scholarly journals Satellite Data and Supervised Learning to Prevent Impact of Drought on Crop Production: Meteorological Drought

2020 ◽  
Author(s):  
Leonardo Ornella ◽  
Gideon Kruseman ◽  
Jose Crossa
Keyword(s):  
Supervised Learning ◽  
Satellite Data ◽  
Crop Production ◽  
Meteorological Drought

Satellite Data Based Soil Water Index as a Tool to Monitor Droughts and Agricultural Crisis -An Example of Yavatmal District, Maharashtra, India

2020 ◽  
Vol 4 (1-2) ◽  
pp. 12-18
Author(s):  
Vijendra Boken
Keyword(s):  
Soil Water ◽  
Satellite Data ◽  
Suicide Rate ◽  
Crop Yields ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Coefficient Of Correlation ◽  
Water Index ◽  
Farmer Suicides ◽  
June July

Yavatmal is one of the drought prone districts in Maharashtra state of India and has witnessed an agricultural crisis to the extent that hundreds of its farmers have committed suicides in recent years. Satellite data based products have previously been used globally for monitoring and predicting of drought, but not for monitoring their extreme impacts that may include farmer-suicides. In this study, the performance of the Soil Water Index (SWI) derived from the surface soil moisture estimated by the European Space Agency’s Advanced Scatterometer (ASCAT) is assessed. Using the 2007-2015 data, it was found that the relationship of the SWI anomaly was bit stronger (coefficient. of correlation = 0.59) with the meteorological drought or precipitation than with the agricultural drought or crop yields of major crops (coefficient. of correlation = 0.50).  The farmer-suicide rate was better correlated with the SWI anomaly averaged annually than with the SWI anomaly averaged only for the monsoon months (June, July, August, and September). The correlation between the SWI averaged annually increased to 0.89 when the averages were taken for three years, with the highest correlation occurring between the suicide rate and the SWI anomaly averaged for three years. However, a positive relationship between SWI and the suicide rate indicated that drought was not a major factor responsible for suicide occurrence and other possible factors responsible for suicide occurrence need to examine in detail.

scholarly journals Supervised Learning for Microclimatic parameter Estimation in a Greenhouse environment for productive Agronomics

2020 ◽  
Vol 2 (3) ◽  
pp. 170-176
Author(s):  
Dr. Samuel Manoharan
Keyword(s):  
Supervised Learning ◽  
Crop Production ◽  
Learning Algorithm ◽  
Crop Growth ◽  
Outdoor Environment ◽  
Sensor Nodes ◽  
Growth Stages ◽  
Closed Field ◽  
Growth Environment ◽  
Model Based

Maximum crop returns are essential in modern agriculture due to various challenges caused by water, climatic conditions, pests and so on. These production uncertainties are to be overcome by appropriate evaluation of microclimate parameters at commercial scale for cultivation of crops in a closed-field and emission free environment. Internet of Things (IoT) based sensors are used for learning the parameters of the closed environment. These parameters are further analyzed using supervised learning algorithms under MATLAB Simulink environment. Three greenhouse crop production systems as well as the outdoor environment are analyzed for comparison and model-based evaluation of the microclimate parameters using the IoT sensors. This analysis prior to cultivation enables creating better environment and thus increase the productivity and harvest. The supervised learning algorithm offers self-tuning reference inputs based on the crop selected. This offers a flexible architecture and easy analysis and modeling of the crop growth stages. On comparison of three greenhouse environment as well as outdoor settings, the functional reliability as well as accuracy of the sensors are tested for performance and validated. Solar radiation, vapor pressure deficit, relative humidity, temperature and soil fertility are the raw data processed by this model. Based on this estimation, the plant growth stages are analyzed by the comfort ratio. The different growth stages, light conditions and time frames are considered for determining the reference borders for categorizing the variation in each parameter. The microclimate parameters can be assessed dynamically with comfort ratio index as the indicator when multiple greenhouses are considered. The crop growth environment is interpreted better with the Simulink model and IoT sensor nodes. The result of supervised learning leads to improved efficiency in crop production developing optimal control strategies in the greenhouse environment.

