scholarly journals Thermal environment effect of land surface water bodies in Beijing based on satellite data

2013 ◽  
Vol 25 (1) ◽  
pp. 73-81 ◽  
Author(s):  
LIU Yonghong ◽  
◽  
XUAN Chunyi ◽  
QUAN Weijun
2021 ◽  
pp. 77-88
Author(s):  
V. S. Vuglinskii ◽  
◽  
D. V. Vysotskii ◽  
T. I. Yakovleva ◽  
◽  
...  

The article gives a brief analysis of the development of the hydrological network in the Russian Federation in the last century and provides information on the phased modernization and technical re-equipment of the Hydrological Observation System at the beginning of the current century. At present, the national hydrological network, subordinated to Roshydromet, is the basis of the national monitoring system for surface water bodies in the Russian Federation. Within this system, a national technological complex named Hydrological Observation System, which ensures regular observations for the land surface water bodies, collection, processing and storage of information obtained as a result of observations and their provision to consumers.


2019 ◽  
Vol 11 (23) ◽  
pp. 6754 ◽  
Author(s):  
Najeebullah Khan ◽  
Shamsuddin Shahid ◽  
Eun-Sung Chung ◽  
Sungkon Kim ◽  
Rawshan Ali

Recent climate change has resulted in the reduction of several surface water bodies (SWBs) all around the globe. These SWBs, such as streams, rivers, lakes, wetlands, reservoirs, and creeks have a positive impact on the cooling of the surrounding climate and, therefore, reduction in SWBs can contribute to the rise of land surface temperature (LST). This study presents the impact of SWBs on the LST across Bangladesh to quantify their roles in the rapid temperature rise of Bangladesh. The moderate resolution imaging spectroradiometer (MODIS) LST and water mask data of Bangladesh for the period 2000–2015 are used for this purpose. Influences of topography and geography on LST were first removed, and then regression analysis was conducted to quantify the impact of SWBs on the LST. The non-parametric Mann–Kendall (MK) test was used to assess the changes in LST and SWBs. The results revealed that SWBs were reduced from 11,379 km2 in 2000 to 9657 km2 in 2015. The trend analysis showed that changes in SWBs have reduced significantly at a 90% level of confidence, which contributed to the acceleration of LST rise in the country due to global warming. The spatial analysis during the specific years showed that an increase in LST can be seen with the reduction of SWBs. Furthermore, the reduction of 100 m2 of SWBs can reduce the LST of the surrounding regions from −1.2 to −2.2 °C.


2014 ◽  
pp. 69-95 ◽  
Author(s):  
Naga M. Velpuri ◽  
Gabriel B. Senay ◽  
James Rowland ◽  
James P. Verdin ◽  
Henok Alemu

2021 ◽  
Author(s):  
Andreas Gericke ◽  
Judith Mahnkopf ◽  
Markus Venohr

2019 ◽  
Vol 11 (3) ◽  
pp. 327 ◽  
Author(s):  
Xia Wang ◽  
Feng Ling ◽  
Huaiying Yao ◽  
Yaolin Liu ◽  
Shuna Xu

Mapping land surface water bodies from satellite images is superior to conventional in situ measurements. With the mission of long-term and high-frequency water quality monitoring, the launch of the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B provides the best possible approach for near real-time land surface water body mapping. Sentinel-3 OLCI contains 21 bands ranging from visible to near-infrared, but the spatial resolution is limited to 300 m, which may include lots of mixed pixels around the boundaries. Sub-pixel mapping (SPM) provides a good solution for the mixed pixel problem in water body mapping. In this paper, an unsupervised sub-pixel water body mapping (USWBM) method was proposed particularly for the Sentinel-3 OLCI image, and it aims to produce a finer spatial resolution (e.g., 30 m) water body map from the multispectral image. Instead of using the fraction maps of water/non-water or multispectral images combined with endmembers of water/non-water classes as input, USWBM directly uses the spectral water index images of the Normalized Difference Water Index (NDWI) extracted from the Sentinel-3 OLCI image as input and produces a water body map at the target finer spatial resolution. Without the collection of endmembers, USWBM accomplished the unsupervised process by developing a multi-scale spatial dependence based on an unsupervised sub-pixel Fuzzy C-means (FCM) clustering algorithm. In both validations in the Tibet Plate lake and Poyang lake, USWBM produced more accurate water body maps than the other pixel and sub-pixel based water body mapping methods. The proposed USWBM, therefore, has great potential to support near real-time sub-pixel water body mapping with the Sentinel-3 OLCI image.


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