Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (11): 1580-1594.doi: 10.1007/s11442-018-1530-9
• Special Issue: Land system dynamics: Pattern and process • Previous Articles Next Articles
Di CHEN1(), Qiangyi YU1,*(
), Qiong HU1, Mingtao XIANG1, Qingbo ZHOU1, Wenbin WU1,*(
)
Received:
2018-01-04
Accepted:
2018-06-06
Online:
2018-11-20
Published:
2018-11-20
Contact:
Qiangyi YU,Wenbin WU
E-mail:chendi01@caas.cn;yuqiangyi@caas.cn;wuwenbin@caas.cn
About author:
Author: Chen Di (1991-), PhD Candidate, specialized in agricultural land use change. E-mail:
Supported by:
Di CHEN, Qiangyi YU, Qiong HU, Mingtao XIANG, Qingbo ZHOU, Wenbin WU. Cultivated land change in the Belt and Road Initiative region[J].Journal of Geographical Sciences, 2018, 28(11): 1580-1594.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
Figure 2
Cultivated land change in the BRI between 2000 and 2010 (a) and the identified seven hotspots representing the characteristics of cultivated land change at the seven geographical zones, including: northeast India from South Asia (b), central part of Vietnam from Southeast Asia (c), Yangtze River Delta in China from East Asia (d), south Kazakhstan from Central Asia (e), southwest Iran from West Asia (f), southwest Russia from Central and Eastern Europe (g) and Nile Delta in Egypt from North Africa (h). Detailed elaboration of the seven geographical zones can be found in Section 2.1 and Table S1. A unified legend is provided in the upper figure (a)."
Table S1
Countries in the “Belt and Road Initiative” (BRI) region"
BRI | Geographical zone | Countries |
---|---|---|
China (the start) | East Asia | China |
the Belt | East Asia | Mongolia |
Central Asia | Kazakhstan, Turkmenistan, Tajikistan, Uzbekistan, Kyrgyzstan | |
West Asia | Armenia, Syrian, Lebanese, Afghanistan, Iraq, Kuwait, Jordan, Bahrain, Qatar, Georgia, Israel, Iran, Yemen, Saudi Arabia, United Arab Emirates, Turkey, Oman, Azerbaijan | |
the Road | Southeast Asia | Brunei, East Timor, Laos, Singapore, Cambodia, Myanmar, Thailand, Indonesia, Malaysia, Vietnam, Philippines |
South Asia | Maldives, Sri Lanka, Pakistan, India, Bangladesh, Nepal, Bhutan | |
North Africa | Egypt | |
Central and Eastern Europe (the end) | Central and Eastern Europe | Estonia, Latvia, Lithuania, Belarus, Poland, Czech, Slovakia, Moldova, Hungary, Slovenia, Romania, Serbia, Ukraine, Bosnia and Herzegovina, Croatia, Bulgaria, Macedonia, Albania, Russia, Montenegro |
Table S2
Cultivated land area change (104 km2) and changing rate (%) of seven geographical zones and each country in the BRI region between 2000 and 2010"
Geographical zone | Country | Area change | Area changing rate | |||
---|---|---|---|---|---|---|
East Asia | China | -1.95 | -0.95 | |||
Mongolia | -0.03 | -2.00 | ||||
Subtotal | -1.98 | -0.96 | ||||
Central Asia | Kazakhstan | 0.17 | 0.40 | |||
Turkmenistan | 0.17 | 4.87 | ||||
Tajikistan | 0.02 | 1.86 | ||||
Uzbekistan | -0.06 | -0.89 | ||||
Kyrgyzstan | 0.02 | 0.92 | ||||
Subtotal | 0.31 | 0.55 | ||||
West Asia | Armenia | 0.0001 | 0.02 | |||
Syrian | -0.003 | -0.04 | ||||
Lebanese | -0.02 | -7.31 | ||||
Afghanistan | 0.21 | 3.57 | ||||
Iraq | -0.001 | -0.01 | ||||
