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Zhengwei Yang

Researcher at United States Department of Agriculture

Publications -  85
Citations -  2726

Zhengwei Yang is an academic researcher from United States Department of Agriculture. The author has contributed to research in topics: Geospatial analysis & Web service. The author has an hindex of 17, co-authored 77 publications receiving 2143 citations. Previous affiliations of Zhengwei Yang include KLA-Tencor & Nanjing Agricultural University.

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Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program

TL;DR: The National Agricultural Statistics Service (NASS) of the US Department of Agriculture (USDA) produces the Cropland Data Layer (CDL) product, which is a raster-formatted, geo-referenced, crop-specific, land cover map as mentioned in this paper.
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Toward mapping crop progress at field scales through fusion of Landsat and MODIS imagery

TL;DR: In this article, the authors evaluated remote sensing approaches for mapping crop phenology using vegetation index time-series generated by fusing Landsat and MODIS surface reflectance imagery to improve temporal sampling over that provided by Landsat alone.
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CropScape: A Web service based application for exploring and disseminating US conterminous geospatial cropland data products for decision support

TL;DR: CropScape as mentioned in this paper is an interactive Web CDL exploring system that allows users to query, visualize, disseminate, and analyze CDL data geospatially through standard geospatial Web services in a publicly accessible online environment.
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Invariant matching and identification of curves using B-splines curve representation

TL;DR: This paper deals with the problem of using B-splines for shape recognition and identification from curves, with an emphasis on the following applications: affine invariant matching and classification of 2-D curves with applications in identification of aircraft types based on image silhouettes and writer-identification based on handwritten text.
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Image registration and object recognition using affine invariants and convex hulls

TL;DR: A set of local absolute affine invariants derived from the convex hull of scattered feature points extracted from the image are presented, which are very well suited to handle the occlusion and/or appearance of new objects.