Mapping paddy rice agriculture in southern China using multi-temporal MODIS images

Xiao, Xiangming; Boles, Stephen; Liu, Jiyuan; Zhuang, Dafang; Frolking, Steve; Li, Changsheng; Salas, William; Moore, Berrien

doi:10.1016/j.rse.2004.12.009

Cited by 835 publications

(678 citation statements)

References 36 publications

Supporting

Mentioning

662

Contrasting

Unclassified

Order By: Relevance

“…In recent years, substantial progress has been achieved in both satellite sensor capability and data analysis methods application to predict rice crop distributions. For example, it is nowadays possible to routinely map and monitor rice paddy agriculture (Xiao et al, 2005(Xiao et al, , 2006 and cropping intensity in Asia, using images from the moderate resolution imaging spectroradiometer (MODIS) sensor onboard the NASA Terra satellite. The satellite-based algorithms permit the production of maps and monitoring of cropping intensity, the crop calendar (planting and harvesting dates) and irrigation practices at moderate spatial resolution (250-500 m) and in near-real time fashion.…”

Section: Introductionmentioning

confidence: 99%

Avian influenza, domestic ducks and rice agriculture in Thailand

Gilbert

Xiao

Chaitaweesub

et al. 2007

Agriculture, Ecosystems & Environment

Self Cite

118

View full text Add to dashboard Cite

Highly pathogenic avian influenza (HPAI) caused by H5N1 viruses has become a global scale problem which first emerged in southern China and from there spread to other countries in Southeast and East Asia, where it was first confirmed in end 2003. In previous work, geospatial analyses demonstrated that free grazing ducks played critical role in the epidemiology of the disease in Thailand in the winter 2004/2005, both in terms of HPAI emergence and spread. This study explored the geographic association between free grazing duck census counts and current statistics on the spatial distribution of rice crops in Thailand, in particular the crop calendar of rice production. The analysis was carried out using both district level rice statistics and rice distribution data predicted with the aid of remote sensing, using a rice-detection algorithm. The results indicated a strong association between the number of free grazing ducks and the number of months during which second-crop rice harvest takes place, as well as with the rice crop intensity as predicted by remote sensing. These results confirmed that free grazing duck husbandry was strongly driven by agricultural land use and rice crop intensity, and that this later variable can be readily predicted using remote sensing. Analysis of rice cropping patterns may provide an indication of the location of populations of free grazing ducks in other countries with similar mixed duck and rice production systems and less detailed duck census data. Apart from free ranging ducks and rice cropping, the role of hydrology and seasonality of wetlands and water bodies in the HPAI risk analysis is also discussed in relation to the presumed dry season aggregation of wild waterfowl and aquatic poultry offering much scope for virus transmission.

show abstract

Section: Introductionmentioning

confidence: 99%

Avian influenza, domestic ducks and rice agriculture in Thailand

Gilbert

Xiao

Chaitaweesub

et al. 2007

Agriculture, Ecosystems & Environment

Self Cite

118

View full text Add to dashboard Cite

show abstract

“…The reflectance in Band 6 became higher than that in Band 4. In the previous literature, many water indices have been developed using the visible and infrared bands [23][24][25]. The green spectral range is highly sensitive to the Chl-a concentration over a wide range of variation and, thus, is helpful for the remote sensing of vegetation [30].…”

Section: Spectral Characteristics Of Rice During the Flooding And Tramentioning

confidence: 99%

“…However, because the reflectance of rice pixels during the flooding and transplanting stage is a mixture of water and vegetation, the sensitivity of the spectral index to flooding features should be further improved for rice mapping. The Land Surface Water Index (LSWI), which was formulated by combining the red and shortwave infrared channels of MODIS, has been used for the identification of rice pixels [25]. However, the threshold between the LSWI and the EVI was determined by considering local practices and rice cropping systems.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images

Shi

Huang

2015

Remote Sensing

View full text Add to dashboard Cite

Abstract:A large-area map of the spatial distribution of rice is important for grain yield estimations, water management and an understanding of the biogeochemical cycling of carbon and nitrogen. In this paper, we developed the Normalized Weighted Difference Water Index (NWDWI) for identifying the unique characteristics of rice during the flooding and transplanting period. With the aid of the ASTER Global Digital Elevation Model and the phenological data observed at agrometeorological stations, the spatial distributions of single cropping rice and double cropping early and late rice in the Yangtze River Delta region were generated using the NWDWI and time-series Enhanced Vegetation Index data derived from MODIS/Terra data during the 2000-2010 period. The accuracy of the MODIS-derived rice planting area was validated against agricultural census data at the county level. The spatial accuracy was also tested based on a land use map and Landsat ETM+ data. The decision coefficients for county-level early and late rice were 0.560 and 0.619, respectively. The MODIS-derived area of late rice exhibited higher consistency with the census data during the 2000-2010 period. The algorithm could detect and monitor rice fields with different cropping patterns at the same site and is useful for generating spatial datasets of rice on a regional scale.

show abstract

“…Satellite-based flood inundation maps can be a very important input for assessing the progression of floodwaters and the severity of the flood situation. In the past several years, many satellite techniques that use optical sensors have been proposed to detect flood inundation, including National Oceanic and Atmospheric Administration (NOAA)/advanced very high resolution radiometer (AVHRR) (Jain et al 2006), Landsat multispectral scanner system (MSS), thematic mapper (TM) (Hallberg et al 1973;Rango & Solomonson 1974), advanced land imager (ALI) (Amarnath 2013), Indian remote-sensing satellite (IRS) (Jain et al 2006), Satellite Pour l'Observation de la Terre (SPOT) VEGETATION (Nguyen et al 2012) and Terra MODIS (Xiao et al 2005;Sakamoto et al 2007). …”

Section: Introductionmentioning

confidence: 99%

An evaluation of flood inundation mapping from MODIS and ALOS satellites for Pakistan

Amarnath

Rajah

2015

Geomatics, Natural Hazards and Risk

View full text Add to dashboard Cite

The paper presents a moderate resolution imaging spectroradiometer (MODIS) time-series imagery-based algorithm for detection and mapping of seasonal and annual changes in flood extent, and tests this using the flooding of the Indus River Basin in 2010 À one of the greatest recent disasters that affected more than 25 million people in Pakistan. The algorithm was applied to produce inundation maps for 10 annual flood seasons over the period from 2000 to 2011. The MODIS flood products were validated in comparison with advanced land observing system (ALOS) sensors, which have both advanced visible and near infrared radiometer and phased array type L-band synthetic images using the flood fraction comparison method. A simple threshold method is created to cluster the data to identify the flood pixels in the imagery. Calculations are then made to estimate a flood area for each resolution. A statistical study is performed to analyze false positive and false negative rates using the ALOS sensors as 'ground truth'. Comparison of two flood products at a grid size of 10 km resulted in the coefficient of determination range of 0.72À0.97. This research points to a relevant spatial resolution that could be effectively used to obtain accurate mapped products of the extent of the inundated area. The approach can be used to quantify the damage caused by floods.

show abstract

Mapping paddy rice agriculture in southern China using multi-temporal MODIS images

Cited by 835 publications

References 36 publications

Avian influenza, domestic ducks and rice agriculture in Thailand

Avian influenza, domestic ducks and rice agriculture in Thailand

Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images

An evaluation of flood inundation mapping from MODIS and ALOS satellites for Pakistan

Contact Info

Product

Resources

About