scholarly journals Assessment of Meteorological and Agricultural Drought Occurrence in Central Poland in 1961–2020 as an Element of the Climatic Risk to Crop Production

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 855
Author(s):  
Renata Kuśmierek-Tomaszewska ◽  
Jacek Żarski
Keyword(s):  
Crop Production ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Research Strategy ◽  
Economic Effects ◽  
Agricultural Drought ◽  
Central Poland ◽  
Dry Spell ◽  
Statistical Trends ◽  
Meteorological Droughts

The results of numerous studies concerning meteorological drought show that there is a considerable impact of this phenomenon on several regions in Europe. On the other hand, statistical trends of dry spell occurrences in some areas of the continent are unclear or even negative. Therefore, further research should be directed towards a better understanding of this hazard, particularly the seasonal changes, in order to elaborate adequate strategies to prevent and mitigate its undesirable effects. The main goal of the work, conducted as part of the research strategy on contemporary climate change, was to confirm the hypothesis of increasing frequency and intensity of droughts during the period of active plant growth and development (May–August) in central Poland in 1961–2020. The prevailing rainfall conditions in this period determine the production and economic effects of agricultural output. The analysis covered a multiannual period, including two separate climate normals: 1961–1990 and 1991–2020. The work is also aimed at detecting relationships between indicators characterizing meteorological drought (the Standardized Precipitation Index—SPI) and agricultural drought (the actual precipitation deficiency—PAdef). It was found that the frequency of meteorological droughts in the studied period amounts to 30.0% (severe and extreme constitute 6.7%). No significant increase in the frequency and intensity of meteorological droughts over time was observed. Relationships between meteorological and agricultural drought indicators were significant, so the SPI can be considered an indicator of plant irrigation needs in the studied area.

scholarly journals Development and Evaluation of an Agricultural Drought Index by Harnessing Soil Moisture and Weather Data

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1375 ◽  
Author(s):  
Ali Ajaz ◽  
Saleh Taghvaeian ◽  
Kul Khand ◽  
Prasanna H. Gowda ◽  
Jerry E. Moorhead
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Drought Index ◽  
Root Zone ◽  
Correlation Coefficients ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Growth Stages

A new agricultural drought index was developed for monitoring drought impacts on agriculture in Oklahoma. This new index, called the Soil Moisture Evapotranspiration Index (SMEI), estimates the departure of aggregated root zone moisture from reference evapotranspiration. The SMEI was estimated at five locations across Oklahoma representing different climates. The results showed good agreement with existing soil moisture-based (SM) and meteorological drought indices. In addition, the SMEI had improved performance compared to other indices in capturing the effects of temporal and spatial variations in drought. The relationship with crop production is a key characteristic of any agricultural drought index. The correlations between winter wheat production and studied drought indices estimated during the growing period were investigated. The correlation coefficients were largest for SMEI (r > 0.9) during the critical crop growth stages when compared to other drought indices, and r decreased by moving from semi-arid to more humid regions across Oklahoma. Overall, the results suggest that the SMEI can be used effectively for monitoring the effects of drought on agriculture in Oklahoma.

scholarly journals AN EFFECTIVE INFORMATION SYSTEM OF DROUGHT IMPACT ON RICE PRODUCTION BASED ON REMOTE SENSING

2017 ◽  
Vol 11 (2) ◽  
pp. 153
Author(s):  
Rizatus Shofiyati ◽  
Wataru Takeuchi ◽  
Soni Darmawan ◽  
Parwati Sofan
Keyword(s):  
Information System ◽  
Satellite Data ◽  
Drought Index ◽  
Data Transfer ◽  
Meteorological Drought ◽  
Rice Production ◽  
Agricultural Drought ◽  
Drought Impact ◽  
Management Actions ◽  
The Government

