Journal ArticleDOI
National-scale soybean mapping and area estimation in the United States using medium resolution satellite imagery and field survey
Xiao-Peng Song,Peter Potapov,Alexander Krylov,Lee Ann King,Carlos Marcelo Di Bella,Carlos Marcelo Di Bella,Carlos Marcelo Di Bella,A. Hudson,Ahmad Khan,Bernard Adusei,Stephen V. Stehman,Matthew C. Hansen +11 more
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TLDR
In this paper, a method for estimating in-season crop acreage using a probability sample of field visits and producing wall-to-wall crop type maps at national scales is presented.About:
This article is published in Remote Sensing of Environment.The article was published on 2017-03-01. It has received 166 citations till now. The article focuses on the topics: Satellite imagery.read more
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A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach
TL;DR: The research uses the USDA's Common Land Units to aggregate spectral information for each field based on a time-series Landsat image data stack to largely overcome the cloud contamination issue while exploiting a machine learning model based on Deep Neural Network and high-performance computing for intelligent and scalable computation of classification processes.
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Key issues in rigorous accuracy assessment of land cover products
TL;DR: The current status of accuracy assessment that has emerged from nearly 50 years of practice is described and improved methods are required to address new challenges created by advanced technology that has expanded the capacity to map land cover extensively in space and intensively in time.
Journal ArticleDOI
A comparison of global agricultural monitoring systems and current gaps
Steffen Fritz,Linda See,Juan Carlos Laso Bayas,François Waldner,François Waldner,Damien Christophe Jacques,Inbal Becker-Reshef,A. K. Whitcraft,Bettina Baruth,Rogerio Bonifacio,Jim Crutchfield,Felix Rembold,Oscar Rojas,Anne Schucknecht,Marijn van der Velde,James P. Verdin,Bingfang Wu,Nana Yan,Liangzhi You,Sven Gilliams,Sander Mücher,Robert Tetrault,Inian Moorthy,Ian McCallum +23 more
TL;DR: This paper provides an overview of the eight main global and regional scale agricultural monitoring systems currently in operation and compares them based on the input data and models used, the outputs produced and other characteristics such as the role of the analyst, their interaction with other systems and the geographical scale at which they operate.
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High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms
Xiuliang Jin,Pablo J. Zarco-Tejada,Urs Schmidhalter,Matthew P. Reynolds,Malcolm J. Hawkesford,Rajeev K. Varshney,Tao Yang,Chengwei Nie,Zhenhai Li,Bo Ming,Yonggui Xiao,Yongdun Xie,Shaokun Li +12 more
TL;DR: 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 change; in this regard, genomics-assisted breeding has become a popular approach to food security.
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Examining earliest identifiable timing of crops using all available Sentinel 1/2 imagery and Google Earth Engine
Nanshan You,Jinwei Dong +1 more
TL;DR: Wang et al. as discussed by the authors examined earliest identifiable timing (EIT) of major crops (rice, soybean, and corn) and generated early season crop maps independent of within-year field surveys in the Heilongjiang province, one most important province of grain production in China.
References
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Classification and regression trees
TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
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Red and photographic infrared linear combinations for monitoring vegetation
TL;DR: In this article, the relationship between various linear combinations of red and photographic infrared radiances and vegetation parameters is investigated, showing that red-IR combinations to be more significant than green-red combinations.
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High-Resolution Global Maps of 21st-Century Forest Cover Change
Matthew C. Hansen,Peter Potapov,Rebecca Moore,M. Hancher,Svetlana Turubanova,Alexandra Tyukavina,David Thau,Stephen V. Stehman,Scott J. Goetz,Thomas R. Loveland,Anil Kommareddy,A. Egorov,Louise Chini,Christopher O. Justice,John R. Townshend +14 more
TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
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Overview of the radiometric and biophysical performance of the MODIS vegetation indices
TL;DR: In this paper, the authors evaluated the performance and validity of the MODIS vegetation indices (VI), the normalized difference vegetation index (NDVI) and enhanced vegetation index(EVI), produced at 1-km and 500-m resolutions and 16-day compositing periods.