SPATIO-TEMPORAL PATTERNS OF RICE SUBMERGENCE IN NORTH-EASTERN THAILAND WITH TERRA-MODIS

2014

Egypt faces a great challenge. Fixed water resources and increasing water demands. Rice is the main water–consuming crop planted in Egypt Delta. Thus mapping of where and when rice is planted is important. The planting occurs over a wide spatial and temporal span. Thus, rice mapping with traditional methods is doubtful. Elshorbagy (2013) developed a model for rice mapping utilizing MODIS (MOD09A1, MOD09Q1) products where the dynamics of Land Surface Water Index (LSWI), Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) throughout the rice-planting season were combined with an arable mapping module for rice area mapping. In the present study, ten years of historical multi-temporal MODIS imagery (2002-2011) were analyzed applying the developed model. For each main irrigation directorate an inventory of where and when rice was planted in the target period was mapped. The date intervals of maximum rice transplanting were identified. The most critical image...

Journal of Applied Remote Sensing, 2011

Our goal is to map the rice areas of six South Asian countries using moderateresolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R 2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). Use: http://spiedl.org/terms Gumma et al.: Mapping rice areas of South Asia using MODIS multitemporal data

Environment, Development and Sustainability, 2012

ABSTRACT Sub-Saharan African countries are being strongly urged to enhance their rice production, because their rice consumption and importation rates have been rapidly increasing in recent years. Areas planted to rice in Africa are classified agro-ecologically into rainfed upland, rainfed lowland, and irrigated. Rainfed lowland includes extensive areas of unexploited land that has great potential for the promotion of rice growing. For the unexploited rainfed lowlands of Ghana, we have been studying the development of low-cost rice-farming systems that require no large-scale irrigation or land reclamation. For such systems, it is important to select suitable areas where water for rice farming can be obtained naturally; floodwaters offer promise for this purpose. Delineation and mapping of floodwater prone areas suitable for rice production is important for successful utilization of this land resource. Here, we propose a method of assessing flood probability from submergence frequency, as estimated from satellite imagery and geospatial data. ALOS/PALSAR images acquired in May, June, August, and September 2010 were used to classify land and water, and then a submerged-area map was produced. From the results, we were able to accurately detect non-submerged areas and submerged areas with water depths of at least 3 cm. The number of times classified into submerged area was defined as submergence frequency, and it was approximated by distance from reservoirs representing White Volta River, ponds, and swamps. In addition, flood extent derived from reservoirs was simulated using digital elevation model (DEM). Finally, a flood probability assessment map was produced by integration of the estimated submergence frequency and flood extent simulation. The results of a comparison of soil moisture data measured at 69 points in the field and the NDVIs computed by ALOS/AVNIR showed that areas with high potential for flooding retained high levels of soil moisture and were more likely to show less deterioration of vegetation in the dry season. The validation of these results confirmed the adequacy of the flood probability assessment method.

Australian Journal of Experimental Agriculture, 2003

Discriminating crops by remote sensing remains reasonably complex and expensive for many agricultural land managers. The current study was conducted to facilitate the operational use of remote sensing for field-level rice monitoring in Australia by determining (i) whether existing methods relating to simple moisture-based rice classification could be further simplified, and (ii) whether the high accuracies resulting from that moisture-based methodology could be further increased. First, the impact of removing the most complicated processing step, atmospheric correction, on rice classification accuracies was assessed for the 2000-01 summer growing season at the Coleambally Irrigation Area, New South Wales. The primary error sources of rice classification were then identified and simple rules developed in an attempt to reduce errors associated with confusion between unharvested winter cereals and flooded rice paddies early in the summer growing season. These newly defined rules were then used on imagery acquired in the subsequent summer growing season in order to assess their repeatability. The assessment of atmospheric correction showed that during the critical time frame associated with high rice identification (October-November), using non-atmospherically corrected data increased overall accuracy, although the improvement was small (about 1%). Overall accuracy also increased for every case tested for both growing seasons as a result of the rule-based classification (ranging from about 1 to 14%), revealing that the methods were sufficiently repeatable. This study moves per-field rice monitoring at the Coleambally Irrigation Area closer to an operational application and shows that simple rule-based remote sensing classifications can be very effective when site practices are known.

