Statistical features for land use and land cover classification in Google Earth Engine

WR Becker, TB Ló, JA Johann, E Mercante - Remote Sensing Applications …, 2021 - Elsevier
The possibility of identifying and quantifying agricultural areas objectively and quickly is a
relevant aspect in the Brazilian agricultural context, given the territorial extent of the country …

[HTML][HTML] DeepForest: Novel deep learning models for land use and land cover classification using multi-temporal and-modal sentinel data of the amazon basin

E Cherif, M Hell, M Brandmeier - Remote Sensing, 2022 - mdpi.com
Land use and land cover (LULC) map** is a powerful tool for monitoring large areas. For
the Amazon rainforest, automated map** is of critical importance, as land cover is …

Global crop calendars of maize and wheat in the framework of the WorldCereal project

B Franch, J Cintas, I Becker-Reshef… - GIScience & Remote …, 2022 - Taylor & Francis
Crop calendars provide valuable information on the timing of important stages of crop
development such as the planting or Start of Season (SOS) and harvesting dates or End of …

[HTML][HTML] Estimating crop sowing and harvesting dates using satellite vegetation index: A comparative analysis

G Rodigheri, IDA Sanches, J Richetti, RY Tsukahara… - Remote sensing, 2023 - mdpi.com
In the last decades, several methodologies for estimating crop phenology based on remote
sensing data have been developed and used to create different algorithms. Although many …

Map** summer soybean and corn with remote sensing on Google Earth Engine cloud computing in Parana state–Brazil

A Paludo, WR Becker, J Richetti… - … Journal of Digital …, 2020 - Taylor & Francis
Brazilian farming influences directly the worldwide economy. Thus, fast and reliable
information on areas sown with the main crops is essential for planning logistics and public …

[HTML][HTML] A Method for Estimating Soybean Sowing, Beginning Seed, and Harvesting Dates in Brazil Using NDVI-MODIS Data

CTC Santana, IDA Sanches, MM Caldas, M Adami - Remote Sensing, 2024 - mdpi.com
Brazil, as a global player in soybean production, contributes about 35% to the world's supply
and over half of its agricultural exports. Therefore, reliable information about its development …

Harvest date forecast for soybeans from maximum vegetative development using satellite images

WR Becker, LCDA Silva, J Richetti, TB Ló… - International Journal of …, 2021 - Taylor & Francis
ABSTRACT The knowledge of Sowing Dates (SD), Maximum Vegetative Development
Dates (MVDD), and Harvest Dates (HD) of crops is important for estimating and forecasting …

Extraction of crop information through the spatiotemporal fusion of OLI and MODIS images

LV Oldoni, E Mercante, JFG Antunes… - Geocarto …, 2022 - Taylor & Francis
Spatiotemporal data fusion algorithms have been developed to fuse satellite imagery from
sensors with different spatial and temporal resolutions and generate predicted imagery. In …

Agroclimatic and spectral regionalization for soybean in different agricultural settings in the state of Paraná, Brazil

PP Gasparin, EM da Silva, WR Becker… - The Journal of …, 2024 - cambridge.org
Information related to the climate, sowing time, harvest, and crop development is essential
for defining appropriate strategies for agricultural activities, which helps both producers and …

Global wheat normalization. A robust approach based on Growing Degree Days accumulation

JM Cintas Rodríguez - 2024 - roderic.uv.es
Global agriculture is mainly driven by climate. Hence, under the different climate change
scenarios, it is facing several challenges such as a greater frequency of extreme events (eg …