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

The land use and land cover change phenomenon has become one concern over many regions worldwide, including Indonesia. Land use and land cover change due to human activities triggered alteration terrestrial ecosystems and its services including climate control functions. The study aimed to analyze land use and land cover change in Banyuwangi regency during 1995 – 2019. Four satellite images from acquisition year 1995, 2000, 2014 and 2019 were used to analyze the spatial and temporal changes along with field observations. The classification processes of land use and land cover included determination of training areas, supervised classification, and accuracy assessment. There are 12 land use and land cover based on supervised classification as follow primary forest, secondary forest, plantation forest, mangrove forest, plantation, settlement, cropland, paddy field, shrubs, water, fishpond and barren land. The result showed during observation period of 1995 until 2019 land use and land cover which tends to decrease are secondary forest, mangrove forest, and rice fields. On the other hand, the area of settlements, shrubs and fishponds were increased significantly.

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Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo

Sustainability ◽

10.3390/su13126898 ◽

2021 ◽

Vol 13 (12) ◽

pp. 6898

Author(s):

Opelele Omeno Michel ◽

Yu Ying ◽

Fan Wenyi ◽

Chen Chen ◽

Kachaka Sudi Kaiko

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Multilayer Perceptron ◽

Secondary Forest ◽

Biosphere Reserve ◽

Primary Forest ◽

Fallow Land ◽

Land Use Land Cover ◽

Landscape Metric

Villages within the Luki Biosphere Reserve and the surrounding cities have undergone rapid demographic growth and urbanization that have impacted the reserve’s natural landscape. However, no study has focused on the spatiotemporal analysis of its land use/land cover. The present research aims at providing a comprehensive analysis of land use/land cover change in the Luki Biosphere Reserve from the year 1987 to 2020, and to predict its future change for the year 2038. Landsat images were classified in order to provide land use/land cover maps for the years 1987, 2002, 2017 and 2020. Based on these maps, change detection, gradient direction, and landscape metric analyses were performed. In addition, land use/land cover change prediction was carried out using the Multilayer Perceptron Markov model. The results revealed significant land use/land cover changes in the Luki Biosphere Reserve during the study period. Indeed, tremendous changes in the primary forest, which lost around 17.8% of its total area, were noted. Other classes, notably savannah, secondary forest, built-up area, fallow land and fields had gained 79.35, 1150.36, 67.63, 3852.12 hectares, respectively. Based on the landscape metric analysis, it was revealed that built-up areas and fallow land and fields experienced an aggregation trend, while other classes showed disaggregation and fragmentation trends. Analysis further revealed that village expansion has significantly affected the process of land use/land cover change in the Luki Biosphere Reserve. However, the prediction results revealed that the primary forest will continue to increase while built-up area, fallow land and fields will follow a trend similar to a previous one. As for secondary forest and savannah, the forecast revealed a decrease of the extent during the period extending from 2020 to 2038. The present findings will benefit the decision makers, particularly in the sustainable natural resources management of the Luki Biosphere Reserve.

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Spatial near future modeling of land use and land cover changes in the temperate forests of Mexico

PeerJ ◽

10.7717/peerj.6617 ◽

2019 ◽

Vol 7 ◽

pp. e6617 ◽

Cited By ~ 1

Author(s):

Jesús A. Prieto-Amparán ◽

Federico Villarreal-Guerrero ◽

Martin Martínez-Salvador ◽

Carlos Manjarrez-Domínguez ◽

Griselda Vázquez-Quintero ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Temperate Forests ◽

Secondary Forest ◽

Primary Forest ◽

Support Vector ◽

Land Cover Changes ◽

Land Use Land Cover ◽

Kappa Index

The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

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Spatial near future modeling of land use and land cover changes in the temperate forests of Mexico

10.7287/peerj.preprints.27542 ◽

2019 ◽

Author(s):

Jesús A Prieto-Amparán ◽

Federico Villarreal-Guerrero ◽

Martin Martínez-Salvador ◽

Carlos Manjarrez-Domínguez ◽

Griselda Vázquez-Quintero ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Temperate Forests ◽

Secondary Forest ◽

Primary Forest ◽

Support Vector ◽

Land Cover Changes ◽

Land Use Land Cover ◽

Kappa Index

The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and, on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

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Land Use - Land Cover Change Analysis of Karur Town - A GIS Approach

International Journal of Scientific Research in Science and Technology ◽

10.32628/ijsrst218373 ◽

2021 ◽

pp. 360-366

Author(s):

