Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Land-cover/land-use change dynamics modeling based on land change modeler
https://orcid.org/0000-0002-5941-6022
Abstract Forest cover in the Rherhaya watershed of the Moroccan High Atlas region, characterized by its critical natural conditions, faces strong human pressure, leading to the fragmentation of the landscape. To improve natural capital management, to support stakeholders in their decision-making process and to sustain ecosystem services provided by the watershed, this work aims at developing a long-term vision of the local landscape. Land-use/land-cover change dynamics have been analyzed at 1984, 2000 and 2017 timestamps, and prospective modeling based on the Land Change Modeler (LCM) model has been used to develop a future vision of forest landscapes. LCM modeling approaches rely on two types of input maps: (1) maps of land cover at times before the calibration period and (2) maps of explanatory variables (that precludes land-use or land-cover change over time such as slope, altitude and accessibility: distance to roads or human settlement). The model is validated through the juxtaposition of the 2017 observed map and the predicted map for the same year using the trained model. The result shows an overall accuracy of 64.58 per cent. Based on the hypothesis of human pressures intensification in the future, the forecasted land-cover map by 2040 has been derived as a result of the explanatory variables. This prospective modeling, therefore, predicts by 2040 an expansion of buildings that will be made at the expense of bare soil surfaces. Indeed, this expansion will be linked to population growth stemming mainly due to a strong migration of populations from neighboring regions in search of better living conditions.
Land-cover/land-use change dynamics modeling based on land change modeler
https://orcid.org/0000-0002-5941-6022
Abstract Forest cover in the Rherhaya watershed of the Moroccan High Atlas region, characterized by its critical natural conditions, faces strong human pressure, leading to the fragmentation of the landscape. To improve natural capital management, to support stakeholders in their decision-making process and to sustain ecosystem services provided by the watershed, this work aims at developing a long-term vision of the local landscape. Land-use/land-cover change dynamics have been analyzed at 1984, 2000 and 2017 timestamps, and prospective modeling based on the Land Change Modeler (LCM) model has been used to develop a future vision of forest landscapes. LCM modeling approaches rely on two types of input maps: (1) maps of land cover at times before the calibration period and (2) maps of explanatory variables (that precludes land-use or land-cover change over time such as slope, altitude and accessibility: distance to roads or human settlement). The model is validated through the juxtaposition of the 2017 observed map and the predicted map for the same year using the trained model. The result shows an overall accuracy of 64.58 per cent. Based on the hypothesis of human pressures intensification in the future, the forecasted land-cover map by 2040 has been derived as a result of the explanatory variables. This prospective modeling, therefore, predicts by 2040 an expansion of buildings that will be made at the expense of bare soil surfaces. Indeed, this expansion will be linked to population growth stemming mainly due to a strong migration of populations from neighboring regions in search of better living conditions.
Land-cover/land-use change dynamics modeling based on land change modeler
https://orcid.org/0000-0002-5941-6022
Abstract Forest cover in the Rherhaya watershed of the Moroccan High Atlas region, characterized by its critical natural conditions, faces strong human pressure, leading to the fragmentation of the landscape. To improve natural capital management, to support stakeholders in their decision-making process and to sustain ecosystem services provided by the watershed, this work aims at developing a long-term vision of the local landscape. Land-use/land-cover change dynamics have been analyzed at 1984, 2000 and 2017 timestamps, and prospective modeling based on the Land Change Modeler (LCM) model has been used to develop a future vision of forest landscapes. LCM modeling approaches rely on two types of input maps: (1) maps of land cover at times before the calibration period and (2) maps of explanatory variables (that precludes land-use or land-cover change over time such as slope, altitude and accessibility: distance to roads or human settlement). The model is validated through the juxtaposition of the 2017 observed map and the predicted map for the same year using the trained model. The result shows an overall accuracy of 64.58 per cent. Based on the hypothesis of human pressures intensification in the future, the forecasted land-cover map by 2040 has been derived as a result of the explanatory variables. This prospective modeling, therefore, predicts by 2040 an expansion of buildings that will be made at the expense of bare soil surfaces. Indeed, this expansion will be linked to population growth stemming mainly due to a strong migration of populations from neighboring regions in search of better living conditions.
Land-cover/land-use change dynamics modeling based on land change modeler
Qacami, Meryem (Autor:in) / Khattabi, Abdellatif (Autor:in) / Lahssini, Said (Autor:in) / Rifai, Nabil (Autor:in) / Meliho, Modeste (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
BKL:
83.64$jRegionalwirtschaft
/
74.12
Stadtgeographie, Siedlungsgeographie
/
38.00$jGeowissenschaften: Allgemeines
/
38.00
Geowissenschaften: Allgemeines
/
83.64
Regionalwirtschaft
/
74.12$jStadtgeographie$jSiedlungsgeographie
RVK:
ELIB39
/
ELIB18
/
ELIB45
Lokalklassifikation FBW:
oek 4450
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