Kuwait | 0.001 | 2.39 | ||||
Jordan | -0.05 | -11.18 | ||||
Geographical zone | Country | Area change | Area changing rate | |||
Bahrain | -0.00003 | -0.96 | ||||
Qatar | 0.00005 | 0.35 | ||||
Georgia | -0.01 | -0.58 | ||||
Israel | -0.12 | -18.92 | ||||
Iran | 0.32 | 1.40 | ||||
Yemen | -0.04 | -3.16 | ||||
Saudi Arabia | 0.08 | 2.97 | ||||
United Arab Emirates | 0.01 | 6.44 | ||||
Turkey | -0.04 | -0.15 | ||||
Oman | 0.02 | 10.50 | ||||
Azerbaijan | 0.10 | 3.20 | ||||
Subtotal | 0.44 | 0.52 | ||||
Southeast Asia | Brunei | 0.0006 | 15.83 | |||
East Timor | 0.0007 | 1.78 | ||||
Laos | 0.24 | 12.24 | ||||
Singapore | 0.0006 | 5.07 | ||||
Cambodia | 0.28 | 4.78 | ||||
Myanmar | 0.10 | 0.64 | ||||
Thailand | -0.22 | -0.82 | ||||
Indonesia | 0.42 | 1.67 | ||||
Malaysia | 0.01 | 0.49 | ||||
Vietnam | 0.21 | 1.68 | ||||
Philippines | 0.003 | 0.05 | ||||
Subtotal | 1.05 | 1.11 | ||||
South Asia | Maldives | 0.00 | 0.00 | |||
Sri Lanka | 0.06 | 3.28 | ||||
Pakistan | 0.27 | 1.01 | ||||
India | 0.57 | 0.29 | ||||
Bangladesh | -0.22 | -2.53 | ||||
Nepal | -0.01 | -0.25 | ||||
Bhutan | 0.02 | 20.25 | ||||
Subtotal | 0.69 | 0.29 | ||||
North Africa | Egypt | 0.35 | 8.75 | |||
Subtotal | 0.35 | 8.75 | ||||
Central and Eastern Europe | Estonia | 0.003 | 0.18 | |||
Latvia | -0.03 | -1.03 | ||||
Lithuania | -0.02 | -0.47 | ||||
Belarus | -0.18 | 1.72 | ||||
Poland | -0.08 | -0.39 | ||||
Geographical zone | Country | Area change | Area changing rate | |||
Czech | -0.003 | -0.06 | ||||
Slovakia | -0.01 | -0.42 | ||||
Moldova | 0.003 | 0.12 | ||||
Hungary | 0.66 | 11.69 | ||||
Slovenia | -0.004 | -0.59 | ||||
Romania | 0.39 | 2.98 | ||||
Serbia | 0.01 | 0.13 | ||||
Ukraine | 0.50 | 1.25 | ||||
Bosnia and Herzegovina | -0.01 | -0.45 | ||||
Croatia | 0.01 | 0.58 | ||||
Bulgaria | 0.02 | 0.35 | ||||
Macedonia | -0.001 | -0.15 | ||||
Albania | 0.004 | 0.55 | ||||
Russia | 1.59 | 1.02 | ||||
Montenegro | -0.0004 | -0.15 | ||||
Subtotal | 2.86 | 1.02 | ||||
The BRI region | Total | 3.73 | 0.39 |
Table S3
Share (%) of cultivated land converted into other land cover types, and other land cover types converted into cultivated land in the BRI region between 2000 and 2010"
Geographical zone | Country | Cultivated land converted OUT | Cultivated land converted IN | ||||||
---|---|---|---|---|---|---|---|---|---|
(to) forest | (to) grassland | (to) artificial surfaces | (to) bare land | (from) forest | (from) grassland | (from) artificial surfaces | (from) bare land | ||
East Asia | China | 1.22 | 1.41 | 1.77 | 0.04 | 1.33 | 1.28 | 0.72 | 0.20 |
Mongolia | 0.04 | 5.21 | 0.02 | 0.01 | 0.08 | 3.22 | 0.01 | 0.04 | |
Subtotal | 1.22 | 1.43 | 1.76 | 0.04 | 1.32 | 1.30 | 0.72 | 0.20 | |
Central Asia | Kazakhstan | 0.15 | 3.83 | 0.09 | 0.02 | 0.30 | 3.85 | 0.03 | 0.19 |
Turkmenistan | 0.02 | 4.05 | 0.61 | 0.50 | 0.13 | 3.16 | 0.65 | 5.32 | |
Tajikistan | 0.04 | 2.86 | 1.40 | 0.28 | 0.10 | 3.44 | 1.18 | 1.31 | |
Uzbekistan | 0.01 | 2.12 | 1.61 | 0.24 | 0.10 | 1.44 | 0.96 | 0.50 | |
Kyrgyzstan | 0.01 | 0.85 | 0.56 | 0.05 | 0.13 | 1.62 | 0.13 | 0.37 | |
Subtotal | 0.12 | 3.51 | 0.36 | 0.08 | 0.25 | 3.42 | 0.22 | 0.58 | |
West Asia | Armenia | 0.31 | 1.91 | 0.76 | 0.00 | 3.83 | 15.05 | 0.87 | 0.07 |
