The Comparative Study on the Automatic Extraction Methods of Artificial Channel Based on ETM Image

2012 ◽  
Vol 500 ◽  
pp. 506-510
Author(s):  
Cheng Lu ◽  
Qiang Li ◽  
Li Jun Yu
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Large Scale ◽  
Water Shortage ◽  
Extraction Methods ◽  
Scientific Basis ◽  
Wetland Protection ◽  
Gis Technology ◽  
Band Method ◽  
Spatio Temporal

It’s urgent for China to solve the water shortage. Quickly and accurately extracting water resources from satellite remote sensing has become an important means of the investigation and monitoring of water resources and wetland protection. The fact that the spatio-temporal span of channel is large made the investigation difficult especially by the conventional way. Remote Sensing plays an increasing important role in the water resources protection with advantages of large scale, integration, dynamics and fastness. The RS images recorded the truth of the surface landscape in history and can reflect the distributing and the status quo of the channel in different courses of history. The article analyses the spectral and spatial feature of channel in ETM images in order to extraction the channel automatically with the different RS methods combined with GIS technology. A comparison among these methods is made. In addition, the article assesses the results of single-band method and multi-band method qualitatively and quantitatively. This study provide a scientific basis for the protection of water resource.

Transferring Simulation of Pollutants in YinLuan River Open Channel under Traffic Accidents

2013 ◽  
Vol 385-386 ◽  
pp. 429-432 ◽  
Author(s):  
Chun Xue Zhang ◽  
Li Lin Wang ◽  
Chao Wang ◽  
Shu Yi Yang ◽  
Xue Yi You
Keyword(s):  
Water Supply ◽  
Large Scale ◽  
Traffic Accidents ◽  
Open Channel ◽  
Water Shortage ◽  
Scientific Basis ◽  
Decision Makers ◽  
Water Diversion ◽  
Tianjin City ◽  
Efdc Model

The water diversion project from Luanhe River to Tianjin is a large-scale project, which solved the water shortage of Tianjin city. Because the long water supply open channel along highroads, the traffic emergent incidents bring great potential dangers to the water supply of Tianjin. In this paper, the prediction model of traffic emergent incidents in YinLuan River Open Channel was built and the transferring of pollutants under typical scenes was simulated by EFDC model. The evolution and affective area of pollutant in open channel was obtained. The results provide a scientific basis for the decision makers to take effective measures.

scholarly journals Remote Sensing Based Estimation of Evapo-Transpiration Using Selected Algorithms: The Case of Wonji Shoa Sugar Cane Estate, Ethiopia

2017 ◽  
Author(s):  
Mulugeta Genanu ◽  
Tena Alamirew ◽  
Gabriel Senay ◽  
Mekonnen Gebremichael
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Large Scale ◽  
Surface Energy Balance ◽  
Wet Season ◽  
Total Crop ◽  
Spatio Temporal ◽  
Water Surplus ◽  
Soil Moisture Variability

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map on a pixel-by-pixel basis, the actual evapotranspiration (ETa) of the Wonji Shoa Sugarcane Estate using the Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0 - 6.85, 0.0 – 9.36, 0.0 – 3.61, 0.0 – 6.83 mm/day; using SSEB 0.0 - 6.78, 0.0 – 7.81, 0.0 – 3.65, 0.0 – 6.46 mm/day, and SSEBop were 0.05 - 8.25, 0.0 – 8.82, 0.2 – 4.0, 0.0 – 7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ETa over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop had higher ETa values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season, ETa is limited to water surplus areas only and in wet season, ETa was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ETa over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ETa estimated for the whole estate were 107 Mm3, 140 Mm3, and 178 Mm3 using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate.

Comparison of Coastline Extraction Methods and Block Classification Method to Extract Coastlines based on Remote Sensing

2021 ◽  
Author(s):  
Zongmei Li ◽  
Hongmei Chen ◽  
Qin Nie
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Extraction Methods ◽  
Classification Method ◽  
Segmentation Method ◽  
Visual Interpretation ◽  
Threshold Segmentation ◽  
Detection Algorithms ◽  
Block Classification ◽  
Interpretation Method

Abstract Coastlines change with urbanization, and methods to extract coastlines have been previously reported. However, comparisons of these methods are rare. Based on remote sensing image, methods of coastline extraction, namely, the visual interpretation method, the threshold segmentation method, improved normalized water indexes and edge detection algorithms and were studied in Xiamen City, China. The best method to extract coastlines was then determined. The results show that the visual interpretation method for coastline extraction was inefficient. The threshold segmentation method was suitable for small-scale, but not large-scale, coastline extraction, based on coastline area. Improved normalized water indexes were insensitive to sediment shadows. The Sobel method (edge detection algorithms) was suitable for large-scale coastline extraction but could yield false edges. Finally, the block classification method, which combines the advantages of different extraction methods, specifically the threshold segmentation method and improved normalized water indexes, was studied. The results of this study show that coastline extraction by the block classification method is easier and produces better results than coastline extraction by other methods. Therefore, block classification is recommended for the study of coastlines and coastal ecology in large areas.

