JW
J.C. Wiggins
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2 records found
1
Estimating Total Suspended Matter in Low to Extremely High Level Turbid River Surface Waters using a WISP-3 Hyperspectral Radiometer and Sentinel-2 Optical Imagery
A case study conducted on the Brantas River Basin, East-Java, Indonesia
Master thesis
(2020)
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J.C. Wiggins, M.W. Ertsen, W. Citrosiswoyo, T. Hariyanto, O.A.C. Hoes, M. Laanen, S.L.M. Lhermitte
This research focuses on using Sentinel-2 optical imagery to provide a means of high-resolution monitoring and evaluation of changes in Total Suspended Matter (TSM) concentration in the Brantas river basin. In situ spectral measurements as well as laboratory results show an extremely turbid nature of the Brantas River surface water. Current monitoring of the river water quality, is done by point measurements representing point estimations of the water quality in time and pace. Interactions within the system are mostly unknown. Having accurate knowledge of near real time water quality information will greatly enhance the effectiveness of the monitoring organizations, especially if this comes in a high
spatial and temporal resolution. The Sentinel- 2 remote sensing platform delivers information which can be used to derive such data with a 10m resolution and revisit time of 5 days. To estimate TSM concentrations a multi-conditional algorithm is developed. It uses linear regression for low to medium
TSM concentrations based on the green and red band reflectance values and polynomial regression for high to extremely high TSM concentrations based on the red edge NIR band. Testing the multi-conditional algorithm on the WISP-3 in situ spectral data shows the model’s performance is good with r2 = 0.79, RMSE
= 66.5 mg/L and NRMSE = 9.7%. Performance of the multi-conditional algorithm is found to be poor when based on Sentinel-2 (S2) bottom of atmosphere data from bands green, red and red edge NIR. However, when recalibrating the polynomial model on Sentinel-2 atmospherically uncorrected top of atmosphere
data, results are more promising: r2 = 0.75, RMSE = 64.2 mg/L and NRMSE = 11.3% . Also, TSM estimates from remote sensing reflectances atmospherically corrected by different processors are compared, from which ACOLITE (RMSE = 5.0 mg/L, NRMSE = 25.3%) performs significantly better than C2RCC (RMSE =
11.3 mg/L, NRMSE = 57.5%) and Sen2Cor (RMSE = 42.8 mg/L, NRMSE = 217%). This study shows that 1) high-resolution spatial and temporal variation of TSM concentration estimation can be made visible within the Brantas river basin, 2) an overview of TSM concentration estimation of the entire basin at one
moment in time can be achieved and visualised, 3) an extensive historical record of TSM concentration estimations can be accessed, and 4) information is provided to prioritize sampling locations and field surveying times. ...
spatial and temporal resolution. The Sentinel- 2 remote sensing platform delivers information which can be used to derive such data with a 10m resolution and revisit time of 5 days. To estimate TSM concentrations a multi-conditional algorithm is developed. It uses linear regression for low to medium
TSM concentrations based on the green and red band reflectance values and polynomial regression for high to extremely high TSM concentrations based on the red edge NIR band. Testing the multi-conditional algorithm on the WISP-3 in situ spectral data shows the model’s performance is good with r2 = 0.79, RMSE
= 66.5 mg/L and NRMSE = 9.7%. Performance of the multi-conditional algorithm is found to be poor when based on Sentinel-2 (S2) bottom of atmosphere data from bands green, red and red edge NIR. However, when recalibrating the polynomial model on Sentinel-2 atmospherically uncorrected top of atmosphere
data, results are more promising: r2 = 0.75, RMSE = 64.2 mg/L and NRMSE = 11.3% . Also, TSM estimates from remote sensing reflectances atmospherically corrected by different processors are compared, from which ACOLITE (RMSE = 5.0 mg/L, NRMSE = 25.3%) performs significantly better than C2RCC (RMSE =
11.3 mg/L, NRMSE = 57.5%) and Sen2Cor (RMSE = 42.8 mg/L, NRMSE = 217%). This study shows that 1) high-resolution spatial and temporal variation of TSM concentration estimation can be made visible within the Brantas river basin, 2) an overview of TSM concentration estimation of the entire basin at one
moment in time can be achieved and visualised, 3) an extensive historical record of TSM concentration estimations can be accessed, and 4) information is provided to prioritize sampling locations and field surveying times. ...
This research focuses on using Sentinel-2 optical imagery to provide a means of high-resolution monitoring and evaluation of changes in Total Suspended Matter (TSM) concentration in the Brantas river basin. In situ spectral measurements as well as laboratory results show an extremely turbid nature of the Brantas River surface water. Current monitoring of the river water quality, is done by point measurements representing point estimations of the water quality in time and pace. Interactions within the system are mostly unknown. Having accurate knowledge of near real time water quality information will greatly enhance the effectiveness of the monitoring organizations, especially if this comes in a high
spatial and temporal resolution. The Sentinel- 2 remote sensing platform delivers information which can be used to derive such data with a 10m resolution and revisit time of 5 days. To estimate TSM concentrations a multi-conditional algorithm is developed. It uses linear regression for low to medium
TSM concentrations based on the green and red band reflectance values and polynomial regression for high to extremely high TSM concentrations based on the red edge NIR band. Testing the multi-conditional algorithm on the WISP-3 in situ spectral data shows the model’s performance is good with r2 = 0.79, RMSE
= 66.5 mg/L and NRMSE = 9.7%. Performance of the multi-conditional algorithm is found to be poor when based on Sentinel-2 (S2) bottom of atmosphere data from bands green, red and red edge NIR. However, when recalibrating the polynomial model on Sentinel-2 atmospherically uncorrected top of atmosphere
data, results are more promising: r2 = 0.75, RMSE = 64.2 mg/L and NRMSE = 11.3% . Also, TSM estimates from remote sensing reflectances atmospherically corrected by different processors are compared, from which ACOLITE (RMSE = 5.0 mg/L, NRMSE = 25.3%) performs significantly better than C2RCC (RMSE =
11.3 mg/L, NRMSE = 57.5%) and Sen2Cor (RMSE = 42.8 mg/L, NRMSE = 217%). This study shows that 1) high-resolution spatial and temporal variation of TSM concentration estimation can be made visible within the Brantas river basin, 2) an overview of TSM concentration estimation of the entire basin at one
moment in time can be achieved and visualised, 3) an extensive historical record of TSM concentration estimations can be accessed, and 4) information is provided to prioritize sampling locations and field surveying times.
