Farmland Ecosystem

Chinese Cropland Quality and Its Temporal and Spatial Changes due to Urbanization in 2000-2015

  • WANG Chunyu 1, 2 ,
  • SUN Xiaofang , 1, * ,
  • WANG Meng 1 ,
  • WANG Junbang , 2, * ,
  • DING Qingfu 3
Expand
  • 1. College of Geography and Tourism, Qufu Normal University, Rizhao, Shandong 276826, China
  • 2. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 3. Shangdong Provincial Institute of Land Surveying and Mapping, Jinan 250013, China
*Corresponding author: SUN Xiaofang, E-mail: ; WANG Junbang, E-mail:

Received date: 2018-11-12

  Accepted date: 2019-01-20

  Online published: 2019-03-30

Supported by

National Key Research and Development Program of China (2017YFC0503803)

National Natural Science Foundation of China (41501428)

Humanities and Social Sciences Foundation of the Ministry of Education (16YJCZH098)

Copyright

All rights reserved

Abstract

The acceleration of urbanization has led to the occupation of more cropland, especially higher quality cropland, which could pose a huge threat to food security and have other implications for the inadequate cropland resource supply in China. Though the spatial status of Chinese cropland quality has been assessed, its temporal changes since 2000 to 2015 are still not clear. An accumulated probability distribution method was used to determine the criteria of cropland quality using the net primary production data product (MOD17) from Moderate Resolution Imaging Spectroradiometer (MODIS). Then the cropland quality of higher, median and lower production was spatially mapped and its changes due to occupation by urbanization were analyzed through the land use changes (LUCC) data primarily from Landsat TM images in the three periods of 2000-2005, 2005-2010, and 2010-2015. The results showed that of the total cropland reduction area the proportion taken by urbanization increased from 47.29% in the early stage to 77.46% in the recent period. The quality of Chinese cropland was dominated by low- and medium-yield fields, accounting for 40.81% and 48.74%, respectively, with high-yield fields accounting for only 10.44% of the total cropland in the country in 2000. The high-yield areas have been seriously threatened by the expansion of construction land fields, with the ratio of high-yield area to total area occupied by urbanization increasing from 9.71% in 2000-2005 to 15.63% in 2010-2015. Spatially, this phenomenon has been moving from eastern and southern China to central and western China, especially in Northwest China where the ratio has arrived at the highest proportion, with 52.97% of high-yield cropland in the total land taken by the expansion by 2015. This study not only provides a method to assess cropland quality but also reveals the threatening trend from the expansion of urbanization on high-quality cropland. More attention should be paid to the latter in land use planning and policies made to prevent threats to food security from declines in both cropland quantity and quality.

Cite this article

WANG Chunyu , SUN Xiaofang , WANG Meng , WANG Junbang , DING Qingfu . Chinese Cropland Quality and Its Temporal and Spatial Changes due to Urbanization in 2000-2015[J]. Journal of Resources and Ecology, 2019 , 10(2) : 174 -183 . DOI: 10.5814/j.issn.1674-764X.2019.02.008

