Drought assessment in paddy rice fields using remote sensing technology towards achieving food security and SDG2

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hadi Shams Esfandabadi ◽  
Mohsen Ghamary Asl ◽  
Zahra Shams Esfandabadi ◽  
Sneha Gautam ◽  
Meisam Ranjbari
Keyword(s):  
Rice Yield ◽  
Vegetation Indices ◽  
Condition Index ◽  
Google Earth ◽  
Paddy Rice ◽  
Rice Fields ◽  
Drought Risk ◽  
Rice Paddies ◽  
Northern Iran ◽  
Content Type

PurposeThis research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.Design/methodology/approachA three-step methodology is applied. First, the paddy rice fields are mapped by using three satellite-based datasets, namely SRTM DEM, Landsat8 TOA and MYD11A2. Second, the maps of indices are extracted using MODIS. And finally, the trend of indices over rice-growing seasons is extracted and compared with the rice yield data.FindingsRice paddies maps and vegetation indices maps are provided. Vegetation Health Index (VHI) combining average Temperature Condition Index (TCI) and minimum Vegetation Condition Index (VCI), and also VHI combining TCImin and VCImin are found to be the most proper indices to predict rice yield.Practical implicationsThe results serve as a guideline for policy-makers and practitioners in the agro-food industry to (1) support sustainable agriculture and food safety in terms of rice production; (2) help balance the supply and demand sides of the rice market and move towards SDG2; (3) use yield prediction in the rice supply chain management, pricing and trade flows management; and (4) assess drought risk in index-based insurances.Originality/valueThis study, as one of the first research assessing and mapping vegetation indices for rice paddies in northern Iran, particularly contributes to (1) extracting the map of paddy rice fields in Mazandaran Province by using satellite-based data on cloud-computing technology in the Google Earth Engine platform; (2) providing the map of VCI and TCI for the period 2010–2019 based on MODIS data and (3) specifying the best index to describe rice yield through proposing different calculation methods for VHI.

scholarly journals Cloud Cover throughout All the Paddy Rice Fields in Guangdong, China: Impacts on Sentinel 2 MSI and Landsat 8 OLI Optical Observations

2021 ◽  
Vol 13 (15) ◽  
pp. 2961
Author(s):  
Rui Jiang ◽  
Arturo Sanchez-Azofeifa ◽  
Kati Laakso ◽  
Yan Xu ◽  
Zhiyan Zhou ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Southern China ◽  
Vegetation Indices ◽  
Paddy Rice ◽  
Rice Fields ◽  
Optical Observations ◽  
Landsat 8 ◽  
Monthly Basis ◽  
Satellite Sensors ◽  
Sentinel 2

Cloud cover hinders the effective use of vegetation indices from optical satellite-acquired imagery in cloudy agricultural production areas, such as Guangdong, a subtropical province in southern China which supports two-season rice production. The number of cloud-free observations for the earth-orbiting optical satellite sensors must be determined to verify how much their observations are affected by clouds. This study determines the quantified wide-ranging impact of clouds on optical satellite observations by mapping the annual total observations (ATOs), annual cloud-free observations (ACFOs), monthly cloud-free observations (MCFOs) maps, and acquisition probability (AP) of ACFOs for the Sentinel 2 (2017–2019) and Landsat 8 (2014–2019) for all the paddy rice fields in Guangdong province (APRFG), China. The ATOs of Landsat 8 showed relatively stable observations compared to the Sentinel 2, and the per-field ACFOs of Sentinel 2 and Landsat 8 were unevenly distributed. The MCFOs varied on a monthly basis, but in general, the MCFOs were greater between August and December than between January and July. Additionally, the AP of usable ACFOs with 52.1% (Landsat 8) and 47.7% (Sentinel 2) indicated that these two satellite sensors provided markedly restricted observation capability for rice in the study area. Our findings are particularly important and useful in the tropics and subtropics, and the analysis has described cloud cover frequency and pervasiveness throughout different portions of the rice growing season, providing insight into how rice monitoring activities by using Sentinel 2 and Landsat 8 imagery in Guangdong would be impacted by cloud cover.

