We analyzed 27 established and new simple and therefore perhaps portable satellite phycocyanin pigment reflectance algorithms for estimating cyanobacterial values in a temperate 8.9 km² reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense coincident water surface observations collected from 44 sites within 1 h of image acquisition. The algorithms were adapted to real Compact Airborne Spectrographic Imager (CASI), synthetic WorldView-2, Sentinel-2, Landsat-8, MODIS and Sentinel-3/MERIS/OLCI imagery resulting in 184 variants and corresponding image products. Image products were compared to the cyanobacterial coincident surface observation measurements to identify groups of promising algorithms for operational algal bloom monitoring. Several of the algorithms were found useful for estimating phycocyanin values with each sensor type except MODIS in this small lake. In situ phycocyanin measurements correlated strongly (r² = 0.757) with cyanobacterial sum of total biovolume (CSTB) allowing us to estimate both phycocyanin values and CSTB for all of the satellites considered except MODIS in this situation.

In previous studies, empirical models have been widely used to map water quality parameters for inland waters using remotely sensed imagery. Due to the complex optical properties of inland waters, empirical models often have limited performances and they cannot be extended or reused across space and time. To overcome the limitations of traditional empirical models, this article further explores the ensemble method for water quality parameter retrieval. Based on the Sentinel-2 multispectral images and extensive coincident in situ water quality data, we examined different implementation strategies and evaluated the extensibility of a multipredictor ensemble model for retrieving chlorophyll-a (Chl-a) across space and time. Our analysis shows that the multipredictor ensemble model can improve the Chl-a prediction accuracy by 46% compared with the best traditional empirical model. Our experiments suggest that the selection of heterogeneous component models improves the performance of the ensemble model and the new iterative $K$ -fold calibration approach results in a considerably better ensemble model than the global calibration approach. To evaluate the spatial extensibility, our ensemble model calibrated for Harsha Lake was applied to Caesar Creek Lake and Brookville Lake. This ensemble model calibrated with the data sets acquired on October 7, 2016 was also applied to Sentinel-2 images of Harsha Lake acquired on October 2, 2017 and August 23, 2018, to evaluate its extensibility for different years. Our evaluation results show that the ensemble model can be transferred and reused across space and time to provide reliable and accurate Chl-a estimates.

This paper provides a summary of the current state of telecommunications for eight Arctic nations and a common vision for a Wireless Arctic Network to unite the Arctic Circumpolar Community. It presents detailed requirements based on the North

Ice formation and breakup on Arctic rivers strongly influence river flow, sedimentation, river ecology, winter travel, and subsistence fishing and hunting by Alaskan Natives. We use time-series ground imagery of the Meade River to examine the process at high temporal and spatial resolution. Freezeup from complete liquid cover to complete ice cover of the Meade River at Atqasuk, Alaska in the fall of 2008 occurred in less than three days between 28 September and 2 October 2008. Breakup in 2009 occurred in less than two hours between 23:47 UTC on 23 May 2009 and 01:27 UTC on 24 May 2009. All times in UTC. Breakup in 2009 and 2010 was of the thermal style in contrast to the mechanical style observed in 1966 and is consistent with a warming Arctic.