Syrian | 0.00 | 0.12 | 0.02 | 0.00 | 0.07 | 0.02 | 0.01 | 0.00 | |
Lebanese | 0.97 | 8.80 | 0.51 | 0.19 | 0.97 | 1.50 | 0.80 | 0.16 | |
Afghanistan | 0.01 | 3.31 | 0.16 | 1.03 | 0.11 | 2.66 | 0.10 | 4.66 | |
Iraq | 0.02 | 0.05 | 0.02 | 0.11 | 0.01 | 0.03 | 0.02 | 0.10 | |
Kuwait | 0.01 | 0.09 | 1.48 | 5.08 | 0.09 | 0.41 | 0.63 | 7.69 | |
Jordan | 0.66 | 9.03 | 0.44 | 5.65 | 0.27 | 1.28 | 0.67 | 2.89 | |
Bahrain | 0.00 | 0.00 | 1.93 | 0.00 | 0.00 | 0.00 | 0.99 | 0.00 | |
Geographical zone | Country | Cultivated land converted OUT | Cultivated land converted IN | ||||||
(to) forest | (to) grassland | (to) artificial surfaces | (to) bare land | (from) forest | (from) grassland | (from) artificial surfaces | (from) bare land | ||
Qatar | 0.05 | 0.35 | 0.25 | 3.43 | 0.02 | 0.20 | 0.04 | 4.05 | |
Georgia | 0.73 | 2.24 | 1.13 | 0.00 | 4.84 | 4.25 | 0.92 | 0.00 | |
Israel | 4.28 | 14.16 | 1.34 | 3.92 | 0.55 | 1.10 | 2.59 | 1.20 | |
Iran | 0.06 | 1.67 | 0.22 | 0.85 | 0.14 | 1.80 | 0.16 | 1.34 | |
Yemen | 0.10 | 1.17 | 0.08 | 2.93 | 0.10 | 0.11 | 0.15 | 1.08 | |
Saudi Arabia | 0.01 | 0.09 | 0.50 | 4.75 | 0.06 | 0.36 | 0.23 | 7.26 | |
United Arab Emirates | 0.04 | 0.00 | 0.85 | 3.98 | 0.14 | 0.02 | 0.24 | 10.11 | |
Turkey | 0.55 | 1.17 | 0.20 | 0.00 | 0.49 | 1.12 | 0.11 | 0.00 | |
Oman | 0.00 | 0.00 | 1.69 | 1.06 | 1.60 | 0.00 | 0.60 | 9.59 | |
Azerbaijan | 0.22 | 2.40 | 0.70 | 0.00 | 1.61 | 11.83 | 0.71 | 0.02 | |
Subtotal | 0.28 | 1.44 | 0.24 | 0.59 | 0.43 | 1.74 | 0.18 | 1.03 | |
Southeast Asia | Brunei | 4.78 | 0.06 | 0.09 | 0.00 | 7.52 | 0.45 | 9.95 | 0.00 |
East Timor | 1.05 | 8.61 | 0.00 | 7.17 | 10.52 | 6.46 | 0.82 | 0.43 | |
Laos | 5.20 | 0.78 | 0.17 | 0.00 | 12.90 | 3.26 | 0.05 | 0.01 | |
Singapore | 0.86 | 0.04 | 3.14 | 0.00 | 7.52 | 0.45 | 9.95 | 0.00 | |
Cambodia | 0.24 | 0.06 | 0.16 | 0.00 | 3.50 | 0.51 | 0.17 | 0.00 | |
Myanmar | 3.13 | 0.65 | 0.68 | 0.02 | 3.61 | 1.58 | 0.24 | 0.06 | |
Thailand | 2.58 | 0.10 | 0.47 | 0.00 | 1.72 | 0.39 | 0.14 | 0.00 | |
Indonesia | 3.07 | 0.29 | 0.42 | 0.00 | 4.89 | 0.27 | 0.46 | 0.00 | |
Malaysia | 3.45 | 0.13 | 0.83 | 0.00 | 4.17 | 0.13 | 0.50 | 0.00 | |
Vietnam | 2.96 | 0.97 | 1.04 | 0.01 | 4.18 | 1.56 | 0.70 | 0.10 | |
Philippines | 0.98 | 0.11 | 0.22 | 0.02 | 1.12 | 0.18 | 0.19 | 0.01 | |
Subtotal | 2.67 | 0.37 | 0.54 | 0.01 | 3.57 | 0.76 | 0.32 | 0.02 | |
South Asia | Maldives | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Sri Lanka | 4.46 | 0.03 | 0.18 | 0.00 | 5.48 | 1.76 | 0.32 | 0.09 | |
Pakistan | 0.14 | 0.23 | 0.13 | 0.16 | 0.21 | 0.53 | 0.11 | 0.72 | |
India | 0.30 | 0.29 | 0.16 | 0.09 | 0.49 | 0.31 | 0.11 | 0.08 | |
Bangladesh | 1.89 | 0.13 | 4.13 | 0.05 | 0.30 | 0.15 | 2.64 | 0.25 | |
Nepal | 1.26 | 0.19 | 0.05 | 0.01 | 0.99 | 0.12 | 0.05 | 0.08 | |
Bhutan | 8.48 | 3.57 | 0.00 | 0.00 | 25.80 | 0.65 | 0.09 | 2.36 | |
Subtotal | 0.39 | 0.27 | 0.30 | 0.09 | 0.51 | 0.33 | 0.20 | 0.16 | |
North Africa | Egypt | 0.07 | 0.02 | 1.29 | 2.21 | 0.03 | 0.01 | 0.84 | 10.26 |
Subtotal | 0.07 | 0.02 | 1.29 | 2.21 | 0.03 | 0.01 | 0.84 | 10.26 | |
Central and Eastern Europe | Estonia | 1.89 | 0.48 | 0.46 | 0.00 | 2.05 | 0.20 | 0.50 | 0.00 |
Latvia | 3.07 | 0.10 | 0.36 | 0.00 | 1.74 | 0.03 | 0.37 | 0.00 | |