1 Introduction

Cropland is the most valuable natural resource and it is also the most fundamental resource for agricultural production. Cropland quantity directly affects total grain yield, and its quality directly determines grain yield per unit area (Wu et al., 2010). Therefore, the decreasing quantity or quality of cropland will severely affect the effective supply of grain and the level of grain security of a country or region (Wu et al., 2010). Due to the uneven distribution of water and soil nutrients, most cropland has low to medium yields, and the reserve resources of cropland are limited and usually of relatively low quality (Xu et al., 2011). Since the 1990s due to the acceleration of industrialization and urbanization, the cropland area has shrunk significantly, and the occupation of more cropland with higher yield has resulted in the retention of lower-yield cropland in China (Li, 2011). Under the accelerated urbanization, it is essential to analyze and reveal the changes and trends of the quantity and quality of cropland on the national scale, which will promote the protection of cropland and ensure food security (Liu et al., 2009; Liu et al., 2014).
Much previous research has focused on the land use changes of cropland, grain production and its driving mechanisms, such as urbanization (Zhang et al., 2007; Zhao et al., 2014; Song et al., 2015; Chen, 2000; Liu et al., 2010; Cheng et al., 2010; Shi et al., 2016). Reducing high-yielding fields per unit area has a greater impact on grain production than reducing low-yielding fields, and the cropland quality and its evolution have always been hot research topics (Pan et al., 2015).
The main methods for evaluating cropland quality can be classified as agricultural productivity capacity evaluation, cropland potential evaluation, suitability evaluation, soil and environmental quality evaluation, sustainability evaluation and grading (Fu et al., 2015). Net Primary Productivity (NPP) refers to the total amount of organic dry matter accumulated by green plants per unit time and unit area (Field et al., 1998). The remotely sensed NPP is considered to reflect the actual production capacity of cropland, and it has become an effective and feasible method for dynamically monitoring and evaluating the yield level of cropland. For spatially explicit and temporally repeated remote sensing, this method not only clearly describes the regional heterogeneity of cropland, but also accurately compares the spatial differences among regions (Ji et al., 2015).
In this study, based on both remotely sensed NPP and land use change data, we quantitatively assessed the spatial-temporal changes and trends in the quantity and quality of cropland that had become occupied by urbanization from 2000 to 2015 in the nine regions of China. We aimed to accurately quantify the status, spatial characteristics and temporal trajectory of cropland quality in China and the results are expected to provide scientific support for policy making in the pursuit of the rational utilization of cropland resources while maintaining the balance between quantity and quality of cropland in China.

2 Data sources and methods

2.1 Data sources

The land use and cover change (LUCC) data based on Landsat and NPP data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used in this study. The LUCC data for 2000, 2005, 2010 and 2015 were provided by the land-use database of the Resources and Environment Scientific Data Center, Chinese Academy of Sciences (RESDC, http://www.resdc.cn). The data were visually interpreted from Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper (ETM) images and are of good quality with the user mapping accuracy above 94.3% for the six classes of land use, and the overall accuracy above 91.2% for the 25 subclasses on the 1: 100000 scale (Liu et al., 2003a; Liu et al., 2003b; Liu et al., 2010; Xu et al., 2012; Zhang et al., 2016). This database provided raster data with a spatial resolution of 1 km×1 km in four periods of land use status and corresponding changes in three periods of 2000-2005, 2005-2010 and 2010-2015 in this study.
The NPP data came from the MODIS land product MOD17A3 with a spatial resolution of 1×1 km2. MOD17A3 is based on the net photosynthetic rate (PsnNet) algorithm with inputs of re-analyzed meteorological data, and the LAI/FPAR product of MODIS, which has global annual estimates of NPP within 9.0% of average published results (Hasenauer et al., 2012; Smith et al., 2015; Zhao et al., 2005; Zhao et al., 2015). This is the annual composited data of terrestrial net primary productivity of the globe and has been widely used in the study of vegetation growth, biomass estimation, environmental monitoring and global change in different regions worldwide (Yu et al., 2018). Considering the available LUCC data for 2015, the NPP data for 2000 to 2015 were processed and matched with the LUCC data by the MODIS Reprojection Tool (MRT) for further analysis.

2.2 Methods

The method based on the probability distribution analysis of net primary production was developed and applied to quantify and assess the cropland quality and its changes. It is hypothesized that NPP has a normal probability distribution for a given district with relatively uniform land management and the differences among NPP values are mainly determined by the status of climate and soil, that is, cropland quality (Ji et al., 2015). Therefore, in the histogram of the frequency distribution of NPP in each district, the quality of cropland could be classified according to the distribution status of averaged NPP values. To eliminate the influences of the extreme values, we rejected the NPP before 5% and after 95% of the accumulated probability distribution, then divided the remaining values into three equal parts. The NPPs at the 35% and 65% positions of the accumulated probability distribution were defined as the critical values for the upper value of low-yield cropland and the lower value of high-yield cropland, respectively.
To avoid making disparate comparisons between favorable and harsh environments, a climate zone assessment was applied to define critical values for each zone. In this study, the upper NPP of lower yield cropland and the lower NPP of higher yield cropland were calculated for the nine regions in China (Table 1).
Table 1 The NPP (gC m-2 yr-1) criteria for defining higher, medium and lower yield cropland for the nine regions (climatic zones) in China
Region Upper value of low-yield cropland Lower value of high-yield cropland
Inner Mongolia 165.46 273.98
Northwest China 188.36 387.18
Tibetan Plateau 164.53 372.79
Southwest China 587.89 878.65
Central China 427.35 560.24
Northeast China 245.20 365.19
North China 245.29 446.07
Southeast China 437.17 654.33
South China 541.82 873.34

