scholarly journals Spatial Differentiation Analysis of Water Quality in Dianchi Lake Based on GF-5 NDVI Characteristic Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hu Lin ◽  
Gan Shu ◽  
Yuan Xiping ◽  
Li Yan ◽  
Chen Guokun ◽  
...  
Keyword(s):  
Water Quality ◽  
Aquatic Plants ◽  
Near Infrared ◽  
Aquatic Vegetation ◽  
Spectral Response ◽  
Dianchi Lake ◽  
Clear Understanding ◽  
Infrared Band ◽  
Protection Measures ◽  
The Government

Remote sensing monitoring of aquatic vegetation is critical to the water quality evaluation of plateau lakes. To obtain a clear understanding of the water environment status of Dianchi Lake, a GF-5 hyperspectral characteristics-based optimal NDVI approach was employed to quantify the aquatic vegetation cover and analyze water quality. By characteristic bands recognition, the optimal NDVI was obtained; the spatial distribution of aquatic plants and water quality in Dianchi Lake were then analyzed. Results showed the following: (1) For Caohai, the optimal NDVI value was calculated by B86 in the red band range and B151 in the near-infrared band range, which achieve the best spectral response. For Waihai, the respective bands were B86 in the red band range and B99 in the near-infrared band range. (2) We also found significant regional differences in aquatic plants distribution for the study area. Caohai was dominated by aquatic plants and high-quality water areas only occurred in the northern tip. While the situation for Waihai was much optimistic, areas with poor water quality were mainly found in the north and south parts. Water quality also showed a descending trend from the lakeside zone to the lake center. (3) By comparing to previous studies, we concluded that policy interventions and water protection measures carried out by the government during the past years are extremely effective. The optimal NDVI method provides a reliable evaluation and is potentially transferable to other plateau lake areas as a robust approach for the rapid assessment of water quality.

scholarly journals Cartographie De La Salinite A La Surface Du Sol Dans Une Zone Du Prerif. Cas De La Region De L’ouergha

2016 ◽  
Vol 12 (3) ◽  
pp. 197
Author(s):  
Mohamed Sadiki ◽  
Amal Markhi ◽  
Hicham Elbelrhiti ◽  
Souad Mrabet
Keyword(s):  
Soil Salinity ◽  
Near Infrared ◽  
Salt Water ◽  
Spectral Response ◽  
Surface Condition ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Soil Salinization ◽  
Landsat Tm ◽  
Infrared Band

The soil and groundwater salinization phenomenon in semi-arid to arid climate is considered as a real threat to safety and food quality. There are several factors that present soil salinity, some factors are purely climatic (temperature, rainfall levels, lack of drainage, composition of the rock) or human-induced (using salt water to irrigation). The aim of the work is to take stock of the surface condition at a specified scale of soil salinity by taking satellite images Landsat TM 2009 and ASTER 2003 with 15 m and 30 m of resolution respectively. This study allows us to detect the potential of remote sensing data to see a set of thematic maps that distinguish, evaluate and locate their extended saline soils on the surface of the study area. The methods of satellite image processing are for understanding of soil salinization process, assess their extensive and locate areas vulnerable to soil and water salinization. Evaluation of the results of applying this method on Landsat TM gave an accuracy of 87%. This study also allows us to highlight spectral indices that again demonstrate the natural origin, related to the lithology of groundwater salinity in the study area. These various indices largely exploit the difference spectral response of vegetation and soils in the red band (R) and near infrared band (PIR) which is related to the density of green vegetation the NDSI and NDVI which allows a very good distinction between areas of salinity and vegetation area.

scholarly journals SEGMENTATION OF SINGLE STANDING DEAD TREES IN HIGH-RESOLUTION AERIAL IMAGERY WITH GENERATIVE ADVERSARIAL NETWORK-BASED SHAPE PRIORS

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 717-723
Author(s):  
P. Polewski ◽  
J. Shelton ◽  
W. Yao ◽  
M. Heurich
Keyword(s):  
Near Infrared ◽  
Spectral Response ◽  
Mathematical Formulation ◽  
Dimensional Manifold ◽  
Shape Priors ◽  
Tree Crown ◽  
Infrared Band ◽  
Generative Adversarial Network ◽  
Convolutional Network ◽  
Adversarial Network