Lithuania | 2.15 | 0.08 | 0.67 | 0.00 | 1.45 | 0.03 | 0.65 | 0.00 | |
Belarus | 3.62 | 1.32 | 1.01 | 0.00 | 1.50 | 0.97 | 1.06 | 0.00 | |
Geographical zone | Country | Cultivated land converted OUT | Cultivated land converted IN | ||||||
(to) forest | (to) grassland | (to) artificial surfaces | (to) bare land | (from) forest | (from) grassland | (from) artificial surfaces | (from) bare land | ||
Poland | 1.09 | 0.16 | 0.69 | 0.00 | 0.95 | 0.04 | 0.40 | 0.00 | |
Czech | 1.74 | 0.05 | 0.77 | 0.00 | 1.62 | 0.08 | 0.69 | 0.00 | |
Slovakia | 0.80 | 0.01 | 0.75 | 0.00 | 0.45 | 0.01 | 0.65 | 0.00 | |
Moldova | 0.65 | 0.73 | 1.14 | 0.00 | 0.33 | 0.85 | 1.43 | 0.00 | |
Hungary | 0.71 | 0.03 | 0.49 | 0.01 | 0.66 | 0.16 | 0.39 | 0.00 | |
Slovenia | 4.76 | 0.02 | 1.13 | 0.01 | 4.23 | 0.03 | 0.81 | 0.01 | |
Romania | 1.00 | 0.13 | 0.91 | 0.01 | 1.00 | 0.12 | 0.96 | 0.02 | |
Serbia | 1.04 | 0.05 | 0.44 | 0.00 | 0.99 | 0.29 | 0.37 | 0.00 | |
Ukraine | 0.89 | 0.74 | 0.74 | 0.00 | 0.61 | 1.83 | 0.84 | 0.01 | |
Bosnia and Herzegovina | 3.11 | 0.06 | 0.50 | 0.01 | 2.65 | 0.07 | 0.39 | 0.01 | |
Croatia | 1.35 | 0.02 | 0.61 | 0.04 | 1.47 | 0.02 | 0.58 | 0.04 | |
Bulgaria | 0.97 | 0.13 | 0.75 | 0.01 | 1.13 | 0.22 | 0.78 | 0.01 | |
Macedonia | 1.45 | 0.05 | 0.53 | 0.00 | 1.54 | 0.05 | 0.35 | 0.00 | |
Albania | 1.20 | 0.73 | 0.48 | 0.01 | 1.42 | 0.86 | 0.58 | 0.03 | |
Russia | 1.10 | 2.05 | 0.34 | 0.00 | 1.23 | 2.57 | 0.32 | 0.02 | |
Montenegro | 2.28 | 0.19 | 0.64 | 0.00 | 2.38 | 0.23 | 0.40 | 0.00 | |
Subtotal | 1.22 | 1.33 | 0.52 | 0.00 | 1.13 | 1.76 | 0.50 | 0.01 | |
The Belt region | Subtotal | 0.21 | 2.27 | 0.28 | 0.39 | 0.35 | 2.41 | 0.19 | 0.85 |
The Road region | Subtotal | 1.04 | 0.30 | 0.38 | 0.09 | 1.38 | 0.45 | 0.25 | 0.25 |
The BRI region | Total | 1.01 | 1.13 | 0.70 | 0.10 | 1.14 | 1.30 | 0.41 | 0.26 |
Table S4
Changing rate (%) in multi-cropping index, and fragmentation index of seven geographical zones and each country in the BRI region between 2000 and 2010"
Geographical zone | Country | MCI changing rate | FI changing rate | |||||
---|---|---|---|---|---|---|---|---|
East Asia | China | 6.01 | 2.17 | |||||
Mongolia | 27.77 | -2.82 | ||||||
Subtotal | 6.06 | 2.16 | ||||||
Central Asia | Kazakhstan | 22.71 | -17.35 | |||||
Turkmenistan | -2.76 | -8.55 | ||||||
Tajikistan | 0.62 | 15.53 | ||||||
Uzbekistan | 1.45 | 14.44 | ||||||
Kyrgyzstan | -3.21 | -2.20 | ||||||
Subtotal | 14.72 | -14.28 | ||||||
West Asia | Armenia | 4.11 | -0.34 | |||||
Syrian | 6.40 | -0.97 | ||||||
Lebanese | -5.49 | 3.82 | ||||||
Afghanistan | 20.06 | 2.13 | ||||||
Geographical zone | Country | MCI changing rate | FI changing rate | |||||
Iraq | -1.76 | 0.95 | ||||||
Kuwait | 87.13 | 19.41 | ||||||
Jordan | 32.04 | -21.81 | ||||||
Bahrain | 36.26 | 13.58 | ||||||
Qatar | -29.94 | 0.00 | ||||||
Georgia | -45.10 | 1.62 | ||||||
Israel | 21.05 | -21.72 | ||||||
Iran | 18.88 | -0.28 | ||||||
Yemen | 41.95 | -49.59 | ||||||
Saudi Arabia | -30.48 | -1.40 | ||||||
United Arab Emirates | -11.03 | 36.70 | ||||||
Turkey | -9.60 | 34.67 | ||||||
Oman | -19.38 | 3.42 | ||||||
Azerbaijan | 19.35 | -1.89 | ||||||
Subtotal | 2.21 | 4.19 | ||||||
Southeast Asia | Brunei | -25.74 | 22.88 | |||||
