scholarly journals Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI)

2015 ◽  
Vol 18 (1) ◽  
pp. 53-63 ◽  
Author(s):  
Dipanwita Dutta ◽  
Arnab Kundu ◽  
N.R. Patel ◽  
S.K. Saha ◽  
A.R. Siddiqui
Keyword(s):  
Remote Sensing ◽  
Standardized Precipitation Index ◽  
Condition Index ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Vegetation Condition ◽  
Vegetation Condition Index

scholarly journals Drought assessment for kharif rice using standardized precipitation index (SPI) and vegetation condition index (VCI)

2021 ◽  
Vol 21 (2) ◽  
pp. 182-187
Author(s):  
DEEPA B. KAMBLE ◽  
SHWETA GAUTAM ◽  
HIMANI BISHT ◽  
SHRADDHA RAWAT ◽  
ARNAB KUNDU
Keyword(s):  
Standardized Precipitation Index ◽  
Condition Index ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Productivity Index ◽  
Weather Data ◽  
Multiple Regression Equation ◽  
Drought Assessment ◽  
Vegetation Condition ◽  
Vegetation Condition Index

The monthly weather data for 31 years from 1985-2015 was used to analyze the extent of meteorological drought using standardized precipitation index (SPI) over Allahabad, Kanpur and Lucknow. MODIS NDVI data from 2000-2015 was used for monitoring of agricultural drought through NDVI based vegetation condition index (VCI) for all the three districts. The monthly SPI and VCI values from July to October were correlated with productivity index (PI) of kharif rice.Both the indices (SPI and VCI) were positively correlated with PI for all the districts. In Allahabad SPI and VCI during September month showed a significant correlation (0.70**& 0.61*) while in Kanpur VCI during October and SPI of July and August were significantly correlated with PI of kharif Rice. The multiple regression equation developed for predicting kharif rice PI in Allahabad, Kanpur and Lucknow districts explained 69 to 76 per cent variabilityin PI. 

scholarly journals Comparison of Multi-Year Reanalysis, Models, and Satellite Remote Sensing Products for Agricultural Drought Monitoring over South Asian Countries

2021 ◽  
Vol 13 (16) ◽  
pp. 3294
Author(s):  
Muhammad Shahzaman ◽  
Weijun Zhu ◽  
Irfan Ullah ◽  
Farhan Mustafa ◽  
Muhammad Bilal ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
South Asia ◽  
Satellite Remote Sensing ◽  
Crop Production ◽  
Condition Index ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Vegetation Condition ◽  
Vegetation Condition Index

The substantial reliance of South Asia (SA) to rain-based agriculture makes the region susceptible to food scarcity due to droughts. Previously, most research on SA has emphasized the meteorological aspects with little consideration of agrarian drought impressions. The insufficient amount of in situ precipitation data across SA has also hindered thorough investigation in the agriculture sector. In recent times, models, satellite remote sensing, and reanalysis products have increased the amount of data. Hence, soil moisture, precipitation, terrestrial water storage (TWS), and vegetation condition index (VCI) products have been employed to illustrate SA droughts from 1982 to 2019 using a standardized index/anomaly approach. Besides, the relationships of these products towards crop production are evaluated using the annual national production of barley, maize, rice, and wheat by computing the yield anomaly index (YAI). Our findings indicate that MERRA-2, CPC, FLDAS (soil moisture), GPCC, and CHIRPS (precipitation) are alike and constant over the entire four regions of South Asia (northwest, southwest, northeast, and southeast). On the other hand, GLDAS and ERA5 remain poor when compared to other soil moisture products and identified drought conditions in regions one (northwest) and three (northeast). Likewise, TWS products such as MERRA-2 TWS and GRACE TWS (2002–2014) followed the patterns of ERA5 and GLDAS and presented divergent and inconsistent drought patterns. Furthermore, the vegetation condition index (VCI) remained less responsive in regions three (northeast) and four (southeast) only. Based on annual crop production data, MERRA-2, CPC, FLDAS, GPCC, and CHIRPS performed fairly well and indicated stronger and more significant associations (0.80 to 0.96) when compared to others. Thus, the current outcomes are imperative for gauging the deficient amount of data in the SA region, as they provide substitutes for agricultural drought monitoring.

scholarly journals DROUGHT MONITORING OVER PADDY FIELD AREA IN INDRAMAYU DISTRICT, WEST JAVA USING REMOTELY SENSED INDICES

2010 ◽  
Vol 5 (1) ◽  
Author(s):  
Parwati ◽  
Miao Jungang ◽  
Orbita Roswintiarti
Keyword(s):  
Soil Moisture ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Condition Index ◽  
Dry Season ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
West Java ◽  
Vegetation Health

In this research, several meteorological and agricultural drought indices based on remote sensing data are built for drought monitoring over paddy area in Indramayu District, West Java, Indonesia. The meteorological drought index of Standardized Precipitation Index (SPI) is developed from monthly Outgoing Long Wave Radiation (OLR) data from 1980 to 2005. The SPI represents the deficient of precipitation. Meanwhile, the agricultural drought of Vegetation Health Index (VHI) was developed from daily Moderate-resolution ImagingSpectroradiometer (MODIS) data during dry season (May-August) 2003-2006. The VHI was designed to monitoring vegetation health, soil moisture, and thermal conditions. The result shows that the agricultural drought occurate in Indramayu District, especially in the northern and southern part during the dry season in 2003 and 2004. It is found that there is a strong correlation between VHI and soil moisture measured in the field (r=0.84). Key words:Agricultural drought, Meteorological drought, Standardized Precipitation Index, Temperature Condition Index, Vegetation Condition Index.