International journal of applied earth observation and geoinformation, 2018

Information on the vulnerability to flooding is vital to understand the potential damages from flood events. A method to determine the vulnerability to flooding in irrigated rice fields using the Enhanced Vegetation Index (EVI) was proposed in this study. In doing so, the time-series EVI derived from time-series 8 day 500 m spatial resolution MODIS imageries (MOD09A1) was used to generate cropping patterns in irrigated rice fields in West Java. Cropping patterns were derived from the spatial distribution and phenology metrics so that it is possible to show the variation of vulnerability in space and time. Vulnerability curves and cropping patterns were used to determine the vulnerability to flooding in irrigated rice fields. Cropping patterns capture the shift in the vulnerability, which may lead to either an increase or decrease of the degree of damage in rice fields of origin and other rice fields. The comparison of rice field areas between MOD09A1 and ALOS PALSAR and MOD09A1 and Agricultural Statistics showed consistent results with R 2 = 0.81 and R 2 = 0.93, respectively. The estimated and observed DOYs showed RMSEs = 9.21, 9.29, and 9.69 days for the Start of Season (SOS), heading stage, and End of Season (EOS), respectively. Using the method, one can estimate the relative damage provided available information on the flood depth and velocity. The results of the study may support the efforts to reduce the potential damages from flooding in irrigated rice fields.

Sustainability, 2020

Flooding or submergence is one of the major environmental stressors affecting many man-made and natural ecosystems worldwide. The increase in the frequency and duration of heavy rainfall due to climate change has negatively affected plant growth and development, which eventually causes the death of plants if it persists for days. Most crops, especially rice, being a semi-aquatic plant, are greatly affected by flooding, leading to yield losses each year. Genetic variability in the plant response to flooding includes the quiescence scheme, which allows underwater endurance of a prolonged period, escape strategy through stem elongation, and alterations in plant architecture and metabolism. Investigating the mechanism for flooding survival in wild species and modern rice has yielded significant insight into developmental, physiological, and molecular strategies for submergence and waterlogging survival. Significant progress in the breeding of submergence tolerant rice varieties has been made during the last decade following the successful identification and mapping of a quantitative trait locus for submergence tolerance, designated as SUBMERGENCE 1 (SUB1) from the FR13A landrace. Using marker-assisted backcrossing, the SUB1 QTL (quantitative trait locus) has been incorporated into many elite varieties within a short time and with high precision as compared with conventional breeding methods. Despite the advancement in submergence tolerance, for future studies, there is a need for practical approaches exploring genome-wide association studies (GWA) and QTL in combination with specific tolerance traits, such as drought, salinity, disease and insect resistance.

Cropping intensity is one of the most important decisions made independently by farmers in Vietnam. It is a crucial variable of various economic and process-based models. Rice is grown under irrigated triple-and double-rice cropping systems and a rainfed single-rice cropping system in the Vietnamese Mekong Delta (VMD). These rice cropping systems are adopted according to the geographical location and water infrastructure. However, little work has been done to map triple-cropping of rice using Sentinel-1 along with the effects of water infrastructure on the rice cropping intensity decision. This study is focused on monitoring rice cropping patterns in the An Giang province of the VMD from March 2017 to March 2018. The fieldwork was carried out on the dates close to the Sentinel-1A acquisition. The results of dual-polarized (VV and VH) Sentinel-1A data show a strong correlation with the spatial patterns of various rice growth stages and their association with the water infrastructure. The VH backscatter (σ •) is strongly correlated with the three rice growth stages, especially the reproductive stage when the backscatter is less affected by soil moisture and water in the rice fields. In all three cropping patterns, σ • VV and σ • VH show the highest value in the maturity stage, often appearing 10 to 12 days before the harvesting of the rice. A rice cropping pattern map was generated using the Support Vector Machine (SVM) classification of Sentinel-1A data. The overall accuracy of the classification was 80.7% with a 0.78 Kappa coefficient. Therefore, Sentinel-1A can be used to understand rice phenological changes as well as rice cropping systems using radar backscattering.