East Timor | 20.44 | -1.78 | ||||||
Laos | 23.36 | -16.52 | ||||||
Singapore | 49.09 | -40.20 | ||||||
Cambodia | 54.40 | -2.88 | ||||||
Myanmar | 39.15 | -8.26 | ||||||
Thailand | 15.37 | 1.09 | ||||||
Indonesia | 24.42 | 52.22 | ||||||
Malaysia | 9.30 | -6.67 | ||||||
Vietnam | 7.55 | -7.46 | ||||||
Philippines | 9.39 | -8.32 | ||||||
Subtotal | 20.40 | 10.47 | ||||||
South Asia | Maldives | 0.00 | 0.00 | |||||
Sri Lanka | 7.03 | -12.32 | ||||||
Pakistan | 2.13 | 3.66 | ||||||
India | 8.82 | -30.71 | ||||||
Bangladesh | 8.16 | 10.11 | ||||||
Nepal | 7.44 | -0.57 | ||||||
Bhutan | -22.18 | 129.89 | ||||||
Subtotal | 7.98 | -16.67 | ||||||
North Africa | Egypt | 2.35 | -5.91 | |||||
Subtotal | 2.35 | -5.91 | ||||||
Central and Eastern Europe | Estonia | -24.44 | 9.85 | |||||
Latvia | 16.04 | 58.77 | ||||||
Lithuania | -6.02 | 69.96 | ||||||
Geographical zone | Country | MCI changing rate | FI changing rate | |||||
Belarus | -9.55 | 3.59 | ||||||
Poland | -7.45 | 133.17 | ||||||
Czech | -16.51 | 89.39 | ||||||
Slovakia | -11.25 | 6.66 | ||||||
Moldova | -11.01 | 75.19 | ||||||
Hungary | -20.58 | -9.42 | ||||||
Slovenia | 0.79 | 17.63 | ||||||
Romania | -4.76 | 60.83 | ||||||
Serbia | 93.08 | 28.88 | ||||||
Ukraine | 3.38 | 77.19 | ||||||
Bosnia and Herzegovina | 2.53 | 38.88 | ||||||
Croatia | -24.36 | 74.29 | ||||||
Bulgaria | 2.76 | 113.41 | ||||||
Macedonia | -15.55 | 34.42 | ||||||
Albania | 24.88 | 63.98 | ||||||
Russia | -24.33 | 6.40 | ||||||
Montenegro | -28.60 | 89.90 | ||||||
Subtotal | -13.44 | 23.41 | ||||||
The BRI region | Total | 4.27 | 6.51 |
[1] | Arezki R, Deininger K, Selod H, 2011. What drives the global “land rush”? Policy Research Working Paper - World Bank, (5864). doi: 10.5089/9781463923334.001. |
[2] | Ba S, 2013. Ukraine will become China’s largest overseas farm, provides 3 million hectares of farmland. People’s Daily, . (in Chinese) |
[3] | Cao X, Chen X, Zhang W et al.Zhang W , 2016. Global cultivated land mapping at 30 m spatial resolution. Science China Earth Sciences, 46(11): 1426-1435. (in Chinese) |
[4] |
Chen J, Chen J, Liao A P et al., 2014. Concepts and key techniques for 30 m global land cover mapping.Acta Geodaetica et Cartographica Sinica, 43(6): 551-557. (in Chinese)
doi: 10.13485/j.cnki.11-2089.2014.0089 |
[5] |
Chen J, Chen J, Liao A P et al., 2015. Global land cover mapping at 30 m resolution: A POK-based operational approach.ISPRS Journal of Photogrammetry and Remote Sensing, 103: 7-27.
doi: 10.1016/j.isprsjprs.2014.09.002 |
[6] | Chen W, Wu X, 2015. Import demand changes of the countries along the Maritime Silk Route and the response strategy of China.International Economics and Trade Research, 31(4): 87-100. (in Chinese) |
[7] |
Chen X, Lin Y, Zhang M et al., 2017. Assessment of the cropland classifications in four global land cover datasets: A case study of Shaanxi Province, China.Journal of Integrative Agriculture, 16(2): 298-311.
doi: 10.1016/S2095-3119(16)61442-9 |
[8] |
Chen Y, Li X, Wang L et al., 2017. Is China different from other investors in global land acquisition? Some observations from existing deals in China’s going global strategy.Land Use Policy, 60: 362-372.