3 Results

3.1 Temporal and spatial patterns of cropland occupied by construction

As the top land cover type, the percentage of cropland that was occupied by construction land for urbanization and industrialization increased on the whole country level in the three periods of 2000 to 2005, 2005 to 2010, and 2010 to 2015 (Table 2). The cropland area decreased by 7320 km2, 5383 km2 and 1854 km2 and the proportional area occupied by construction land was 47.29%, 62.42% and 77.46% in the three periods in the whole country (Table 2). The cropland occupied by urbanization differed among the nine regions (climate zones), and the top three were Southeast China (80.69%), South China (68.10%) and North China (55.15%) during the three periods.
Table 2 The net change of cropland area (km2) and the area of cropland occupied by construction land expansion (km2) and its proportion (%) from 2000 to 2015
Region Net change in cropland area (km2) Cropland area occupied by
construction land (km2)
Proportion of cropland occupied
by construction land (%)
2000-2005 2005-2010 2010-2015 2000-2005 2005-2010 2010-2015 2000-2005 2005-2010 2010-2015
Inner Mongolia 11 358 -158 125 33 690 4.93 20.12 47.26
Northwest China 6092 2415 8372 357 128 1149 13.08 15.92 55.48
Tibetan Plateau -22 50 -79 35 10 79 27.78 45.45 81.44
Southwest China -1471 -1308 -2630 725 591 2349 32.51 42.98 80.86
Central China -1148 -572 -2020 351 393 1683 28.70 67.76 75.91
Northeast China 1222 311 1821 392 346 856 27.80 27.16 67.24
North China -5005 -2437 -2593 3537 1886 3137 55.15 69.13 86.39
Southeast China -4918 -3427 -3552 4608 3187 3916 80.69 89.15 89.30
South China -2081 -773 -1015 1477 491 1055 68.10 61.68 86.83
Total -7320 -5383 -1854 11607 7065 14914 47.29 62.42 77.46
In response to China's urbanization, the cropland was mainly occupied by construction land in the eastern coastal areas, but its spatial pattern showed a trend moving from the eastern coastal to central China during the period from 2000 to 2015 (Fig.1).
Fig. 1 The spatial pattern of cropland occupied by construction land expansion
Note: The number in legend is the maximum value for the bars.
In the early period from 2000 to 2005, the cropland occupied by construction land was mainly concentrated in Shanghai, Zhejiang and southern Jiangsu in Southeast China, in the Pearl River Delta in South China, and in Beijing, Tianjin, Hebei Province and Shandong Peninsula in North China. In middle period from 2005 to 2010, it spread widely with a radial pattern surrounding the cropland occupied in the previous period across the whole country.
In the recent period from 2010 to 2015, however, it shows a trend moving from coastal to inland China. For example, the cropland area occupied by construction land appears in northeast Guizhou and Sichuan Province of southwest China, west Gansu of Northwest China, and western Hubei and southern Hunan of Central China.

