yecheng YUAN, Baolin LI, Xizhang GAO, Haijiang LIU, Lili XU, Chenghu ZHOU
A method of characterizing land-cover swap changes in the arid zone of China
Net area change analysis can dramatically underestimate total change of land cover, even sometimes seriously misinterpret ecological processes of the ecosystem, especially in arid or semiarid zones. In this paper, a suite of indices are presented to characterize land-cover swaps that may seriously damage the ecosystem in arid or semiarid zones, based on swap-change areas extracted from remotely sensed images. First, swap percentage of total area and swap intensity of total changes were used to determine the status of land-cover swap change in an area. Then, dominated swap category and individual swap-change intensity for a land-cover category were used to determine flagged land-cover swap-change categories. Finally, swap-change mode and Pielou’s index were used to determine the land-cover swap-change processes of dominant categories. A case study is conducted using this approach, based on two land-cover maps in the 1980s and 2000 in Naiman Qi, Tongliao City, Inner Mongolia, China. This study shows that the approach can clearly quantify the severity and flagged classes of land-cover swap-change and reveal their relationship with ecological processes of the ecosystem. These results indicate that the approach can give deep insights into swap change, which can be very valuable to land-cover policy making and management.
land cover swap / swap-change status / flagged swap-change categories / swap-change process / arid/semiarid zone
[1] |
Braimoh A K (2006). Random and systematic land-cover transitions in northern Ghana. Agric Ecosyst Environ, 113(1−4): 254–263
CrossRef
Google scholar
|
[2] |
Condit R, Hubbell S P, Lafrankie J V, Sukumar R, Manokaran N, Foster R B, Ashton P S (1996). Species-area and species-individual relationships for tropical trees: a comparison of three 50-ha plots. J Ecol, 84(4): 549–562
CrossRef
Google scholar
|
[3] |
Gray J S (2000). The measurement of marine species diversity, with an application to the benthic fauna of the Norwegian continental shelf. Journal of Experimental Marine Biology and Ecology, 250: 23–49
|
[4] |
Huang J L, Pontius R G Jr, Li Q S, Zhang Y J (2012). Use of intensity analysis to link patterns with processes of land change from 1986 to 2007 in a coastal watershed of southeast China. Appl Geogr, 34: 371–384
CrossRef
Google scholar
|
[5] |
Kassas M (1995). Desertification: a general review. J Arid Environ, 30(2): 115–128
CrossRef
Google scholar
|
[6] |
Kempton R A (1979). The structure of species abundance and measurement of diversity. Biometrics, 35(1): 307–321
CrossRef
Google scholar
|
[7] |
Li B L, Zhou Q M (2009). Accuracy assessment on multi-temporal land-cover change detection using a trajectory error matrix. Int J Remote Sens, 30(5): 1283–1296
CrossRef
Google scholar
|
[8] |
Li F R, Zhang H, Zhang T H, Shirato Y (2003). Variations of sand transportation rates in sandy grasslands along a desertification gradient in northern China. Catena, 53(3): 255–272
CrossRef
Google scholar
|
[9] |
Li S G, Harazono Y, Zhao H L, He Z Y, Chang X L, Zhao X Y, Zhang T H, Oikawa T (2002). Micrometeorological changes following establishment of artificially established artemisia vegetation on desertified sandy land in the Horqin sandy land, China and their implication on regional environmental change. J Arid Environ, 52(1): 101–119
CrossRef
Google scholar
|
[10] |
Liu J Y, Liu M L, Tian H Q, Zhuang D F, Zhang Z X, Zhang W, Tang X M, Deng X Z (2005). Spatial and temporal patterns of China's cropland during 1990−2000: an analysis based on Landsat TM data. Remote Sens Environ, 98(4): 442–456
CrossRef
Google scholar
|
[11] |
Lu D, Mausel P, Brondizio E, Moran E (2004). Change detection techniques. Int J Remote Sens, 25(12): 2365–2401
CrossRef
Google scholar
|
[12] |
Macleod R D, Congalton R G (1998). A quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely sensed data. Photogramm Eng Remote Sensing, 64(3): 207–216
|
[13] |
Manandhar R, Odeh I O A, Pontius R G Jr (2010). Analysis of twenty years of categorical land transitions in the Lower Hunter of New South Wales, Australia. Agric Ecosyst Environ, 135(4): 336–346
CrossRef
Google scholar
|
[14] |
Nagendra H, Munroe D K, Southworth J (2004). From pattern to process: landscape fragmentation and the analysis of land use/land cover change. Agric Ecosyst Environ, 101(2−3): 111–115
CrossRef
Google scholar
|
[15] |
Narumalani S, Mishra D R, Rothwell R G (2004). Change detection and landscape metrics for inferring anthropogenic processes in the greater EFMO area. Remote Sens Environ, 91(3−4): 478–489
CrossRef
Google scholar
|
[16] |
Pérez-Hugalde C, Romero-Calcerrada R, Delgado-Pérez P, Novillo C J (2011). Understanding land cover change in a Special Protection Area in Central Spain through the enhanced land cover transition matrix and a related new approach. J Environ Manage, 92(4): 1128–1137
CrossRef
Google scholar
|
[17] |
Pielou E (1966). The measurement of diversity in different types of biological collections. J Theor Biol, 13: 131–144
CrossRef
Google scholar
|
[18] |
Pontius R G Jr, Shusas E, McEachern M (2004). Detecting important categorical land changes while accounting for persistence. Agric Ecosyst Environ, 101(2−3): 251–268
CrossRef
Google scholar
|
[19] |
Poulter B, Pederson N, Liu H Y, Zhu Z C, D’Arrigo R, Ciais P, Davi N, Frank D, Leland C, Myneni R, Piao S L, Wang T (2013). Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change. Agric Meteorol, 178−179: 31–45
CrossRef
Google scholar
|
[20] |
Robbins P, Birkenholtz T (2003). Turfgrass revolution: measuring the expansion of the American lawn. Land Use Policy, 20(2): 181–194
CrossRef
Google scholar
|
[21] |
Teferi E, Bewket W, Uhlenbrook S, Wenninger J (2013). Understanding recent land use and land cover dynamics in the source region of the Upper Blue Nile, Ethiopia: spatially explicit statistical modeling of systematic transitions. Agric Ecosyst Environ, 165: 98–117
CrossRef
Google scholar
|
[22] |
Wang Y, Ding Y J, Ye B S, Liu F J, Wang J, Wang J (2013). Contributions of climate and human activities to changes in runoff of the Yellow and Yangtze rivers from 1950 to 2008. Science China-Earth Sciences, 56(8): 1398–1412
CrossRef
Google scholar
|
[23] |
Zhang T H, Zhao H L, Li S G, Li F R, Shirato Y, Ohkuro T, Taniyama I (2004). A comparison of different measures for stabilizing moving sand dunes in the Horqin Sandy Land of Inner Mongolia, China. J Arid Environ, 58(2): 203–214
CrossRef
Google scholar
|
[24] |
Zhou Q, Li B, Kurban A (2008). Trajectory analysis of land cover change in arid environment of China. Int J Remote Sens, 29(4): 1093–1107
CrossRef
Google scholar
|
[25] |
Zhou Q M, Li B L, Chen Y M (2011). Remote sensing change detection and process analysis of long-term land use change and human impacts. Ambio, 40(7): 807–818
CrossRef
Google scholar
|
/
〈 | 〉 |