High resolution wheat yield mapping using Sentinel-2

ML Hunt, GA Blackburn, L Carrasco… - Remote Sensing of …, 2019 - Elsevier
Accurate crop yield estimates are important for governments, farmers, scientists and
agribusiness. This paper provides a novel demonstration of the use of freely available …

Improvement in land cover and crop classification based on temporal features learning from Sentinel-2 data using recurrent-convolutional neural network (R-CNN)

V Mazzia, A Khaliq, M Chiaberge - Applied Sciences, 2019 - mdpi.com
Understanding the use of current land cover, along with monitoring change over time, is vital
for agronomists and agricultural agencies responsible for land management. The increasing …

Using negative soil adjustment factor in soil-adjusted vegetation index (SAVI) for aboveground living biomass estimation in arid grasslands

H Ren, G Zhou, F Zhang - Remote Sensing of Environment, 2018 - Elsevier
All values of soil adjustment factor (L) from 0 to 1 in the soil-adjusted vegetation index (SAVI)
were found to be undesirable in arid areas with sparse vegetation cover. We hypothesized …

Methodological evaluation of vegetation indexes in land use and land cover (LULC) classification

VS da Silva, G Salami, MIO da Silva… - Geology, Ecology …, 2020 - Taylor & Francis
Vegetation indices are intended to emphasize the vegetation spectral behavior in relation to
the soil and other terrestrial surface targets. The objective of this study was to evaluate the …

Impact of land use/land cover changes on groundwater resources in Al Ain region of the United Arab Emirates using remote sensing and GIS techniques

MU Liaqat, MM Mohamed, R Chowdhury… - Groundwater for …, 2021 - Elsevier
Urbanisation causes land degradation problems, including an increased pressure on
natural resources and management of water resources. This study aims to investigate the …

Improving the forecasting of winter wheat yields in Northern China with machine learning–dynamical hybrid subseasonal-to-seasonal ensemble prediction

J Cao, H Wang, J Li, Q Tian, D Niyogi - Remote Sensing, 2022 - mdpi.com
Subseasonal-to-seasonal (S2S) prediction of winter wheat yields is crucial for farmers and
decision-makers to reduce yield losses and ensure food security. Recently, numerous …

Autumn crop yield prediction using data-driven approaches:-support vector machines, random forest, and deep neural network methods

C Dang, Y Liu, H Yue, JX Qian… - Canadian journal of remote …, 2021 - Taylor & Francis
Accurate prediction of crop yield before harvest is critical to food security and importation.
The calculated ten explanatory factors and autumn crop yield data were used as data …

Land use/land cover change along the Eastern Coast of the UAE and its impact on flooding risk

K Hussein, K Alkaabi, D Ghebreyesus… - … , Natural Hazards and …, 2020 - Taylor & Francis
This study was conducted to investigate the spatiotemporal changes of land use/land cover
(LULC) along the eastern coast of the United Arab Emirates (UAE) over a 20-year period …

Wheat yield forecasting for the Tisza River catchment using landsat 8 NDVI and SAVI time series and reported crop statistics

A Nagy, A Szabó, OD Adeniyi, J Tamás - Agronomy, 2021 - mdpi.com
Due to the increasing global demand of food grain, early and reliable information on crop
production is important in decision making in agricultural production. Remote sensing (RS) …

Crop type mapping using LiDAR, Sentinel-2 and aerial imagery with machine learning algorithms

AJ Prins, A Van Niekerk - Geo-Spatial Information Science, 2021 - Taylor & Francis
LiDAR data are becoming increasingly available, which has opened up many new
applications. One such application is crop type mapping. Accurate crop type maps are …