Article
Geosciences, Multidisciplinary
Soheila Pouyan, Mojgan Bordbar, Venkatesh Ravichandran, John P. Tiefenbacher, Mehrzad Kherad, Hamid Reza Pourghasemi
Summary: This study utilized drought indicators to monitor drought in Iran spatially. Four drought indicators, including the temperature condition index (TCI), vegetation condition index (VCI), vegetation health index (VHI), and precipitation condition index (PCI) were analyzed based on data from 2016 to 2020. The results revealed severe drought in most of Iran in 2020 according to the TCI. The VCI showed that the northern region had the highest vegetation condition without drought. The VHI indicated increasing vegetation stress throughout the study period and severe and moderate droughts reached their peak in the aforementioned years. The PCI demonstrated a decrease in rainfall amounts across most of the country during the study period. The 30-year standardized precipitation index (SPI) showed that northern Iran had adequate rainfall, while most of the country experienced extreme and severe dryness. The analysis of the VHI index for agricultural plants identified critical drought conditions in 27.71% of Iran's agricultural regions, including the provinces of Razavi Khorasan, Hamadan, and Khozestan. This study provides valuable insights into drought monitoring indicators and enhances the understanding of drought in arid and semiarid regions.
Article
Environmental Sciences
Israel R. Orimoloye, Olusola O. Ololade, Johanes A. Belle
Summary: The study used Terra MOD13Q1 satellite data to assess drought events in the Free State Province, South Africa from 2001 to 2019. MODIS products and climate data were obtained from AppEEARS and NASA databases for analysis, with R programming used to process the data. The study identified water-stressed years, seasonal drought patterns, and compared drought events using the Vegetation Condition Index, highlighting the severity of summer droughts compared to winter droughts in the region. The results can be used for drought monitoring, decision-making, and disaster preparedness.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Environmental Sciences
Wilson Kalisa, Jiahua Zhang, Tertsea Igbawua, Alexis Kayiranga, Fanan Ujoh, Igbalumun Solomon Aondoakaa, Pacifique Tuyishime, Shuaishuai Li, Claudien Habimana Simbi, Deborah Nibagwire
Summary: This study assessed drought using four drought indices from 1982 to 2015, applying methods such as OLR and Hurst exponent, and analyzing trends and persistence at different time scales. Results revealed significant regional differences in drought trends, as well as the uncertainty of persistence, reversal, or extreme changes in drought conditions.
Article
Environmental Sciences
Israel R. Orimoloye, Johanes A. Belle, Olusola O. Ololade
Summary: This study assessed drought disaster using space-based data and R programming in the Free State Province, South Africa for the years 2003, 2007, 2012, and 2019. The results showed variable drought conditions across different months in these years.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Geosciences, Multidisciplinary
Omidreza Mikaili, Majid Rahimzadegan
Summary: This study evaluates the performance of satellite vegetation indices in monitoring agricultural drought. The results show that NDVI-based indices have the highest correlation with drought on a long-term timescale in cold climates, while VCI is the most effective index for studying agricultural drought in different climate regions.
Article
Environmental Sciences
Anjana N. J. Kukunuri, Deepak Murugan, Dharmendra Singh
Summary: Vegetation health condition can be accurately assessed and drought can be classified by combining satellite data on vegetation moisture and thermal stresses. The random weighing fusion method can effectively estimate agricultural drought without requiring prior information.
GEOCARTO INTERNATIONAL
(2022)
Review
Environmental Sciences
Mxolisi B. B. Mukhawana, Thokozani Kanyerere, David Kahler
Summary: The devastating impacts of recent droughts have highlighted the need for improved drought monitoring in South Africa (SA). This study reviewed the performance and applicability of various drought indices in SA and recommended a combination of the SPI, SPEI, VCI, SSI, and SGI for integrated drought monitoring. The PDSI and SWSI were found to be impractical in SA due to complexity and data limitations. Further research on GRACE-based groundwater drought indices is needed.
Article
Geosciences, Multidisciplinary
V. K. Prajapati, M. Khanna, M. Singh, R. Kaur, R. N. Sahoo, D. K. Singh
Summary: The present study characterized drought in the Marathwada region of Maharashtra using meteorological, hydrological and agricultural drought indices. The study found that the 3-month SPI and 5-month VCI were the most appropriate time scales to observe meteorological and agricultural droughts, respectively, while none of the SDI's time scales could capture hydrological drought.
