Rice monitoring using ENVISAT-ASAR data: preliminary results of a case study in the Mekong River Delta, Vietnam

Vietnam is one of the world’s largest rice exporting countries, and the fertile Mekong River Delta at the southern tip of Vietnam accounts for more than half of the country’s rice production. Unfortunately, a large part of rice crop growing time coincides with a rainy season, resulting in a limited number of cloud-free optical remote sensing images for rice monitoring. Synthetic aperture radar (SAR) data allows for observations independent of weather conditions and solar illumination, and is potentially well suited for rice crop monitoring. The aim of the study was to apply new generation Envisat ASAR data with dual polarization (HH and VV) to rice cropping system mapping and monitoring in An Giang province, Mekong River Delta. Several sample areas were established on the ground, where selected rice parameters (e.g. rice height and biomass) are periodically being measured over a period of 12 months. A correlation analysis of rice parameters and radar imagery values is then being conducted to determine the significance and magnitude of the relationships. This paper describes a review of the previous research studies on rice monitoring using SAR data, the context of this on-going study, and some preliminary results that provide insights on how ASAR imagery could be useful for rice crop monitoring. More work is being done to develop algorithms for mapping and monitoring rice cropping systems, and to validate a rice yield prediction model for one year cycle using time-series SAR imagery

Effects of changing cultural practices on C-band SAR backscatter using Envisat ASAR data in the Mekong River Delta

International audienceChanges in rice cultivation systems have been observed in the Mekong River Delta, Vietnam. Among the changes in cultural practices, the change from transplanting to direct sowing, the use of water-saving technology, and the use of high production method could have impacts on radar remote sensing methods previously developed for rice monitoring. Using Envisat (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) data over the province of An Giang, this study showed that the radar backscattering behaviour is much different from that of the reported traditional rice. At the early stage of the season, direct sowing on fields with rough and wet soil surface provides very high backscatter values for HH (Horizontal transmit - Horizontal receive polarisation) and VV (Vertical transmit - Vertical receive polarisation) data, as a contrast compared to the very low backscatter of fields covered with water before emergence. The temporal increase of the backscatter is therefore not observed clearly over direct sowing fields. Hence, the use of the intensity temporal change as a rice classifier proposed previously may not apply. Due to the drainage that occurs during the season, HH, VV and HH/VV are not strongly related to biomass, in contrast with past results. However, HH/VV ratio could be used to derive the rice/non-rice classification algorithm for all conditions of rice fields in the test province. The mapping results using the HH/VV polarization ratio at a single date in the middle period of the rice season were assessed using statistical data at different districts in the province, where very high accuracy was found. The method can be applied to other regions, provided that the synthetic aperture radar data are acquired during the peak period of the rice season, and that few training fields provide adjusted threshold values used in the method

Mortality as a key driver of the spatial distribution of aboveground biomass in Amazonian forest: Results from a dynamic vegetation model

International audienceDynamic Vegetation Models (DVMs) simulate energy, water and carbon fluxes between the ecosystem and the atmosphere, between the vegetation and the soil, and between plant organs. They also estimate the potential biomass of a forest in equilibrium having grown under a given climate and atmospheric CO2 level. In this study, we evaluate the Above Ground Woody Biomass (AGWB) and the above ground woody Net Primary Productivity (NPPAGW) simulated by the DVM ORCHIDEE across Amazonian forests, by comparing the simulation results to a large set of ground measurements (220 sites for biomass, 104 sites for NPPAGW). We found that the NPPAGW is on average overestimated by 63%. We also found that the fraction of biomass that is lost through mortality is 85% too high. These model biases nearly compensate each other to give an average simulated AGWB close to the ground measurement average. Nevertheless, the simulated AGWB spatial distribution differs significantly from the observations. Then, we analyse the discrepancies in biomass with regards to discrepancies in NPPAGW and those in the rate of mortality. When we correct for the error in NPPAGW, the errors on the spatial variations in AGWB are exacerbated, showing clearly that a large part of the misrepresentation of biomass comes from a wrong modelling of mortality processes. Previous studies showed that Amazonian forests with high productivity have a higher mortality rate than forests with lower productivity. We introduce this relationship, which results in strongly improved modelling of biomass and of its spatial variations. We discuss the possibility of modifying the mortality modelling in ORCHIDEE, and the opportunity to improve forest productivity modelling through the integration of biomass measurements, in particular from remote sensing. © Author(s) 2010

Induced systemic resistance against rice grassy stunt virus – a promising field for ecological rice production: Research article

