[HTML][HTML] Fifty years of Landsat science and impacts

MA Wulder, DP Roy, VC Radeloff, TR Loveland… - Remote Sensing of …, 2022 - Elsevier
Since 1972, the Landsat program has been continually monitoring the Earth, to now provide
50 years of digital, multispectral, medium spatial resolution observations. Over this time …

High-throughput estimation of crop traits: A review of ground and aerial phenotyping platforms

X Jin, PJ Zarco-Tejada, U Schmidhalter… - … and Remote Sensing …, 2020 - ieeexplore.ieee.org
Crop yields need to be improved in a sustainable manner to meet the expected worldwide
increase in population over the coming decades as well as the effects of anticipated climate …

Massive soybean expansion in South America since 2000 and implications for conservation

XP Song, MC Hansen, P Potapov, B Adusei… - Nature …, 2021 - nature.com
A prominent goal of policies mitigating climate change and biodiversity loss is to achieve
zero deforestation in the global supply chain of key commodities, such as palm oil and …

[HTML][HTML] Global trends of forest loss due to fire from 2001 to 2019

A Tyukavina, P Potapov, MC Hansen… - Frontiers in Remote …, 2022 - frontiersin.org
Forest fires contribute to global greenhouse gas emissions and can negatively affect public
health, economic activity, and provision of ecosystem services (Aragão et al., 2018; Cascio …

Key issues in rigorous accuracy assessment of land cover products

SV Stehman, GM Foody - Remote Sensing of Environment, 2019 - Elsevier
Accuracy assessment and land cover mapping have been inexorably linked throughout the
first 50 years of publication of Remote Sensing of Environment. The earliest developers of …

A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

Y Cai, K Guan, J Peng, S Wang, C Seifert… - Remote sensing of …, 2018 - Elsevier
Accurate and timely spatial classification of crop types based on remote sensing data is
important for both scientific and practical purposes. Spatially explicit crop-type information …

DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping

J Xu, Y Zhu, R Zhong, Z Lin, J Xu, H Jiang… - Remote Sensing of …, 2020 - Elsevier
Accurate crop mapping provides important and timely information for decision support on the
estimation of crop production at large scale. Most existing crop-specific cover products …

[HTML][HTML] A comparison of global agricultural monitoring systems and current gaps

S Fritz, L See, JCL Bayas, F Waldner, D Jacques… - Agricultural systems, 2019 - Elsevier
Global and regional scale agricultural monitoring systems aim to provide up-to-date
information regarding food production to different actors and decision makers in support of …

Towards interpreting multi-temporal deep learning models in crop mapping

J Xu, J Yang, X Xiong, H Li, J Huang, KC Ting… - Remote Sensing of …, 2021 - Elsevier
Multi-temporal deep learning approaches have exhibited excellent classification
performance in large-scale crop mapping. These approaches efficiently and automatically …

Examining earliest identifiable timing of crops using all available Sentinel 1/2 imagery and Google Earth Engine

N You, J Dong - ISPRS Journal of Photogrammetry and Remote …, 2020 - Elsevier
Timely and accurate information on crop planting areas is critical for estimating crop
production, and earlier crop mapping can benefit decision-making related to crop insurance …