Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan
Iman Rousta,Iman Rousta,Haraldur Ólafsson,Moniruzzaman,Hao Zhang,Yuei An Liou,Terence Darlington Mushore,Amitesh Gupta +7 more
TLDR
The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, however, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed.Abstract:
Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed with R = 0.66 (p value = 0.05). Based on VCI for the same two years (2001 and 2008), 84% and 72% of the country were subject to drought conditions, respectively. Coherently, TRMM data confirm that 2001 and 2008 were the least rainfall years of 108 and 251 mm, respectively. On the other hand, years 2009 and 2010 were registered with the largest vegetation coverage of 16.3% mainly due to lower annual LST than average LST of 14 degrees and partially due to their slightly higher annual rainfalls of 378 and 425 mm, respectively, than the historical average of 327 mm. Based on the derived VCI, 28% and 21% of the study area experienced drought conditions in 2009 and 2010, respectively. It is also found that correlations are relatively high between NDVI and VCI (r = 0.77, p = 0.0002), but slightly lower between NDVI and precipitation (r = 0.51, p = 0.03). In addition, LST played a key role in influencing the value of NDVI. However, both LST and precipitation must be considered together in order to properly capture the correlation between drought and NDVI.read more
Citations
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Journal ArticleDOI
Comparison of Multi-Year Reanalysis, Models, and Satellite Remote Sensing Products for Agricultural Drought Monitoring over South Asian Countries
Muhammad Shahzaman,Weijun Zhu,Irfan Ullah,Farhan Mustafa,Muhammad Bilal,Shazia Ishfaq,Shazia Nisar,Muhammad Arshad,Rashid Iqbal,Rana Waqar Aslam +9 more
TL;DR: In this paper, the relationship between soil moisture, precipitation, terrestrial water storage (TWS), and vegetation condition index (VCI) was evaluated using the annual national production of barley, maize, rice, and wheat by computing the yield anomaly index (YAI).
Journal ArticleDOI
Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing
Moniruzzaman,Praveen K. Thakur,Pradeep Kumar,Ashraful Alam,Vaibhav Garg,Iman Rousta,Haraldur Ólafsson +6 more
TL;DR: In this paper, a study was conducted to quantify the changes in land use/land cover (LULC) and urban runoff extent based on the Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978-2018.
Journal ArticleDOI
Remote Sensing Indices for Spatial Monitoring of Agricultural Drought in South Asian Countries
Muhammad Shahzaman,Weijun Zhu,Muhammad Bilal,Birhanu Asmerom Habtemicheal,Farhan Mustafa,Muhammad Arshad,Irfan Ullah,Shazia Ishfaq,Rashid Iqbal +8 more
TL;DR: In this article, the authors explore the performance of the evaporative stress index (ESI), vegetation health index (VHI), enhanced vegetation index (EVI), and standardized anomaly index (SAI) based on satellite remote sensing data from 2002-2019 for agricultural drought assessment in Afghanistan, Pakistan, India, and Bangladesh.
Posted ContentDOI
GCI30: a global dataset of 30 m cropping intensity using multisource remote sensing imagery
Miao Zhang,Bingfang Wu,Hongwei Zeng,Guojin He,Chong Liu,Shiqi Tao,Qi Zhang,Mohsen Nabil,Mohsen Nabil,Fuyou Tian,José Bofana,José Bofana,Awetahegn Niguse Beyene,Abdelrazek Elnashar,Abdelrazek Elnashar,Nana Yan,Zhengdong Wang,Yiliang Liu +17 more
TL;DR: Zhang et al. as mentioned in this paper used multiple satellite data to develop a global, spatially continuous cropping intensity map dataset (GCI30), which exhibited high agreement with visually interpreted validation samples and in situ observations from the PhenoCam network.
Journal ArticleDOI
Comparison of Harmonic Analysis of Time Series (HANTS) and Multi-Singular Spectrum Analysis (M-SSA) in Reconstruction of Long-Gap Missing Data in NDVI Time Series
Hamid Reza Ghafarian Malamiri,Hadi Zare,Iman Rousta,Haraldur Ólafsson,Emma Izquierdo Verdiguier,Hao Zhang,Terence Darlington Mushore +6 more
TL;DR: The evaluation of the performance of gap filling capability of HANTS and M-SSA by filling artificially created gaps in data using Landsat and MODIS data presents a favorable option for solving the missing data challenge in NDVI time series.
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