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Crop Monitoring Using a Multiple Cropping Index Based on Multi-Temporal MODIS Data

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Crop Monitoring Using a Multiple Cropping Index Based on Multi-Temporal MODIS Data African Journal of Agricultural Research Vol. 7(26), pp. 3828-3838, 10 July, 2012 Available online at http://www.academicjournals.org/AJAR DOI: 10.5897/ AJAR11.2455 ISSN 1991-637X © 2012 Academic Journals Full Length Research Paper Crop monitoring using a Multiple Cropping Index based on multi-temporal MODIS data Dailiang Peng1, Cunjun Li2*, Jingfeng Huang3, Bin Zhou4 and Xiaohua Yang5 1Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China. 2Beijing Research Center for Information Technology in Agriculture, Beijing, 100097, China. 3Institute of Agricultural Remote Sensing and Information Application, Zhejiang University, Hangzhou, 310029, China. 4Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou, 310036, China. 5 Space Weather Center, Meteorological and Hydrographic Department, Beijing, 100094, China Accepted 22 May, 2012 Food shortage and security attracts global attention and at this moment in time, intensive farming has a large impact on agricultural resources. In this respect, multiple cropping is an effective agricultural practice increasing the combined yield of crops and agricultural output. Over-cropping however, is a major cause of cultivated land degradation. The multiple cropping index (MCI) is an important parameter in arable farming systems. It reflects the utilization of water, soil, incoming radiation, as well as other natural resources. Hence, MCI monitoring is an important activity in the resources and food security assessment of agriculture. Therefore, the objective of this paper is to investigate the MCI monitoring method using multi-temporal moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data, for the time period of 2001 to 2004 in the study area of Southeastern China. The annual cycle of crop phenology inferred from remote sensing is characterized by four key transition periods: (1) greenup; (2) maturity; (3) senescence and (4) dormancy. The maximum of the NDVI time-series profile for cropland is a proxy for maximum leaf area. Hence, MCI of arable land in Southeastern China from 2001 to 2004 was monitored by the acquisition of peak frequencies in NDVI time series profiles. The results showed that the MCI increases from north to south for every year, 41.18% areas of Southeastern China had the largest MCI in 2004. The MCI from the MODIS-NDVI elicit a significant correlation with statistical MCI, and most of the relative errors were less 10%. All these results indicated that the method used to estimate MCI described in this paper is dependable. Key words: Multiple cropping index, moderate resolution imaging spectroradiometer (MODIS), normalized difference vegetation index (NDVI), phenology, Southeastern China. INTRODUCTION Half of the world‟s population in the developing countries reforms brought about a massive land development all lives on a low per capita income and experiences over the country, leading to the loss of arable land at an sporadic shortages of nutritious food stuffs. Clearly, alarming rate. However, newly reclaimed low-grade ensuring an adequate availability of food is a major arable land in environmentally fragile frontier regions has challenge. Agriculture activity in China has changed dra- never been able to compensate for the loss of fertile land matically since the 1950‟s. China‟s arable land resources in the southeastern part of China where multiple cropping are extremely scarce in comparison to the world‟s index (MCI) and population density are high (George and average. A dramatic economic expansion since the1978 Samuel, 2003). Brown (1994) even put forward: „Who will feed China?‟ There is an urgent need for China to use its limited arable land resources more efficiently for the sake of not only its own growing population but also the *Corresponding author. E-mail: [email protected] or dlpeng@ globalizing world. ceode.ac.cn. Although chemical fertilizer, agricultural chemicals and Peng et al. 3829 high quality seed can increase food production per unit acceptable temporal resolution is constrained by the low area, improved arable farming systems are a better spatial resolution of this remote sensing imagery. alternative (Ogbuehi and Orzolek, 1987; Philippe and Moderate Resolution Imaging spectroradiometer Paul, 2007). Traditional crops and cropping systems in (MODIS) aboard the NASA‟s earth observing system small-farm agriculture are the result of many years of (EOS) Terra satellite, combines high spatial and temporal evolution and selection by farmers. These systems are resolution (250 m pixel size for MODIS band 1 and 2, and genuinely based on intercropping and multiple cropping almost daily