Dynamic of the Land Use and Land Cover Change  in Banyuwangi Regency From 1995-2019

Wahyuni, Nurlita Indah; Hasyim, Abdul Wahid; Soemarno, Soemarno

doi:10.20886/jwas.v8i2.6707

Cited by 5 publications

(5 citation statements)

References 24 publications

(34 reference statements)

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“…Visual analysis is often carried out on aerial photos or other high-resolution imagery. Visual analysis can also be carried out on medium resolution image data in combination with several digital processing techniques (Kosasih, 2019, Wahyuni, 2021, Seidlova, 2021, Grishkin, and Karimov, 2021, Ramadhan and Hidayati, 2022. In general, analysis is carried out on remote sensing data in printed form, although this analysis can also be carried out on digital media.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial Mapping of Coconut Plantation in Airmadidi District, North Sulawesi Using Geographical Information System

Rotinsulu,

Margaretha,

Pakasi

2024

JoA

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Coconut (Cocos nucifera L.) known by many as the "tree of life is a leading agricultural commodity in North Sulawesi. Coconut is one of the most significant palm crops for both commercial and subsistence use worldwide. Airmadidi District has the potential for plantation land, especially coconut, which is indicated by the area of ??coconut plantation land in Airmadidi in 2021 of 3,373.13 Ha. This research aims to produce spatial mapping of coconut plantation in Airmadidi District using visual interpretation techniques; and to determine the area of ??coconut plantations in Airmadidi District. Visual interpretation method using on screen classification of satelite imagery SPOT 2022 obtained from SAS Planet. Images were digitized with a geographic information system using ArcGIS 10.8.2 software. The results of the visual interpretation show a map of the distribution of coconut plantations spread across all villages in Airmadidi District, North Minahasa Regency. The total area of coconut plantations in Airmadidi District is 3 023 Ha. Tanggari village has the largest spread of coconut plantations, namely 870,460 Ha, while Sarongsong Satu village has the smallest area, only 2.24 Ha. There was a decrease in the area of coconut plantation during the period of three year which was 305,51 Ha. The decline in the area of coconut plantations in North Sulawesi, especially in Airmadidi District, is thought to be caused by the conversion of coconut plantation land into residential or industrial areas.

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Section: Literature Reviewmentioning

confidence: 99%

Spatial Mapping of Coconut Plantation in Airmadidi District, North Sulawesi Using Geographical Information System

Rotinsulu,

Margaretha,

Pakasi

2024

JoA

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“…The migration of the spatial center of gravity can be used to characterize the pattern of spatial change in a landscape. The principle of population geography's center of gravity [53,54] is used to analyze the direction and distance of desertification land's center of gravity migration, as well as the spatial dynamic changes associated with various grades of desertification land. The coordinates of a given grade of desertification land's center of gravity in year t are calculated using the following formula [55,56]:…”

Section: Center Of Gravity Migration Model Of Desertification Landmentioning

confidence: 99%

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Yan

Wang

Zhao

et al. 2022

Water

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Monitoring the spatio-temporal dynamics of desertification is critical for desertification control. Using the Urat front flag as the study area, Landsat remote sensing images between 2010 and 2020 were selected as data sources, along with MOD17A3H as auxiliary data. Additionally, RS and GIS theories and methods were used to establish an Albedo–NDVI feature space based on the normalized difference vegetation index (NDVI) and land surface albedo. The desertification difference index (DDI) was developed to investigate the dynamic change and factors contributing to desertification in the Urat front banner. The results show that: ① the Albedo–NDVI feature space method is effective and precise at extracting and classifying desertification information, which is beneficial for quantitative analysis and monitoring of desertification; ② from 2010 to 2020, the spatial distribution of desertification degree in the Urat front banner gradually decreased from south to north; ③ throughout the study period, the area of moderate desertification land increased the most, at an annual rate of 8.2%, while the area of extremely serious desertification land decreased significantly, at an annual rate of 9.2%, indicating that desertification degree improved during the study period; ④ the transformation of desertification types in Urat former banner is mainly from very severe to moderate, from severe to undeserted, and from mild to undeserted, with respective areas of 22.5045 km2, 44.0478 km2, and 319.2160 km2. Over a 10-year period, the desertification restoration areas in the study area ranged from extremely serious desertification to moderate desertification, from serious desertification to non-desertification, and from weak desertification to non-desertification, while the desertification aggravation areas ranged mainly from serious desertification to moderate desertification; ⑤ NPP dynamic changes in vegetation demonstrated a zonal increase in distribution from west to east, and significant progress was made in desertification control. The change in desertification has accelerated significantly over the last decade. Climate change and irresponsible human activities have exacerbated desertification in the eastern part of the study area.

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“…The early detection of land cover changes and projection of land cover to assess sustainable forest management in FMU is mandatory to inform future forest management. However, previous land cover change assessments in relevant decades only measured past and current land cover change (Hussain and Karuppannan 2023;Wahyuni et al 2021). This constraint is a very important thing to discuss because by knowing future events, we can develop a risk mitigation plan.…”

Section: Introductionmentioning

confidence: 99%

Modeling Land Cover Change Using MOLUSCE in Kahayan Tengah Forest Management Unit, Kalimantan Tengah

Iskandar,

Saidah,

Kurnia

et al. 2024

J. Sylva Lestari

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A management unit-based land cover change analysis was examined in Kahayan Tengah Forest Management Unit (FMU) to understand past, present, and future land cover to assist forest management planning in Kahayan Tengah FMU. This study aims to model land cover change in 2011 and 2016, predict 2021, and simulate land cover in 2026 in Kahayan Tengah FMU. Modeling land cover prediction and simulation using MOLUSCE from the QGIS plugin. The results revealed that agricultural land experienced significant increase in total area during 2011–2016. Modeling potential land cover transitions in 2011 and 2016 with the Artificial Neural Network method showed a Kappa coefficient of 0.701 in the good category, and simulation of land cover in 2021 with the Cellular Automata method showed a Kappa coefficient of 0.672 in the good category. By 2026, the agricultural land will continue to increase while forest land tends to remain stable in its total area. This study managed to predict land cover in 2021 and simulated 2026 with good accuracy. Thus, this data and information can support forest management planning in Kahayan Tengah FMU. Keywords: forest management unit, Kahayan Tengah, land cover change, land cover prediction, MOLUSCE

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Dynamic of the Land Use and Land Cover Change in Banyuwangi Regency From 1995-2019

Cited by 5 publications

References 24 publications

Spatial Mapping of Coconut Plantation in Airmadidi District, North Sulawesi Using Geographical Information System

Spatial Mapping of Coconut Plantation in Airmadidi District, North Sulawesi Using Geographical Information System

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Modeling Land Cover Change Using MOLUSCE in Kahayan Tengah Forest Management Unit, Kalimantan Tengah

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