Detalhe da pesquisa
1.
Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs.
J Environ Manage
; 349: 119518, 2024 Jan 01.
Artigo
Inglês
| MEDLINE | ID: mdl-37944321
2.
Satellite and in situ cyanobacteria monitoring: Understanding the impact of monitoring frequency on management decisions.
J Hydrol (Amst)
; 619: 1-14, 2023 Apr 01.
Artigo
Inglês
| MEDLINE | ID: mdl-38273893
3.
Providing a framework for seagrass mapping in United States coastal ecosystems using high spatial resolution satellite imagery.
J Environ Manage
; 337: 117669, 2023 Jul 01.
Artigo
Inglês
| MEDLINE | ID: mdl-36966636
4.
Assessing the suitability of lakes and reservoirs for recreation using Landsat 8.
Environ Monit Assess
; 195(11): 1353, 2023 Oct 21.
Artigo
Inglês
| MEDLINE | ID: mdl-37864113
5.
Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales.
Ecol Indic
; 140: 1-14, 2022 Jul 01.
Artigo
Inglês
| MEDLINE | ID: mdl-36425672
6.
Merging of the Case 2 Regional Coast Colour and Maximum-Peak Height chlorophyll-a algorithms: validation and demonstration of satellite-derived retrievals across US lakes.
Environ Monit Assess
; 194(3): 179, 2022 Feb 14.
Artigo
Inglês
| MEDLINE | ID: mdl-35157155
7.
Acute health effects associated with satellite-determined cyanobacterial blooms in a drinking water source in Massachusetts.
Environ Health
; 20(1): 83, 2021 07 16.
Artigo
Inglês
| MEDLINE | ID: mdl-34271918
8.
Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a.
Remote Sens Environ
; 266: 1-14, 2021 Dec 01.
Artigo
Inglês
| MEDLINE | ID: mdl-36424983
9.
Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales.
Ecol Indic
; 128: 1-107822, 2021 Sep 01.
Artigo
Inglês
| MEDLINE | ID: mdl-35558093
10.
Performance across WorldView-2 and RapidEye for reproducible seagrass mapping.
Remote Sens Environ
; 250: 112036, 2020 Dec 01.
Artigo
Inglês
| MEDLINE | ID: mdl-34334824
11.
Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing.
Ecol Indic
; 111: 105976, 2020 Apr 01.
Artigo
Inglês
| MEDLINE | ID: mdl-34326705
12.
Exploring the potential value of satellite remote sensing to monitor chlorophyll-a for US lakes and reservoirs.
Environ Monit Assess
; 192(12): 808, 2020 Dec 02.
Artigo
Inglês
| MEDLINE | ID: mdl-33263783
13.
Performance metrics for the assessment of satellite data products: an ocean color case study.
Opt Express
; 26(6): 7404-7422, 2018 Mar 19.
Artigo
Inglês
| MEDLINE | ID: mdl-29609296
14.
Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems.
Ecol Appl
; 28(3): 749-760, 2018 04.
Artigo
Inglês
| MEDLINE | ID: mdl-29509310
15.
Spatio-Temporal Dynamics of Inherent Optical Properties in Oligotrophic Northern Gulf of Mexico Estuaries.
Cont Shelf Res
; 166: 92-107, 2018 Aug 15.
Artigo
Inglês
| MEDLINE | ID: mdl-36419821
16.
Mobile device application for monitoring cyanobacteria harmful algal blooms using Sentinel-3 satellite Ocean and Land Colour Instruments.
Environ Model Softw
; 109: 93-103, 2018.
Artigo
Inglês
| MEDLINE | ID: mdl-31595145
17.
Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking source waters.
Ecol Indic
; 80: 84-95, 2017 Sep.
Artigo
Inglês
| MEDLINE | ID: mdl-30245589
18.
Recent changes in cyanobacteria algal bloom magnitude in large lakes across the contiguous United States.
Sci Total Environ
; 897: 165253, 2023 Nov 01.
Artigo
Inglês
| MEDLINE | ID: mdl-37394074
19.
Identifying lakes at risk of toxic cyanobacterial blooms using satellite imagery and field surveys across the United States.
Sci Total Environ
; 869: 161784, 2023 Apr 15.
Artigo
Inglês
| MEDLINE | ID: mdl-36702268
20.
Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery.
Remote Sens (Basel)
; 15(19): 1-25, 2023 Sep 26.
Artigo
Inglês
| MEDLINE | ID: mdl-38362160