Comparative Analysis of the Land Use and Land Cover Changes in Different Governorates of Oman using Spatiotemporal Multi-spectral Satellite Data
Land cover and land use (LULC) changes are key applications of satellite imagery, and they have critical roles in resource management, urbanization, protection of soils and the environment, and enhancing sustainable development. The literature has heavily utilized multispectral spatiotemporal satellite data alongside advanced machine learning algorithms to monitor and predict LULC changes. This study analyzes and compares LULC changes across various governorates (provinces) of the Sultanate of Oman from 2016 to 2021 using annual time steps. For the chosen region, multispectral spatiotemporal data were acquired from the open-source Sentinel-2 satellite dataset. Supervised machine learning algorithms were used to train and classify different land covers, such as water bodies, crops, urban, etc. The constructed model was subsequently applied within the study region, allowing for an effective comparative evaluation of LULC changes within the given timeframe.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementSimilar Papers 제목 키워드 기반
Land Cover Change Detection via Semantic Segmentation
This paper presents a change detection method that identifies land cover changes from aerial imagery, using semantic segmentation, a machine learning approach. We present a land cover classification training pipeline wit…
Change DetectionGeneral ClassificationLand Cover ClassificationManagement+2Analysis of Fractional Vegetation Coverage and its Dynamic Change in the Yalong River Basin based on Dimidiate Pixel Model
Fractional vegetation coverage (FVC) and its spatio-temporal variations are critical indicators of regional ecological changes, which are of great significance to study the laws of surface variation and analyze regional …
Landcover classification and change detection using remote sensing and machine learning: a case study of Western Fiji
As a developing country, Fiji is facing rapid urbanisation, which is visible in the massive development projects that include housing, roads, and civil works. In this study, we present machine learning and remote sensing…
Change DetectionTropical Land Use Land Cover Mapping in Pará (Brazil) using Discriminative Markov Random Fields and Multi-temporal TerraSAR-X Data
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high …
Comparative Analysis of Static and Contextual Embeddings for Analyzing Semantic Changes in Medieval Latin Charters
The Norman Conquest of 1066 C.E. brought profound transformations to England's administrative, societal, and linguistic practices. The DEEDS (Documents of Early England Data Set) database offers a unique opportunity to e…
Word Embeddings