scholarly journals Radar vision in the mapping of forest biodiversity from space

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Soyeon Bae ◽  
Shaun R. Levick ◽  
Lea Heidrich ◽  
Paul Magdon ◽  
Benjamin F. Leutner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
External Validation ◽  
Predictive Ability ◽  
Radar Data ◽  
Forest Regions ◽  
Local Species ◽  
Spatio Temporal ◽  
Derived Data

Abstract Recent progress in remote sensing provides much-needed, large-scale spatio-temporal information on habitat structures important for biodiversity conservation. Here we examine the potential of a newly launched satellite-borne radar system (Sentinel-1) to map the biodiversity of twelve taxa across five temperate forest regions in central Europe. We show that the sensitivity of radar to habitat structure is similar to that of airborne laser scanning (ALS), the current gold standard in the measurement of forest structure. Our models of different facets of biodiversity reveal that radar performs as well as ALS; median R² over twelve taxa by ALS and radar are 0.51 and 0.57 respectively for the first non-metric multidimensional scaling axes representing assemblage composition. We further demonstrate the promising predictive ability of radar-derived data with external validation based on the species composition of birds and saproxylic beetles. Establishing new area-wide biodiversity monitoring by remote sensing will require the coupling of radar data to stratified and standardized collected local species data.

Remote sensing for assessment of groundwater resources, A case study of Stampriet Transboundary Aquifer

2021 ◽  
Author(s):  
Irene Kinoti ◽  
Marc Leblanc ◽  
Albert Olioso ◽  
Maciek Lubczynski ◽  
Angelique Poulain
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Groundwater Recharge ◽  
Real Time ◽  
Unsaturated Zone ◽  
Driving Forces ◽  
Groundwater Resources ◽  
Time Step ◽  
Groundwater Storage ◽  
Spatio Temporal

<p>Distributed integrated hydrological models (IHMs) are the most effective tools for estimating groundwater recharge in arid and semi-arid areas characterized by thick unsaturated zone. It is also important to capture spatio-temporal aquifer dynamics by using real-time or near-real-time data, for sustainable water resources management. However, such data is often unavailable in developing countries where monitoring networks are scarce. In recent years, remote sensing has played an important role in providing spatio-temporal information for evaluation and management of water resources. Nevertheless, application of remote sensing in groundwater studies is still limited and has mainly focused on assessment of groundwater recharge and groundwater storage as well as to provide boundary conditions and driving forces for both standalone groundwater models and IHMs. This study entails application of remote sensing data in developing the distributed integrated hydrological model for Stampriet transboundary multi-layered aquifer system shared between Namibia, Botswana and South Africa. A numerical model has been set – up using MODFLOW 6 coupled with the Unsaturated Zone Flow (UZF) Package where Climate Hazards Infrared Precipitation with stations (CHIRPS) rainfall data and Global Land Evaporation Amsterdam Model (GLEAM) potential evapotranspiration data were implemented as the model driving forces. Other input data used include digital elevation model, and land-use/landcover and also soil datasets to define unsaturated zone parameters. The model has been calibrated with groundwater level measurements as the state variables in transient conditions at daily time step for a period of 16 years. The model-simulated unsaturated zone and groundwater storage was compared to GRACE-derived sub-surface storage anomaly, further also used to constrain the model. The calibrated model provides spatio-temporal water flux dynamics as well as water balances and hence an understanding of the groundwater-resource dynamics and replenishment. This information is shown useful for proper management of the transboundary water resource as well as for policy making.</p>

scholarly journals A Cloud Detection Approach Based on Hybrid Multispectral Features with Dynamic Thresholds for GF-1 Remote Sensing Images

2020 ◽  
Vol 12 (3) ◽  
pp. 450 ◽  
Author(s):  
Quan Xiong ◽  
Yuan Wang ◽  
Diyou Liu ◽  
Sijing Ye ◽  
Zhenbo Du ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cloud Detection ◽  
Remote Sensing Images ◽  
Solar Altitude ◽  
Time Consumption ◽  
Detection Approach ◽  
Spatio Temporal

