Huajun Tang

Application of fuzzy logic to land suitability for rubber production in peninsular Thailand

Abstract This paper aims to determine the quantitative impact of land qualities on rubber production, using the theory of fuzzy logic. This theory is applied in a land suitability assessment for rubber production in the northern part of the rubber growing area of peninsular Thailand. The proposed method differs from the usual technical land evaluation procedures by (1) the use of an explicit weight for the effect of each land quality on crop performance, and (2) the way of combining the evaluation of land qualities into a final land suitability class or land suitability index. The methodology was tested by comparing the estimated yields and land indices calculated by fuzzy set theory with those obtained by conventional procedures: (1) maximum limitation method; (2) parametric-Storie method, and (3) multiple linear regression. In the last approach the land index is replaced by the predicted relative yield from multiple regression on the various land qualities. The considered rubber clone, RRIM 600 is grown on a wide range of soils under different climatic conditions. The best relationship is given by the fuzzy set approach, which illustrates the potential usefulness of this theory in land evaluation.

Mapping Single‐, Double‐, and Triple‐crop Agriculture in China at 0.5° × 0.5° by Combining County‐scale Census Data with a Remote Sensing‐derived Land Cover Map

Abstract Assessments of agriculture at the national scale require the best possible information on the distribution of cropland and the management of that cropland. Official cropland statistics for China contain much information on the distribution of crop types, but are known to underestimate total cropland area and are generally at coarse spatial resolution. Remote sensing products can provide moderate to fine spatial resolution estimates of cropland location and extent, but usually supply little information on crop type or management. We combined 1990 county‐scale agricultural census statistics on total cropland area and sown area of 17 major crops with a fine‐resolution land‐cover map derived from 1995‐96 optical remote sensing (Landsat Thematic Mapper) data to generate 0.5° resolution maps of the distribution of 47 different single‐ and multi‐crop rotations in mainland China. We estimated that, of 1.3‐million km2 of cropland, approximately 60% was single‐cropped, 30% was double‐cropped, and 10% was triple‐cropped. Total sown or planted area was 2.0‐million km2.

Evaluation of MODIS Land Cover and LAI Products in Cropland of North China Plain Using In Situ Measurements and Landsat TM Images

Global maps of land cover and leaf area index (LAI) from the moderate resolution imaging spectroradiometer (MODIS) are available from the earth resources observation system data center. Validation of these MODIS terrestrial products is crucial for scientific research. Numerous pre- and postlaunch validation activities have been completed during the last several years. However, such work was mainly located in North America, Europe, and Africa. The validated vegetation types were principally focused on woodland and savanna. In this paper, we evaluated the Collection 3 MODIS land cover (MOD12Q1) and the Collection 4 MODIS LAI (MOD15A2) products in the North China Plain (NCP). We placed the emphasis on croplands by: (1) developing an accurate land cover map, based on the MODIS LAI/fraction of photosynthetically active radiation land cover classification scheme; (2) deriving empirical LAI validation maps, based on in situ measurement and landsat thematic mapper imagery; and (3) conducting an initial MODIS validation exercise to assess the quality of MODIS products. The results indicate that an apparent misclassification exists between grasses/cereal crop and broadleaf crop biomes in the MODIS land cover product. Although MODIS LAI could resemble the general pattern of the LAI seasonal vegetation variation in the NCP, the MODIS LAI algorithm markedly underestimated LAI values (down to 2-3 m2/m2) for the April 2004 winter wheat cropland. Biome misclassification and the atmospheric effect of cloud or aerosol were proven to decrease the value of MODIS LAI, but these impacts cannot fully explain the significant underestimation. Additional studies are needed to understand the main reasons for this underestimation in the study area.

