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Modeling the Spatiotemporal Distribution
of Agricultural-Feasible Land in China
Fei Carnes
Center for Geographic Analysis, Harvard University
Weihe Wendy Guan [email protected]
Kang Wu [email protected]
Fei Carnes [email protected]
2016 ESRI USER CONFERENCE
mailto:[email protected]:[email protected]:[email protected]
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Research Questions:
• Where are agricultural-feasible lands in China?
• How feasible to agriculture the land is naturally, in different parts of China?
• Where are lands lost to urbanization in the recent decades?
• How feasible these urban-claimed lands are to agriculture?
• How severe this lose is in different parts of China, over the recent decades?
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Datasets Used for Agricultural Feasibility Analysis
Model factors Variables Data Source Source Data Year
Climate
Accumulated
temperature ≥10℃CAS 1981-1990 average
Sunshine hours CAAS 1991-2000 average
Hydrology
Annual rainfall (ml) CAS 1991-2000 average
Distance to rivers (m)USGS (derived from
River vectors)-
Soil
Soil PH FAO GeoNetwork 2007
Soil depth (cm) FAO GeoNetwork 2007
Soil moisture storage
capacity (mm/m)FAO GeoNetwork 2007
Topography
Elevation USGS -
SlopeUSGS (derived from
Elevation raster)-
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Derived data layers and fuzzy variables weight for
agricultural feasibility analysis
Factors Weight1 Fuzzy variables Weight2
Hydrology 0.3Fuzzy annual rainfall 1
Fuzzy distance to rivers 0.4
Climate 0.3Fuzzy accumulated temperature ≥10℃ 0.75
Fuzzy sunshine hours 0.25
Soil 0.2
Fuzzy soil PH 0.2
Fuzzy soil Depth 0.4
Fuzzy soil Moisture Storage Capacity 0.4
Topography 0.2Fuzzy elevation 0.25
Fuzzy slope 0.75
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Fuzzy methods for continuous data
Annual
Precipitation
Accumulated
Temperature>=10°C
Elevation SlopeDistance to River
within 30,000 metersSunshine Hour
Sigmoidal
increasing
0 1500ml
FuzzyLarge
0 30,000m
Linear
0 max
Linear
Fuzzy
Precipitation
Fuzzy
Temperature
Fuzzy
ElevationFuzzy
SlopeFuzzy
Distance to River
Fuzzy
Sunshine hour
2400 °C (midpoint)
0.5
-153 7227m
Sigmoidal decreasing
15 (midpoint)
FuzzySmall
0.5
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Fuzzy methods for categorical data
Soil
DepthSoil Moisture Storage Capacity
Fuzzy Soil PH Fuzzy Soil Moisture Storage Capacity
8.5
Non-soil (water, Rock..)
[4.5, 5.5) or [7.2,8.5)
0.2
0.5
0
[5.5, 7.2] 1
Old Values New Values
Fuzzy Soil Depth
Shallow (10-50cm)
Very shallow (
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Agricultural feasibility indexes across China
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Version 4 DMSP-OLS Nighttime Lights Time Series
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Average Visible, Stable Lights, & Cloud Free Coverages
Year\Sat. F10 F12 F14 F15 F16 F18
1992 F101992 ------- ------- ------- ------- -------
1993 F101993 ------- ------- ------- ------- -------
1994 F101994 F121994 ------- ------- ------- -------
1995 ------- F121995 ------- ------- ------- -------
1996 ------- F121996 ------- ------- ------- -------
1997 ------- F121997 F141997 ------- ------- -------
1998 ------- F121998 F141998 ------- ------- -------
1999 ------- F121999 F141999 ------- ------- -------
2000 ------- ------- F142000 F152000 ------- -------
2001 ------- ------- F142001 F152001 ------- -------
2002 ------- ------- F142002 F152002 ------- -------
2003 ------- ------- F142003 F152003 ------- -------
2004 ------- ------- ------- F152004 F162004 -------
2005 ------- ------- ------- F152005 F162005 -------
2006 ------- ------- ------- F152006 F162006 -------
2007 ------- ------- ------- F152007 F162007 -------
2008 ------- ------- ------- ------- F162008 -------
2009 ------- ------- ------- ------- F162009 -------
2010 ------- ------- ------- ------- ------- F182010
2011 ------- ------- ------- ------- ------- F182011
2012 ------- ------- ------- ------- ------- F182012
2013 ------- ------- ------- ------- ------- F182013
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South of Beijing where night
light pixel value equals 9 in 2013
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Southwest of Beijing where night
light pixel value equals 20 in 2013
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South of Beijing where night light
pixel value equals 32 in 2013
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West of Tianjin where night light
pixel value equals 41 in 2013
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Southwest of Tianjin where night
light pixel value equals 50 in 2013
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Night light pixel values as indications of percentage of
constructed land cover
Pixel Value % Land Constructed
0-5 0
5-10 10
10-15 20
15-20 30
20-25 40
25-30 50
30-35 60
35-40 70
40-45 80
45-50 90
50-63 100
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Reclassification of the agricultural feasibility index
values into 11 integer
From To New
0.144929662 0.216596265 0
0.216596265 0.288262867 1
0.288262867 0.359929469 2
0.359929469 0.431596072 3
0.431596072 0.503262674 4
0.503262674 0.574929277 5
0.574929277 0.646595879 6
0.646595879 0.718262481 7
0.718262481 0.789929084 8
0.789929084 0.861595686 9
0.861595686 0.933262289 10
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The change in number of pixels
belonging to each combination of
night light brightness and agricultural
feasibility class between 1992 and
2013.