Most rice protection methods have currently used toxic chemicals to control pathogens and pests, which leads to environmental pollution. Systemic acquired resistance (SAR) taking advantage of natural defence reaction of plants could be proposed as an alternative, ecologically friendly approach for plant protection. Its application into rice production could minimize the chemicals quantity used and could contribute to the decrease of environmental pollution and the development of sustainable agriculture. The research was conducted to select the most effective chemical and suitable method to improve the health of rice plants infected by grassy stunt disease in net-house of Can Tho University. SAR chemicals were used at very low concentrations (in mM). Results showed that the height of rice plants treated with SAR chemicals was higher than that of plants untreated. Besides, the number of diseased plants was reduced and the ratio of firm grain and yield increased when plants were applied by SAR. Among the used substances, oxalic acid provided the best systemic acquired resistance. With oxalic acid, seed soaking was better than seed coating in systemic acquired resistance against rice grassy stunt disease.Hầu hết các phương pháp sản xuất lúa hiện nay đều sử dụng các hóa chất độc hại trong việc phòng trừ bệnh và côn trùng gây hại, nên dẫn đến ô nhiễm môi trường. Kích thích tính kháng lưu dẫn giúp kích hoạt cơ chế tự nhiên kháng bệnh của cây có thể là giải pháp bảo vệ thực vật thay thế an toàn với môi trường. Việc ứng dụng tiến bộ này vào trong sản xuất lúa có thể làm giảm lượng hóa chất sử dụng, đóng góp vào việc giảm thiểu ô nhiễm môi trường và sự phát triển của một nền nông nghiệp bền vững. Nghiên cứu đã được thực hiện tại nhà lưới trường Đại học Cần Thơ để tuyển chọn hóa chất và phương pháp sử dụng hóa chất để tăng cường sức khỏe giúp cây lúa vượt qua bệnh vàng lùn. Hóa chất kích kháng được sử dụng ở một nồng độ rất thấp (đơn vị là mM). Kết quả cho thấy chiều cao cây lúa khi xử lý chất kích kháng tốt hơn so đối chứng không xử lý. Bên cạnh đó, số cây lúa nhiễm bệnh giảm, tỉ lệ hạt chắc và năng suất tăng khi cây lúa được xử lý với chất kích kháng. Trong số các chất kích kháng đã sử dụng, acid oxalic cho hiệu quả vượt trội. Với chất acid oxalic, phương pháp ngâm hạt cho hiệu quả kích kháng tốt hơn phương pháp áo hạt

La influencia del fenómeno ENSO sobre la fenología primaveral en los bosques boreales de Siberia central

Ponencia presentada en: V Congreso Internacional de la Asociación Española de Climatología celebrado en Zaragoza del 18 al 21 de septiembre de 2006.[ES]Se analiza la influencia de El Niño-Southern Oscillation (ENSO) sobre la variabilidad interanual de las fechas de aparición de las hojas e inicio de la actividad vegetal primaveral en los bosques boreales del hemisferio norte entre 1982 y 2004. Los resultados muestran negativas y significativas correlaciones entre el fenómeno ENSO, cuantificado mediante el Southern Oscillation Index (SOI), y la fecha de aparición de las hojas en Siberia central, con un retraso en dicha influencia de hasta 9 meses. La correlación entre la fecha de aparición de las hojas y la temperatura de superficie oceánica a escala global muestran un patrón espacial que asemeja al fenómeno ENSO, con correlaciones positivas y significativas en el Este del Pacífico y negativas en el Oeste. Esta influencia se explica por el papel del fenómeno ENSO sobre la presión en superficie, el geopotencial a 500hPa, la dirección e intensidad de los flujos de viento y la temperatura de superficie durante los meses en los que aparecen las hojas (abrilmayo) en las zonas boreales de Siberia central.[EN]This paper analyses the role of the El Niño-Southern Oscillation (ENSO) on the interannual variability of the leaf appearance dates of boreal forests in the Northern hemisphere (1982- 2004). We find significant negative correlations between the ENSO, quantified by means of the Southern Oscillation Index (SOI), and the leaf appearance dates in central Siberia with up to 9 months lag. The correlations between leaf appearance dates and summer Sea Surface Temperatures (SST) show a pattern that resembles the ENSO phenomena with positive and significant correlations in the East pacific and negative in the West. These findings are explained by the role of SOI on Sea Level Pressures, 500 hPa Geopotential and the wind flow direction and intensity during the months of leaf appearance (April and May) and on average temperatures, which determine noticeably the date of leaf appearance.Este trabajo se ha realizado gracias a la financiación del proyecto Siberia II (5º Programa Marco de la Comisión Europea)