doi: 10.1016/j.landusepol.2016.10.045 |
[9] |
Cheng L K, Fleisher B M, Huang K X et al., 2016. Three questions on China’s “Belt and Road Initiative”.China Economic Review, 40: 309-313.
doi: 10.1016/j.chieco.2016.07.008 |
[10] | Coppedge B R, Engle D M, Fuhlendorf S D et al., 2001. Landscape cover type and pattern dynamics in fragmented southern Great Plains grasslands, USA. Landscape Ecology, 16: 677-690. |
[11] | Du S, Shi P, Rompaey A.2014. The relationship between urban sprawl and farmland displacement in the Pearl River Delta, China.Land, 3(1): 34-51. |
[12] | Duan F, Ji Q, Liu B et al., 2017. Energy investment risk assessment for nations along China’s Belt & Road Initiative.Journal of Cleaner Production, 170: 535-547. |
[13] |
Dubovyk O, Menz G, Conrad C et al., 2013. Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling. Environmental Monitoring and Assessment, 185(6): 4775-4790.
doi: 10.1007/s10661-012-2904-6 pmid: 3641299 |
[14] |
Eitelberg D A, van Vliet J, Verburg P H, 2015. A review of global potentially available cropland estimates and their consequences for model-based assessments.Global Change Biology, 21(3): 1236-1248.
doi: 10.1111/gcb.12733 pmid: 25205590 |
[15] |
Erb K H, Haberl H, Jepsen M R et al., 2013. A conceptual framework for analyzing and measuring land-use intensity.Current Opinion in Environmental Sustainability, 5: 464-470.
doi: 10.1016/j.cosust.2013.07.010 pmid: 24143156 |
[16] |
Estel S, Kuemmerle T, Alcántara C et al., 2015. Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series.Remote Sensing of Environment, 163: 312-325.
doi: 10.1016/j.rse.2015.03.028 |
[17] |
Fritz S, See L, Mccallum I et al., 2015. Mapping global cropland and field size.Global Change Biology, 21(5): 1980-1992.
doi: 10.1111/gcb.12838 pmid: 25640302 |
[18] |
Foley J A, 2005. Global consequences of land use.Science, 309(5734): 570-574.
doi: 10.1126/science.1111772 |
[19] |
Foley J A, Ramankutty N, Brauman K A et al., 2011. Solutions for a cultivated planet.Nature, 478(7369): 337-342.
doi: 10.1038/nature10452 pmid: 21993620 |
[20] |
Forman R T T, 1995. Some general principles of landscape and regional ecology.Landscape Ecology, 10: 133-142.
doi: 10.1007/BF00133027 |
[21] | Gong B, Song Z, Liu W, 2015. Commodity structure of trade between China and countries in the Belt and Road Initiative area.Progress in Geography, 30(5): 571-580. (in Chinese) |
[22] |
Gray J, Friedl M, Frolking S et al., 2014. Mapping Asian cropping intensity with MODIS.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(8): 3373-3379.
doi: 10.1109/JSTARS.2014.2344630 |
[23] |
Grekousis G, Mountrakis G, Kavouras M, 2015. An overview of 21 global and 43 regional land-cover mapping products.International Journal of Remote Sensing, 36(21): 5309-5335.
doi: 10.1080/01431161.2015.1093195 |
[24] |
He M, Huang Z, Zhang N, 2016. An empirical research on agricultural trade between China and “The Belt and Road” countries: Competitiveness and complementarity.Modern Economy, 7: 1671-1686.
doi: 10.4236/me.2016.714147 |
[25] |
He Y, Lee E, Warner T A, 2017. A time series of annual land use and land cover maps of China from 1982 to 2013 generated using AVHRR GIMMS NDVI3g data.Remote Sensing of Environment, 199: 201-217.
doi: 10.1016/j.rse.2017.07.010 |
[26] | Hong K, 2008. The impact of global food crisis on Southeast Asian countries and China’s countermeasures. Southeast Asian Studies,(6): 31-35, 84. (in Chinese) |
[27] |
Huang Y, 2016. Understanding China’s Belt & Road Initiative: Motivation, framework and assessment.China Economic Review, 40: 314-321.
doi: 10.1016/j.chieco.2016.07.007 |
[28] |
Islam M, Miah M, Inoue Y, 2016. Analysis of land use and land cover changes in the coastal area of Bangladesh using Landsat imagery.Land Degradation & Development, 27(4): 899-909.
doi: 10.1002/ldr.2339 |
[29] |
Kühling I, Broll G, Trautz D, 2016. Spatio-temporal analysis of agricultural land-use intensity across the western Siberian grain belt.Science of the Total Environment, 544: 271-280.
doi: 10.1016/j.scitotenv.2015.11.129 pmid: 26657373 |
[30] |
Lambin E F, Gibbs H K, Ferreira L et al., 2013. Estimating the world’s potentially available cropland using a bottom-up approach.Global Environmental Change, 23(5): 892-901.