Long droughts experienced in the past are identified as one of the main factors in the failure of rice production. In this regard, special attention to monitor the condition is encouraged to reduce the damage. Currently, various satellite data and approaches can withdraw valuable information for monitoring and anticipating drought hazards. MODIS, MTSAT, AMSR-E, TRMM and GSMaP have been used in this activity. Meteorological drought index (SPI) of the daily and monthly rainfall data from TRMM and GSMaP have analyzed for last 10-year period. While, agronomic drought index has been studied by observing the character of some indices (EVI, VCI, VHI, LST, and NDVI) of sixteen-day and monthly MODIS, MTSAT, and AMSR-E data at a period of 4 years. Network for satellite data transfer has been built between LAPAN (data provider), ICALRD (implementer), IAARD Cloud Computing, University of Tokyo (technical supporter), and NASA. Two information system have been developed: 1) agricultural drought using the model developed by LAPAN, and 2) meteorological drought developed by Takeuchi (University of Tokyo).The accuracy study using quantitative method for LAPAN model uses VHI is 60% (Kappa 0,44), while that of for University of Tokyo model uses qualitative model with KBDI value 500-600 shows an early indication of  drought for paddy field. This will help the government or field officers in rapid management actions for the indicated drought area.This paper describes the implementation and dissemination of drought impact monitoring model on the area of rice production center using an integrated information system satellite based model. The two developed information systems are effective for spatially dissemination of drought information.

scholarly journals COMBINATION OF METEOROLOGICAL INDICES AND SATELLITE DATA FOR DROUGHT MONITORING IN TWO DIFFERENT ENVIRONMENTS IN IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 197-200
Author(s):  
M. Behifar ◽  
A. A. Kakroodi ◽  
M. Kiavarz ◽  
F. Amiraslani
Keyword(s):  
Satellite Data ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Drought Monitoring ◽  
Spatial Characteristic ◽  
Drought Indices ◽  
Precipitation Data ◽  
Spi Index ◽  
The Standardized Precipitation Index

Abstract. The main problem using meteorological drought indices include inappropriate distribution of meteorological stations. Satellite data have reliable spatial and temporal resolution and provide valuable information used in many different applications. The Standardized precipitation index has several advantages. The SPI is based on rainfall data alone and has a variable time scale and is thus conducive to describing drought conditions for different application.This study aims to calculate SPI using satellite precipitation data and compare the results with traditional methods. To do this, satellite-based precipitation data were assessed against station data and then the standardized precipitation index was calculated. The results have indicated that satellite-based SPI could illustrate drought spatial characteristic more accurate than station-based index. Also, the standardized property of the SPI index allows comparisons between different locations, which is one of the remote sensing drought indices limitations.

scholarly journals Meteorological Drought Assessment in Sharjah, UAE Using Drought Indices

2022 ◽  
Vol 13 (1) ◽  
pp. 16-20
Author(s):  
Mhamd S. Oyounalsoud ◽  
◽  
Arwa Najah ◽  
Abdullah G. Yilmaz ◽  
Mohamed Abdallah ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Crop Production ◽  
Standardized Precipitation Index ◽  
Extended Period ◽  
Meteorological Drought ◽  
Distribution Functions ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Drought Assessment ◽  
The Standardized Precipitation Index

Drought is a natural disaster that significantly affects environmental and socio-economic conditions. It occurs when there is a period of below average precipitation in a region, and it results in water supply shortages affecting various sectors and life adversely. Droughts impact the ecosystems, crop production, and erode livelihoods. Monitoring drought is essential especially in the United Arab Emirates (UAE) due to the scarcity of rainfall for an extended period of time. In this study, drought is assessed in Sharjah UAE using monthly precipitation and average temperature data recorded for 35 years (1981-2015) at the Sharjah International Airport. The standardized precipitation Index (SPI), and the Reconnaissance Drought Index (RDI) are selected to predict future droughts in the region. SPI and RDI are fitted to the statistical distribution functions (gamma and lognormal) in an annual time scale and then, a trend analysis of index values is carried out using Mann-Kendal test. The correlation between SPI and RDI indices was found to be high where both showed high drought frequencies and a tendency to get drier over time, thus indicating the need of appropriate drought management and monitoring.

Wheat crop production estimation using satellite data

2002 ◽  
Vol 30 (4) ◽  
pp. 213-219 ◽  
Author(s):  
G D Bairagi ◽  
ZIA-UL Hassan
Keyword(s):  
Satellite Data ◽  
Crop Production ◽  
Wheat Crop
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