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监测与预测郊区建成区的发展:以印度尼西亚日惹市斯勒曼为例

Monitoring and predicting development of built-up area in sub-urban areas: A case study of Sleman, Yogyakarta, Indonesia.

作者信息

Arif Nursida, Toersilawati Laras

机构信息

Department of Geography Education, Universitas Negeri Yogyakarta, Yogyakarta, 55281, Indonesia.

National Research and Innovation Agency (BRIN), Bandung, 40135, Indonesia.

出版信息

Heliyon. 2024 Jul 14;10(14):e34466. doi: 10.1016/j.heliyon.2024.e34466. eCollection 2024 Jul 30.

Abstract

Monitoring built-up areas in the previous year and possible predictions for the following year are important in planning regional development and controlling the expansion of built-up areas. This study detects changes in the built-up area (2018-2022). It predicts the future (2026) using Landsat satellite imagery in the Sleman Regency, Yogyakarta Special Region, Indonesia study area. Mapping built-up areas is identified using the Normalized Difference Built-Up Index (NDBI). Vegetation conditions were analyzed using the Normalized Difference Vegetation Index (NDVI). Changes in the built-up area are predicted using the CA-Markov chain model for 2026. The prediction is calibrated by comparing the simulated map with the results of the classification of built-up areas in 2022. The research findings show that the built-up area has increased by 12.84 % from 2018 to 2022 and is predicted to increase by 15.48 % in 2026. The existence of built-up areas has an influence on land surface temperatures where the analysis results show a moderate correlation between NDBI and LST, namely 2018 (R2 = 0.401), 2019 (R2 = 0.323), 2020 (R2 = 0.401), 2021 (R2 = 0.415), and 2022 (R2 = 0.384). The higher the NDBI value, the higher the LST value, and vice versa. Therefore, regional development planning, mainly built-up areas, is an important recommendation for decision-makers in the study area.

摘要

监测上一年的建成区并对下一年进行可能的预测,对于区域发展规划和控制建成区扩张至关重要。本研究检测了建成区(2018 - 2022年)的变化。它利用印度尼西亚日惹特别行政区斯勒曼摄政区研究区域的陆地卫星图像预测了未来(2026年)的情况。使用归一化差异建成指数(NDBI)来识别建成区的地图。利用归一化差异植被指数(NDVI)分析植被状况。使用CA - 马尔可夫链模型预测2026年建成区的变化。通过将模拟地图与2022年建成区分类结果进行比较来校准预测。研究结果表明,建成区面积从2018年到2022年增加了12.84%,预计2026年将增加15.48%。建成区的存在对地表温度有影响,分析结果表明NDBI与LST之间存在中等相关性,即2018年(R2 = 0.401)、2019年(R2 = 0.323)、2020年(R2 = 0.401)、2021年(R2 = 0.415)和2022年(R2 = 0.384)。NDBI值越高,LST值越高,反之亦然。因此,区域发展规划,主要是建成区规划,是研究区域决策者的一项重要建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b86/11305289/d03b0c1fe153/gr1.jpg

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