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Evaluating Forest and Land Rehabilitation Using Remote Sensing: A Case Study in Maros Regency

Jurnal Penelitian Kehutanan Wallacea · Vol. 14 No. 1 (2025) · pp. 35–44

DOI
10.24259/jpkwallacea.v14i1.36726
ISSN
2407-7860, 2302-299X
Published
2025-05-16
Publisher
Foresty Faculty of Hasanuddin University
Language
en

Abstract

Remote sensing technology has become crucial in vegetation monitoring, particularly for assessing vegetation density. Despite its broad application, its use in evaluating land rehabilitation efforts remains limited. The increasing extent of degraded lands has underscored the importance of effective forest and land rehabilitation activities. Traditionally, evaluating these efforts involves direct site visits to monitor plant growth annually for three years post-planting, which is time-consuming, labor-intensive, and costly. According to rehabilitation standards, a program is successful if 75% of the planted vegetation survives until the end of the third year. This study presents an efficient alternative by evaluating a rehabilitation site in Maros Regency, using remote sensing technology to monitor planting success over periods of 15 years (2007), nine years (2013), and three years (2019). The evaluation utilizes multispectral drone imagery and Normalized Difference Vegetation Index (NDVI) analysis to assess vegetation density through multi-temporal analysis across wide areas. The findings reveal that the percentage of forested areas after three, nine, and fifteen years of rehabilitation activities was 24.6%, 3.1%, and 23.5%, respectively. This research demonstrates the potential for further application of Unmanned Aerial Vehicle imagery in monitoring the success of land rehabilitation projects.

Keywords

Collaboration network of the authors

15 authors · 45 co-authorship links

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Co-authorOrganisationJoint articles
Samuel A. PaembonanAffiliation unknown2
Syamsuddin MillangAffiliation unknown2
Leny RachmawatiAffiliation unknown2
Andang Suryana SomaAffiliation unknown2
A. MujetahidAffiliation unknown2
Nasri NasriAffiliation unknown1
Abdur Rahman ArifAffiliation unknown1
Risye DwiyaniAffiliation unknown1
Lady ChaniaAffiliation unknown1
Ida Bagus Oka AgastyaAffiliation unknown1
Dian Adhetya Arif ArifAffiliation unknown1
Aulia NurfadillaAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/wallacea/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en">Evaluating Forest and Land Rehabilitation Using Remote Sensing: A Case Study in Maros Regency</dc:title>
	<dc:creator xml:lang="en">Rijal, Syamsu</dc:creator>
	<dc:creator xml:lang="en">Nursaputra, Munajat</dc:creator>
	<dc:creator xml:lang="en">A, Chairil</dc:creator>
	<dc:subject xml:lang="en">Forest Rehabilitation</dc:subject>
	<dc:subject xml:lang="en">Remote Sensing</dc:subject>
	<dc:subject xml:lang="en">Vegetation Monitoring</dc:subject>
	<dc:subject xml:lang="en">NDVI Analysis</dc:subject>
	<dc:subject xml:lang="en">Unmanned Aerial Vehicles (UAVs)</dc:subject>
	<dc:description xml:lang="en">Remote sensing technology has become crucial in vegetation monitoring, particularly for assessing vegetation density. Despite its broad application, its use in evaluating land rehabilitation efforts remains limited. The increasing extent of degraded lands has underscored the importance of effective forest and land rehabilitation activities. Traditionally, evaluating these efforts involves direct site visits to monitor plant growth annually for three years post-planting, which is time-consuming, labor-intensive, and costly. According to rehabilitation standards, a program is successful if 75% of the planted vegetation survives until the end of the third year. This study presents an efficient alternative by evaluating a rehabilitation site in Maros Regency, using remote sensing technology to monitor planting success over periods of 15 years (2007), nine years (2013), and three years (2019). The evaluation utilizes multispectral drone imagery and Normalized Difference Vegetation Index (NDVI) analysis to assess vegetation density through multi-temporal analysis across wide areas. The findings reveal that the percentage of forested areas after three, nine, and fifteen years of rehabilitation activities was 24.6%, 3.1%, and 23.5%, respectively. This research demonstrates the potential for further application of Unmanned Aerial Vehicle imagery in monitoring the success of land rehabilitation projects.</dc:description>
	<dc:publisher xml:lang="en">Foresty Faculty of Hasanuddin University</dc:publisher>
	<dc:date>2025-05-16</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/wallacea/article/view/36726</dc:identifier>
	<dc:identifier>10.24259/jpkwallacea.v14i1.36726</dc:identifier>
	<dc:source xml:lang="en">Jurnal Penelitian Kehutanan Wallacea; Vol. 14 No. 1 (2025); 35-44</dc:source>
	<dc:source>2407-7860</dc:source>
	<dc:source>2302-299X</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/wallacea/article/view/36726/12819</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Jurnal Penelitian Kehutanan Wallacea</dc:rights>
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