Land use/land cover prediction based on land change modeler approach

Landscape transformations in rapidly urbanizing Guangdong, Hong Kong, and Macao (GHKM) regions of South China represent the most complex and dynamic processes altering the local ecology and environment. In this study, Land Change Modeler (LCM) is applied to land use land cover (LULC) maps for the years 2005, 2010, and 2017, derived from Landsat images, with the aim of understanding land use land cover change patterns during 2005–2017 and, further, to predict the future scenario of the years 2024 and 2031. Furthermore, the changes in spatial structural patterns are quantified and analyzed using selected landscape morphological metrics. The results show that the urban area has increased at an annual rate of 4.72% during 2005–2017 and will continue to rise from 10.31% (20,228.95 km2) in 2017 to 16.30% (31,994.55 km2) in 2031. This increase in urban area will encroach further into farmland and fishponds. However, forest cover will continue to increase from 45.02% (88,391.98 km2) in 2017 to 46.88% (92,049.62 km2) in 2031. This implies a decrease in the mean Euclidian nearest neighbor distance (ENN_MN) of forest patches (from 217.57 m to 206.46 m) and urban clusters (from 285.55 m to 245.06 m) during 2017–2031, indicating an accelerated landscape transformation if the current patterns of the change continues over the next decade. Thus, knowledge of the current and predicted LULC changes will help policy and decision makers to reconsider and develop new policies for the sustainable development and protection of natural resources.

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Spatio-temporal analysis of land use/land cover dynamics in Sokoto Metropolis using multi-temporal satellite data and Land Change Modeller

Indonesian Journal of Geography ◽

10.22146/ijg.46615 ◽

2020 ◽

Vol 52 (3) ◽

pp. 306

Author(s):

Murtala Dangulla ◽

Latifah Abd Manaf ◽

Firuz Ramli Mohammad

Keyword(s):

Land Use ◽

Land Cover ◽

Open Space ◽

Urban Expansion ◽

Land Use Land Cover ◽

Land Change ◽

Landsat Images ◽

Green Area ◽

Rate Of Increase ◽

Green Areas

Urbanization is currently one of the most pressing environmental issues which cuts across all countries at unprecedented rates and intensities, with far reaching consequences on ecosystems, biodiversity and human wellbeing. This paper assessed urban expansion and land use/land cover changes in Sokoto metropolis, North-western Nigeria using Remote Sensing and GIS. Landsat images of 1990, 1999 and 2015 were processed for LULC classification and change detection using the Maximum Likelihood Classification, Post Classification Comparison techniques and the Land Change Modeler. The classification revealed five broad land cover classes which include Built-up Area, Farmland, Green Area, Open Space and Wetland/Water. The Built-up and Green areas continuously increased while Farmland and Open space decreased throughout the study period. The metropolis expanded radially at a faster rate between 1999 and 2015 with the highest rate of increase (1890.5ha per annum) recorded in the Built-up Area. This implies a doubling time of approximately 30 years at the expense of Farmland and Open space which may be completely exhausted in 40 and 29 years respectively. Infrastructural provision should thus align with the rate and direction of growth and where the Green Area is converted, replacement should be made to ensure continued supply and stability of the numerous ecosystem services green areas provide.

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Land use/land cover change and statistical modelling of cultivated land change drivers in Nigeria

Regional Environmental Change ◽

10.1007/s10113-017-1186-5 ◽

2017 ◽

Vol 18 (1) ◽

pp. 247-259 ◽

Cited By ~ 25

Author(s):

Aisha Olushola Arowolo ◽

Xiangzheng Deng

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Statistical Modelling ◽

Land Use Land Cover ◽

Cultivated Land ◽

Land Change

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Análise espaço-temporal das mudanças no uso e cobertura do solo no município de São Thomé das Letras / Spatio-temporal land use land and cover changes analysis in the São Thomé das Letras municipality

Caderno de Geografia ◽

10.5752/p.2318-2962.2016v26n45p79 ◽

2015 ◽

Vol 26 (45) ◽

pp. 79

Author(s):

Nayara Lage Silva ◽

Bráulio Magalhães Fonseca

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Temporal Analysis ◽

Minas Gerais ◽

Time Range ◽

Land Change ◽

Land Change Modeler ◽

Rupestrian Fields ◽

Multi Temporal

O mapeamento do uso e cobertura do solo por meio da utilização de dados de sensoriamento remoto e técnicas de processamento digital de imagens tem se difundindo globalmente por permitir uma análise espacial e dinâmica das tipologias de uso e cobertura. A mineração é uma das atividades transformadoras do meio que mais causa impactos aos ambientes naturais, mesmo que de maneira concentrada, devido ao fator de rigidez locacional da atividade. É uma atividade que demanda controle ambiental em todo processo para reduzir os impactos negativos e garantir o equilíbrio dos processos ambientais. Neste contexto o trabalho objetivou: 1 - realizar uma análise multitemporal da cobertura do solo no município de São Thomé das Letras, no estado de Minas Gerais; 2 - quantificar e espacializar as alterações no período determinado entre 1984 a 2011. Buscou-se visualizar o comportamento da atividade de mineração desde seu início até os dias atuais, e consequentemente, observar a dinamicidade das mudanças ocorridas na cobertura do solo das outras classes mapeadas. Para o mapeamento do uso e cobertura do solo foi utilizado o programa SPRING/INPE e para a análise temporal/espacial de mudanças utilizou-se o modelo Land Change Modeler acoplado ao programa IDRISI. A partir da análise dos resultados foi possível quantificar e espacializar o avanço da mineração sob o campo rupestre/afloramento rochoso; a perda substancial da vegetação densa no intervalo do período analisado; o crescimento exponencial da ocupação urbana; e o surgimento da atividade reflorestamento.Palavras-chave: Análise multitemporal. Uso e Cobertura do Solo. Mineração. Sensoriamento Remoto. AbstractThe land use and land cover mapping using remote sensing data and techniques of digital image processing has been widely used by enabling a dynamic spatial analysis of land use and land cover types. Mining is a human activity that transforms the landscape and is one of the most impactful for natural environments, even in a concentrated way, due to locational rigidity factor of activity. It is an activity that requires environmental control throughout the process to reduce the negative impacts and ensure a balance of environmental processes. In that context the study aimed to: 1 - conduct a multi-temporal analysis of land use and land cover in São Thomé das Letras municipality, in Minas Gerais State, Brazil; 2- quantify and map changes from 1984 to 2011 in the area studied. We attempted to visualize the behavior of mining activity from its inception to the present day, and therefore observe the dynamics of change in land use and land cover of other mapped classes. To map land use and land cover was used SPRING/INPE software and to analyze the changes used the Land Change Modeler model, coupled to the IDRISI software. From the analysis of the results was possible to quantify and spatialize the advancement of mining under the outcrop and Rupestrian Fields; occurred substantial loss of dense vegetation in the analyzed time range; the exponential growth of urban occupation; and the emergence of reforestation activity. Keywords: Multi-temporal analysis. Land Use and Land Cover. Mining. Remote sensing.

