Zobrazeno 1 - 10
of 203
pro vyhledávání: '"Cuizhen Wang"'
Publikováno v:
Remote Sensing, Vol 16, Iss 11, p 1823 (2024)
Accompanying climate change and sea level rise, tidal marsh mortality in coastal wetlands has been globally observed that urges the documentation of high-resolution, 3D marsh inventory to assist resilience planning. Drone Lidar has proven useful in e
Externí odkaz:
https://doaj.org/article/f4e302a152904e6f89793811dce80bc6
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 118, Iss , Pp 103235- (2023)
Permafrost soils store more than one fourth of global soil organic carbon. This important carbon pool is threatened by carbon release from permafrost thawing. Especially in sub-Arctic transition zones, accurate mapping of permafrost is crucial for ti
Externí odkaz:
https://doaj.org/article/eacc3f487e3d4b259fac3bccc7e48d4c
Publikováno v:
Annals of GIS, Vol 0, Iss 0, Pp 1-15 (2022)
Coastal wetlands contribute greatly to our coasts economically and ecologically. The utility of coastal wetland vegetation, along with the multitude of dynamic forces they encounter, suggests the need of regular monitoring for sustainable management.
Externí odkaz:
https://doaj.org/article/6cb022c43346493aa7bcec8947a722d6
Publikováno v:
Drones, Vol 7, Iss 8, p 535 (2023)
This study investigates the use of small unoccupied aerial systems (sUAS) as a new remote sensing tool to identify and track the spatial distribution of wrack on coastal tidal marsh systems. We used sUAS to map the wrack movement in a Spartina altern
Externí odkaz:
https://doaj.org/article/441890d0d82c437584450f027a07064d
Publikováno v:
International Journal of Digital Earth, Vol 14, Iss 1, Pp 71-87 (2021)
The Belt and Road (B&R) region, a vital area with historical, economic, cultural and political significance, has undergone rapid urbanization in the past several decades, especially in the form of urban expansion. In this study, 20 megacities in the
Externí odkaz:
https://doaj.org/article/bc0047a6ac5f43c7911bea40beb6d39d
Publikováno v:
Big Earth Data, Vol 5, Iss 1, Pp 112-133 (2021)
In the Big Data era, Earth observation is becoming a complex process integrating physical and social sectors. This study presents an approach to generating a 100 m population grid in the Contiguous United States (CONUS) by disaggregating the US censu
Externí odkaz:
https://doaj.org/article/7d6399d3d47041fe907a3efc49035dc0
Publikováno v:
International Journal of Digital Earth, Vol 13, Iss 12, Pp 1467-1483 (2020)
This study reports an inventory of marsh dieback events from spatial and temporal perspectives in the North Inlet-Winyah Bay (NIWB) estuary, South Carolina (SC). Past studies in the Gulf/Atlantic coast states have reported acute marsh dieback events
Externí odkaz:
https://doaj.org/article/2aeaa39ea19e4ad483bfae41d3d150de
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 107, Iss , Pp 102704- (2022)
Collecting long-term satellite image series in high latitudes has been challenging due to its short growing season. For off-peak imagery, its reflective properties need to be corrected to maintain the spectral consistency. This study compares three s
Externí odkaz:
https://doaj.org/article/b9277bfebf444918a26941ecff42fcc7
Publikováno v:
International Journal of Digital Earth, Vol 13, Iss 9, Pp 1017-1039 (2020)
In recent years, social media platforms have played a critical role in mitigation for a wide range of disasters. The highly up-to-date social responses and vast spatial coverage from millions of citizen sensors enable a timely and comprehensive disas
Externí odkaz:
https://doaj.org/article/95a873f45d4043349c960a18a84115d6
Publikováno v:
International Journal of Digital Earth, Vol 12, Iss 11, Pp 1248-1264 (2019)
In recent years, social media such as Twitter have received much attention as a new data source for rapid flood awareness. The timely response and large coverage provided by citizen sensors significantly compensate the limitations of non-timely remot
Externí odkaz:
https://doaj.org/article/9a081688df0f4847950ccfe315b68cd4