doi: 10.1016/j.gloenvcha.2013.05.005 |
[31] | Li F, Dong S, Yuan L et al., 2016. Study on agriculture patterns and strategy of the Belt and Road.Bulletin of Chinese Academy of Sciences, 31(6): 678-688. (in Chinese) |
[32] | Li J, Mancini M, Su B et al., 2017. Monitoring water resources and water use from earth observation in the Belt and Road Countries.Bulletin of the Chinese Academy of Sciences, 32(Suppl.1): 62-73. |
[33] |
Li X, Wang X, 2003. Changes in agricultural land use in China: 1981-2000.Asian Geographer, 22(1/2): 27-42.
doi: 10.1080/10225706.2003.9684097 |
[34] |
Liu J, Kuang W, Zhang Z et al., 2014. Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s.Acta Geographica Sinica, 69(1): 3-14. (in Chinese)
doi: 10.1007/s11442-014-1082-6 |
[35] | Liu J, Peng S, Chen J et al., 2015. Knowledge based quality checking method and engineering practice of GlobeLand30 cropland data.Bulletin of Surveying and Mapping, (4): 42-48. (in Chinese) |
[36] | Liu J, Zhang Z, Xu X et al., 2009. Spatial patterns and driving forces of land use change in China in the early 21st century.Acta Geographica Sinica, 64(12): 1411-1420. (in Chinese) |
[37] |
Liu W, Dunford M, 2016. Inclusive globalization: Unpacking China’s Belt and Road Initiative.Area Development and Policy, 1(3): 323-340.
doi: 10.1080/23792949.2016.1232598 |
[38] |
Loayza N V, Raddatz C, 2010. The composition of growth matters for poverty alleviation.Journal of Development Economics, 93: 137-151.
doi: 10.1016/j.jdeveco.2009.03.008 |
[39] |
Lu M, Wu W, Zhang L et al., 2016. A comparative analysis of five global cropland datasets in China.Science China Earth Sciences, 59(12): 2307-2317.
doi: 10.1007/s11430-016-5327-3 |
[40] |
Lu M, Wu W, You L et al., 2017. A synergy cropland of China by fusing multiple existing maps and statistics.Sensors, 17(1613): 1-16.
doi: 10.1109/JSEN.2017.2761499 |
[41] |
Lu X, Huang X, Zhong T et al., 2011. A review of farmland fragmentation in China. Journal of Natural Resources, 26(3): 530-540. (in Chinese)
doi: 10.5814/j.issn.1674-764x.2013.04.007 |
[42] |
Meiyappan P, Roy P, Sharma Y et al., 2017. Dynamics and determinants of land change in India: Integrating satellite data with village socioeconomics.Reg. Environ. Change, 17(3): 753-766.
doi: 10.1007/s10113-016-1068-2 |
[43] |
Meyfroidt P, Schierhorn F, Prishchepov A et al., 2016. Drivers, constraints and trade-offs associated with recultivating abandoned cropland in Russia, Ukraine and Kazakhstan.Global Environmental Change, 37: 1-15.
doi: 10.1016/j.gloenvcha.2016.01.003 |
[44] |
Neumann K, Verburg P H, Stehfest E et al., 2010. The yield gap of global grain production: A spatial analysis.Agricultural Systems, 103(5): 316-326.
doi: 10.1016/j.agsy.2010.02.004 |
[45] |
Ramankutty N, Evan A T, Monfreda C et al., 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles,(22): GB1003. doi: 10.1029/2007GB002952.
doi: 10.1029/2007GB002952 |
[46] | Sudaryanto T, 2009. Policy response to the impact of global food crisis in Indonesia.Extension Bulletin - Food & Fertilizer Technology Center, (624): 1-10. |
[47] |
Tal A, 2016. Rethinking the sustainability of Israel’s irrigation practices in the drylands.Water Research, 90: 387-394.
doi: 10.1016/j.watres.2015.12.016 pmid: 26771161 |
[48] |
Wang L, Li C, Ying Q et al., 2012. China’s urban expansion from 1990 to 2010 determined with satellite remote sensing.Chinese Science Bulletin, 57(22): 2802-2812.
doi: 10.1007/s11434-012-5235-7 |
[49] | Wu F, Zhang H, 2017. China’s Global Quest for Resources: Energy, Food and Water. Oxon, New York: Routledge, 5-6. |
[50] | Wu L, Liu Q, Li L, 2009. A review of the progress of the national Green for Grain Project.Forestry Economics, 9: 21-37. doi: 10.13843/j.cnki.lyjj.2009.09.007. (in Chinese) |
[51] |
Wu W, Verburg P H, Tang H, 2014. Climate change and the food production system: Impacts and adaptation in China.Reg. Environ. Change, 14(1): 1-5.
doi: 10.1007/s10113-013-0528-1 |
[52] |
Wu W, Yu Q, Verburg P H et al., 2014. How could agricultural land systems contribute to raise food production under global change. Journal of Integrative Agriculture, 13(7): 1432-1442.
doi: 10.1016/S2095-3119(14)60819-4 |
[53] |
Wu W, Yu Q, You L et al., 2018. Global cropping intensity gaps: Increasing food production without cropland expansion.Land Use Policy, 76: 515-525.
