Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review
Accurate yield estimation and optimised nitrogen management is essential in agriculture.
Remote sensing (RS) systems are being more widely used in building decision support tools …
Remote sensing (RS) systems are being more widely used in building decision support tools …
Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …
promises significant advances to support the Sustainable Development Goals (SDGs). New …
Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2's red-edge bands to land-use and land-cover mapping in Burkina Faso
The availability of freely available moderate-to-high spatial resolution (10–30 m) satellite
imagery received a major boost with the recent launch of the Sentinel-2 sensor by the …
imagery received a major boost with the recent launch of the Sentinel-2 sensor by the …
[HTML][HTML] Crop mapping from image time series: Deep learning with multi-scale label hierarchies
The aim of this paper is to map agricultural crops by classifying satellite image time series.
Domain experts in agriculture work with crop type labels that are organised in a hierarchical …
Domain experts in agriculture work with crop type labels that are organised in a hierarchical …
Urban tree species classification using a WorldView-2/3 and LiDAR data fusion approach and deep learning
S Hartling, V Sagan, P Sidike, M Maimaitijiang… - Sensors, 2019 - mdpi.com
Urban areas feature complex and heterogeneous land covers which create challenging
issues for tree species classification. The increased availability of high spatial resolution …
issues for tree species classification. The increased availability of high spatial resolution …
Mapping crop types in southeast India with smartphone crowdsourcing and deep learning
High resolution satellite imagery and modern machine learning methods hold the potential
to fill existing data gaps in where crops are grown around the world at a sub-field level …
to fill existing data gaps in where crops are grown around the world at a sub-field level …
Predicting the chlorophyll content of maize over phenotyping as a proxy for crop health in smallholder farming systems
Smallholder farmers depend on healthy and productive crop yields to sustain their socio-
economic status and ensure livelihood security. Advances in South African precision …
economic status and ensure livelihood security. Advances in South African precision …
Evaluation of five deep learning models for crop type mapping using sentinel-2 time series images with missing information
H Zhao, S Duan, J Liu, L Sun, L Reymondin - Remote Sensing, 2021 - mdpi.com
Accurate crop type maps play an important role in food security due to their widespread
applicability. Optical time series data (TSD) have proven to be significant for crop type …
applicability. Optical time series data (TSD) have proven to be significant for crop type …
Fully convolutional recurrent networks for multidate crop recognition from multitemporal image sequences
Crop recognition in tropical regions is a challenging task because of the highly complex crop
dynamics, with multiple crops per year. Nevertheless, most automatic methods proposed …
dynamics, with multiple crops per year. Nevertheless, most automatic methods proposed …
[HTML][HTML] The feasibility of hand-held thermal and UAV-based multispectral imaging for canopy water status assessment and yield prediction of irrigated African …
This study was conducted to evaluate the feasibility of a mobile phone-based thermal and
UAV-based multispectral imaging to assess the irrigation performance of African eggplant …
UAV-based multispectral imaging to assess the irrigation performance of African eggplant …