3.2 Spatial pattern of Cropland quality

Fig. 2 shows the spatial pattern of Chinese cropland quality in 2000, 2005, 2010 and 2015, and Fig. 3 shows the proportions of low-, medium- and high-yield cropland in each of the nine regions (climatic zones) of China in each of the four years.
Fig. 2 The spatial pattern of high-, medium- and low-yield cropland in China in 2000(a), 2005(b), 2010(c) and 2015(d).
Fig. 3 The proportions of high-, medium- and low-yield cropland of each sub-region (climate zone) in the total cropland area of China in 2000(a), 2005(b), 2010(c) and 2015(d).
Note: I M-Inner Mongolia; Nw C-Northwest China; TP-Tibetan Plateau; Sw C-Southwest China; C C-Central China; Ne C-Northeast China; N C-North China; Se C-Southeast China; S C-South China.
In 2000, the quality of cropland in the country was dominated by low- and medium-yield fields, accounting for 40.81% and 48.74% of the total cropland, respectively, with high-yield fields only representing 10.44%. The top three regions with larger areas of high yield fields are Northeast China, North China and Southeast China, which accounted for 2.07%, 2.06% and 1.69% of the total cropland area in China, respectively (Fig. 3a).
In 2005, the proportion of low-yield fields dropped sharply, while the medium- and high-yield fields increased to 56.61% and 17.97%, respectively (Fig. 3b). The most significant increases in the high-yield fields occurred in Northeast, North China and Inner Mongolia. Chinese cropland quality showed an improvement from 2000 to 2005, which is supported by other studies (Yang, 2014).
In 2010, however, the medium- and high-yield fields decreased by 1.24% and 2.19% respectively and Chinese cropland quality overall decreased compared to that in 2005. Specifically, the decline happened in the Northeast China and Southwest China, though some larger increases were seen in Southeast China and North China, and slight increases in Northwest China, South China and Central China (Fig. 3c).
In 2015, the high-yield fields increased by 22.69% while the low- and medium-yield fields decreased by 14.61% and 8.08%, respectively, when compared to 2010. The changes mainly took place in North China Plain and Northeast China Plain with more higher-yield fields, and western Loess Plateau and Yun-Gui Plateau with more low-yield fields (Fig. 3d). In North China Plain, it is interesting that more medium-yield cropland was transformed into high-yield cropland, which increased by 8.48%. Accounting for 14.58% of the total cropland area in China, this area became as the largest area of high-yield farmland in China during this period.

3.3 Changes of cropland quality for urbanization

There are many factors contributing to the changes of the cropland quality, and construction land expansion was further analyzed in this study. We found that the construction mainly occupied cropland with the quality of medium-yield in China in the period from 2000 to 2015 (Fig. 4; Fig. 5; Fig. 6). The medium-yield fields were occupied at about 54% compared to the low-yield fields at 36% and the high-yield fields at 10% in the three periods (Fig. 7).
Fig. 4 The spatial pattern of high-, medium- and low-yield cropland occupied by construction land expansion from 2000 to 2005
Note: The number in legend is the maximum value for the bars.
Fig. 5 The spatial pattern of high-, medium- and low-yield cropland occupied by construction land expansion from 2005 to 2010
Note: The number in legend is the maximum value for the bars.
Fig. 6 The spatial pattern of high-, medium- and low-yield cropland occupied by construction land expansion from 2010 to 2015.
Note: The number in legend is the maximum value for the bars.
Fig. 7 The proportion of high-, medium- and low-yield cropland occupied by construction land expansion in each sub-region (climate zone) from 2000 to 2015.
It should be highlighted that the high-quality cropland occupied by construction land increased 6.95% in the recent period from 2010 to 2015 compared to the first two periods. This change was mainly attributed to Northwest China (Fig.6). The cropland quality of North China showed improvement while the high-yield fields occupied by construction land expansion reached 52.97% and 50.99% compared to the first two periods. Though dominated by the occupation of medium-yield fields, the occupied high-yield fields increased by 9.02%, 2.42% and 2.69% in North China, Central China and Southeast China, respectively, compared with the previous period.

4 Discussion

4.1 Loss of cropland due to urbanization

The conflict between cropland and urban development has attracted much attention worldwide (Peng et al., 1998; Boland, 2000; López et al., 2001; Cai et al., 2002; Liu et al., 2005; Tan et al., 2005; Pan et al., 2017; Ju et al., 2018). In this study, in the three periods spanning 2000-2015, the proportion of cropland area occupied by construction land expansion within the total amount of cropland reduction in China was 47.29%, 62.42% and 77.46%, respectively. Another study reported it to be about 30% before 2000 and 71.1% in 2005-2010 (Ju et al., 2018). Though there are some uncertainties for the differences in the LUCC data source, the numbers of are relatively close among different studies and the obvious trend of cropland loss due to urbanization has become an increasingly important problem which cannot be ignored.