overpasses) (Gonzalo et al., 2007). In (Jaime, 1987). Multiple cropping effectively increases the contrast to its predecessors, MODIS incorporates combined yield of crops (Ogbuehi and Orzolek, 1987), enhanced cloud screening, atmospheric correction, im- and it can be of great help to make better and more proved geo-referencing and a new compositing scheme intensive use of available resources, thus increasing which reduces angular, sun-target-sensor variations agricultural output and income (Beets, 1975; Sundara (Running et al., 1994, 1999; Sinkyu et al., 2003). Hence, and Subramanian, 1987). On the other hand, multiple MODIS vegetation data are more suitable for regional cropping can enhance the level of soil organic matter vegetation research. accretion (Ayanlaja and Sanwo, 1991), and suitable The objective of this paper is to study the method of combinations of crops can improve soil quality (Nair, MCI monitoring using MODIS imagery using the relation- 1973; Wade and Sanchez, 1984). ship between the seasonal variation of the NDVI for MCI is the planting frequency of the crop in the same cropland and different multiple cropping systems. South- arable land in one year (Shen and Liu, 1983), which can eastern China was selected as the study region to test reflect the utilization ratio of water, soil, light energy, and this method of MCI monitoring. other natural resources (Fan and Wu, 2004). Although research of arable farming systems are constantly reported, especially in recent years (Gerowitt, 2003; MATERIALS AND METHODS Helander and Delin, 2004; Gosling and Shepherd, 2005; Study area Yann et al., 2007), MCI studies mainly focused on the 1980‟s (Beets, 1975, 1982; Plucknett, 1981; Ilyas et al., Southeastern China approximate latitudinal and longitudinal ranges 1989), The 1980‟s have been neglected quite some time are N23°~N38°and E114°~E123°, respectively (Figure 1); the total 2 as a result of the influence of mono-cropping oriented land area is about 605 800 km including 58 cities. In this paper, Southeastern China was selected as the study region for the research in the western world (Fan and Wu, 2004). following reasons: Hence, monitoring MCI in arable farming systems is quite meaningful for agricultural resources assessment and the (1) It has a favorable natural environment suitable for intensive crop world‟s food security. It is a requirement for policy makers cultivation, and is the main food provider in China. China feeds 22% to plan and evaluate managerial decisions in a rational, of its population with less than 10% of the arable land in the world. objective way in this respect. MCI is traditionally Moreover, Southeastern China feeds about 25% of its population with 17% of the arable land of China. Hence, food production in this calculated by the ratio between the total harvest area and region is very important for China and world. the arable land area in one year with statistical data of (2) Due to the government policy to protect arable land in China, local governments (Shen and Liu, 1983; Wang and Li, the total area of arable land in Southeastern China has not 2003; George and Samuel, 2003). This method is hardly decreased. The per-capita area has decreased slightly between used in agro-climatic and crop growth models at all and 2001 and 2004 because of the increasing population. On the other hence, is not simple for policy makers to find data on the hand, the per-capita arable land area in Southeastern China is lower than at the national level (about 0.1 hectares for the years temporal and spatial variations. Therefore, an urgent mentioned) (Table 1). Hence, the problem of food security is widely need is the development of a new method using new concerned in this area. data to extract MCI independent of statistical data (Fan (3) The variability of topography in Southeastern China is specific and Wu, 2004). and therefore typical. There are many hills and mountains in the Remote sensing techniques have been developed from southern part of the study area, which is a typical broken and mountainous terrain, and the dominant terrain is flat in the northern 1960‟s onward and rapidly developed over the past 50 part of the study area, and most of the arable land is planted with years. It is applied nowadays in investigating, appraising, one crop type. programming and managing agricultural resources, to perform forecasting, monitoring and the evaluation of calamities, to perform dynamic agro-monitoring, and to Experimental data estimate agricultural yields (Wang and Malingreau, 1990; MOD13Q1 16-day composite NDVI imagery acquired from 2001 to Wang and Hang, 2002). Nevertheless, research of MCI 2004 has been collected by the Warehouse Inventory Search Tool using remote sensing techniques is very scarce (WIST). The spatial resolution is 250 m. MODIS NDVI improves
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