Spatial Metrics of Deforestation in Kampar and Indragiri Hulu, Riau Province

Rijal, Syamsu; Saleh, Muhammad Buce; Jaya, Indra; Tiryana, Tatang

doi:10.7226/jtfm.22.1.24

Cited by 6 publications

(17 citation statements)

References 12 publications

(17 reference statements)

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“…The image processing is through pre-processing with geometric and radiometric correction stages, layer stacking, mosaic, and cropping using ArcGIS 10.1. Image classification using the on-screen digitation technique follows the PPIK land cover classification guidelines, Forestry Planning Agency (2008) [10,26,30].…”

Section: Data Processingmentioning

confidence: 99%

“…Declining forest quality is characterized by a reduction in canopy cover. Deforestation also results in increasingly fragmented forests [21,[24][25][26]. This incident resulted in forest cover forming a specific pattern into groups of forests that were scattered and not as compact as before.…”

Section: Introductionmentioning

confidence: 99%

“…Deforestation in Indonesia needs to be controlled immediately. Deforestation control raises the need for indicators of environmental change [26], namely the development of deforestation assessment indicators. These environmental indicators include the development of deforestation assessment indicators.…”

Section: Introductionmentioning

confidence: 99%

“…This information is needed for priority handling and control in the right areas to prevent deforestation. Spatial patterns of deforestation indicate factors driving deforestation [8,10] such as those caused by logging, encroachment, fire, grazing, large and small-scale plantations, agriculture, agriculture and other events such as natural disasters [26].…”

Section: Introductionmentioning

confidence: 99%

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Profile, Level of Vulnerability and Spatial Pattern of Deforestation in Sulawesi Period of 1990 to 2018

Rijal

Barkey

Nasri

et al. 2019

Forests

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Deforestation is an event of loss of forest cover to another cover. Sulawesi forests have the potential to be deforested as with Sumatra and Kalimantan. This study aims to provide information on deforestation events in Sulawesi from 1990 to 2018. The data used in this study are (1) land cover in 1990, 2000, 2010; (2) Landsat 8 imagery in 2018; (3) administrative map of BIG in 2018. The methods used are (1) image classification with on-screen digitation techniques following the PPIK land cover classification guidelines, Forestry Planning Agency (2008) using ArcGIS Desktop 10.6 from ESRI; (2) overlapping maps; (3) analysis of deforestation; (4) analysis of deforestation profiles, (5) vulnerability analysis; and (6) analysis of distribution patterns of deforestation. The results showed that the profile of deforestation occurring on Sulawesi Island in the 1990–2018 observation period was dominated by profile 3-1-1 (the proportion of large forest area, the highest incidence of deforestation early stage at the beginning, at a low rate) in 13 districts. The level of vulnerability to deforestation is a non-vulnerable category (37 districts) which is directed to become a priority in handling deforestation in Sulawesi. Spatial patterns of the deforestation that occurred randomly and were scattered are dominated by shrubs, dryland agricultural activities, and small-scale plantations.

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Section: Data Processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Profile, Level of Vulnerability and Spatial Pattern of Deforestation in Sulawesi Period of 1990 to 2018

Rijal

Barkey

Nasri

et al. 2019

Forests

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“…Tidak dapat dipungkiri bahwa kebutuhan akan lahan tempat tinggal, pertanian skala kecil dan perkebunan menjadi salah satu pendorong penduduk membuka areal hutan yang seringkali dilakukan dengan cara membakar hutan. Temuan (Rijal, Jaya, Tiryana, & Saleh, 2016) juga menemukan variabel penyebab kerusakan areal hutan di kawasan Kampar dan Indragiri Hulu selain pertanian skala kecil dan perkebunan juga disebabkan faktor kebakaran hutan.…”

Section: Pendahuluanunclassified

Determinan Deforestasi Negara-Negara Di Kawasan Asia Tenggara Periode 2008-2015

Handalani¹

2019

pwk

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This study aims to analyze the process of changing forest area or deforestation that is multidimensional and complex, encompassing economic aspects, aspects of governance, social and demographic aspects and physical and environmental aspects represented by 15 independent variables in 10 countries in Southeast Asia in the year period 2008-2015. The analysis and study besides relying on the theoretical foundation and previous research also included several variables that describe the complexity and multidimensional changes in forest area. However, these efforts are often constrained by incomplete data and data reliability. In contrast to some previous studies which focused more on economic aspects or aspects of population increase that affected changes in forest area. This research also includes aspects of governance and social and demographic aspects as well as environmental aspect which are expected to complement the spectrum and study of the problems of deforestation and forest degradation. The method used in this study uses pooled least squares and a series of tests to produce the best model specifications and estimators. In research that uses a 95% confidence level on p-value at a value of α = 0.05, it was found that from 15 variables there were only 6 (six) variables that significantly affected the increase in the human development index.

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A spatial study of landscape patterns in landslide-prone areas at cikakak sub-district, west java

Aisyah

Supriatna²,

Rustanto³

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Landslides have a record of deadliest impact in Indonesia during 2015 – 2017. Landslide may be caused by human activities which deteriorate the environment condition such as by reconstructing the landscapes that may reduce the ecological functions. Therefore, mapping the landslide-prone area is necessary as one of the efforts to mitigate the disaster that could be following. The methods used in this study are the landscape metrics with FRAGSTATS 4.2. and Index Storie. Landscape metrics is useful to map the landscape pattern while the Index Storie can be used to map the landslide-prone area, both Indexes then being used for further analysis to determine the relationship between landscape patterns and landslide-prone areas in the study area. Deforestation in the study area is indicated by the values of PD, LPI, and IJI, the Index Storie shows that areas of moderate landslide-prone areas dominate the study area and have specific characteristics that trigger the landslides. A combination of landscape metrics and Index Storie show that the relationship between landscape patterns and landslide-prone areas can be one of the priorities determining tools used for monitoring and planning land cover as an effort to mitigate landslides.

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Spatial Metrics of Deforestation in Kampar and Indragiri Hulu, Riau Province

Cited by 6 publications

References 12 publications

Profile, Level of Vulnerability and Spatial Pattern of Deforestation in Sulawesi Period of 1990 to 2018

Profile, Level of Vulnerability and Spatial Pattern of Deforestation in Sulawesi Period of 1990 to 2018

Determinan Deforestasi Negara-Negara Di Kawasan Asia Tenggara Periode 2008-2015

A spatial study of landscape patterns in landslide-prone areas at cikakak sub-district, west java

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