4.2 The changes of cropland quality

Traditionally, the term of “cropland quality” mainly refers to soil quality, however, it should be a more wholistic concept that is also determined by climate resources and management practices other than those related to soil quality, and it should also account for changes temporally. In this study the high-yield cropland in 2010 decreased 1.92% relative to that in 2005. Among its driving factors, climate change would be a considerable contributor in addition to the land taken by urbanization. Taking 2010 as an example, Southwest China was hit by the once-in-a-century drought which resulted in tremendous losses of its crop yields (Li et al., 2010; Hao et al., 2015;Wang et al., 2015) and led to the declining area in its high-yield cropland. The decline was also found in Northeast China with a decrease of 3.33%, and in Inner Mongolia with a decrease of 1.76%, which could be attributed to chilling damages (Yang et al., 2016).
On the other hand, the improvements in land use management could lead to the expansion of high-yield cropland. This could explain the overall increase of 22.69% in high-yield cropland area and the decrease of 14.61% and 8.08% in low- and medium-yield cropland area in the period from 2010 to 2015 relative to the previous period. These improved management practices include the basic work and pilot work of graded conversion in 2005 (Chen et al., 2009), the high suitability of new cropland in 2007 (Xu et al., 2015) and large-scale construction of high standard farmland for drought and flood protection in 2011 and 2013 (Xue et al., 2014) implemented by the Ministry of Land and Resources.

4.3 High-quality cropland threatened by urbanization

Urbanization has been considered as a great threat to Chinese agricultural production (Chen, 2007). In this study, we found that urbanization was increasingly occupying the high-quality cropland, from 9.7% and 8.7% in the first two periods to 15.6% in the third period, which was more severe and to a great extent than reported by others (Shi et al., 2013). Research in North China has found that more “above average” quality and irrigated cropland was converted to urban or other non-agricultural uses than was obtained by reclamation, and the rapid urbanization appears to be a potential threat to the food security of the area, and potentially even the whole of China (Shi et al., 2013).
As a serious world-wide problem, the projected urban area expansion will occupy some of the world’s higher quality croplands and pose a threat to future food systems and livelihoods, especially in mega-urban regions in Asia and Africa, according to the research on the global scale (Bren et al., 2016). In both Asia and Africa, much of the occupied cropland has more than twice the productivity compared with the national averages (Bren et al., 2016). In our study, we found that the area of the high-yield fields significantly decreased mainly due to the rapid urbanization in Suzhou, Wuxi, Changzhou and Shanghai in Southeast China in the period from 2010 to 2015. Therefore, future cropland conservation has to seek a reasonable urbanization mode to balance regional economic development and food security. The successful implementation of the National Strategic Plan on Revitalizing the Rural Area (2018﹣2022), which aims to mitigate poverty and integrate urban and rural development (Gain Report, 2018), would be a good way to approach this balance and is similar to the approach taken by Germany (Qu et al., 2012) .

4.4 Methods for cropland quality assessment

Remote sensing can provide land surface information that is spatially explicit and periodically revisited in a long time-series (for example, since the 1970s for Landsat) and can be used to monitor and assess cropland quality and its changes (Yan et al., 2009; Li, 2013; Olena et al., 2013; Qin et al., 2013; Liu et al., 2015; Shi et al., 2013). The MODIS based NPP used in this study can reflect the actual productivity of cropland, which is probably determined by climate, soil, hydrology, biology and human activities (Zhao et al., 2005; Zhao et al., 2010), and it has been widely used to detect the status of terrestrial ecosystem productivity, phenology changes and their responses to global climate changes (Li et al., 2016; Wang et al., 2017; Mathias et al., 2018; Robinson et al., 2018). Since it can capture the status of the cropping systems under different natural and human management conditions it was applied to grade cropland quality in each Chinese sub-region (climate zone).
A method was developed to determine the criteria for cropland quality based on an accumulated probability distribution of NPP in the climatic sub-regions, and grade high-, medium-, and low-yield fields. This approach was first suggested by Ji et al. (2015) and further developed in this study. Our results showed a good agreement with several previous studies, such as Zhang et al. (2011), Chen et al. (2011), Xu et al. (2015), Wei et al. (2015), Yan et al. (2016) and Ju et al. (2018). But this study is the first to provide a change in the proportion of cropland occupied by construction land expansion since 2000, though global climate changes would influence the quality of cropland and should be considered in the future.