Article
Water Resources
Muhammad Waseem, Tahira Khursheed, Adnan Abbas, Ijaz Ahmad, Zeeshan Javed
Summary: The study quantitatively analyzed the impact of meteorological drought on maize crop production in Punjab, Pakistan, highlighting the sensitivity of yields in the southern region and the significant effect of short-term drought during critical growth periods. Around 27% of yield variations were attributed to meteorological drought, with districts showing increasing sensitivity over time. Recommendations for adopting management strategies and mitigation measures were made based on the spatial and temporal patterns of drought effects on maize production.
JOURNAL OF WATER AND CLIMATE CHANGE
(2022)
Article
Remote Sensing
Tuyen V. Ha, Soner Uereyen, Claudia Kuenzer
Summary: This paper presents the first comprehensive analysis of agricultural and vegetative droughts in mainland Southeast Asia, using the Vegetation Condition Index (VCI) based on MODIS-based vegetation time-series data. The study reveals that central Myanmar experiences the most frequent droughts, while the Lower Mekong area suffers from both frequent and prolonged drought conditions. Recent severe droughts are predominantly observed in Cambodia, indicating a drying trend in this region. The findings provide valuable information for drought early warning management and agricultural planning.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Engineering, Civil
Ayseguel Kuzucu, Guelay Onusluel Gul
Summary: Drought is a regional phenomenon caused by unbalanced climate dynamics on a global scale, and it requires continuous analysis in both time and space. Drought indices are fundamental for analyzing drought, but their effectiveness is limited by the availability of input data. Traditional methods of analyzing drought indices rely on measurements from hydro-meteorological stations, but they fail to capture the spatiotemporal continuity required for accurate assessments. This study compares different approaches to drought analysis and provides mapped results for comparing estimated future drought characteristics with those of the reference period.
WATER RESOURCES MANAGEMENT
(2023)
Article
Environmental Sciences
Muhammad Waseem, Ali Hasan Jaffry, Muhammad Azam, Ijaz Ahmad, Adnan Abbas, Jae-Eun Lee
Summary: This study investigates the impacts of drought on wheat production in the Punjab province of Pakistan, which is the agricultural hub of the country. The results show that drought episodes during the wheat cropping season are recurrent, and drought significantly affects wheat yields, especially in zones 1 and 2. This study provides valuable evidence for authorities in disaster management and agricultural policy-making.
Article
Geography, Physical
Eunbeen Park, Hyun-Woo Jo, Woo-Kyun Lee, Sujong Lee, Cholho Song, Halim Lee, Sugyeong Park, Whijin Kim, Tae-Hyung Kim
Summary: This study developed a diagnostic drought prediction model (DDPM) integrating meteorological and satellite data for advanced drought assessment in Kyrgyzstan, showing higher accuracy in explaining regional drought severity compared to the PDPM model. The integration of earth observation big data is expected to support policymakers and technical officials in establishing effective disaster risk reduction policies and action plans.
GISCIENCE & REMOTE SENSING
(2022)
Article
Engineering, Environmental
Chaima Elair, Khalid Rkha Chaham, Abdessamad Hadri
Summary: Climate change has increased the frequency of drought in the semi-arid Marrakech-Safi region of Morocco. This study analyzed precipitation data and remote sensing indices to reveal the alternating dry and wet periods of drought in the region, with an overall upward trend. The findings emphasize the importance of considering multiple time scales in assessing the impact of climate on vegetation.
Article
Agronomy
Fernando Salas-Martinez, Ofelia Andrea Valdes-Rodriguez, Olivia Margarita Palacios-Wassenaar, Aldo Marquez-Grajales
Summary: The study found that drought in the Veracruz region of Mexico has intensified over the past few decades, affecting nearly 50% of the area and leading to reductions in corn production and impact on livestock. This phenomenon is primarily due to the increase in maximum temperatures and the higher occurrence of El Nino/La Nina events in recent years.