Ochratoxin A analysis in rice samples of different cities of Mazandaran (a province in Northern Iran)

2014 ◽  
Vol 44 (3) ◽  
pp. 223-229 ◽  
Author(s):  
Issa Gholampour Azizi ◽  
Hassan Ghadi ◽  
Samaneh Rouhi
Keyword(s):  
Rice Fields ◽  
Blue Color ◽  
Northern Iran ◽  
Content Type ◽  
Sample Extract ◽  
Rice Samples ◽  
Standard Solution ◽  
Spss Software ◽  
Contamination Levels ◽  
Practical Implications

Purpose – OTA is primarily produced by species of Penicillium and Aspergillus. This toxin has been detected worldwide in different grains such as rice. Due to OTA's toxicity and its effects on human's health, the authors performed this study to analyze the OTA's contamination levels in rice samples that gathered in different cities of Mazandaran (a province in northern Iran). The paper aims to discuss these issues. Design/methodology/approach – In this study, 80 rice samples were collected from several cities of Mazandaran. Data were analyzed using CD-ELISA method for OTA. Conjugated enzyme was added to uncoated-antibody wells and standard solution and sample extract were added to it. Solutions were transferred to the coated-antibody wells. Then, substrate was added to produce blue color. Finally, stopping solution was added to stop the reaction. The color intensity was inversely proportional to the OTA concentration, measured with the ELISA reader and calculated by analysis of variance by using the SPSS software package. Findings – None of the samples that were collected in Mazandaran were contaminated with >5 μg/kg of OTA in October. Also none of the samples from Amol, Fereydonkenar, Babol or Behshahr were contaminated with >5 μg/kg of this toxin in November. But in sari, Nowshahr and Ramsar the authors encountered samples that had >5 μg/kg of OTA contamination which is more than the acceptable limit. Practical implications – Screening and analyzing the rice fields are vital to detect any OTA contamination and can be effective for removing the contaminated rice. So proper strategies and management tactics are required in order to prevent OTA production in rice fields in pre- and post-harvest time and people must share their experiences regarding fighting this contamination. Originality/value – Since rice is used extensively all over the world, consumption of contaminated rice causes diseases for humans. Therefore, determination, management, and prevention of OTA should be considered seriously.

Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine

2020 ◽  
Vol 166 ◽  
pp. 278-293 ◽  
Author(s):  
Mrinal Singha ◽  
Jinwei Dong ◽  
Sangeeta Sarmah ◽  
Nanshan You ◽  
Yan Zhou ◽  
...  
Keyword(s):  
Google Earth ◽  
Paddy Rice ◽  
Rice Fields ◽  
Google Earth Engine

scholarly journals Drought Analysis for the Seyhan Basin with NDVI and VCI Vegetation Indices

2021 ◽  
Author(s):  
Murat Aksel ◽  
Mehmet Dikici
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Condition Index ◽  
Drought Indices ◽  
Drought Risk ◽  
Vegetation Condition Index ◽  
Management Plans

Abstract Various drought indices have been developed to monitor the drought, which is one of the results of climate change and mitigates its adverse effects on water resources, especially agriculture. Vegetation indices determined by remote sensing have been the subject of many studies in recent years and shed light on drought risk management. This study is examined in the Seyhan River Basin, a basin with Turkey’s considerable population density counts and is situated south of the country. Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI) are the most widely used vegetation indices and are very useful because they give results only based on satellite images. This study examined the Seyhan Basin by using satellite data in which the vegetation transformation occurring due to the decline of agricultural and forest areas was also seen. An increase in drought frequency was detected in the Seyhan Basin using NDVI and VCI indices. It was determined that climate change and drought increased with a linear uptrend. It is recommended that decision-makers should take the necessary measures by considering the drought risk maps and that long-term drought management plans should be made and implemented.

scholarly journals Mapping Paddy Rice Fields by Combining Multi-Temporal Vegetation Index and Synthetic Aperture Radar Remote Sensing Data Using Google Earth Engine Machine Learning Platform

2020 ◽  
Vol 12 (18) ◽  
pp. 2992 ◽  
Author(s):  
Nengcheng Chen ◽  
Lixiaona Yu ◽  
Xiang Zhang ◽  
Yonglin Shen ◽  
Linglin Zeng ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Google Earth ◽  
Paddy Rice ◽  
Synthetic Aperture ◽  
Google Earth Engine ◽  
Data Missing

