scholarly journals Automatic Extraction of Open Water Using Imagery of Landsat Series

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1928
Author(s):  
Dandan Xu ◽  
Dong Zhang ◽  
Dan Shi ◽  
Zhaoqing Luan
Keyword(s):  
Surface Water ◽  
Algal Blooms ◽  
Water Surface ◽  
Near Infrared ◽  
Anthropogenic Activities ◽  
Eastern China ◽  
Water Extraction ◽  
Open Surface ◽  
Infrared Band ◽  
Shortwave Infrared

Open surface freshwater is an important resource for terrestrial ecosystems. However, climate change, seasonal precipitation cycling, and anthropogenic activities add high variability to its availability. Thus, timely and accurate mapping of open surface water is necessary. In this study, a methodology based on the concept of spatial autocorrelation was developed for automatic water extraction from Landsat series images using Taihu Lake in south-eastern China as an example. The results show that this method has great potential to extract continuous open surface water automatically, even when the water surface is covered by floating vegetation or algal blooms. The results also indicate that the second shortwave-infrared band (SWIR2) band performs best for water extraction when water is turbid or covered by surficial vegetation. Near-infrared band (NIR), first shortwave-infrared band (SWIR1), and SWIR2 have consistent extraction success when the water surface is not covered by vegetation. Low filter image processing greatly overestimated extracted water bodies, and cloud and image salt and pepper issues have a large impact on water extraction using the methods developed in this study.

scholarly journals Forest and land fire smoke detection using GCOM-C data (case study: Pulang Pisau, Central Kalimantan)

2021 ◽  
Vol 893 (1) ◽  
pp. 012068
Author(s):  
K I N Rahmi ◽  
N Febrianti ◽  
I Prasasti
Keyword(s):  
Near Infrared ◽  
Thermal Infrared ◽  
Short Wave ◽  
Forest Land ◽  
Visual Interpretation ◽  
Infrared Band ◽  
Central Kalimantan ◽  
Fire Smoke ◽  
Shortwave Infrared

Abstract Forest/land fire give bad impact of heavy smoke on peatland area in Indonesia. Forest/land fire smoke need to be identified the distribution periodically. New satellite of GCOM-C has been launched to monitor climate condition and have visible, near infrared and thermal infrared. This study has objective to identify fire smoke from GCOM-C data. GCOM-C data has wavelength range from 0.38 to 12 μm it covers visible, near infrared, short-wave infrared and thermal infrared. It is relatively similar to MODIS or Himawari-8 images which could identify forest/land fire smoke. The methodology is visual interpretation to detect forest/land fire smoke using near infrared band (VN08), shortwave infrared band (SW03), and thermal bands (T01 and T02). Hotspot data is overlaid with GCOM-C image to represent the location of fire events. Combination of composite RGB image has been applied to detect forest/land fire smoke. GCOM-C image of VN8 bands and combination of thermal band in composite image could be used to detect fire smoke in Pulang Pisau, Central Kalimantan.

scholarly journals Application of Image Segmentation in Surface Water Extraction of Freshwater Lakes using Radar Data

2020 ◽  
Vol 9 (7) ◽  
pp. 424 ◽  
Author(s):  
Sulong Zhou ◽  
Pengyu Kan ◽  
Janet Silbernagel ◽  
Jiefeng Jin
Keyword(s):  
Image Segmentation ◽  
Surface Water ◽  
Water Surface ◽  
Poyang Lake ◽  
Google Earth ◽  
Water Extraction ◽  
Freshwater Lakes ◽  
Essential Information ◽  
Advantages And Disadvantages ◽  
Otsu Method

Freshwater lakes supply a large amount of inland water resources to sustain local and regional developments. However, some lake systems depend upon great fluctuation in water surface area. Poyang lake, the largest freshwater lake in China, undergoes dramatic seasonal and interannual variations. Timely monitoring of Poyang lake surface provides essential information on variation of water occurrence for its ecosystem conservation. Application of histogram-based image segmentation in radar imagery has been widely used to detect water surface of lakes. Still, it is challenging to select the optimal threshold. Here, we analyze the advantages and disadvantages of a segmentation algorithm, the Otsu Method, from both mathematical and application perspectives. We implement the Otsu Method and provide reusable scripts to automatically select a threshold for surface water extraction using Sentinel-1 synthetic aperture radar (SAR) imagery on Google Earth Engine, a cloud-based platform that accelerates processing of Sentinel-1 data and auto-threshold computation. The optimal thresholds for each January from 2017 to 2020 are − 14.88 , − 16.93 , − 16.96 and − 16.87 respectively, and the overall accuracy achieves 92 % after rectification. Furthermore, our study contributes to the update of temporal and spatial variation of Poyang lake, confirming that its surface water area fluctuated annually and tended to shrink both in the center and boundary of the lake on each January from 2017 to 2020.

