Ridwan Saidi
Universitas Pendidikan Indonesia

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Pemanfaatan Citra Landsat 8 untuk Identifikasi Sebaran Vegetasi di Kecamatan Pangandaran Ridwan Saidi; Nisvi Nur’adqiah; Yusifa Muzri; Lu’lu’ Izzatul Fawziah; Reza Pahlawan; Dede Sugandi; Riki Ridwana
JPG (Jurnal Pendidikan Geografi) Vol 7, No 1 (2020)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jpg.v7i1.7607

Abstract

This study aims to determine: (1) the density of vegetation in Pangandaran district. (2)the result of comparison of vegetation density from digital image interpretation using the NDVI transformation with the results of validation. This research was done in pangandaran regency, which is located at coordinates 108º 41 - 1090 East Longitude and 07o 41-07 07 50 South Latitude has an area of up to 61 km². This research was conducted in several stages, namely: (1) the preparation of tools and data, (2) digital data processing, (3) field data collection, and (4) data analysis. Thanks to the density of vegetation can be done quickly by way of digital image interpretation using NDVI (Normalized Difference Vegetation Index) transformation. The purpose of this research is to know the land arrangement in Pangandaran District and for vegetation index of residential area in Pangandaran District. The object of this research is residential area in Pangandaran District. The data used are Landsat Image 8 year 2018. The software used is ENVI 5.1 and ArcGIS 10.3 software. The method used is the classification of land use and the calculation of NDVI in ENVI which then classified based on the range of NDVI index values. The results showed that the density of vegetation in Pangandaran District was dominating  classified and as quite dense but it needed a lot of updating of its digital image and data so that the accuracy rate increased between imagery and field data. Vegetation in Pangandaran Subdistrict is mostly dominated by teak, waru, coconut, Chinese petai, goat, santigi, and ketapang. Based on the results of the interpretation accuracy test, obtained an accuracy value for the entire sample of 57% so that the results of image interpretation and field checks regarding vegetation density cannot be accepted because the expected level of interpretation accuracy is 85%, while the accuracy test results get a value of 57%. To get a complete picture of the availability of green open space in Pangandaram Regency, fast and relatively more accurate analysis of high spatial resolution is needed. The satellite imagery used in this study is Landsat 8 Imagery which has never been used in previous studies. Analysis of these images uses a vegetation index / NDVI that can directly distinguish plants from non-plants. The results of this image analysis also produce digital data that can be processed quantitatively for further research purposes.
Analysis of Disaster Awareness Culture Formation Through Geography Learning in Schools: A Literature Review Ridwan Saidi; Bagja Waluya; Annisa Joviani Astari
JPG (Jurnal Pendidikan Geografi) Vol 13, No 2 (2026)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jpg.v13i2.26846

Abstract

A disaster aware culture is a critical component of disaster risk reduction within school environments. Geography education has substantial potential to foster this culture because its subject matter inherently encompasses geosphere processes, spatial relationships, human–environment interactions, and hazard mitigation. However, empirical evidence regarding the specific contributions of geography pedagogy to a disaster-aware culture remains fragmented across instructional strategies, disaster contexts, and student outcome metrics. This study employed a scoping review design guided by the PRISMA-ScR framework to map and synthesize current empirical evidence. A literature search via Google Scholar using Publish or Perish yielded 60 initial records. Following a two-stage screening process based on predefined criteria, 24 empirical studies (2010–2025) were selected for final qualitative content analysis. Synthesis identified seven dominant pedagogical approaches: contextual learning (n = 5), project-based learning (n = 3), experiential learning (n = 4), disaster simulations and drills (n = 3), geospatial-technology-based learning (n = 4), disaster-literacy-based learning (n = 3), and the whole-school approach (n = 2). Geography instruction positively influenced core indicators of a disaster-aware culture, primarily disaster knowledge (n = 4), disaster literacy (n = 3), risk awareness (n = 3), preparedness (n = 4), attitudes (n = 2), mitigation behavior (n = 2), decision-making (n = 2), environmental responsibility (n = 1), geographical awareness (n = 2), and disaster resilience (n = 1). Nevertheless, these findings reflect identified pedagogical patterns rather than uniform causal effects due to corpus heterogeneity. Methodological limitations include database reliance and selection bias. Future research should utilize multi-database strategies, standardized operational definitions, and longitudinal designs to evaluate long-term efficacy across diverse school contexts.