A comparative analysis of multitemporal MODIS EVI and NDVI data for large-scale rice yield estimation

Son, N. T.; Chen, Chi Farn; Chen, C.R.; Minh, Võ Quang; Trung, Nguyễn Hiếu

doi:10.1016/j.agrformet.2014.06.007

Cited by 193 publications

(107 citation statements)

References 71 publications

(71 reference statements)

Supporting

Mentioning

105

Contrasting

Order By: Relevance

“…This result was comparable with our result of the yield estimation. Son et al [79] performed the comparative analysis of MODIS EVI and NDVI time series data for the rice yield estimation and the EVI-based model obtained the higher accuracy with a RMSE of 6.9-8.1%, which was a little better than our result. However, the accuracy of the forecasting method for county or state areas would become less reliable for small areas, and few literature focussed on the quantitative estimation of the yield at the field scale using the satellite data [6,80].…”

Section: Discussioncontrasting

confidence: 53%

Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations

et al. 2018

View full text Add to dashboard Cite

Abstract:The rapid and accurate estimation of wheat production at a regional scale is crucial for national food security and sustainable agricultural development. This study developed a new gross primary productivity (GPP) estimation model (denoted as the [ACPM]), based on the effects of light, heat, soil moisture, and nitrogen content (N) on the light-use efficiency of winter wheat. The ACPM model used the quantic additivity of the environmental factors to improve the minimum form or multiple multiplication form in the previous model and thus characterized the joint effects of heat, soil moisture, and N on crop photosynthesis performance. The key parameters (i.e., light) were determined from the photosynthetically active radiation product of the Himawari-8 sensor and the fraction of photosynthetically active radiation product of Moderate Resolution Imaging Spectroradiometer (MODIS). The heat was determined from the land temperature products of MODIS. The soil moisture was obtained from the inversion using a visible and shortwave infrared drought index (VSDI), whereas the N stress of winter wheat was detected using the newly developed modified ratio vegetation index (MRVI), which could accurately obtain the spatiotemporal distribution of the leaf chlorophyll content of winter wheat. The ACPM and two other previous models (named the GPP1 and GPP2 models) were applied on the Himawari-8 and MODIS images in Hengshui City. The evaluation results, based on the ground measurement, indicated that the ACPM models exhibited the best estimate of dry aboveground biomass (DAM) and the wheat yield in Hengshui City, with errors of <10% and <12% for the DAM and yield, respectively. Considering the easy operation of the ACPM model and the accessibility of the corresponding satellite images, the Agriculture Crop Photosynthesis Model (ACPM) can be expected to provide information on the winter wheat shortfalls and surplus ahead of the availability of official statistical data.

show abstract

Section: Discussioncontrasting

confidence: 53%

Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Son et al [18] noted that EVI-based models were slightly more accurate than those from NDVI-based models in rice crop yields estimation in the Mekong River Delta of Vietnam. On the other hand, Li et al [19] in a study carried out in Northern Hebei Province of China indicate that NDVI has a stronger correlation with field data of vegetation covers than EVI and so has obvious advantages for predicting natural vegetation coverage better than EVI.…”

Section: Introductionmentioning

confidence: 99%

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Zoungrana

Christopher

Amekudzi

et al. 2014

Climate

View full text Add to dashboard Cite

show abstract

“…NDVI values are assumed to be indicative of rice yield and production in this region, which is supported by a number of studies (e.g. Rahman et al, 2012;Son et al, 2014). Ideally, this assumption is validated using ground observations of rice yield and production in the years and seasons studied.…”

Section: Environment-nutrition Linkagesmentioning

confidence: 82%

“…Gumma et al, (2014 also used MODIS NDVI data to map the rice crop extent and area for the year 2010, finding slightly higher rice area estimates (3-6%) than sub-national statistics. Similar studies have been carried out in other rice dominated areas such as the Mekong delta (Nguyen et al, 2015;Son et al, 2014). Whilst the production of irrigated rice can be assessed with NDVI, the response to variation in rainfall may be different than that of nonirrigated rice due to the potentially different timings of water availability.…”

Section: Normalised Difference Vegetation Indexmentioning

confidence: 89%

Food and nutrition security trends and challenges in the Ganges Brahmaputra Meghna (GBM) delta

Soesbergen

Nilsen

Burgess

et al. 2017

Elementa: Science of the Anthropocene

View full text Add to dashboard Cite

The population of the Ganges Brahmaputra Meghna (GBM) delta is highly vulnerable to food insecurity and malnutrition due to the specific environmental, climatic and human development factors affecting agricultural production and fisheries. To better understand the impacts of climate and environmental change on food security and nutrition in this delta, this study combines spatially explicit data from the 2007 and 2011 Bangladesh Demographic and Health Survey (BDHS) with a standard satellite remotely sensed vegetation greenness index (Normalised Difference Vegetation Index, NDVI), used as a proxy for rice production. The strength of association between NDVI and child nutrition in this tropical mega-delta were tested, showing correlations between two widely used indicators of child malnutrition; stunting and wasting, and deviations from a 10 year mean NDVI (anomalies) for rice crop growing seasons – regarded as critical to individual children’s early lives. For children surveyed in 2007 we found that the likelihood of being stunted decreased with increased NDVI as a measure of food production. Similarly, for children surveyed in 2011, the likelihood of being wasted reduced with increased NDVI. However, regression results for stunting in 2011 and wasting in 2007 were not statistically significant. Our findings suggest that NDVI can be regarded as indicative of climatic variability and periods of low food production but is only partly successful as an indicator of climate related impacts on child nutrition in the GBM delta. Furthermore, our study highlights some of the uncertainties and challenges with linking environmental indicators such as the NDVI with household survey data across spatial and temporal scales.

show abstract

A comparative analysis of multitemporal MODIS EVI and NDVI data for large-scale rice yield estimation

Cited by 193 publications

References 71 publications

Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations

Winter Wheat Production Estimation Based on Environmental Stress Factors from Satellite Observations

Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Food and nutrition security trends and challenges in the Ganges Brahmaputra Meghna (GBM) delta

Contact Info

Product

Resources

About