Article
Water Resources
Sally Rangecroft, Anne F. Van Loon, Hector Maureira, Koen Verbist, David M. Hannah
HYDROLOGICAL SCIENCES JOURNAL
(2019)
Article
Computer Science, Theory & Methods
Ayan Seal, Angel Garcia-Pedrero, Debotosh Bhattacharjee, Mita Nasipuri, Mario Lillo-Saavedra, Ernestina Menasalvas, Consuleo Gonzalo-Martin
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING
(2020)
Article
Computer Science, Artificial Intelligence
Angel Garcia-Pedrero, Ana I. Garcia-Cervigon, Jose M. Olano, Miguel Garcia-Hidalgo, Mario Lillo-Saavedra, Consuelo Gonzalo-Martin, Cristina Caetano, Saul Calderon-Ramirez
NEURAL COMPUTING & APPLICATIONS
(2020)
Article
Environmental Sciences
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Hylke E. Beck, Ian McNamara, Lars Ribbe, Alexandra Nauditt, Christian Birkel, Koen Verbist, Juan Diego Giraldo-Osorio, Nguyen Xuan Thinh
REMOTE SENSING OF ENVIRONMENT
(2020)
Article
Agriculture, Multidisciplinary
Eduardo Holzapfel, Mario Lillo-Saavedra, Diego Rivera, Viviana Gavilan, Angel Garcia-Pedrero, Consuelo Gonzalo-Martin
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2020)
Article
Environmental Sciences
Andres Perez, Octavio Lagos, Mario Lillo-Saavedra, Camilo Souto, Jeronimo Paredes, Jose Luis Arumi
Article
Multidisciplinary Sciences
Hylke E. Beck, Seth Westra, Jackson Tan, Florian Pappenberger, George J. Huffman, Tim R. McVicar, Gaby J. Grundemann, Noemi Vergopolan, Hayley J. Fowler, Elizabeth Lewis, Koen Verbist, Eric F. Wood
Article
Engineering, Geological
Bastian Morales, Elizabet Lizama, Marcelo A. Somos-Valenzuela, Mario Lillo-Saavedra, Ningsheng Chen, Ivo Fustos
Summary: The study aims to detect and predict landslides in Northern Patagonia of Chile, utilizing machine learning methods to identify key environmental variables such as climate indices, indicators of extreme events, and geological triggers. The study area is influenced by both terrain evolution and climatic conditions, highlighting the importance of understanding the interaction between geological and climatic processes and assessing the future impact of natural hazards.
Article
Agriculture, Multidisciplinary
Consuelo Gonzalo-Martin, Angel Garcia-Pedrero, Mario Lillo-Saavedra
Summary: This study investigates a methodology to detect sorghum heads in unmanned aerial vehicle imagery and evaluates its performance using mean average precision. The results demonstrate that in sorghum head detection, test-time augmentation (TTA) strategies outperform detection based only on individual transformed testing sets. By applying different weights during the ensemble of TTA results, these findings are further improved.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Environmental Sciences
Mario Lillo-Saavedra, Viviana Gavilan, Angel Garcia-Pedrero, Consuelo Gonzalo-Martin, Felipe de la Hoz, Marcelo Somos-Valenzuela, Diego Rivera
Summary: This study introduces a new methodology to characterize the water demand of crops by integrating data from multiple sources, including satellite observations, field campaigns, and public databases. The results show that spatial-temporal information on water availability and demand pairing can help close the water gap and enable better management of water resources.
Article
Biology
Cesar Ortiz-Toro, Angel Garcia-Pedrero, Mario Lillo-Saavedra, Consuelo Gonzalo-Martin
Summary: This study evaluates the potential of three image characterisation methods (radiomics, fractal dimension, and superpixel-based histon) for detecting pneumonia in chest X-ray images and generates models using three different AI algorithms. The tested methods demonstrate high accuracy and sensitivity in two datasets, confirming their validity as reliable and easy-to-implement automatic diagnostic tools for pneumonia.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Environmental Sciences
Bastian Morales, Angel Garcia-Pedrero, Elizabet Lizama, Mario Lillo-Saavedra, Consuelo Gonzalo-Martin, Ningsheng Chen, Marcelo Somos-Valenzuela
Summary: Landslide inventories are essential for studying the dynamics, risks, and effects of these processes on mountain landscapes. The use of artificial intelligence models based on deep learning techniques can automate landslide detection, but there is a lack of research in the Andes region. This study aims to narrow this gap by creating a large dataset for the Patagonian Andes and applying a deep learning model, achieving promising results with high accuracy and segmentation capabilities, despite some errors.
Article
Agronomy
Mario Lillo-Saavedra, Alberto Espinoza-Salgado, Angel Garcia-Pedrero, Camilo Souto, Eduardo Holzapfel, Consuelo Gonzalo-Martin, Marcelo Somos-Valenzuela, Diego Rivera
Summary: Crop yield forecasting is crucial for farmers' decision-making and planning. However, current methods have limitations, such as limited data collection time. This study presents a methodology using unmanned aerial vehicles and multispectral sensors to predict tomato yield at different stages of crop development, achieving a 9.28% error rate.
Article
Computer Science, Information Systems
Alberto Jopia, Francisco Zambrano, Waldo Perez-Martinez, Paulina Vidal-Paez, Julio Molina, Felipe de la Hoz Mardones
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2020)
Article
Environmental Sciences
K. M. J. Verbist, H. Maureira-Cortes, P. Rojas, S. Vicuna
CLIMATE RISK MANAGEMENT
(2020)