5 Conclusions

Based on remotely sensed NPP and criteria determination from an accumulated probability distribution, this study mapped the cropland quality in China and analyzed its loss due to urbanization. The proportion of cropland occupied by construction land expansion in the total cropland reduction has continued to rise in the three periods spanning 2000﹣2015, and reached 77.46% in the last period. The expansion of construction land has become the dominant factor in the reduction of cropland. From 2000 to 2015 urbanization was occupying the high-quality cropland at an accelerated pace, from 9.7% and 8.7% in the first two periods to 15.6% in the third period. This trend was especiallly pronounced in Northwest China, where the ratio arrived the highest proportion, 52.97%, of high-yield cropland in the total land taken by the expansion by 2015. Therefore, future cropland conservation should seek a reasonable urbanization mode to balance regional economic development and food security and the successful implementation of the National Strategic Plan on Revitalizing the Rural Area (2018-2022) would be a good approach.

The authors have declared that no competing interests exist.

[1]
Boland A.2000. Feeding fears: competing discourses of interdependency, sovereignty, and China's food security.Political Geography, 19(1): 55-76.

[2]
Bren d’A, Christopher, Reitsma F, Baiocchi G, et al.2016. Future urban land expansion and implications for global croplands.Proceedings of the National Academy of Sciences of the United States of America, 114(34): 8939.

[3]
Cai Y, Fu Z, Dai E.2002. The minimum area per capita of cultivated land and its implication for the optimization of land resource allocation.Acta Geographica Sinica, 57(2): 127-134. (in Chinese)

[4]
Chen G, Cheng F, Su Q, et al.2009. Research progress on quantity and quality of supplementary cultivated land by grade conversion.Resources & Industries, 11(2): 5-7. (in Chinese)

[5]
Chen J.2007. Rapid urbanization in China: A real challenge to soil protection and food security.Catena, 69(1): 1-15.

[6]
Chen Y, Wang J, Xiao B, et al.2011. Trends in the change of cultivated land quality of China.Chinese Journal of Agricultural Resources and Regional Planning, 32(2): 1-5. (in Chinese)

[7]
Chen Y.2000. Arable-land use change and its effects on the grain production in China.Transactions of the Chinese Society of Agricultural Engineering, 16(6): 29-32. (in Chinese)

[8]
Cheng C, Yang X, Li Y, et al.2010. The effects of cultivated Land Change on regional potential productivity in China from 2005 to 2008.Geo-Information Science, 12(5): 620-627. (in Chinese)

[9]
Field C, Behrenfeld M, Randerson J, et al.1998. Primary production of the biosphere: integrating terrestrial and oceanic components.Science, 281(5374): 237-240.

[10]
Fu G, Bai W.2015. Advances and prospects of evaluating cultivated land quality.Resources Science, 37(2): 226-236. (in Chinese)

[11]
Hao C, Zhang J, Yao F.2015. Multivariate drought frequency estimation using copula method in Southwest China.Theoretical & Applied Climatology, 127(3-4): 1-15.

[12]
Hasenauer H, Petritsch R, Zhao M, et al.2012. Reconciling satellite with ground data to estimate forest productivity at national scales.Forest Ecology & Management, 276: 0-208.

[13]
Ji Y, Yan H, Liu J, et al.2015. A MODIS data derived spatial distribution of high-, medium- and low-yield cropland in China.Acta Geographica Sinica, 70(5): 766-778. (in Chinese)

[14]
Ju H, Zhang Z, Zhao X, et al.2018. The changing patterns of cropland conversion to built-up land in China from 1987 to 2010.Journal of Geographical Sciences, 28(11): 1595-1610.

[15]
Kim Michael Ward, Gene.2018. China's Annual Agricultural Policy Goals The 2018 No.1 Document of the CCCPC and the State Council.GAIN Report, 2018-02-03

[16]
Li Q, Yan N, Zhang F, et al.2010. Drought Monitoring and Its Impacts Assessment in Southwest China Using Remote Sensing in the Spring of 2010.Acta Geographica Sinica, 65(7): 771-780. (in Chinese)

[17]
Li W.2011. Spatial-temporal characteristics of the effect of urbanization on cultivated land in Zhejiang Province.China Land Science, 25(5): 50-55. (in Chinese)

[18]
Li X.2013. Prospects on future developments of quantitative remote sensing.Acta Geographica Sinica, 68(9): 1163-1169. (in Chinese)

[19]
Li Z, Chen Y, Wang Y, et al.2016. Dynamic changes in terrestrial net primary production and their effects on evapotranspiration.Hydrology and Earth System Sciences, 20(6): 2169-2178.

