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Variance-Based Fusion of VCI and TCI for Efficient Classification of Agriculture Drought Using Landsat Data in the High Atlas (Morocco, North Africa)
2023
Fathallah Fatima Ezzahra, Algouti Ahmed and Algouti Abdellah
Drought assessment using drought indices has been widely carried out for drought monitoring. Remote sensing-based indices use remotely sensed data to map drought conditions in a particular area or region. Therefore, the objective of the present study is to make a study on drought risk based on the calculation of an indicator from biophysical parameters extracted from NOAA/AVHRR satellite data, namely TCI and VCI, to obtain a better understanding of the differentiation between each index, and their application for drought monitoring in the High Atlas of Marrakech on the Chchaoua Morocco watershed during 1980-2020. Landsat oli7 and8 data were used to construct the indices. The result showed that each index proved to be a useful, fast, sufficient, and inexpensive tool for drought monitoring. However, each index has its differences. The TCI was found to be drought sensitive during the dry season or in months when high temperatures occurred. While VCI detected drought more sensitively in the rainy season as well (December-January-February to May) than TCI and VCI. Meanwhile, VCI, including the improved TCI, combined two indicators to better understand drought occurrence. These indices were calculated using GIS, QGis, ArcGis satellite imagery scenes, and Landsat. After a comparative study of these years, from 1984 to 2020, the evolution of the VCI and TCI was highlighted.
Show more [+] Less [-]Economic Impact of Climate Change on Agriculture: A Study of India and its Neighbouring Countries Using ARDL Approach
2023
Mashud Ahmed and Paramita Saha
This study aims to analyze the association between the share of agriculture in GDP and changes in climatic variables, notably per capita CO2 emissions and temperature change, using time series data of India, Bangladesh, and Nepal for the period 1961-2018. The ARDL bounds testing method was applied to analyze the relationships among the research variables for both short-term and long-term. The results revealed that in the long run, per capita CO2 emissions and temperature change have no statistically significant relationship with India and Nepal’s share of agriculture in GDP. However, temperature change has demonstrated a positive and statistically significant relationship with the share of agriculture in Bangladesh’s GDP. Temperature change has a significant and adverse impact on the share of agriculture in India’s GDP in the short run, whereas CO2 has no significant effect. In the short run, CO2 shows a positive and significant connection with the share of agriculture in Bangladesh’s GDP. Still, temperature change is negatively and significantly associated with the proportion of agriculture in the nation’s GDP. Different lag values of both CO2 and temperature change have significant relationships with the share of GDP in agriculture in the short run in Nepal. As agriculture is a key source of GDP for all three countries, it is vital to implement suitable policies and make plans and strategies to mitigate climate change’s harmful consequences in agriculture.
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