scholarly journals 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

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.

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

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6617 ◽  
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.

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

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.

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

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.

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

Forests ◽  
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.

scholarly journals Analysis of the Impact of Land-Use/Land-Cover Change on Land-Surface Temperature in the Villages Within the Luki Biosphere Reserve

2021 ◽  
Vol 13 (20) ◽  
pp. 11242
Author(s):  
Michel Opelele Omeno ◽  
Ying Yu ◽  
Wenyi Fan ◽  
Tolerant Lubalega ◽  
Chen Chen ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Biosphere Reserve ◽  
Fallow Land ◽  
Land Use Land Cover ◽  
The Impact

Major land-use/land-cover change due to rapid urbanization has been known to increase the land-surface temperature around the world. Consequently, examining the variation of land-surface temperatures and mitigating the related impacts remain a challenge. The present study employed remote-sensing and geoinformational techniques to examine land-use/land-cover change and its effects on land-surface temperature variations in the villages within the Luki Biosphere Reserve, Democratic Republic of Congo. Land-use/land-cover change for the year 2038 was predicted by using the CA–Markov chain. Additionally, focus-group discussions (FGDs) with local communities from different villages were applied to better understand the impact of climate change, considering the increase of land-surface temperature. The results revealed major changes in land-use/land-cover in the four villages from 2002 to 2020, principally the expansion of fallow land and built-up areas, as well as the decline in forest land, and the complex of young secondary and degraded forest. There was an increase in mean LST values over all villages between 2002 and 2020. The highest value was observed in Tsumba kituti (25.12 °C), followed by Kisavu (24.87 °C), Kibuya (23.31 °C) and Kiobo (21.82 °C). Between 2002 and 2020, the mean LST of built-up areas increased from 23.18 to 25.12 °C, 21.55 to 23.38 °C, 21.4 to 25.78 °C and 22.31 to 25.62 °C in Tsumba kituti, Kiobo, Kisavu and Kibuya, respectively. Moreover, the mean LST of fallow land increased from 20.8 to 23.2 °C, 21.13 to 22.12 °C, 21.89 to 23.12 °C and 20.31 to 23.47 °C in Tsumba, Kiobo, Kibuya and Kisavu, respectively. This indicates that built-up and fallow land experienced the highest land-surface temperature compared to other land-use/land-cover categories. Meanwhile, the conversion of all land-use/land-cover categories into built-up areas in all the villages resulted in the increase of the land-surface temperature. FGDs results recognize the recurrent land-use/land-cover change as the major driver of the increase in LST (86%). However, it was predicted that farmland and built-up area will still increase within all the villages, while the forest land will decline. As for the complex of secondary and degraded forest, it will decrease in Tsumba kituti, while, in Kiobo and Kisavu, it is expected to increase. Through a combination of remote-sensing and primary data, this study provides accurate information that will benefit decision-makers to implement appropriate landscape-planning techniques to mitigate the effect of the increased land-surface temperature in the villages.

scholarly journals Land use land cover change detection through geospatial analysis in an Indian Biosphere Reserve

2020 ◽  
Vol 2 ◽  
pp. 100018 ◽  
Author(s):  
Tarun Kumar Thakur ◽  
Digvesh Kumar Patel ◽  
Arvind Bijalwan ◽  
Mammohan J. Dobriyal ◽  
Anirudh Kumar ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Land Cover Change ◽  
Biosphere Reserve ◽  
Geospatial Analysis ◽  
Land Use Land Cover ◽  
Land Cover Change Detection

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

Jurnal Wasian ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 121-132
Author(s):  
Nurlita Wahyuni ◽  
◽  
Abdul Hasyim ◽  
Soemarno Soemarno
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Mangrove Forest ◽  
Supervised Classification ◽  
Secondary Forest ◽  
Primary Forest ◽  
Forest Plantation ◽  
Climate Control ◽  
Barren Land

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.

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

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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