[20]
Liu G, Zhang L, Zhang Q, et al.2015. The response of grain production to changes in quantity and quality of cropland in Yangtze River Delta, China.J Sci Food Agric, 95(3): 480-489.

[21]
Liu J, Liu M, Zhuang D, et al. 2003a. Study on spatial pattern of land-use change in China during 1995-2000. Science in China Series D: Earth Sciences, 2003, 46(4): 373-384.

[22]
Liu J, Zhan J, Deng X.2005. Spatio-temporal patterns and driving forces of urban land expansion in China during the economic reform era.Ambio, 34(6): 450-455.

[23]
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)

[24]
Liu J, Zhang Z, Xu X, et al.2010. Spatial patterns and driving forces of land use change in China during the early 21st century. Journal of Geographical Sciences, 20(4): 483-494.

[25]
Liu J, Zhang Z, Zhuang D, et al.2003b. A study on the spatial-temporal dynamic changes of land-use and driving forces analyses of China in the 1990s.Geographica Research, 6(3): 38-42.

[26]
Liu L, Xu X, Liu J, et al.2014. Impact of farmland changes on production potential in China during recent two decades.Acta Geographica Sinica, 69(12): 1767-1778. (in Chinese)

[27]
Liu Y, Zhang Y, Guo L.2010. Towards realistic assessment of cultivated land quality in an ecologically fragile environment: A satellite imagery-based approach.Applied Geography, 30(2): 271-281.

[28]
López T, Aide T, Thomlinson J.2001. Urban expansion and the loss of prime agricultural lands in Puerto Rico.Ambio, 30(1): 49-54.

[29]
Mathias N, Smith P.2018. Carbon uptake by European agricultural land is variable, and in many regions could be increased: Evidence from remote sensing, yield statistics and models of potential productivity.Science of The Total Environment, 643: 902-911.

[30]
Olena D, Gunter M, Christopher 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 & Assessment, 185(6): 4775-4790.

[31]
Pan P, Wang X, Yang G, et al.2015. Research on temporal and spatial variation of cultivated land quality in the region with rapid development.Geography and Geo-Information Science, 31(4): 65-70. (in Chinese)

[32]
Pan P, Yang G, Wang X, et al.2017. Research on spatial heterogeneity of cropland change rapid economic development area.Resource and Encironment in the Yangtze Basin, 26(10): 1587-1596. (in Chinese)

[33]
Peng C, Coomes O.1998. Feeding and fueling China in the 21st century.World Development,26(8): 1413-1429.

[34]
Qin Y, Yan H, Liu J, et al.2013. Impacts of ecological restoration projects on agricultural productivity in China.Acta Geographica Sinica, 23(3): 404-416.

[35]
Qu W, Spindler K.2012. Implication of village renewal planning in Germany.China Land Sciences.

[36]
Robinson N, Allred B, Smith W, et al.2018. Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m.Remote Sensing in Ecology & Conservation.

[37]
Shi K, Chen Y, Yu B, et al.2016. Urban expansion and agricultural land loss in China: A Multiscale Perspective.Sustainability, 8(8): 790.

[38]
Shi W, Tao F, Liu J.2013. Changes in quantity and quality of cropland and the implications for grain production in the Huang-Huai-Hai Plain of China.Food Security, 5(1): 69-82.

[39]
Smith W K, Zhao M, Running S W.2015. Global bioenergy capacity as constrained by observed biospheric productivity rates.Bioscience, 62(10): 07.

[40]
Song W, Pijanowski B, Tayyebi A.2015. Urban expansion and its consumption of high-quality farmland in Beijing, China.Ecological Indicators, 54(54): 60-70.

[41]
Tan M, Li X, Lu C.2005. Urban land expansion and arable land loss of the major cities in China in the 1990s.Science in China, 48(9): 1492-1500.