scholarly journals GEOSPATIAL APPROACH TO CATEGORIZE AND COMPARE THE AGRO-CLIMATOLOGICAL DROUGHTS OVER MARATHWADA REGION OF MAHARASHTRA, INDIA

2018 ◽  
Vol IV-5 ◽  
pp. 279-285
Author(s):  
S. Kulkarni ◽  
S. Gedam
Keyword(s):  
Management Strategies ◽  
Standardized Precipitation Index ◽  
Interdisciplinary Approach ◽  
Condition Index ◽  
Agricultural Drought ◽  
Drought Severity ◽  
Severe Drought ◽  
Vegetation Condition Index ◽  
Rainfall Trends ◽  
Drought Mitigation

<p><strong>Abstract.</strong> The present study mainly focuses on the comparison and quantification of meteorological droughts with agricultural droughts to understand their relationship to the occurrences and intensities of droughts. This study is based on analysis of the changing agro-climatological drought conditions from the year 2001 to 2017, over the districts of Marathwada, which are known to be the most drought-prone regions of the Maharashtra, India. To quantify the drought severity, Standardized Precipitation Index (SPI) from TRMM and Vegetation Condition Index (VCI) from MODIS datasets have been derived and compared. This study indicated that the years 2002, 2009, 2014 and 2015 were the most severe drought periods over Marathwada. Parts of Nanded, Aurangabad and Latur districts were the highest drought-affected areas from last 17 years, where the frequency of agricultural drought incidence was more than eight years. Over the districts of Hingoli and Parbhani, decreasing rainfall trends plus highly negative values of SPI (&amp;leq;<span class="thinspace"></span>&amp;minus;1.5) in the month of July shows a major concern for agricultural activities. Positive correlation-ship (41%) was noticed between SPI and VCI during the study period, but it was not statistically significant. In the year 2015, which was one of the intense drought years, it is noted that the agricultural drought was the most influencing drought type covering about 53% of the affected area. This study thus can help in identification of drought types and their intensities with spatial extent through an area specific interdisciplinary approach which in turn will help to develop region-specific drought mitigation and management strategies.</p>

scholarly journals VARIAÇÃO ESPAÇO-TEMPORAL DA CONDIÇÃO DA VEGETAÇÃO NO INTERIOR PAULISTA

Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 582
Author(s):  
Roberto Filgueiras ◽  
Donizeti Aparecido Pastori Nicolete ◽  
Antonio Ribeiro Cunha ◽  
Célia Regina Lopes Zimback
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Local Level ◽  
Condition Index ◽  
Vegetation Pattern ◽  
Semideciduous Forest ◽  
Vegetation Condition ◽  
Vegetation Condition Index ◽  
Landsat 5 Tm ◽  
Spatio Temporal

A compreensão da dinâmica das condições da vegetação ao longo do tempo tem sido ampliada devido ao avanço das técnicas de sensoriamento remoto. O presente trabalho teve como objetivo analisar a dinâmica espaço-temporal da vegetação estratificada por diferentes usos e cobertura da terra, em área localizada no município de Botucatu-SP. Para isso, foram utilizadas 21 imagens da plataforma Landsat-5/TM, totalizando uma série temporal de 25 anos (1985 a 2010). As imagens foram submetidas aos processos de conversão dos números digitais para valores físicos, correção atmosférica e correção topográfica. As imagens corrigidas foram utilizadas para estimar os valores do VCI (Vegetation Condition Index). Os resultados da estimativa do VCI foram promissores para subsidiar a análise espaço-temporal da condição da vegetação em nível local, sendo sensível às variações locais de precipitação pluviométrica, amplificando a variabilidade intra-classe de uso da terra para o vigor da vegetação. O comportamento característico da floresta semidecidual (classe de uso da terra = Floresta) presente na propriedade foi perceptível nessa análise, fato que faz com se recomende essa metodologia em pesquisas futuras relacionadas a análise da condição da vegetação.Palavras-chave: monitoramento ambiental; sensoriamento remoto; séries temporais. SPATIAL AND TEMPORAL CHANGES IN VEGETATION CONDITIONS IN PAULIST INTERIOR ABSTRACT: There is an increasing demand to better understand the dynamics of the vegetation conditions over time as a result of the improvement of remote sensing techniques. Yhis study aimed to analyse the spatio-temporal behavior of vegetation, stratified by land use in area located in Botucatu-SP. We sused21 Landsat-5 TM images in 25 years (1985 – 2010) of analysis. We applied conversion of the digital numbers to physical values, atmospheric and topographic corrections, which allowed to analyze the vegetation changes by using the VCI (Vegetation Condition Index) calculation. The VCI showed a good performance in analyzing the spatiotemporal vegetation condition at a local level, it is sensitive to local variations of rainfall, it enhances the variability of the intra-class land use for the vigor of vegetation. By applying the VCI we were able to observe the vegetation pattern of the semideciduous forest (land use class = Forest) present in the area, fact that makes this methodology recommended in future researches related to the analysis of the vegetation condition.Keywords: environmental monitoring; remote sensing; time series.

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