scholarly journals Biomass-burning-induced surface darkening and its impact on regional meteorology in eastern China

2020 ◽  
Vol 20 (10) ◽  
pp. 6177-6191 ◽  
Author(s):  
Rong Tang ◽  
Xin Huang ◽  
Derong Zhou ◽  
Aijun Ding
Keyword(s):  
Biomass Burning ◽  
Surface Albedo ◽  
Near Infrared ◽  
Regional Climate ◽  
Eastern China ◽  
Weather Forecast ◽  
Early Summer ◽  
Adjacent Area ◽  
Infrared Band ◽  
Sharp Drop

Abstract. Biomass burning has attracted great concerns for the emission of particular matters and trace gases, which substantially impacts air quality, human health, and climate change. Meanwhile, large areas of dark char, carbon residue produced in incomplete combustion, can stick to the surface over fire-prone areas after open burning, leading to a sharp drop in surface albedo, so-called “surface darkening”. However, exploration into such surface albedo declines and the radiative and meteorological effects is still fairly limited. As one of the highest-yield agricultural areas, eastern China features intensive straw burning every early summer, the harvest season for winter wheat, which was particularly strong in 2012. Satellite retrievals show that the surface albedo decline over fire-prone areas was significant, especially in the near-infrared band, which can reach −0.16. Observational evidence of abnormal surface warming was found by comparing radiosonde and reanalysis data. Most sites around intensive burned scars show a positive deviation, extending especially in the downwind area. Comparisons between “pre-fire” and “post-fire” from 2007 to 2015 indicated a larger temperature bias of the forecast during the post-fire stage. The signal becomes more apparent between 14:00 and 20:00 LT. Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulations suggest that including surface darkening can decrease model bias and well-captured temperature variation after burning at sites in fire areas and their adjacent area. This work highlights the importance of biomass burning induced albedo change in weather forecast and regional climate.

scholarly journals Study of Water-rock Interaction with Hydrochemical and Isotopic Datum in Laizhou Bay

2015 ◽  
Vol 9 (1) ◽  
pp. 90-97 ◽  
Author(s):  
Liu Feng ◽  
Ma Fengshan ◽  
Guo Jie ◽  
Ding Kuo
Keyword(s):  
Surface Water ◽  
Fresh Water ◽  
Water Surface ◽  
Saline Water ◽  
Eastern China ◽  
Laizhou Bay ◽  
Rock Interaction ◽  
Aquifer System ◽  
Isotopic Analyses ◽  
Water Rock Interaction

Water-rock interaction of the groundwater in aquifer system has been analyzed and inferred with hydrochemical and isotopic datum in Laizhou Bay, eastern China. 32 samples of groundwater from three boreholes (96-5#, 96-6#, 112- 1#), couples of seawater, saline water, fresh water, surface water and rainfall are obtained in study area for hydrochemical and isotopic analyses. The origin of groundwater is generally concluded by stable isotope (§18O and §D) and the analytic results of Na+, Ca2+, Mg2+, Cl-, SO2- , HCO3- changing with depth, combined with total dissolved solids (TDS), electrical conductivity (EC), can be apparently proofs for serious water-rock interaction. The conclusion reveals that the origin of 96-5#, 112-1# is most likely saline water different from that the groundwater of 96-6# which is possible originated from fresh water, surface water or mixing of both. Compared the ion content of same borehole at different depth and different boreholes with same depth, the optimal area for building main well and mining area is determined eventually is around 96-5#.

