Building a GIS Map for Forecasting the MIR Index in An Giang

Abstract

The MIR aquatic plant signal is capable of predicting specific pollution sources of water, contributing significantly to the effective management of surface water resources in An Giang province. The use of aquatic plants in water pollution treatment brings about positive effects through natural self-purification processes as they consume organic and nutrient substances such as N and P. Therefore, it is crucial to develop a tool for monitoring and supervising aquatic plant species. This paper investigates the application of GIS technology to build a GIS map representing the current status of vegetation cover in An Giang province. The background layers of the GIS database, along with detailed attribute layers regarding species composition, dominant species, and vegetation area, will serve as the basis for managing, utilizing, conserving, and restoring vegetation cover in the research area. Additionally, a predictive model for MIR indices has been constructed using machine learning methods. The results indicate that the model has a coefficient of determination (R2) of 91.7% for the dependent variable MIR compared to the independent variables. Subsequently, these results are visually displayed on a GIS map at 18 monitoring points within An Giang province, enabling users to easily observe, compare, evaluate, and propose suitable solutions for surface water quality management. ABSTRAK: Isyarat tumbuhan akuatik MIR mampu meramalkan sumber pencemaran air secara spesifik, iaitu penyumbang penting kepada pengurusan berkesan permukaan sumber air di wilayah An Giang. Penggunaan tumbuhan akuatik dalam rawatan pencemaran membawa kepada kesan positif melalui proses rawatan kendiri secara semula jadi kerana ia mengandungi bahan organik dan nutrien seperti N dan P. Oleh itu, sangat penting bagi membangunkan alat pemantauan dan pengawasan spesies tumbuhan akuatik. Kajian ini mengkaji aplikasi teknologi GIS bagi membangunkan peta GIS mewakili status terkini keseluruhan tumbuhan di wilayah An Giang. Lapisan latar belakang pangkalan data GIS bersama lapisan sifat-sifat terperinci berkenaan spesies komposit, spesies dominan, dan kawasan tumbuh-tumbuhan, dapat menyediakan asas kepada pengurusan, penggunaan, pemuliharaan, dan pemulihan tumbuh-tumbuhan meliputi kawasan kajian.  Tambahan, model ramalan MIR dibangunkan menggunakan kaedah pembelajaran mesin. Dapatan kajian menunjukkan model ini mempunyai pekali penentu (R2) sebanyak 91.7% bagi pembolehubah MIR bersandar berbanding pembolehubah tak bersandar. Menyebabkan dapatan ini secara visual dapat dilihat pada peta GIS menggunakan 18 titik pantauan dalam wilayah An Giang province, membolehkan pengguna mudah melihat, membandingkan, menilai, dan mencadangkan solusi sesuai bagi pengurusan kualiti permukaan air.