Abstract. The use of multispectral imagery for monitoring biodiversity in ecosystems is becoming widespread. A key parameter of forest ecosystems is the distribution of dead wood. This work addresses the segmentation of individual dead tree crowns in nadir-view aerial infrared imagery. While dead vegetation produces a distinct spectral response in the near infrared band, separating adjacent trees within large swaths of dead stands remains a challenge. We tackle this problem by casting the segmentation task within the active contour framework, a mathematical formulation combining learned models of the object’s shape and appearance as prior information. We explore the use of a deep convolutional generative adversarial network (DCGAN) in the role of the shape model, replacing the original linear mixture-of-eigenshapes formulation. Also, we rely on probabilities obtained from a deep fully convolutional network (FCN) as the appearance prior. Experiments conducted on manually labeled reference polygons show that the DCGAN is able to learn a low-dimensional manifold of tree crown shapes, outperforming the eigenshape model with respect to the similarity of the reproduced and referenced shapes on about 45 % of the test samples. The DCGAN is successful mostly for less convex shapes, whereas the baseline remains superior for more regular tree crown polygons.

scholarly journals An Object-Based Image Analysis Workflow for Monitoring Shallow-Water Aquatic Vegetation in Multispectral Drone Imagery

2018 ◽  
Vol 7 (8) ◽  
pp. 294 ◽  
Author(s):  
Dominique Chabot ◽  
Christopher Dillon ◽  
Adam Shemrock ◽  
Nicholas Weissflog ◽  
Eric Sager
Keyword(s):  
Image Analysis ◽  
Near Infrared ◽  
Aquatic Vegetation ◽  
Supervised Machine Learning ◽  
Automated Classification ◽  
Infrared Band ◽  
Vegetation Monitoring ◽  
Object Based Image Analysis ◽  
Initial Separation ◽  
Object Based

High-resolution drone aerial surveys combined with object-based image analysis are transforming our capacity to monitor and manage aquatic vegetation in an era of invasive species. To better exploit the potential of these technologies, there is a need to develop more efficient and accessible analysis workflows and focus more efforts on the distinct challenge of mapping submerged vegetation. We present a straightforward workflow developed to monitor emergent and submerged invasive water soldier (Stratiotes aloides) in shallow waters of the Trent-Severn Waterway in Ontario, Canada. The main elements of the workflow are: (1) collection of radiometrically calibrated multispectral imagery including a near-infrared band; (2) multistage segmentation of the imagery involving an initial separation of above-water from submerged features; and (3) automated classification of features with a supervised machine-learning classifier. The approach yielded excellent classification accuracy for emergent features (overall accuracy = 92%; kappa = 88%; water soldier producer’s accuracy = 92%; user’s accuracy = 91%) and good accuracy for submerged features (overall accuracy = 84%; kappa = 75%; water soldier producer’s accuracy = 71%; user’s accuracy = 84%). The workflow employs off-the-shelf graphical software tools requiring no programming or coding, and could therefore be used by anyone with basic GIS and image analysis skills for a potentially wide variety of aquatic vegetation monitoring operations.

Water quality status of rivers in the coastal city of Manado, North Sulawesi Province, Indonesia

2014 ◽  
pp. 8
Author(s):  
Markus T Lasut ◽  
Adianse Tarigan
Keyword(s):  
Escherichia Coli ◽  
Water Quality ◽  
Government Regulation ◽  
Organic N ◽  
Coastal City ◽  
North Sulawesi ◽  
The Status ◽  
Water Quality Status ◽  
The Government ◽  
Quality Status

