{"title":"利用三维空间权重矩阵的广义 STAR 模型预测印度尼西亚泥炭地的水位","authors":"Utriweni Mukhaiyar, Adilan Widyawan Mahdiyasa, Tarasinta Prastoro, Udjianna Sekteria Pasaribu, Kurnia Novita Sari, Sapto Wahyu Indratno, Indratmo Soekarno, Devi Nandita Choesin, Isro Ismail, Dian Rosleine, Danang Teguh Qoyyimi","doi":"10.1186/s12302-024-00979-6","DOIUrl":null,"url":null,"abstract":"<div><p>The release rate of CO<sub>2</sub> gas can be influenced by peatlands’ physical properties, such as water level and soil moisture, and rainfall. To anticipate the unstable condition which is when the peatland emit more carbon, we developed the Generalized Space Time Autoregressive (GSTAR) model in predicting these physical properties for the following weeks. As the innovation in modelling, the spatial weight matrix was based on three-dimensional coordinates with a modification on the height factor. The data we used are real-time data of water level on the peatlands in Pulang Pisau Regency, Central Kalimantan Province from 20 February 2021 to 18 March 2023. We then used Ordinary Kriging interpolation on the prediction results to create contour maps on different dates. There were empty data on several dates, especially from 24 March until 3 August 2022. To fill the empty data, we used linear interpolation and then we added white noise to the interpolation results. From the data, the water level has a downward trend pattern from around November to September and an upward trend pattern from October to November. Furthermore, we found that the best model for water level was GSTAR (2;0.1) with a modified matrix <span>\\(a=0.1\\)</span> and <span>\\(b=1.1\\)</span>. Based on the predicted water level, there is a risk of changes in the properties of the peatlands in several areas in Pulang Pisau Regency.</p></div>","PeriodicalId":546,"journal":{"name":"Environmental Sciences Europe","volume":"36 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1186/s12302-024-00979-6.pdf","citationCount":"0","resultStr":"{\"title\":\"The generalized STAR modelling with three-dimensional of spatial weight matrix in predicting the Indonesia peatland’s water level\",\"authors\":\"Utriweni Mukhaiyar, Adilan Widyawan Mahdiyasa, Tarasinta Prastoro, Udjianna Sekteria Pasaribu, Kurnia Novita Sari, Sapto Wahyu Indratno, Indratmo Soekarno, Devi Nandita Choesin, Isro Ismail, Dian Rosleine, Danang Teguh Qoyyimi\",\"doi\":\"10.1186/s12302-024-00979-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The release rate of CO<sub>2</sub> gas can be influenced by peatlands’ physical properties, such as water level and soil moisture, and rainfall. To anticipate the unstable condition which is when the peatland emit more carbon, we developed the Generalized Space Time Autoregressive (GSTAR) model in predicting these physical properties for the following weeks. As the innovation in modelling, the spatial weight matrix was based on three-dimensional coordinates with a modification on the height factor. The data we used are real-time data of water level on the peatlands in Pulang Pisau Regency, Central Kalimantan Province from 20 February 2021 to 18 March 2023. We then used Ordinary Kriging interpolation on the prediction results to create contour maps on different dates. There were empty data on several dates, especially from 24 March until 3 August 2022. To fill the empty data, we used linear interpolation and then we added white noise to the interpolation results. From the data, the water level has a downward trend pattern from around November to September and an upward trend pattern from October to November. Furthermore, we found that the best model for water level was GSTAR (2;0.1) with a modified matrix <span>\\\\(a=0.1\\\\)</span> and <span>\\\\(b=1.1\\\\)</span>. Based on the predicted water level, there is a risk of changes in the properties of the peatlands in several areas in Pulang Pisau Regency.</p></div>\",\"PeriodicalId\":546,\"journal\":{\"name\":\"Environmental Sciences Europe\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1186/s12302-024-00979-6.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Sciences Europe\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s12302-024-00979-6\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Sciences Europe","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1186/s12302-024-00979-6","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
The generalized STAR modelling with three-dimensional of spatial weight matrix in predicting the Indonesia peatland’s water level
The release rate of CO2 gas can be influenced by peatlands’ physical properties, such as water level and soil moisture, and rainfall. To anticipate the unstable condition which is when the peatland emit more carbon, we developed the Generalized Space Time Autoregressive (GSTAR) model in predicting these physical properties for the following weeks. As the innovation in modelling, the spatial weight matrix was based on three-dimensional coordinates with a modification on the height factor. The data we used are real-time data of water level on the peatlands in Pulang Pisau Regency, Central Kalimantan Province from 20 February 2021 to 18 March 2023. We then used Ordinary Kriging interpolation on the prediction results to create contour maps on different dates. There were empty data on several dates, especially from 24 March until 3 August 2022. To fill the empty data, we used linear interpolation and then we added white noise to the interpolation results. From the data, the water level has a downward trend pattern from around November to September and an upward trend pattern from October to November. Furthermore, we found that the best model for water level was GSTAR (2;0.1) with a modified matrix \(a=0.1\) and \(b=1.1\). Based on the predicted water level, there is a risk of changes in the properties of the peatlands in several areas in Pulang Pisau Regency.
期刊介绍:
ESEU is an international journal, focusing primarily on Europe, with a broad scope covering all aspects of environmental sciences, including the main topic regulation.
ESEU will discuss the entanglement between environmental sciences and regulation because, in recent years, there have been misunderstandings and even disagreement between stakeholders in these two areas. ESEU will help to improve the comprehension of issues between environmental sciences and regulation.
ESEU will be an outlet from the German-speaking (DACH) countries to Europe and an inlet from Europe to the DACH countries regarding environmental sciences and regulation.
Moreover, ESEU will facilitate the exchange of ideas and interaction between Europe and the DACH countries regarding environmental regulatory issues.
Although Europe is at the center of ESEU, the journal will not exclude the rest of the world, because regulatory issues pertaining to environmental sciences can be fully seen only from a global perspective.