spatial and temporal resolution. The Sentinel- 2 remote sensing platform delivers information which can be used to derive such data with a 10m resolution and revisit time of 5 days. To estimate TSM concentrations a multi-conditional algorithm is developed. It uses linear regression for low to medium
TSM concentrations based on the green and red band reflectance values and polynomial regression for high to extremely high TSM concentrations based on the red edge NIR band. Testing the multi-conditional algorithm on the WISP-3 in situ spectral data shows the model’s performance is good with r2 = 0.79, RMSE
= 66.5 mg/L and NRMSE = 9.7%. Performance of the multi-conditional algorithm is found to be poor when based on Sentinel-2 (S2) bottom of atmosphere data from bands green, red and red edge NIR. However, when recalibrating the polynomial model on Sentinel-2 atmospherically uncorrected top of atmosphere
data, results are more promising: r2 = 0.75, RMSE = 64.2 mg/L and NRMSE = 11.3% . Also, TSM estimates from remote sensing reflectances atmospherically corrected by different processors are compared, from which ACOLITE (RMSE = 5.0 mg/L, NRMSE = 25.3%) performs significantly better than C2RCC (RMSE =
11.3 mg/L, NRMSE = 57.5%) and Sen2Cor (RMSE = 42.8 mg/L, NRMSE = 217%). This study shows that 1) high-resolution spatial and temporal variation of TSM concentration estimation can be made visible within the Brantas river basin, 2) an overview of TSM concentration estimation of the entire basin at one
moment in time can be achieved and visualised, 3) an extensive historical record of TSM concentration estimations can be accessed, and 4) information is provided to prioritize sampling locations and field surveying times.
An intervention study to gain insight on sustainable water supply strategies in El Progreso, Panama
A Multidisciplinary Project in the Colon Province
Student report
(2018)
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Sarah Kleijn, Swaen Visser, Vita Vollaers, Joris Wiggins, Jeroen van Wijngaarden, Maurits Ertsen, Martijn Leijten, Willem Luxemburg, K. de Krijger
The main focus of this project is to gain insight into feasible strategies for sustainable water supply in a community inhabited by indigenous people. This was done by an intervention study in a small village called El Progreso in the province of Colon, on the Caribbean coast of Panama. The project aims to provide safe drinking water to the 80 members of the Embera tribe, living in El Progreso. This is done by constructing rainwater harvesting tanks where rainwater will be collected from roofs of houses and school buildings and stored within the tanks. We want to investigate the impact of this system, which supplies safe drinking water on a daily basis, on the community. The construction of the storage tanks (ferrocement) will stimulate and create local entrepreneurship. In these ways we will take our first step towards a sustainable local enterprise and sustainable employment. This can ultimately result in a long-term development in the El Progreso area. The project consists of 3 study topics: the physical construction of the rainwater harvesting tanks and the project control and quality that comes with this, evaluating the quality and quantity of available water sources in the area of rainwater and rainwater and the possible changes in the community due to this project (both the influence of the newly constructed tanks on daily life as well as the presence of aid in the community and social impacts that comes along with this). The project resulted in the construction of 11 tanks, improved job opportunities for several community members, improved trust in aid organizations as well as connecting the community to a national aid network for future projects.
...
The main focus of this project is to gain insight into feasible strategies for sustainable water supply in a community inhabited by indigenous people. This was done by an intervention study in a small village called El Progreso in the province of Colon, on the Caribbean coast of Panama. The project aims to provide safe drinking water to the 80 members of the Embera tribe, living in El Progreso. This is done by constructing rainwater harvesting tanks where rainwater will be collected from roofs of houses and school buildings and stored within the tanks. We want to investigate the impact of this system, which supplies safe drinking water on a daily basis, on the community. The construction of the storage tanks (ferrocement) will stimulate and create local entrepreneurship. In these ways we will take our first step towards a sustainable local enterprise and sustainable employment. This can ultimately result in a long-term development in the El Progreso area. The project consists of 3 study topics: the physical construction of the rainwater harvesting tanks and the project control and quality that comes with this, evaluating the quality and quantity of available water sources in the area of rainwater and rainwater and the possible changes in the community due to this project (both the influence of the newly constructed tanks on daily life as well as the presence of aid in the community and social impacts that comes along with this). The project resulted in the construction of 11 tanks, improved job opportunities for several community members, improved trust in aid organizations as well as connecting the community to a national aid network for future projects.