Chunyuan Diao
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View article: Evaluating multitemporal vegetation indices from Zhuhai-1 hyperspectral images for detecting a rapidly spreading invasive species - Spartina alterniflora
Evaluating multitemporal vegetation indices from Zhuhai-1 hyperspectral images for detecting a rapidly spreading invasive species - Spartina alterniflora Open
Monitoring the spatiotemporal changes of Spartina alterniflora (SA) is essential in effectively managing coastal ecology since it is one of the most harmful invasive weeds worldwide. However, it remains challenging to accurately identify S…
View article: Multistream STGAN: A Spatiotemporal Image Fusion Model With Improved Temporal Transferability
Multistream STGAN: A Spatiotemporal Image Fusion Model With Improved Temporal Transferability Open
Spatiotemporal satellite image fusion aims to generate remote sensing images satisfying both high spatial and temporal resolution by integrating different satellite imagery datasets with distinct spatial and temporal resolutions. Such fusi…
View article: CropSight: Towards a large-scale operational framework for object-based crop type ground truth retrieval using street view and PlanetScope satellite imagery
CropSight: Towards a large-scale operational framework for object-based crop type ground truth retrieval using street view and PlanetScope satellite imagery Open
Crop type maps are essential in informing agricultural policy decisions by providing crucial data on the specific crops cultivated in given regions. The generation of crop type maps usually involves the collection of ground truth data of v…
View article: EMET: An emergence-based thermal phenological framework for near real-time crop type mapping
EMET: An emergence-based thermal phenological framework for near real-time crop type mapping Open
Near real-time (NRT) crop type mapping plays a crucial role in modeling crop development, managing food supply chains, and supporting sustainable agriculture. The low-latency updates on crop type distribution also help assess the impacts o…
View article: A satellite-field phenological bridging framework for characterizing community-level spring forest phenology using multi-scale satellite imagery
A satellite-field phenological bridging framework for characterizing community-level spring forest phenology using multi-scale satellite imagery Open
Forest phenology, as a sensitive indicator of a forest's response to climate change and variability, has long been monitored using remote sensing, yet has seldom been interpreted or validated with spatially compatible, community-level fiel…
View article: Towards Scalable Within-Season Crop Mapping With Phenology Normalization and Deep Learning
Towards Scalable Within-Season Crop Mapping With Phenology Normalization and Deep Learning Open
Crop-type mapping using time-series remote sensing data is crucial for a wide range of agricultural applications. Crop mapping during the growing season is particularly critical in timely monitoring of the agricultural system. Most existin…
View article: Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology
Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology Open
Detecting crop phenology with satellite time series is important to characterize agroecosystem energy-water-carbon fluxes, manage farming practices, and predict crop yields. Despite the advances in satellite-based crop phenological retriev…
View article: Towards Routine Mapping of Crop Emergence within the Season Using the Harmonized Landsat and Sentinel-2 Dataset
Towards Routine Mapping of Crop Emergence within the Season Using the Harmonized Landsat and Sentinel-2 Dataset Open
Crop emergence is a critical stage for crop development modeling, crop condition monitoring, and biomass accumulation estimation. Green-up dates (or the start of the season) detected from remote sensing time series are related to, but gene…
View article: A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion
A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion Open
Dense time-series remote sensing data with detailed spatial information are highly desired for the monitoring of dynamic earth systems. Due to the sensor tradeoff, most remote sensing systems cannot provide images with both high spatial an…
View article: Development of spectral-phenological features for deep learning to understand Spartina alterniflora invasion
Development of spectral-phenological features for deep learning to understand Spartina alterniflora invasion Open
Invasive Spartina alterniflora (S. alterniflora), a native riparian species in the U.S. Gulf of Mexico, has led to serious degradation to the ecosystem and biodiversity as well as economic losses since it was introduced to China in 1979. A…
View article: A survey of methods incorporating spatial information in image classification and spectral unmixing
A survey of methods incorporating spatial information in image classification and spectral unmixing Open
Over the past decade, the incorporation of spatial information has drawn increasing attention in multispectral and hyperspectral data analysis. In particular, the property of spatial autocorrelation among pixels has shown great potential f…