The knowledge of the area and spatial distribution of paddy rice fields is important for water resource management. However, accurate map of paddy rice is a long-term challenge because of its spatiotemporal discontinuity and short duration. To solve this problem, this study proposed a paddy rice area extraction approach by using the combination of optical vegetation indices and synthetic aperture radar (SAR) data. This method is designed to overcome the data-missing problem due to cloud contamination and spatiotemporal discontinuities of the traditional optical remote sensing method. More specifically, the Sentinel-1A SAR and the Sentinel-2 multispectral imager (MSI) Level-2A imagery are used to identify paddy rice with a high temporal and spatial resolution. Three vegetation indices, namely normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and land surface water index (LSWI), are estimated from optical bands. Two polarization bands (VH (vertical-horizontal) and VV (vertical-vertical)) are used to overcome the cloud contamination problem. This approach was applied with the random forest machine learning algorithm on the Google Earth Engine platform for the Jianghan Plain in China as an experimental area. The results of 39 experiments uncovered the effect of different factors. The results indicated that the combination of VV and VH band showed a better performance compared with other polarization bands; the average producer’s accuracy of paddy rice (PA) is 72.79%, 1.58% higher than the second one VH. Secondly, the combination of three indices also showed a better result than others, with average PA 73.82%, 1.42% higher than using NDVI alone. The classification result presented the best combination is EVI, VV, and VH polarization band. The producer’s accuracy of paddy rice was 76.67%, with the overall accuracy (OA) of 66.07%, and Kappa statistics of 0.45. However, NDVI, EVI, and VH showed better performance in mapping the morphology. The results demonstrated the method developed in this study can be successfully applied to the cloud-prone area for mapping paddy rice to overcome the data missing caused by cloud and rain during the paddy growing season.

Emergence of Weeds in Paddy Rice Fields

1975 ◽  
Vol 20 (3) ◽  
pp. 109-113 ◽  
Author(s):  
Mitsuyoshi SUZUKI ◽  
Takahisa SUTO
Keyword(s):  
Paddy Rice ◽  
Rice Fields

Organizing worn-out neighborhoods with the new-urbanism approach using mixed methods in Rudsar, northern Iran

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Askarizad ◽  
Akram Dadashpour ◽  
Javad Faghirnavaz ◽  
Jinliao He ◽  
Hossein Safari
Keyword(s):  
Mixed Methods ◽  
Spatial Configuration ◽  
New Urbanism ◽  
Northern Iran ◽  
Content Type ◽  
Expert Choice ◽  
Traditional Structure ◽  
Building Information ◽  
The Face ◽  
Hierarchy Process

PurposeThe vulnerability of worn-out textures in the face of natural disasters is one of the most significant challenges that have forced planners and urban managers to intervene in these structures. In this context, the new-urbanism, or the new urbanization, movement is one of the most novel approaches. This paper aims to organizing one of the worn-out neighborhoods in Rudsar, northern Iran with an approach toward the new urbanism.Design/methodology/approachThe procedure adopted in this research is a combination of both quantitative and qualitative practices with an applied approach. Therefore, through utilizing the analytical hierarchy process (AHP) and space syntax methods, the principles of the new urbanism are examined using the Expert Choice and Depthmap software. Subsequently, the appropriate priorities are mentioned for organizing the neighborhood with the new-urbanism approach using the building information system (BIM) and strengths, weaknesses, opportunities and threats (SWOT) techniques.FindingsThe findings of this study indicate that among the main characteristics of the new urbanism, walkability is recognized as the most important factor. Afterward, the components of maintaining the traditional structure of neighborhoods and connectivity were in the second and third ranks, respectively, of importance. Accordingly, by identifying the societal potential of roads according to their spatial configuration, it is possible to boost walkability, as well as economic prosperity in these areas.Originality/valueThe combination and correlation of the four utilized methods in this research can be adopted in the future studies as a new outlook of the mixed methods in the field of urban studies.

Impact of multiple soil conservation practices on rice yields and chemical fertiliser use in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhihai Yang ◽  
Ning Yin ◽  
Amin William Mugera ◽  
Yumeng Wang
Keyword(s):  
Soil Conservation ◽  
Rice Yield ◽  
Smallholder Farmers ◽  
Policy Implications ◽  
Conservation Practices ◽  
Organic Fertiliser ◽  
Content Type ◽  
Straw Retention ◽  
Fertiliser Use ◽  
Chemical Fertiliser

PurposeThis paper analysed survey data of 715 rice-producing households in China to assess the determinants of adoption of five mutually exclusive soil conservation practices (SCPs) and their impact on rice yield and chemical fertiliser use.Design/methodology/approachThe multinomial endogenous treatment effects model was used to account for selection bias and endogeneity arising from both observed and unobserved heterogeneity.FindingsFarms that adopted SCPs as a package experienced an increase in rice yield and decrease in chemical fertiliser use. Adoption of SCPs as a package led to a 12.0% increase in yield and 15.2% decrease in chemical fertiliser use; these results have policy implications for the non-point source pollution control in the agricultural sector. In contrast, adoption of straw retention only significantly reduced yield by 4.9% and increased chemical fertiliser use by 18.1%.Originality/valueThe authors evaluate and compare multi-type of SCPs, such as straw retention, deep tillage and use of organic fertiliser, separately or in combination, and their impacts on smallholder farmers’ rice yield and chemical fertiliser usage.

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