相关论文: Estimating the Impact of Weather on Agriculture
The availability of weather data from remotely sensed Earth observation (EO) data has reduced the cost of including weather variables in econometric models. Weather variables are common instrumental variables used to predict economic…
When publishing socioeconomic survey data, survey programs implement a variety of statistical methods designed to preserve privacy but which come at the cost of distorting the data. We explore the extent to which spatial anonymization…
In the agricultural sector, the COVID-19 threatens to lead to a severe food security crisis in the region, with disruptions in the food supply chain and agricultural production expected to contract between 2.6% and 7%. From the food crop…
High-resolution rainfall estimates from satellite and reanalysis sources (SRE) could play a major role in improving climate services for agriculture. This is particularly relevant in regions that rely on rain-fed farming but lack a dense…
Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation remote sensing data provides a unique source of information to monitor crops in a…
Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern high-resolution models, this is an oversight…
Rainfall is an important variable to be able to monitor and forecast across Africa, due to its impact on agriculture, food security, climate related diseases and public health. Numerical Weather Models (NWM) are an important component of…
Decisions in agriculture are frequently based on weather. With an increase in the availability and affordability of off-the-shelf weather stations, farmers able to acquire localised weather information. However, with uncertainty in the…
In many developing nations, a lack of poverty data prevents critical humanitarian organizations from responding to large-scale crises. Currently, socioeconomic surveys are the only method implemented on a large scale for organizations and…
The proper determination of soil moisture on different scales is important for applications in a variety of fields. We aim to develop a high-level soil moisture product with high temporal and spatial resolution by assimilating the…
The prediction of crop yields internationally is a crucial objective in agricultural research. Thus, this study implements 6 regression models (Linear, Tree, Gradient Descent, Gradient Boosting, K Nearest Neighbors, and Random Forest) to…
Scientists deploy environmental monitoring net-works to discover previously unobservable phenomena and quantify subtle spatial and temporal differences in the physical quantities they measure. Our experience, shared by others, has shown…
Weather data collected from automated weather stations have become a crucial component for making decisions in agriculture and in forestry. Over time, weather stations may become out-of-order or stopped for maintenance, and therefore,…
Across various research domains, remotely-sensed weather products are valuable for answering many scientific questions; however, their temporal and spatial resolutions are often too coarse to answer many questions. For instance, in wildlife…
The main objective of this study is to combine remote sensing and machine learning to detect soil moisture content. Growing population and food consumption has led to the need to improve agricultural yield and to reduce wastage of natural…
Crop yield forecasting plays a significant role in addressing growing concerns about food security and guiding decision-making for policymakers and farmers. When deep learning is employed, understanding the learning and decision-making…
Spatial microeconometric studies typically suffer from various forms of inaccuracies that are not present when dealing with the classical regional spatial econometrics models. Among those, missing data, locational errors, sampling without a…
Weather and soil conditions are particularly important when it comes to farming activities. Study of these factors and their role in nutrient and nitrate absorption rates can lead to useful insights with benefits for both the crop yield and…
Unpredictable weather patterns and a lack of timely, accurate information significantly challenge farmers in Uganda, leading to poor crop management, reduced yields, and heightened vulnerability to environmental stress. This research…
Improving the accuracy of soil moisture estimation is required for advancing irrigation scheduling and water conservation efforts. Central to this task are soil hydraulic parameters, which govern moisture dynamics but are rarely known…