Nowadays, GF-1 (GF is the acronym for GaoFen which means high-resolution in Chinese) remote sensing images are widely utilized in agriculture because of their high spatio-temporal resolution and free availability. However, due to the transferrable rationale of optical satellites, the GF-1 remote sensing images are inevitably impacted by clouds, which leads to a lack of ground object’s information of crop areas and adds noises to research datasets. Therefore, it is crucial to efficiently detect the cloud pixel of GF-1 imagery of crop areas with powerful performance both in time consumption and accuracy when it comes to large-scale agricultural processing and application. To solve the above problems, this paper proposed a cloud detection approach based on hybrid multispectral features (HMF) with dynamic thresholds. This approach combined three spectral features, namely the Normalized Difference Vegetation Index (NDVI), WHITENESS and the Haze-Optimized Transformation (HOT), to detect the cloud pixels, which can take advantage of the hybrid Multispectral Features. Meanwhile, in order to meet the variety of the threshold values in different seasons, a dynamic threshold adjustment method was adopted, which builds a relationship between the features and a solar altitude angle to acquire a group of specific thresholds for an image. With the test of GF-1 remote sensing datasets and comparative trials with Random Forest (RF), the results show that the method proposed in this paper not only has high accuracy, but also has advantages in terms of time consumption. The average accuracy of cloud detection can reach 90.8% and time consumption for each GF-1 imagery can reach to 5 min, which has been reduced by 83.27% compared with RF method. Therefore, the approach presented in this work could serve as a reference for those who are interested in the cloud detection of remote sensing images.

scholarly journals Remote Sensing Based Estimation of Evapo-Transpiration Using Selected Algorithms: The Case of Wonji Shoa Sugar Cane Estate, Ethiopia

2016 ◽  
Author(s):  
Mulugeta Genanu ◽  
Tena Alamirew ◽  
Gabriel Senay ◽  
Mekonnen Gebremichael
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Large Scale ◽  
Surface Energy Balance ◽  
Meteorological Data ◽  
Wet Season ◽  
Spatially Distributed ◽  
Spatio Temporal ◽  
Water Surplus

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map pixel-by-pixel basis, and compare the actual evapotranspiration (ETa) of the Wonji Shoa Sugarcane Estate using Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms on Landsat7 ETM+ images acquired on four days in 2002. The algorithms were based on image processing which uses spatially distributed spectral satellite data and ground meteorological data to derive the surface energy balance components. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0–6.85, 0.0–9.36, 0.0–3.61, 0.0–6.83 mm/day; using SSEB 0.0–6.78, 0.0–7.81, 0.0–3.65, 0.0–6.46 mm/day, and SSEBop were 0.05–8.25, 0.0–8.82, 0.2–4.0, 0.0–7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ETa over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop and water storage areas had higher ETa values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season ETa is limited to water surplus areas only and in wet season, ETa was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ETa over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ETa estimated for the whole estate were 107 Mm3, 140 Mm3, and 178 Mm3 using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate.

scholarly journals Research on Optimal Allocation of Water Resources Based on Large-Scale System Decomposition and Coordination Model

2021 ◽  
Author(s):  
Zhuoran Luo ◽  
Jiahong Liu ◽  
Weiwei Shao ◽  
Yongxiang Zhang ◽  
Ruitao Jia
Keyword(s):  
Water Resources ◽  
Water Supply ◽  
Large Scale ◽  
Optimal Allocation ◽  
Water Shortage ◽  
Water Diversion ◽  
Allocation Model ◽  
System Decomposition ◽  
Optimal Allocation Model ◽  
Wei River

The construction of water resources optimal allocation model is the premise and foundation of solving and evaluating the optimal allocation model of water resources. The allocation of water resources includes not only the simple allocation of water resources, but also the protection of water resources and the analysis of the relationship between water supply and demand. Aiming at the problem of water shortage in the receiving area of water diversion from Hanjiang River to Weihe River, the large-scale system decomposition and coordination algorithm is used to optimally allocate the water use departments of each district of the water diversion area from Han to Wei River in Shaanxi Province, and establish the water diversion project from Han to Wei River. Optimal allocation model of water resources in the water receiving area. The results show that: in the 2030 planning level, the water supply of key cities, Xixian new district, medium/small cities, and industrial parks were 153.57, 368.16, 632.04, and 208.68 million m3, respectively, and the corresponding water shortage rate was 2.8%, 5.6%, 8.4%, 11.2%. The water supply sequence has a lower water shortage rate than the previous one, and the water shortage rate of the domestic water sector in key cities is only 1.2%. From the water shortage situation of various water departments in 2030, it can basically meet the water shortage of water receiving objects and effectively improve the water shortage in water receiving areas.

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