Climate change and the food production system: impacts and adaptation in China

China has received a lot of attention from both the scientific and policy community in its ability to maintain selfreliance in food supply (Verburg et al. 2000; Yang and Li 2000; Yu et al. 2012). Advances in technology and changing agronomic practices have been responsible for significant increases in food production in China over past several decades (Xiong et al. 2012). Yet, since the 1980s, the unprecedented growth of both the economy and the population has led to a decrease in the area of cropland (Deng et al. 2006; He et al. 2013). The growing competition for land, water, and energy, and the overexploitation of fisheries, seriously impairs the production of food. Global environmental change, particularly climate change, makes the situation more challenging. Changes in climate may have implications for climate-sensitive systems such as agriculture, forestry, and other natural resources (Wu et al. 2011; Verburg et al. 2013). China is among the most affected countries by climate change (Ye et al. 2012). Continuous measurements from meteorological stations show that there is a strong warming of China over the past five decades and the temperature has increased by 1.2 C since 1960, which is much higher than the overall rate of global surface temperature change (Piao et al. 2010). Although there is no observed significant longterm trend in country-average precipitation since 1960, there are significant regional precipitation trends. The drier regions of northeastern China (including North China and Northeast China) are receiving less and less precipitation in summer and autumn (a 12 % decline since 1960). By contrast, the wetter region of southern China is experiencing more rainfall during both summer and winter. As for future projections, climate models tell us unambiguously that the warming trend will continue, and China’s average temperature is estimated to increase further by 1–5 C by 2100. This acceleration in temperature warming and its associated changes in precipitation have affected agriculture and food production in China. One of the greatest challenges for China in the twenty-first century will be to ensure that the food supply sustainably meets the needs of the population despite the necessary adaptations to climate change. Meeting this task will require technical and institutional innovations that increase food production and facilitate adaptation to changing climatic conditions. Climate change affects agriculture and the food production system in many ways (Godfray et al. 2011). Changes in climatic variables drive changes in overall food production through interacting effects on crop yields and crop areas. Although there has been much research to investigate the impacts of climate change on crop/food production (Barry and Cai 1996; Chen et al. 2013; Li et al. 2011, 2005; Piao et al. 2010; Wang et al. 2009; Zhang and Huang 2012), these studies are generally either focused on a single aspect of the interactions between climate change and food production or are performed in specific small regions. This causes some inconsistency in assessment results of climate change impacts, and well-recognized conclusions are therefore unavailable (Yang et al. 2013). W. Wu H. Tang Key Laboratory of Agri-Informatics, Ministry of Agriculture of China, Beijing 100081, China e-mail: wuwenbin@caas.cn

Characterizing spatial patterns of phenology in cropland of China based on remotely sensed data.

Abstract This study used time-series of global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) datasets at a spatial resolution of 8 km and 15-d interval to investigate the spatial patterns of cropland phenology in China. A smoothing algorithm based on an asymmetric Gaussian function was first performed on NDVI dataset to minimize the effects of anomalous values caused by atmospheric haze and cloud contamination. Subsequent processing for identifying cropping systems and extracting phenological parameters, the starting date of growing season (SGS) and the ending date of growing season (EGS) was based on the smoothed NVDI time-series data. The results showed that the cropping systems in China became complex as moving from north to south of China. Under these cropping systems, the SGS and EGS for the first growing season varied largely over space, and those regions with multiple cropping systems generally presented a significant advanced SGS and EGS than the regions with single cropping patterns. On the contrary, the phenological events of the second growing season including both the SGS and EGS showed little difference between regions. The spatial patterns of cropping systems and phenology in Chinese cropland were highly related to the geophysical environmental factors. Several anthropogenic factors, such as crop variety, cultivation levels, irrigation, and fertilizers, could profoundly influence crop phenological status. How to discriminate the impacts of biophysical forces and anthropogenic drivers on phenological events of cultivation remains a great challenge for further studies.

An approach to predict land production potential for irrigated and rainfed winter wheat in Pinan county, China

Abstract The methodology described in this paper provides land evaluators and land use planners with a tool to predict the land production potential for irrigated and rainfed winter wheat in Pinan County (China), taking into account environmental conditions and management practices of the local farmers. The correlation between predicted yields and actual reported yields by local farmers suggests a close resemblance between the simulated production environment and the situation in which the farmers operate. Incorporation in the model of quantified effects of limiting factors on crop performance allows estimation of inputs necessary to improve the actual yield level.

Change analysis of rice area and production in China during the past three decades

Rice’s spatial-temporal distributions, which are critical for agricultural, environmental and food security research, are affected by natural conditions as well as socio-economic developments. Based on multi-source data, an effective model named the Spatial Production Allocation Model (SPAM) which integrates arable land distribution, administrative unit statistics of crop data, agricultural irrigation data and crop suitability data, was used to get a series of spatial distributions of rice area and production with 10-km pixels at a national scale — it was applied from the early 1980s onwards and used to analyze the pattern of spatial and temporal changes. The results show that significant changes occurred in rice in China during 1980–2010. Overall, more than 50% of the rice area decreased, while nearly 70% of rice production increased in the change region during 1980–2010. Spatially, most of the increased area and production were in Northeast China, especially, in Jilin and Heilongjiang; most of the decreased area and production were located in Southeast China, especially, in regions of rapidly urbanization in Guangdong, Fujian and Zhejiang. Thus, the centroid of rice area was moved northeast approximately 230 km since 1980, and rice production about 320 km, which means rice production moved northeastward faster than rice area because of the significant rice yield increase in Northeast China. The results also show that rice area change had a decisive impact on rice production change. About 54.5% of the increase in rice production is due to the expansion of sown area, while around 83.2% of the decrease in rice production is due to contraction of rice area. This implies that rice production increase may be due to area expansion and other non-area factors, but reduced rice production could largely be attributed to rice area decrease.

