Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia

P Feng, B Wang, D Li Liu, Q Yu - Agricultural Systems, 2019 - Elsevier
Agricultural drought is a natural hazard arising from insufficient crop water supply. Many
drought indices have been developed to characterize agricultural drought, relying on either …

Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions

S Park, J Im, E Jang, J Rhee - Agricultural and forest meteorology, 2016 - Elsevier
Drought triggered by a deficit of precipitation, is influenced by various environmental factors
such as temperature and evapotranspiration, and causes water shortage and crop failure …

Meteorological drought forecasting for ungauged areas based on machine learning: Using long-range climate forecast and remote sensing data

J Rhee, J Im - Agricultural and Forest Meteorology, 2017 - Elsevier
A high-resolution drought forecast model for ungauged areas was developed in this study.
The Standardized Precipitation Index (SPI) and Standardized Precipitation …

Drought monitoring using landsat derived indices and Google Earth engine platform: A case study from Al-Lith Watershed, Kingdom of Saudi Arabia

N Ejaz, J Bahrawi, KM Alghamdi, KU Rahman… - Remote Sensing, 2023 - mdpi.com
Precise assessment of drought and its impact on the natural ecosystem is an arduous task in
regions with limited climatic observations due to sparsely distributed in situ stations …

Machine-learned prediction of annual crop planting in the US Corn Belt based on historical crop planting maps

C Zhang, L Di, L Lin, L Guo - Computers and Electronics in Agriculture, 2019 - Elsevier
An accurate crop planting map can provide essential information for decision support in
agriculture. The method of post-season and in-season crop map** has been widely …

Analyzing the impact of thermal stress on vegetation health and agricultural drought–a case study from Gujarat, India

C Bhuiyan, AK Saha, N Bandyopadhyay… - GIScience & Remote …, 2017 - Taylor & Francis
Although poor precipitation due to delayed arrival and/or early retreat of the southwest
monsoon is considered the chief architect of drought in India, heat waves may also play a …

Develo** a satellite-based combined drought indicator to monitor agricultural drought: A case study for Ethiopia

YA Bayissa, T Tadesse, M Svoboda… - GIScience & Remote …, 2019 - Taylor & Francis
Develo** a robust drought monitoring tool is vital to mitigate the adverse impacts of
drought. A drought monitoring system that integrates multiple agrometeorological variables …

[HTML][HTML] Map** the spatial-temporal dynamics of vegetation response lag to drought in a semi-arid region

L Hua, H Wang, H Sui, B Wardlow, MJ Hayes, J Wang - Remote Sensing, 2019 - mdpi.com
Drought, as an extreme climate event, affects the ecological environment for vegetation and
agricultural production. Studies of the vegetative response to drought are paramount to …

[HTML][HTML] Utilizing the Google Earth Engine for Agricultural Drought Conditions and Hazard Assessment Using Drought Indices in the Najd Region, Sultanate of Oman

MS Al Nadabi, P D'Antonio, C Fiorentino, A Scopa… - Remote Sensing, 2024 - mdpi.com
Accurately evaluating drought and its effects on the natural environment is difficult in regions
with limited climate monitoring stations, particularly in the hyper-arid region of the Sultanate …

Crop classification and acreage estimation in North Korea using phenology features

H Zhang, Q Li, J Liu, J Shang, X Du… - GIScience & Remote …, 2017 - Taylor & Francis
In North Korea, reliable and timely information on crop acreage and spatial distribution is
hard to obtain. In this study, we developed a fast and robust method to estimate crop …