Agricultural Systems, 2011

Rice (Oryza sativa L.) provides a life support system to millions of resource-poor farmers in rainfed environments; however, yields are very low because of various biotic and abiotic stresses. Submergence caused by typhoons and floods is one of the major reasons for production losses. Because of the complexity of these ecosystems, the breeding framework necessitates adequate feedback and a more in-depth understanding of the ecological and socioeconomic conditions in these flood-prone areas. Within this purview, this study validated the performance in farmers' fields of lines with the SUB1 gene that confers tolerance of submergence for up to two weeks. The SUB1 gene was incorporated through marker-assisted backcrossing, MABC. The evaluation was conducted through participatory approaches to gain understanding of the risks as well as farmers' preferences for these varieties. A baseline survey of 658 farm households accomplished during 2008, focus group discussions, key informant interviews, and adaptability trials were conducted, with focus on farmers commonly affected by submergence in four Southeast Asian countries: the Philippines, Lao PDR, Indonesia, and Southern Viet Nam. The study further examined farmers' criteria in evaluating new varieties through the participatory varietal selection (PVS) process. Results showed that varying conditions of submergence can influence farmers' criteria and preferences for rice cultivars. Depending on the timing of flood with respect to growth stage, shorter duration and shallow flashfloods can result in less than 10% production losses while deeper and stagnant water with two weeks' duration and >100 cm depth can cause damage ranging from 40% to 77%. Major findings of PVS trials and preference analysis indicated that farmers prefer rice cultivars that are tolerant of submergence, have early to medium maturity relative to their commonly grown varieties, are resistant to pests and diseases, and are resistant to lodging, among other traits. To enhance adoption, male and female farmers should be involved in the evaluation process. The results of this study can contribute to enhancing breeding programs to develop appropriate varieties that reduce production losses, improve income, and ultimately reduce poverty incidence in submergence-prone areas.

Environmental and Experimental Botany, 2009

Flash floods adversely affect rice productivity in vast areas of rainfed lowlands in South and Southeast Asia and tropical Africa. Tolerant landraces that withstand submergence for 1–2 weeks were identified; however, incorporation of tolerance into modern high-yielding varieties through conventional breeding methods has been slow because of the complexity of both the tolerance phenotype and floodwater conditions, and the ensuing discrepancies encountered upon phenotyping in different environments. Designing an effective phenotyping strategy requires a thorough understanding of the specific floodwater characteristics that most likely affect survival during flooding. We investigated the implications of floodwater temperature and light penetration, caused by artificial shading, seasonal variation, or water turbidity, for seedling survival after submergence. Three field experiments were conducted using rice genotypes contrasting in their tolerance of submergence: FR13A and Kusuma (tolerant); Gangasiuli (intermediate); Sabita, CRK-2-6 and Raghukunwar (elongating/avoiding types); and IR42 (sensitive). We tested the hypotheses that warmer floodwater decreases plant survival and that turbid water augment plant mortality by causing effects similar to those caused by shading, by reducing light penetration. Plants survive better when water is cooler, and survival decreased at about 8% per unit increase in water temperature above 26 °C. Lower intensity of light and warmer temperatures seem to reduce biomass and increase mortality under flooding. An increase in the concentrations of O2 and CO2 and a decrease in water pH did not improve survival in clear unshaded water. Turbid floodwater was more damaging to rice as plant mortality increased as the percentage of silt increased, and the effects of water turbidity cannot be explained by the reduction in light penetration alone. Even the most tolerant rice cultivar, FR13A, experienced higher mortality when flooded with turbid floodwater. Correlation studies revealed that cultivars with the capacity to maintain higher biomass, higher chlorophyll, and non-structural carbohydrate concentrations after submergence had higher survival. These findings help to understand the variation observed in submergence tolerance when screening is done under different environments. The study could have implications for designing proper screening strategies and assessing the damage submergence causes across different rice-growing regions.