S. Ravichandran ◽

I. K. Manonmani

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Supervised Classification ◽

Agricultural Land ◽

Geographical Information ◽

Land Use Land Cover ◽

Change Analysis ◽

Barren Land

Land use / Land cover change is one of the most sensitive factors that show the interactions between human activities and the ecological environment. This research study demonstrated the importance of geographical information system and remote sensing technologies in spatial temporal data analysis and also this paper shows a GIS and remote sensing approach for modeling of spatial - temporal pattern of land use and land cover change (LULC) in a fastest growing towns / industrial region of Karur town. QGIS 3.10 version and Arc GIS 10.2 software platforms were utilized in the study for Image processing, LULC mapping and change detection analysis. USGS Earth explorer Landsat series satellite imageries were acquired and LULC maps were prepared for the years 1991, 2000, 2010 and 2020. Supervised classification with maximum likelihood algorithm is adopted for LULC classification. The LULC classes are Built upland, Agricultural land, Barren land and Water body based on NRSA Level – I supervised classification. The Built-up area has drastically increased from 1991 to 2020. It has increased more than double. It was 17 percent in 1991 and increased to 40 percent in 2020. This clearly shows Karur town is the becoming more and more urbanized.

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Spatial near future modeling of land use and land cover changes in the temperate forests of Mexico

10.7287/peerj.preprints.27542v1 ◽

2019 ◽

Author(s):

Jesús A Prieto-Amparán ◽

Federico Villarreal-Guerrero ◽

Martin Martínez-Salvador ◽

Carlos Manjarrez-Domínguez ◽

Griselda Vázquez-Quintero ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Temperate Forests ◽

Secondary Forest ◽

Primary Forest ◽

Support Vector ◽

Land Cover Changes ◽

Land Use Land Cover ◽

Kappa Index

The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and, on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

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Long-Term Land-Use/Land-Cover Change Increased the Landscape Heterogeneity of a Fragmented Temperate Forest in Mexico

Forests ◽

10.3390/f12081099 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1099

Author(s):

Claudia K. Legarreta-Miranda ◽

Jesús A. Prieto-Amparán ◽

Federico Villarreal-Guerrero ◽

Carlos R. Morales-Nieto ◽

Alfredo Pinedo-Alvarez

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Secondary Forest ◽

Edge Density ◽

Primary Forest ◽

Support Vector ◽

Land Use Land Cover ◽

Machine Method ◽

Northern Mexico

The temperate forests of northern Mexico possess a great diversity of unique and endemic species, with the greatest associations of pine-oak in the planet occurring within them. However, the ecosystems in this region had experienced an accelerated fragmentation process in the past decades. This study described and quantified the landscape fragmentation level of a degraded watershed located in this region. For that, data from the Landsat series from 1990, 2005 and 2017, classified with the Support Vector Machine method, were used. The landscape structure was analyzed based on six metrics applied at both, the landscape and class levels. Results show considerable gains in surface area for the land use land cover change (LULC) of secondary forest while the Primary Forest (PF) lost 18.1% of its area during 1990–2017. The PF increased its number of patches from 7075 to 12,318, increased its patch density (PD) from 53.51 to 58.46 # of patches/100 ha, and reduced its average patch size from 39.21 to 15.05 ha. This made the PF the most fragmented LULC from the 5 LULCs evaluated. In this study, strong fluctuations in edge density and PD were registered, which indicates the forests of northern Mexico have experienced a reduction in their productivity and have been subjected to a continuous degradation process due to disturbances such as fires, clandestine and non-properly controlled logging, among others.

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ANALISIS PENUTUPAN LAHAN DAN PERUBAHANNYA MENJADI KELAPA SAWIT DI INDONESIA (Studi Kasus di 5 Pulau Besar di Indonesia periode 1990 s.d 2010)

Jurnal Green Growth dan Manajemen Lingkungan ◽

10.21009/jgg.032.02 ◽

2013 ◽

Vol 3 (2) ◽

pp. 10

Author(s):