The Association Between Ambient Temperatures and Hospital Admissions Due to Respiratory Diseases in the Capital City of Vietnam

This study aimed to examine the short-term effects of ambient temperature on hospital admissions due to respiratory diseases among Hanoi residents. We collected 34,653 hospital admissions for 365 days (November 1, 2017, to November 31, 2018) from two hospitals in Hanoi. A quasi-Poisson regression model with time series analysis was used to explore the temperature-health outcome relationship's overall pattern. The non-linear curve indicated the temperatures with the lowest risk range from 22 degrees (Celcius) to 25 degrees (Celcius). On average, cold temperatures showed a higher risk than hot temperatures across all genders and age groups. Hospital admissions risk was highest at 13 degrees (Celcius) (RR = 1.39; 95% CI = 1.26–1.54) for cold effects and at 33 degrees (Celcius) (RR = 1.21, 95% CI = 1.04–1.39) for the hot effects. Temporal pattern analysis showed that the most effect on respiratory diseases occurred at a lag of 0 days for hot effect and at a lag of 1 day for cold effect. The risk of changing temperature among women and people over 5 years old was higher than other groups. Our results suggest that the risk of respiratory admissions was greatest when the temperature was low. Public health prevention programs should be enhanced to improve public awareness about the health risks of temperature changes, especially respiratory diseases risked by low temperatures

Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data

Rice is one of the world’s most dominant staple foods, and hence rice farming plays a vital role in a nation’s economy and food security. To examine the applicability of synthetic aperture radar (SAR) data for large areas, we propose an approach to determine rice age, date of planting (dop), and date of harvest (doh) using a time series of Sentinel-1 C-band in the entire Mekong Delta, Vietnam. The effect of the incidence angle of Sentinel-1 data on the backscatter pattern of paddy fields was reduced using the incidence angle normalization approach with an empirical model developed in this study. The time series was processed further to reduce noise with fast Fourier transform and smoothing filter. To evaluate and improve the accuracy of SAR data processing results, the classification outcomes were verified with field survey data through statistical metrics. The findings indicate that the Sentinel-1 images are particularly appropriate for rice age monitoring with R2  =  0.92 and root-mean-square error (RMSE) = 7.3 days (n  =  241) in comparison to in situ data. The proposed algorithm for estimating dop and doh also shows promising results with R2  =  0.92 and RMSE  =  6.2 days (n  =  153) and R2  =  0.70 and RMSE  =  5.7 days (n  =  88), respectively. The results have indicated the ability of using Sentinel-1 data to extract growth parameters involving rice age, planting and harvest dates. Information about rice age corresponding to the growth stages of rice fields is important for agricultural management and support the procurement and management of agricultural markets, limiting the negative effects on food security. The results showed that multitemporal Sentinel-1 data can be used to monitor the status of rice growth. Such monitoring system can assist many countries, especially in Asia, for managing agricultural land to ensure productivity

An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets:high sensitivity of L-VOD to above-ground biomass in Africa

The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infrared vegetation indices. This study is devoted to the characterization of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (LVOD) data sets (SMOS level 2, level 3 and SMOS-IC) were compared with data sets on tree height, visible/infrared indexes (NDVI, EVI), mean annual precipitation and above-ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationships between L-VOD and the AGB data sets were linear per land cover class but with a changing slope depending on the class type, which makes it a global non-linear relationship. In contrast, the relationship linking L-VOD to tree height (R = 0.87) was close to linear. For vegetation classes other than evergreen broadleaf forest, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlated with the average annual precipitation. SMOS L-VOD showed higher sensitivity to AGB compared to NDVI and K/X/C-VOD (VOD measured at 19, 10.7 and 6.9 GHz). The results showed that, although the spatial resolution of L-VOD is coarse (similar to 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising indicator for large-scale monitoring of the vegetation status, in particular biomass

Study, Design and Construction of an Early Warning Environmental Radiation Monitoring Station

We report on the design and construction of an Early Warning Environmental Radiation Monitoring Station (EWERMS), used ONLINE in the environmental radiation monitoring and early warning network. It has a  high sensitivity and can send a prompt alarm signal via Internet to the emergency management office. It includes four gamma probes: one NaI(Tl) and three Geiger Mueller (GM) detectors. The NaI(TL) detector is used to monitor spectrum environmental radiation and measure the isotopic composition, the GM detectors are used to detect and measure high gamma ray rates. The instrument has been designed to be used outdoor and tolerate large and rapid temperature variations. The photomultiplier tubes (PMT), amplifiers and Analog To Digital (ADC) gains are stabilized using pulsed LEDs as precision reference light sources