Spatio-temporal responses of cropland phenophases to climate change in Northeast China

We investigated the responses of cropland phenophases to changes of agricultural thermal conditions in Northeast China using the SPOT-VGT Normalized Difference Vegetation Index (NDVI) ten-day-composed time-series data, observed crop phenophases and the climate data collected from 1990 to 2010. First, the phenological parameters, such as the dates of onset-of-growth, peak-of-growth and end-of-growth as well as the length of the growing season, were extracted from the smoothed NVDI time-series dataset and showed an obvious correlation with the observed crop phenophases, including the stages of seedling, heading, maturity and the length of the growth period. Secondly, the spatio-temporal trends of the major thermal conditions (the first date of ⩾ 10°C, the first frost date, the length of the temperature-allowing growth period and the accumulated temperature (AT) of ⩾ 10°C) in Northeast China were illustrated and analyzed over the past 20 years. Thirdly, we focused on the responses of cropland phenophases to the thermal conditions changes. The results showed that the onset-of-growth date had an obvious positive correlation with the first date of ⩾ 10°C (P < 0.01), especially in the northern part of the Songnen Plain, the eastern part of the Sanjiang Plain and the middle and eastern parts of Jilin Province. For the extracted length of growing season and the observed growth period, notable correlations were found in almost same regions (P < 0.05). However, there was no obvious correlation between the end-of-growth date and the first frost date in the study area. Opposite correlations were observed between the length of the growing season and the AT of ⩾ 10°C. In the northern part of the Songnen Plain, the eastern part of the Sanjiang Plain and the middle part of Jilin and Liaoning Provinces, the positive correlation coefficients were higher than the critical value of 0.05, whereas the negative correlation coefficients reached a level of 0.55 (P < 0.05) in the middle and southern parts of Heilongjiang Province and some parts of the Sanjiang Plain. This finding indicated that the crop growth periods were shortened because of the elevated temperature; in contrast, the extended growth period usually meant a crop transformation from early- or middle-maturing varieties into middle or late ones.

Modeling the Impacts of Soil Organic Carbon Content of Croplands on Crop Yields in China

Abstract This study quantified the impacts of soil organic carbon (SOC) content on the grain yield of crops using a biogeochemical model (DNDC, denitrification-decomposition). Data on climate, soil properties, and farming management regimes of cropping systems were collected from six typical agricultural zones (northeast, north, northwest, mid-south, east and southwest regions of China, respectively) and integrated into a GIS database to support the model runs. According to the model, if the initial SOC content in the cropland was increased by 1 g C kg−1, the crop yield may be increased by 176 kg ha−1 for maize in the northeast region, 454 kg ha−1 for a maize-wheat rotation in the north region, 328 kg ha−1 for maize in the northwest region, 185 kg ha−1 for single-rice in the mid-south region, 266 kg ha−1 for double-rice in east region, and 229 kg ha−1 for rice and wheat rotation in southwest region. There is a great potential for enhancing the crop yield by improving the SOC content in each region of China.

Modeling Soil Organic Carbon Storage and Its Dynamics in Croplands of China

Abstract Soil organic carbon (SOC) is one of the centre issues related to not only soil fertility but also environmental safety. Assessing SOC dynamics in croplands has been a challenge in China for long due to the lack of appropriate methodologies and data sources. As an alternative approach for studying SOC dynamics, process-based models are adopted to meet the needs. In this paper, a process-based model, DeNitrification-DeComposition (DNDC), was applied to quantify the SOC storage and the spatial distribution in croplands of China in 2003, with the support of a newly compiled county-level soil/climate/land use database. The simulated results showed that the total SOC storage in the top layer (0-30 cm) of the 1.18 × 108 ha croplands of China is 4.7-5.2 Pg C in 2003 with an average value of 4.95 Pg C. The SOC storage in the northeastern provinces (1.3 Pg C) accounts for about 1/4 of the whole national totals due to their dominantly fertile soils with high organic matter content. SOC density ranges from 3.9 to 4.4 kg C m−2, with an average of 4.2 kg C m−2, a level is much lower than the world average level. The model results also indicated that high rates of SOC losses occurred in the croplands with the most common cropping patterns in China as like single soybean > maize > paddy > cotton > winter wheat and corn rotation. The results reported in this paper showed that there was still a great potential for improving SOC status in most croplands of China by adopting proper farming practices and land-use pattern. Therefore, long-term policy to protect SOC is urgently needed.