This article explores the novel application of the Google Earth Engine (GEE) platform using the inversedistanceweighting (IDW) interpolation technique based on an improved version of the modified Shephard method for...
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This article explores the novel application of the Google Earth Engine (GEE) platform using the inversedistanceweighting (IDW) interpolation technique based on an improved version of the modified Shephard method for the development of specialized geotechnical soil maps (GSMs) for mega-district Lahore. The study area was assessed at multiple depths in terms of key geotechnical properties. The result depicts a predominance of fine-grained soil at a shallow depth of 3 m exhibiting low to moderate soil stiffness, consistency and activity along with a few zones of problematic soil with adverse geotechnical characteristics which require due attention. Whereas beyond 3 m the study area exhibits higher bearing values, low plasticity and non-active soil. Besides, the chemical content level was within permissible limits except for a few spots. The comprehensive statistical evaluation based on key performance indices indicates the efficient performance of the novel GEE-based IDW algorithm to yield significantly accurate maps.
In this study, we use the inverse distance weighting algorithm to establish the solar irradiation estimation model. The model was built by obtaining information from 20 solar irradiation monitoring stations in central...
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ISBN:
(纸本)9781538643426
In this study, we use the inverse distance weighting algorithm to establish the solar irradiation estimation model. The model was built by obtaining information from 20 solar irradiation monitoring stations in central and southern Taiwan, and field verification was implemented at Yuan Chang Township town hall and Liujia Campus of Tainan. The Mean Absolute Percentage Error (MAPE) values of the solar irradiation estimation model at the two field verifications were 4.30% and 3.71% respectively.
The power generation potential of a solar photovoltaic (PV) power generation system is closely related to the on-site solar radiation, and sunshine conditions are an important reference index for evaluating the instal...
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The power generation potential of a solar photovoltaic (PV) power generation system is closely related to the on-site solar radiation, and sunshine conditions are an important reference index for evaluating the installation of a solar PV system. Meanwhile, the long-term operation and maintenance of a PV system needs solar radiation information as a reference for system performance evaluation. Obtaining solar radiation information through the installation of irradiation monitoring stations is often very costly, and the cost of sustaining the reliability of the monitoring system, Internet stability and subsequent operation and maintenance can often be alarming. Therefore, the establishment of a solar radiation estimation model can reduce the installation of monitoring stations and decrease the cost of obtaining solar radiation information. In this study, we use an inverse distance weighting algorithm to establish the solar radiation estimation model. The model was built by obtaining information from 20 solar radiation monitoring stations in central and southern Taiwan, and field verification was implemented at Yuan Chang Township town hall and the Tainan Liujia campus. Furthermore, a full comparison between inversedistanceweighting (IDW) and the Kriging method is also given in this paper. The estimation results demonstrate the performance of the IDW method. In the experiment, the performance of the IDW method is better than the Ordinary Kriging (OK) method. The Mean Absolute Percentage Error (MAPE) values of the solar radiation estimation model by IDW at the two field verifications were 4.30% and 3.71%, respectively.
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