A study on water quality status of three riverine systems, S. Bailang (SB), S. Maasing (SM), and S. Tondano (ST), in coastal city of Manado, North Sulawesi Province, has been conducted to measure several water quality parameters, to analyse source and quality of wastewater discharge, and to assess the status of the rivers related to the water quality. Measurement of the parameters was conducted using three indicators, i.e. organic (BOD5) and in-organic (N-NO3 and P-PO4), and pathogenic microorganism (Escherichia coli [EC] and total coliform [TC]). The result showed that the level of water quality varied between the rivers. The average level of water quality (based on the observed parameters) in SB, respectively, was 0.317 mg/l, 0.093 mg/l, 2 mg/l, >2420 MPN, and  >2420 MPN; in SM, respectively, was 0.029 mg/l, 1.859 mg/l, 17.7 mg/l, >2420 MPN, and >2420 MPN; and in ST, respectively, was 0.299 mg/l, 0.252 mg/l, 3.5 mg/l, >2420 MPN, and >2420 MPN. The level of water quality between the rivers was not significantly different (p>0.05), except based on the parameter of N-NO3 which was significantly different (p<0.01). The status of the observed rivers varied based on the classes of their water utilities (according to the Government Regulation of Indonesia, No. 82, 2001); mostly was "unsuitable". Kajian tentang status kualitas air di 3 perairan sungai di kota pesisir Manado, S. Bailang (SB), S. Maasing (SM), dan S. Tondano (ST), Provinsi Sulawesi Utara, telah dilakukan yang bertujuan untuk mengukur beberapa parameter kualitas air, menganalisis sumber dan kualitas buangan limbah domestik, dan menilai status ketiga perairan sungai tersebut. Tiga indikator digunakan, yaitu: bahan organik (BOD5), bahan anorganik (N-NO3 dan P-PO4), dan mikroorganisme patogenik (Escherichia coli [EC] dan coliform total [TC]). Hasil kajian menunjukkan bahwa tingkat kualitas air perairan tersebut berbeda-beda. Konsentrasi rerata parameter kualitas air  (BOD5, N-NO3, P-PO4, EC, dan TC) di SB, berturut-turut, sebesar 0.317 mg/l, 0.093 mg/l, 2 mg/l, >2420 MPN, dan >2420 MPN; di SM, berturut-turut, sebesar 0.029 mg/l, 1.859 mg/l, 17.7 mg/l, >2420 MPN, dan >2420 MPN; dan di ST, berturut-turut, sebesar 0.299 mg/l, 0.252 mg/l, 3.5 mg/l, >2420 MPN, dan >2420 MPN. Konsentrasi kualitas air ketiga sungai tersebut tidak berbeda secara signifikan (p>0.05), kecuali parameter N-NO3 (p<0.01). Secara umum, kondisi kualitas air ketiga sungai tersebut, menurut Peraturan Pemerintah No. 82, 2001) berada dalam status “tidak cocok” untuk peruntukannya.

scholarly journals The application of drones for mosquito larval habitat identification in rural environments: a practical approach for malaria control?

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Michelle C. Stanton ◽  
Patrick Kalonde ◽  
Kennedy Zembere ◽  
Remy Hoek Spaans ◽  
Christopher M. Jones
Keyword(s):  
Image Analysis ◽  
Malaria Control ◽  
Rural Areas ◽  
Near Infrared ◽  
Aquatic Vegetation ◽  
Temporal Trends ◽  
Scale Up ◽  
Larval Habitat ◽  
Habitat Characteristics ◽  
Rural Environments

Abstract Background Spatio-temporal trends in mosquito-borne diseases are driven by the locations and seasonality of larval habitat. One method of disease control is to decrease the mosquito population by modifying larval habitat, known as larval source management (LSM). In malaria control, LSM is currently considered impractical in rural areas due to perceived difficulties in identifying target areas. High resolution drone mapping is being considered as a practical solution to address this barrier. In this paper, the authors’ experiences of drone-led larval habitat identification in Malawi were used to assess the feasibility of this approach. Methods Drone mapping and larval surveys were conducted in Kasungu district, Malawi between 2018 and 2020. Water bodies and aquatic vegetation were identified in the imagery using manual methods and geographical object-based image analysis (GeoOBIA) and the performances of the classifications were compared. Further, observations were documented on the practical aspects of capturing drone imagery for informing malaria control including cost, time, computing, and skills requirements. Larval sampling sites were characterized by biotic factors visible in drone imagery and generalized linear mixed models were used to determine their association with larval presence. Results Imagery covering an area of 8.9 km2 across eight sites was captured. Larval habitat characteristics were successfully identified using GeoOBIA on images captured by a standard camera (median accuracy = 98%) with no notable improvement observed after incorporating data from a near-infrared sensor. This approach however required greater processing time and technical skills compared to manual identification. Larval samples captured from 326 sites confirmed that drone-captured characteristics, including aquatic vegetation presence and type, were significantly associated with larval presence. Conclusions This study demonstrates the potential for drone-acquired imagery to support mosquito larval habitat identification in rural, malaria-endemic areas, although technical challenges were identified which may hinder the scale up of this approach. Potential solutions have however been identified, including strengthening linkages with the flourishing drone industry in countries such as Malawi. Further consultations are therefore needed between experts in the fields of drones, image analysis and vector control are needed to develop more detailed guidance on how this technology can be most effectively exploited in malaria control.

scholarly journals The Equivalent Thermal Conductivity of the Micro/Nano Scaled Periodic Cubic Frame Silver and Its Thermal Radiation Mechanism Analysis