Petrus Gunarso ◽

Manjela Eko Hartoyo ◽

Yuli Nugroho

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Oil Palm ◽

Visual Analysis ◽

Secondary Forest ◽

Quantitative Information ◽

Primary Forest ◽

Rubber Plantation ◽

Oil Palm Plantation

Indonesia is one of the largest crude palm oil (CPO) producing countries in the world and at the same time have experienced high levels of deforestation. The link between deforestation and expansion of oil palm plantation has been a source of controversy, which has been exacerbated by the lack of objective quantitative information on the nature of land use and land cover change and the expansion of oil palm plantations. This report provides an independent analysis of land use and land cover change for a broad range of land cover classes for five main Islands in Indonesia, namely Sumatra, Java, Kalimantan, Sulawesi, and Papua based on Landsat TM satellite images. Visual analysis and on screen digitizing methods were employed to create a nation-wide land cover classification that spans two decades (1990 to 2010). Three temporal epochs (1990 to 2000, 2000 to 2005 and 2005 to 2010) correspond to a period of time with significant changes in land cover and land uses in Indonesia. Expansion of oil palm plantation in Indonesia shows that most of the expansion exists as a follow on transition from disturbed forest (secondary forest), agricultural lands (mainly rubber plantation), and low biomass land cover types, including shrub land and grassland than formerly reported to be majority from undisturbed forest (primary forest).

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Changes in Land Cover Analysis in The Gulf Coast Kendari Using High Resolution Satellite Image (Period: 2003-2009)

Forum Geografi ◽

10.23917/forgeo.v27i2.2375 ◽

2013 ◽

Vol 27 (2) ◽

pp. 179 ◽

Cited By ~ 1

Author(s):

Laode Muh. Golok Jaya

Keyword(s):

Land Use ◽

Land Use Change ◽

Land Cover ◽

Public Space ◽

Land Cover Change ◽

Satellite Imagery ◽

Gulf Coast ◽

Secondary Forest ◽

Satellite Image ◽

Primary Forest

This research was aimed to indentify land cover change in coastal area of Kendari Bay in period 2003 to 2009. The satellite imagery data (Ikonos and Quick Bird) collected in 2003 and 2009 were used in this research to obtain the land cover change. The method used in this research was comparing the classification of satellite imagery. Field survey was conducted using handheld GPS for ground truth. The result of this research showed us the land use change in period 2003-2009. Mangrove vegetation decreased 56.57 Ha and the fishpond also decreased 205.5 Ha. The primary forest decreased into 3.28 Ha in year 2009. The secondary forest also decreases 124.84 Ha. In the same time the urban area increased from 382.37 Ha in year 2003 to 674.37 Ha in 2009. The land use change also occured for the public space which increased from 6.49 Ha in 2003 to 18.46 Ha in 2009 or increased 11,97 Ha.

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Farmers’ Income and Land Cover Change at Lore Lindu National Park in Indonesia

Modern Applied Science ◽

10.5539/mas.v12n12p41 ◽

2018 ◽

Vol 12 (12) ◽

pp. 41

Author(s):

Rustam Abdul Rauf ◽

Adam Malik ◽

Isrun . ◽

Golar . ◽

Alimudin Laapo ◽

...

Keyword(s):

Land Cover ◽

Land Cover Change ◽

National Park ◽

Agricultural Land ◽

Secondary Forest ◽

Forest Area ◽

Farm Income ◽

Primary Forest ◽

Secondary Forests ◽

Lore Lindu National Park

Lore Lindu National Park in Central Sulawesi is one of the protected areas. Although it is protected, many of its areas are experiencing pressure and disruption by human activities. The purpose of this research was to know the relationship between farmers’ income and land cover change at Lore Lindu National Park. The research method was a participatory survey. Variables of incomes were sourced from farming and outside farming (forests). Data of land cover change were obtained using imagery in 2012, 2014 and 2016. The result of research is the average of farming income of IDR 1,387,077 (cocoa farming) and non-farm income of IDR 854,819 (forest honey, resin). In the last five years (2012-2016), the primary forest area decreased by 902.37 ha, while the secondary forest has shown an increase of 2,233.61 ha. The trend of land cover change was drastic, with change in the secondary dry land forest area from 6.9 ha (in 2012) to 2,240.5 ha (in 2016). The increased secondary forest area and the secondary forests have been converted into agricultural land and mixed gardens.

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Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

Remote Sensing ◽

10.3390/rs13163337 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3337

Author(s):

Shaker Ul Din ◽

Hugo Wai Leung Mak

Keyword(s):

Land Use ◽

Support Vector Machine ◽

Land Cover ◽

Land Cover Change ◽

Agricultural Land ◽

Urban Expansion ◽

Support Vector ◽

Land Use Land Cover ◽

Landsat Images ◽

Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

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