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Land change in the central Albertine rift: Insights from analysis and mapping of land use-land cover change in north-western Rwanda

Applied Geography ◽

10.1016/j.apgeog.2017.07.016 ◽

2017 ◽

Vol 87 ◽

pp. 127-138 ◽

Cited By ~ 15

Author(s):

Felicia O. Akinyemi

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Land Use Land Cover ◽

Land Change ◽

Albertine Rift ◽

North Western

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Assessing Land Use/Land Cover Dynamic and Its Impact in Benin Republic Using Land Change Model and CCI-LC Products

Earth Systems and Environment ◽

10.1007/s41748-018-0083-5 ◽

2018 ◽

Vol 3 (1) ◽

pp. 127-137 ◽

Cited By ~ 5

Author(s):

Meminvègni Landry Gildas Guidigan ◽

Charles L. Sanou ◽

Dakéga Saberma Ragatoa ◽

Cham O. Fafa ◽

Varun Narayan Mishra

Keyword(s):

Land Use ◽

Land Cover ◽

Change Model ◽

Land Use Land Cover ◽

Land Change ◽

Benin Republic

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Land use/land cover change evaluation using land change modeller: A comparative analysis between two main cities in Sierra Leone

Remote Sensing Applications Society and Environment ◽

10.1016/j.rsase.2019.100262 ◽

2019 ◽

Vol 16 ◽

pp. 100262

Author(s):

Musa Tarawally ◽

Xu Wenbo ◽

Hou Weiming ◽

Terence Darlington Mushore ◽

Matthew Biniyam Kursah

Keyword(s):

Land Use ◽

Comparative Analysis ◽

Land Cover ◽

Sierra Leone ◽

Land Cover Change ◽

Land Use Land Cover ◽

Land Change

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Vegetation Trends, Drought Severity and Land Use-Land Cover Change during the Growing Season in Semi-Arid Contexts

Remote Sensing ◽

10.3390/rs13050836 ◽

2021 ◽

Vol 13 (5) ◽

pp. 836

Author(s):

Felicia O. Akinyemi

Keyword(s):

Land Use ◽

Time Series ◽

Land Cover ◽

Growing Season ◽

Drought Severity ◽

Land Use Land Cover ◽

Land Change ◽

Vegetation Productivity ◽

Growing Seasons ◽

Semi Arid

Drought severity and impact assessments are necessary to effectively monitor droughts in semi-arid contexts. However, little is known about the influence land use-land cover (LULC) has—in terms of the differences in annual sizes and configurations—on drought effects. Coupling remote sensing and Geographic Information System techniques, drought evolution was assessed and mapped. During the growing season, drought severity and the effects on LULC were examined and whether these differed between areas of land change and persistence. This study used areas of economic importance to Botswana as case studies. Vegetation Condition Index, derived from Normalised Difference Vegetation Index time series for the growing seasons (2000–2018 in comparison to 2020–2021), was used to assess droughts for 17 constituencies (Botswana’s fourth administrative level) in the Central District of Botswana. Further analyses by LULC types and land change highlighted the vulnerability of both human and natural systems to drought. Identified drought periods in the time series correspond to declared drought years by the Botswana government. Drought severity (extreme, severe, moderate and mild) and the percentage of land areas affected varied in both space and time. The growing seasons of 2002–2003, 2003–2004 and 2015–2016 were the most drought-stricken in the entire time series, coinciding with the El Niño southern oscillation (ENSO). The lower-than-normal vegetation productivity during these growing seasons was evident from the analysis. With the above-normal vegetation productivity in the ongoing season (2020–2021), the results suggest the reversal of the negative vegetation trends observed in the preceding growing seasons. However, the extent of this reversal cannot be confidently ascertained with the season still ongoing. Relating drought severity and intensities to LULC and change in selected drought years revealed that most lands affected by extreme and severe drought (in descending order) were in tree-covered areas (forests and woodlands), grassland/rangelands and croplands. These LULC types were the most affected as extreme drought intersected vegetation productivity decline. The most impacted constituencies according to drought severity and the number of drought events were Mahalapye west (eight), Mahalapye east (seven) and Boteti west (seven). Other constituencies experienced between six and two drought events of varying durations throughout the time series. Since not all constituencies were affected similarly during declared droughts, studies such as this contribute to devising appropriate context-specific responses aimed at minimising drought impacts on social-ecological systems. The methodology utilised can apply to other drylands where climatic and socioeconomic contexts are similar to those of Botswana.

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