[42]
Wang J, Dong J, Yi Y, et al.2017. Decreasing net primary production due to drought and slight decreases in solar radiation in China from 2000 to 2012.Journal of Geophysical Research: Biogeosciences, 122(1): 261-278.

[43]
Wang L, Chen W, Zhou W, et al.2015. Drought in Southwest China: A Review.Atmospheric & Oceanic Science Letters, 8(6): 339-344.

[44]
Wei H, Wu K, Zhao H, et al.2015. Spatial distribution characteristics of cultivated land quality gradation in the main grain production area of central China.Resources Science, 37(8): 1552-1560. (in Chinese)

[45]
Wu D, Liu Y, Dong Y, et al.2010. Review on the research of quantity, quality and spatial change of cultivated land in China.Tropical Geography, 30(2): 108-113. (in Chinese)

[46]
Xu H, Huang X, Zhao R, et al.2011. Study on the emergy analysis and efficiency and sustainability evaluation of the coastal region cultivated land system in Jiangsu province.Journal of Natural Resources, (2): 247-257. (in Chinese)

[47]
Xue J, Han J, Zhang F, et al.2014. Development of evaluation model and determination of its construction sequence for well-facilitied capital farmland. Transactions of the Chinese Society of Agricultural Engineering, 30 (5): 193-203(111).

[48]
Xu L, Li B, Yuan Y, et al.2015. Changes in China’s cultivated land and the evaluation of land requisition-compensation balance policy from 2000 to 2010.Resources Science, 37(8): 1543-1551. (in Chinese)

[49]
Xu X, Liu J, Zhuang D.2012. Remote Sensing Monitoring Methods of Land Use/Cover Change in National Scale.Journal of Anhui Agriculture, 40(4): 2365-2369. (in Chinese)

[50]
Yan H, Ji Y, Liu J, et al.2016. Potential promoted productivity and spatial patterns of medium-and low-yield cropland land in China.Journal of Geographical Sciences, 26(3): 259-271.

[51]
Yan H, Liu J, Huang H, et al.2009. Assessing the consequence of land use change on agricultural productivity in China.Global & Planetary Change, 67(1): 13-19.

[52]
Yang R, Chen Y.2014. Analysis of quality of cultivated and land change trend in northeast area.Chinese Journal of Agricultural Resources and Regional Planning, 35(6): 19-24. (in Chinese)

[53]
Yang R, Zhou G.2016. Spatio-temporal distribution of maize chilling damage intensity in the Three Provinces of Northeast China During 1961 to 2013.Acta Ecologica Sinica, 36(14): 4386-4394. (in Chinese)

[54]
Yu H, Yu H2018. Analysis of vegetation ecological variation in Fujian Province based on MODIS data.Journal of Subtropical Resources and Environment, 13( 3) : 82-87. (in Chinese)

[55]
Zhang L, Zhang F, Xue Y, et al.2007. Forecasting the balance between occupation and complementarity of cultivated land by provinces in China.Resources Science, 29(6): 114-119. (in Chinese)

[56]
Zhang Y, Zhang H, Li X.2011. The changes on quality and production capacity of farmland in the main agricultural regions during recent 20 years.Geography and Geo-Information Science, 27(4): 52-56. (in Chinese)

[57]
Zhang Z, Wang X, Wen Q, et al.2016. Research progress of remote sensing application in land resources.Journal of Remote Sensing, 20(5): 1243-1258. (in Chinese)

[58]
Zhao M, Heinsch F, Nemani R, et al.2005. Improvements of the MODIS terrestrial gross and net primary production global data set.Remote Sensing of Environment, 95(2): 164-176.

[59]
Zhao M, Running S W, Nemani R R.2015. Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses.Journal of Geophysical Research Biogeosciences, 111(G1): 338-356.

[60]
Zhao M, Running S W.2010. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009.Science, 329(5994): 940-943.

[61]
Zhao X, Zhang Z, Wang X, et al.2014. Analysis of Chinese cultivated land’s spatial-temporal changes and causes in recent 30 years.Transactions of the Chinese Society of Agricultural Engineering, 30(3): 1-11. (in Chinese)

Outlines

/