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From To New
0 5 10
5 10 9
10 15 8
15 20 7
20 25 6
25 30 5
30 35 4
35 40 3
40 45 2
45 50 1
50 63 0
Reclassification of night light brightness into parts
per tenth of non-constructed land
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Agriculture Potentials in 1992
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Agriculture Potentials in 2002
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Agriculture Potentials in 2013
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Country-wide summary of pixel values from the agricultural
potentials layers
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Losses of Agriculture Potentials between 1992 and 2013
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Province From_Year To_Year Count Min Mas Range Mean STD Sum Variety Majority Minority Mediam
Shanghai 1992 2013 4802 0 90 90 46.8155 26.5263 224808 26 72 48 54
Jiangsu 1992 2013 105452 -9 100 109 25.6562 25.3732 2705501 39 9 25 16
Tianjin 1992 2013 12092 -7 70 77 22.6532 18.7344 273922 18 7 36 14
Zhejiang 1992 2013 101003 -10 100 110 16.3282 25.4416 1649194 32 0 35 0
Beijing 1992 2013 17628 -28 63 91 13.9859 18.6537 246543 27 0 -28 6
Shandong 1992 2013 157498 -49 80 129 13.3835 14.9683 2107878 43 7 -49 7
Guangdong 1992 2013 176268 -30 100 130 11.9757 20.6134 2110934 25 0 -30 0
Taiwan 1992 2013 32631 -45 81 126 10.3790 16.0567 338676 42 0 -32 0
Anhui 1992 2013 150868 -20 100 120 8.8347 16.2665 1332875 41 0 -20 0
Henan 1992 2013 178096 -36 90 126 8.5545 12.8528 1523514 57 0 -36 7
Fujian 1992 2013 123530 -60 100 160 7.8114 17.3658 964937 31 0 -60 0
Hebei 1992 2013 200022 -48 70 118 7.1837 11.6813 1436906 46 0 -4 0
Hainan 1992 2013 31719 -63 100 163 6.4025 13.7842 203080 33 0 -50 0
Chongqing 1992 2013 88703 -27 90 117 4.7235 13.5144 418987 33 0 80 0
Hubei 1992 2013 200091 -56 100 156 4.6597 12.2978 932361 49 0 -56 0
Liaoning 1992 2013 149214 -35 72 107 4.4500 10.0128 664007 38 0 15 0
Shanxi 1992 2013 168294 -70 70 140 4.4219 9.9627 744175 52 0 -63 0
Hongkong 1992 2013 98 -10 40 50 4.2857 8.6897 420 6 0 -10 0
Jiangxi 1992 2013 179708 -30 100 130 3.9930 12.5034 717577 42 0 -27 0
Shaanxi 1992 2013 221524 -28 72 100 3.7333 9.6264 827010 44 0 50 0
Hunan 1992 2013 228143 -60 100 160 3.6643 11.2766 835987 44 0 -60 0
Ningxia 1992 2013 55823 -35 70 105 3.5491 9.9876 198122 45 0 -35 0
Guangxi 1992 2013 249010 -50 100 150 3.3098 10.0354 824161 35 0 7 0
Guizhou 1992 2013 189283 -56 90 146 2.5015 8.9506 473494 50 0 -27 0
Jilin 1992 2013 201052 -35 72 107 2.4075 7.4854 484027 38 0 -35 0
Yunnan 1992 2013 400232 -63 100 163 2.1435 8.3204 857879 60 0 -63 0
Heilongjiang 1992 2013 477205 -35 70 105 2.1043 6.1230 1004167 45 0 -30 0
Sichuan 1992 2013 520460 -45 90 135 1.9169 8.2099 997657 52 0 -5 0
Gansu 1992 2013 435864 -20 70 90 0.8593 4.3509 374528 46 0 27 0
Neimenggu 1992 2013 1215493 -42 70 112 0.6377 4.0490 775095 51 0 -30 0
Xinjiang 1992 2013 1736719 -70 70 140 0.3971 3.3192 689592 65 0 -40 0
Qinghai 1992 2013 770050 -50 60 110 0.1191 1.7436 91701 47 0 -50 0
Xizang 1992 2013 1278149 -8 50 58 0.0215 0.6235 27490 33 0 -2 0
Statistical summary of the loss of agriculture potentials
between 1992 and 2013 by provinces
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Average Losses of Agriculture Potentials by
Province, 1992-2013
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• This study is partially sponsored by:
- The Lee and Juliet Folger Fund,
- Fairbank Center for Chinese Studies, Harvard University, and
- Natural Science Foundation of China (grant No. 41401178).
• Dr. Yu Deng, Visiting Fellow of the Harvard John A. Paulson
School of Engineering and Applied Sciences (2012-2013),
provided the temperature, sunshine and rainfall data from the
Chinese Academy of Sciences.
Acknowledgements
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Thanks!
Questions?
Modeling the Spatiotemporal Distribution of
Agricultural-Feasible Land in China
Weihe Wendy Guan [email protected]
Kang Wu [email protected]
Fei Carnes [email protected]
Center for Geographic Analysis, Harvard University
mailto:[email protected]:[email protected]:[email protected]