Yuanzheng Shao

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Data provenance, also called data lineage, records the derivation history of a data product. In the earth science domain, geospatial data provenance is important because it plays a significant role in data quality and usability evaluation, data trail audition, workflow replication, and product reproducibility. The generation of the geospatial provenance(More)
With the continuously increment of the available amount of spatial data sets, science, industry and administration require web-based geo-information concerning storage, availability and processing. The development of spatial data infrastructures (SDIs) bring about the Web-based sharing of large volumes of distributed geospatial data and computational(More)
This paper presents a fast and effective algorithm for detecting ridge- or ribbon-like linear features from remote sensing imagery. To judge if a pixel is at the center of a linear feature, the first step is to find several biggest pixels by their grey values within orthogonal directional windows, and store them into an evaluation window. A simple(More)
Petabytes of Earth science data have been accumulated through space- and air-borne Earth observation programs during the last several decades. The data are valuable both scientifically and socioeconomically. The value of these data could be further increased significantly if the data from these programs can be easily discovered, accessed, integrated, and(More)
Real-time estimation of crop progress stages is critical to the US agricultural economy and decision making. In this paper, a Hidden Markov Model (HMM) based method combining multisource features has been presented. The multisource features include mean Normalized Difference Vegetation Index (NDVI), fractal dimension, and Accumulated Growing Degree Days(More)
Understanding the event of flood and its impacts, especially towards agriculture, is an extremely significant component; however is exceedingly complicated process at the same time. That said research on identifying flood and its damages in the agricultural sector is not getting as much of attention as it should be. Flood damages on agricultural are(More)
The Global Earth Observation System of Systems (GEOSS) is a new international effort to provide an integrated system on top of the distributed, diverse legacy systems to create an open, public infrastructure for worldwide Earth observation research and applications. One key approach for enabling GEOSS is that legacy systems must support GEOSS-endorsed(More)
Geospatial Web Services (GWS) make geospatial information and computing resources discoverable and accessible over the Web. Among them, Open Geospatial Consortium (OGC) standards-compliant data, catalog and processing services are most popular, and have been widely adopted and leveraged in geospatial research and applications. The GWS metrics, such as visit(More)
Vegetation condition assessment is very useful and helpful for researchers and decision makers to evaluate crop loss and value, and identify and manage risks in the flood hazard areas. Crop responses to flooding vary with crop types, crop growing stages, soil characteristics, weather condition, flood duration and depth, etc. How to measure and understand(More)
Flooding introduces significant changes to crop condition profiles that can be derived from remote sensing. These changes correlate to crop damage caused by flood events. Crop condition profiles can be directly or indirectly constructed using different vegetation indices if specific crop are pre-determined. Crop condition profiles may be resulted from(More)