doi: 10.1016/j.landusepol.2018.02.032 |
[54] |
Yan L, Roy D P, 2016. Conterminous United States crop field size quantification from multi-temporal Landsat data.Remote Sensing of Environment, 172: 67-86.
doi: 10.1016/j.rse.2015.10.034 |
[55] |
Yang D, Cai J, Hull V et al., 2016. New road for telecoupling global prosperity and ecological sustainability.Ecosystem Health and Sustainability, 2(10): e01242.
doi: 10.1002/ehs2.1242 |
[56] | Yang J, Sun J.2009. Probing into the food security issues in the Arabian countries.West Asia and Africa, (11): 33-40. (in Chinese) |
[57] |
Yu Q, Hu Q, van Vliet J et al., 2018. GlobeLand30 shows little cropland area loss but greater fragmentation in China.International Journal of Applied Earth Observation and Geoinformation, 66: 37-45.
doi: 10.1016/j.jag.2017.11.002 |
[58] |
Yu Q, van Vliet J, Verburg P H et al., 2018. Harvested area gaps in China between 1981 and 2010: Effects of climatic and land management factors.Environmental Research Letters, 13: 044006.
doi: 10.1088/1748-9326/aaafe0 |
[59] |
Yu Q, Wu W, Verburg P H et al., 2013. A survey-based exploration of land-system dynamics in an agricultural region of northeast China.Agricultural Systems, 121: 106-116.
doi: 10.1016/j.agsy.2013.06.006 |
[60] |
Zhang Y, Chen J, Chen L et al., 2015. Characteristics of land cover change in Siberia based on GlobeLand30, 2000-2010.Progress in Geography, 34(10): 1324-1333. (in Chinese)
doi: 10.18306/dlkxjz.2015.10.013 |
[61] | Zhang Y, Yang G, Yang Y, 2015. The Belt and Road strategy: To strengthen China and Central Asian agricultural cooperation opportunities.Transnational Business, (1): 31-43. (in Chinese) |
[62] |
Zhao W, 2012. Arable land change dynamics and their driving forces for the major countries of the world.Acta Ecologica Sinica, 32(20): 6452-6462. (in Chinese)
doi: 10.5846/stxb201203080314 |
[63] | Zou J, Liu C, Yin G et al., 2015. Spatial patterns and economic effects of China’s trade with countries along the Belt and Road.Progress in Geography, 34(5): 598-605. (in Chinese) |
[1] | XU Weiyi, JIN Xiaobin, LIU Jing, ZHOU Yinkang. Impact of cultivated land fragmentation on spatial heterogeneity of agricultural agglomeration in China [J]. Journal of Geographical Sciences, 2020, 30(10): 1571-1589. |
[2] | Yuanyuan LI, Minghong TAN, Haiguang HAO. The impact of global cropland changes on terrestrial ecosystem services value, 1992-2015 [J]. Journal of Geographical Sciences, 2019, 29(3): 323-333. |
[3] | Tian XIA, Wenbin WU, Qingbo ZHOU, Wenxia TAN, H. VERBURG Peter, Peng YANG, Liming YE. Modeling the spatio-temporal changes in land uses and its impacts on ecosystem services in Northeast China over 2000-2050 [J]. Journal of Geographical Sciences, 2018, 28(11): 1611-1625. |
[4] | Badabate DIWEDIGA, Sampson AGODZO, Kperkouma WALA, Quang Bao LE. Assessment of multifunctional landscapes dynamics in the mountainous basin of the Mo River (Togo, West Africa) [J]. Journal of Geographical Sciences, 2017, 27(5): 579-605. |
[5] | Guogang WANG, Yansui LIU, Yurui LI, Yangfen CHEN. Dynamic trends and driving forces of land use intensification of cultivated land in China [J]. Journal of Geographical Sciences, 2015, 25(1): 45-57. |
[6] | Chiwei XIAO, Peng Li, Zhiming FENG, Xingyuan WU. Spatio-temporal differences in cloud cover of Landsat-8 OLI observations across China during 2013-2016 [J]. Journal of Geographical Sciences, 2013, 28(4): 429-444. |
[7] | YANG Zhaoping, GAO Jixi, ZHOU Caiping, SHI Peili, ZHAO Lin, SHEN Wenshou, OUYANG Hua. Spatio-temporal changes of NDVI and its relation with climatic variables in the source regions of the Yangtze and Yellow rivers [J]. Journal of Geographical Sciences, 2011, 21(6): 979-993. |
[8] | WANG Fei, LI Rui, JIAO Feng, YANG Qingke, TIAN Junliang. The impact of cropland conversion on environmental effect in the Loess Plateau: a pilot study based on the national experimental bases [J]. Journal of Geographical Sciences, 2005, 15(4): 484-490. |
[9] | LI Shuangcheng, ZHOU Qiaofu, WANG Lei. Road construction and landscape fragmentation in China [J]. Journal of Geographical Sciences, 2005, 15(1): 123-128. |
|