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4158
Author(s):  
Haiyan Yu ◽  
Haochun Zhang ◽  
Heming Wang ◽  
Dong Zhang
Keyword(s):  
Thermal Conductivity ◽  
Thermal Radiation ◽  
Cell Size ◽  
Near Infrared ◽  
High Porosity ◽  
Mechanism Analysis ◽  
Infrared Band ◽  
Spectral Radiation ◽  
Radiation Mechanism ◽  
Equivalent Thermal Conductivity

Currently, there are few studies on the influence of microscale thermal radiation on the equivalent thermal conductivity of microscale porous metal. Therefore, this paper calculated the equivalent thermal conductivity of high-porosity periodic cubic silver frame structures with cell size from 100 nm to 100 µm by using the microscale radiation method. Then, the media radiation characteristics, absorptivity, reflectivity and transmissivity were discussed to explain the phenomenon of the radiative thermal conductivity changes. Furthermore, combined with spectral radiation properties at the different cross-sections and wavelength, the radiative transmission mechanism inside high-porosity periodic cubic frame silver structures was obtained. The results showed that the smaller the cell size, the greater radiative contribution in total equivalent thermal conductivity. Periodic cubic silver frames fluctuate more in the visible band and have better thermal radiation modulation properties in the near infrared band, which is formed by the Surface Plasmon Polariton and Magnetic Polaritons resonance jointly. This work provides design guidance for the application of this kind of periodic microporous metal in the field of thermal utilization and management.

Effects of Metal Stress on Visible/Near-Infrared Reflectance Spectra of Vegetation

2011 ◽  
Vol 347-353 ◽  
pp. 2735-2738 ◽  
Author(s):  
Guang Yu Chi ◽  
Yi Shi ◽  
Xin Chen ◽  
Jian Ma ◽  
Tai Hui Zheng
Keyword(s):  
Heavy Metal ◽  
Structural Changes ◽  
Near Infrared ◽  
Leaf Surface ◽  
Spectral Response ◽  
Spectral Characteristics ◽  
Surface Characteristics ◽  
Heavy Metal Stress ◽  
Metal Stress ◽  
Near Infrared Reflectance

Vegetation which suffers from heavy metal stresses can cause changes of leaf color, shape and structural changes. The spectral characteristics of vegetation leaves is related to leaf thickness, leaf surface characteristics, the content of water, chlorophyll and other pigments. So the eco-physiology changes of plants can be reflected by spectral reflectance. Studies on the spectral response of vegetation to heavy metal stress can provide a theoretical basis for remote sensing monitoring of metal pollution in soils. In recent decades, there are substantial amounts of literature exploring the effects of heavy metals on vegetation spectra.

scholarly journals Snow dunes and glazed surfaces in Antarctica: new field and remote-sensing data

2002 ◽  
Vol 34 ◽  
pp. 81-88 ◽  
Author(s):  
Massimo Frezzotti ◽  
Stefano Gandolfi ◽  
Floriana La Marca ◽  
Stefano Urbini
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Accumulation Rate ◽  
Spectral Response ◽  
Remote Sensing Data ◽  
Snow Accumulation ◽  
Remotely Sensed Data ◽  
Surface Mass ◽  
Glazed Surface ◽  
Transverse Dunes

AbstractAs part of the International Trans-Antarctic Scientific Expedition project, the Italian Antarctic Programme undertook two traverses from the Terra Nova station to Talos Dome and to Dome C. Along the traverses, the party carried out several tasks (drilling, glaciological and geophysical exploration). The difference in spectral response between glazed surfaces and snow makes it simple to identify these areas on visible/near-infrared satellite images. Integration of field observation and remotely sensed data allows the description of different mega-morphologic features: wide glazed surfaces, sastrugi glazed surface fields, transverse dunes and megadunes. Topography global positioning system, ground penetrating radar and detailed snow-surface surveys have been carried out, providing new information about the formation and evolution of mega-morphologic features. The extensive presence, (up to 30%) of glazed surface caused by a long hiatus in accumulation, with an accumulation rate of nil or slightly negative, has a significant impact on the surface mass balance of a wide area of the interior part of East Antarctica. The aeolian processes creating these features have important implications for the selection of optimum sites for ice coring, because orographic variations of even a few metres per kilometre have a significant impact on the snow-accumulation process. Remote-sensing surveys of aeolian macro-morphology provide a proven, high-quality method for detailed mapping of the interior of the ice sheet’s prevalent wind direction and could provide a relative indication of wind intensity.

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