Two-Dimensional Near-Infrared and Shortwave Infrared Molecular Aggregates: Taking Kasha’s Model to the Next Dimension

2019 ◽  
Author(s):  
Arundhati Deshmukh ◽  
Danielle Koppel ◽  
Chern Chuang ◽  
Danielle Cadena ◽  
Jianshu Cao ◽  
...  
Keyword(s):  
Near Infrared ◽  
Photophysical Properties ◽  
Satellite Telemetry ◽  
Transition Dipole Moment ◽  
Short Wave ◽  
Tissue Imaging ◽  
Transition Dipole ◽  
Deep Tissue Imaging ◽  
Excitonic States ◽  
Shortwave Infrared

Technologies which utilize near-infrared (700 – 1000 nm) and short-wave infrared (1000 – 2000 nm) electromagnetic radiation have applications in deep-tissue imaging, telecommunications and satellite telemetry due to low scattering and decreased background signal in this spectral region. However, there are few molecular species, which absorb efficiently beyond 1000 nm. Transition dipole moment coupling (e.g. J-aggregation) allows for redshifted excitonic states and provides a pathway to highly absorptive electronic states in the infrared. We present aggregates of two cyanine dyes whose absorption peaks redshift dramatically upon aggregation in water from ~ 800 nm to 1000 nm and 1050 nm with sheet-like morphologies and high molar absorptivities (e ~ 10<sup>5 </sup>M<sup>-1</sup>cm<sup>-1</sup>). To describe this phenomenology, we extend Kasha’s model for J- and H-aggregation to describe the excitonic states of <i> 2-dimensional aggregates</i> whose slip is controlled by steric hindrance in the assembled structure. A consequence of the increased dimensionality is the phenomenon of an <i>intermediate </i>“I-aggregate”, one which redshifts yet displays spectral signatures of band-edge dark states akin to an H-aggregate. We distinguish between H-, I- and J-aggregates by showing the relative position of the bright (absorptive) state within the density of states using temperature dependent spectroscopy. Our results can be used to better design chromophores with predictable and tunable aggregation with new photophysical properties.

scholarly journals Transport and Fate of Nitrate at the Ground-Water/Surface-Water Interface

2008 ◽  
Vol 37 (3) ◽  
pp. 1034-1050 ◽  
Author(s):  
Larry J. Puckett ◽  
Celia Zamora ◽  
Hedeff Essaid ◽  
John T. Wilson ◽  
Henry M. Johnson ◽  
...  
Keyword(s):  
Surface Water ◽  
Ground Water ◽  
Water Surface ◽  
Water Interface

scholarly journals Identification of peat type and humification by laboratory VNIR/SWIR hyperspectral imaging of peat profiles with focus on fen-bog transition in aapa mires

2020 ◽  
Author(s):  
L. Granlund ◽  
M. Keinänen ◽  
T. Tahvanainen
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Support Vector ◽  
High Resolution Imaging ◽  
Factors Affecting ◽  
Vector Machines ◽  
Resolution Imaging ◽  
Shortwave Infrared ◽  
Type Classification ◽  
Wide Potential

Abstract Aims Hyperspectral imaging (HSI) has high potential for analysing peat cores, but methodologies are deficient. We aimed for robust peat type classification and humification estimation. We also explored other factors affecting peat spectral properties. Methods We used two laboratory setups: VNIR (visible to near-infrared) and SWIR (shortwave infrared) for high resolution imaging of intact peat profiles with fen-bog transitions. Peat types were classified with support vector machines, indices were developed for von Post estimation, and K-means clustering was used to analyse stratigraphic patterns in peat quality. With separate experiments, we studied spectral effects of drying and oxidation. Results Despite major effects, oxidation and water content did not impede robust HSI classification. The accuracy between Carex peat and Sphagnum peat in validation was 80% with VNIR and 81% with SWIR data. The spectral humification indices had accuracies of 82% with VNIR and 56%. Stratigraphic HSI patterns revealed that 36% of peat layer shifts were inclined by over 20 degrees. Spectral indices were used to extrapolate visualisations of element concentrations. Conclusions HSI provided reliable information of basic peat quality and was useful in visual mapping, that can guide sampling for other analyses. HSI can manage large amounts of samples to widen the scope of detailed analysis beyond single profiles and it has wide potential in peat research beyond the exploratory scope of this paper. We were able to confirm the capacity of HSI to reveal shifts of peat quality, connected to ecosystem-scale change.

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