Drought risk assessment using remote sensing and GIS techniques

Belal, Abdel-Aziz; El-Ramady, Hassan; Mohamed, Elsayed Said; Saleh, Ahmed M.

doi:10.1007/s12517-012-0707-2

Cited by 176 publications

(84 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The negative index value can be recorded over the water bodies while values are close to 0 over the land without vegetation. The index value equal to 1 indicates perfect growing conditions (Lillesand and Kiefer, 1994;Belal et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

Drought identification in the eastern Baltic region using NDVI

et al. 2017

View full text Add to dashboard Cite

Abstract. Droughts are phenomena that affect large areas. Remote sensing data covering large territories can be used to assess the impact and extent of droughts. Drought effect on vegetation was determined using the normalized difference vegetation index (NDVI) and Vegetation Condition Index (VCI) in the eastern Baltic Sea region located between 53-60 • N and 20-30 • E. The effect of precipitation deficit on vegetation in arable land and broadleaved and coniferous forest was analysed using the Standardized Precipitation Index (SPI) calculated for 1-to 9-month timescales. Vegetation has strong seasonality in the analysed area. The beginning and the end of the vegetation season depends on the distance from the Baltic Sea, which affects temperature and precipitation patterns. The vegetation season in the southeastern part of the region is 5-6 weeks longer than in the northwestern part. The early spring air temperature, snowmelt water storage in the soil and precipitation have the largest influence on the NDVI values in the first half of the active growing season. Precipitation deficit in the first part of the vegetation season only has a significant impact on the vegetation on arable land. The vegetation in the forests is less sensitive to the moisture deficit. Correlation between VCI and the same month SPI1 is usually negative in the study area. It means that wetter conditions lead to lower VCI values, while the correlation is usually positive between the VCI and the SPI of the previous month. With a longer SPI scale the correlation gradually shifts towards the positive coefficients. The positive correlation between 3-and 6-month SPI and VCI was observed on the arable land and in both types of forests in the second half of vegetation season. The precipitation deficit is only one of the vegetation condition drivers and NDVI cannot be used universally to identify droughts, but it may be applied to better assess the effect of droughts on vegetation in the eastern Baltic Sea region.

show abstract

Section: Methodsmentioning

confidence: 99%

Drought identification in the eastern Baltic region using NDVI

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Since that particular study, no investigations about the productivity of land https://www.ecologyandsociety.org/vol22/iss4/art9/ on a regional scale have been conducted in the Middle East. Drought refers to a relative decrease in water availability, mostly caused by a reduction in rainfall (Belal et al 2014). Much research is focused on the meteorological aspects of drought (i.e., reduction in precipitation); however, an agricultural perspective that focuses on soil moisture and crop production can provide more indepth insight into the socioeconomic impacts of drought (Eklund and Seaquist 2015).…”

Section: Introductionmentioning

confidence: 99%

Differences in resource management affects drought vulnerability across the borders between Iraq, Syria, and Turkey

Eklund¹,

Thompson²

2017

E&S

View full text Add to dashboard Cite

ABSTRACT. Much discussion has taken place exploring a potential connection between the 2007-2009 Fertile Crescent drought and Syria's uprising-turned civil war beginning in 2011. This study takes an integrated perspective on the 2007-2009 drought in the border region of Iraq, Syria, and Turkey by looking at the meteorological, agricultural, and socioeconomic aspects of drought vulnerability. Satellite-based precipitation and vegetation data help outline the drought's spatial and temporal properties. In order to understand the context in which this drought happened, we also look at the trends in vegetation productivity between 2001 and 2015, as well as each country's different politico-economic factors affecting land and water resource management leading up to the drought. The findings show that, although the drought was severe in Syria, it was not the only country affected, nor necessarily the worst hit meteorologically. The agricultural drought lasted 2 yr in most affected areas on the Iraqi and Syrian sides, however, only 1 yr in the affected areas on the Turkish side. The vegetation trend analysis shows a striking difference between the Syrian and Turkish sides of the border. Turkey experienced a general improvement in land productivity between 2001 and 2015, whereas Iraq and Syria show a generally negative productivity trend. The fact that the decline in rainfall had different effects on crops in each of the three countries highlights the role government and private sector resource management and infrastructure play in reducing drought vulnerability. The findings of this study highlight the need for an integrated approach to research that investigates the interconnection between climate and conflict.

show abstract

“…The water scarcity is being further compounded by droughts which affect both surface water and groundwater resources and can lead to reduced water supply, deteriorated water quality, crop failure, and disturbed riparian habitats [6]. Hence, this research study has been carried because understanding drought and modeling its components have drawn attention of ecologists, hydrologists, meteorologists, and agricultural scientists [7]. Therefore, a simple but robust definition of the marginal value of a unit of water, highlighting key aspects of water scarcity and illustrating its many biophysical and socioeconomic determinants is required [8].…”

Section: Introductionmentioning

confidence: 99%

Using GIS and Remote Sensing in Assessment of Water Scarcity in Nakuru County, Kenya

Changwony¹,

Sichangi²,

Ngigi³

2017

ARS

View full text Add to dashboard Cite

Water is at the core of sustainable development and is critical for socio-economic development, healthy ecosystems and for human survival. This research study has been carried out in Nakuru County, a tropical region in the Rift Valley of Kenya, bounded between latitude 0.28˚N and 1.16˚S, and longitude 36.27˚E and 36.55˚E. The objective of the study has been to use GIS and remote sensing in assessment of water scarcity using Land use Land cover area changes, standard precipitation index and crop yields. Landsat satellite images for the year 1985, 1995, 2005 and 2015 were used. Classification was done using maximum likelihood algorithm while classification accuracy assessment entailed the use of confusion matrix method and ground truth data. Post classification change detection results gave percentage cropland areas as 21% in 1985, 29% in 1995, 53% in 2005 and also 53% in 2015. Eleven (11) ground rainfall stations and TRMM satellite rainfall data from 1985 to 2015 has been used to show meteorological drought. Validation of rainfall data done using correlation coefficient (R 2 ) and root mean square (RMS) methods showed that ground rainfall data and TRMM data correlate. Modelling of 3 months SPI for each of the three seasons (MAM, JJA and OND) has been done using interpolation distance weighted method (IDW). 3 months SPI time scales curves gave October 1987, May 1993, and July 2004 as water scarce and dry seasons and were categorized as either Normal, moderately dry, severely dry and extremely dry. Crop yield trends curves showed crop yield decrease in this identified water scarce and dry years. Conclusion reached is that crop yields is not dependent on size of land ploughed only but mostly on rainfall quantities. Therefore, the findings of this research can be used as drought monitoring tools.

show abstract

Drought risk assessment using remote sensing and GIS techniques

Cited by 176 publications

References 28 publications

Drought identification in the eastern Baltic region using NDVI

Drought identification in the eastern Baltic region using NDVI

Differences in resource management affects drought vulnerability across the borders between Iraq, Syria, and Turkey

Using GIS and Remote Sensing in Assessment of Water Scarcity in Nakuru County, Kenya

Contact Info

Product

Resources

About