scholarly journals Commodity flow estimation models incorporating land use characteristics and economic factors

2011 ◽  
Author(s):  
T. G. Jin ◽  
M. Saito ◽  
D. L. Eggett
Keyword(s):  
Land Use ◽  
Economic Factors ◽  
Commodity Flow ◽  
Flow Estimation ◽  
Estimation Models

Implication of Socio-economic Factors on Land Use and Forest Cover Changes in and Around Magamba Nature Reserve in Tanzania

2019 ◽  
Vol 5 (1) ◽  
pp. 108-117
Author(s):  
Solomon Jeremiah Sembosi
Keyword(s):  
Land Use ◽  
Forest Cover ◽  
Nature Reserve ◽  
Agricultural Land ◽  
Population Pressure ◽  
Economic Factors ◽  
Rural Settlements ◽  
Mountainous Regions ◽  
Use Of Resources ◽  
Socio Economic Factors

Rural settlements in mountainous regions are a typical process that occurs in many places around the world and have a number of implications on the landscape. Among them is a threat it possesses to the conservation and management of Afromontane ecosystems. This study assessed the socio-economic factors that drive the changes in land use and forest cover and the extent of land use and vegetation cover in and around Magamba Nature Reserve. Focus group discussion, direct field observation and household survey were used to acquire socio-economic information that impacts land use and forest cover. Through the use of Remote Sensing and GIS methods Landsat satellite images of 1995, 2008 and 2015 were employed to identify the extent of the changes in land use and forest cover. The perceived factors for the changes include education level, unemployment, landless/limited, landholding, population pressure, expansion of built-up areas and agricultural land at the expense of other land covers. This study revealed the transformation of natural forest and associated vegetation from one form to another. There was a decrease in natural vegetation from 61.06% in 1995 to 26.02% in 2015 and increase in built-up areas by 6.69% and agricultural areas by 4.70%. This study recommends conservation monitoring and strong law enforcement relating to natural resources so as to promote sustainable use of resources to rescue the diminishing ecosystem services.

scholarly journals Landscape pattern and economic factors’ effect on prediction accuracy of cellular automata-Markov chain model on county scale

2020 ◽  
Vol 12 (1) ◽  
pp. 626-636
Author(s):  
Wang Song ◽  
Zhao Yunlin ◽  
Xu Zhenggang ◽  
Yang Guiyan ◽  
Huang Tian ◽  
...  
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Markov Model ◽  
Prediction Accuracy ◽  
Driving Mechanism ◽  
Economic Factors ◽  
Chain Model ◽  
The Impact ◽  
County Scale

AbstractUnderstanding and modeling of land use change is of great significance to environmental protection and land use planning. The cellular automata-Markov chain (CA-Markov) model is a powerful tool to predict the change of land use, and the prediction accuracy is limited by many factors. To explore the impact of land use and socio-economic factors on the prediction of CA-Markov model on county scale, this paper uses the CA-Markov model to simulate the land use of Anren County in 2016, based on the land use of 1996 and 2006. Then, the correlation between the land use, socio-economic data and the prediction accuracy was analyzed. The results show that Shannon’s evenness index and population density having an important impact on the accuracy of model predictions, negatively correlate with kappa coefficient. The research not only provides a reference for correct use of the model but also helps us to understand the driving mechanism of landscape changes.

scholarly journals Effects of the German Renewable Energy Sources Act and environmental, social and economic factors on biogas plant adoption and agricultural land use change

2020 ◽  
Author(s):  
Xueqing Yang ◽  
Yang Liu ◽  
Daniela Thrän ◽  
Alberto Bezama ◽  
Mei Wang
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Biogas Production ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Small Scale ◽  
Agricultural Land Use ◽  
Economic Factors ◽  
Silage Maize ◽  
Biogas Plants

Abstract Background: The German energy transition strategy calls for a reform of the German energy sector. As a result, the Germany Renewable Energy Sources Act (EEG) was passed in 2000 and is widely regarded as successful legislation for promoting bioenergy development. More than 1,000 biogas plants were constructed in Central Germany (CG) between 2000 and 2014. Despite this, few studies have been conducted for this period that systematically investigate how environmental, social and economic factors, as well as various EEG amendments have impacted biogas production and what the environmental consequence of biogas production development in CG have been. Methods: The impacts of environmental, social and economic factors and different EEG amendments on biogas production decisions in CG were quantified using multivariate linear regression model and the event study econometric technique. A GIS-based spatial analysis was also conducted to provide insight into the changes to agricultural land use that resulted from the development of biogas plants during the EEG period. Results: The main finding was that the income diversification effect resulting from biogas production was the most important factor in a farmer’s decision to adopt biogas production. In addition, all of the EEG amendments had a significant influence on the adoption of biogas production, however EEG III and IV, which tried to promote small-scale plants, were unable to reduce the average size of the plants constructed in these two amendment periods. From a landscape perspective, there was a striking increase in the cultivation of silage maize in CG from 2000 to 2014. Silage maize was intensively cultivated in regions with a high installed biogas plant capacity. Since the first EEG amendment, permanent grassland area slightly increased while arable land area declined in CG. Conclusions: The adoption of biogas production in CG was strongly driven by economic incentives for the farmers, more precisely, by the incentive to diversify their income sources. In addition to increase the subsidy, future EEG amendments should find new measures to encourage the adoption of small-scale biogas plants, which had been unsuccessful in EEG amendments III and IV.

scholarly journals Study of Changes in Geospatial Based Land Use in Ambarawa District, Pringsewu Regency

2021 ◽  
Vol 8 (2) ◽  
pp. 94
Author(s):  
Dedy Miswar ◽  
Listumbinang Halengkara ◽  
I Gede Sugiyanta ◽  
Ahmad Sahid Al Azhari
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Data ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Image Interpretation ◽  
Economic Factors ◽  
The West ◽  
Overlay Technique

Ambarawa District has allegedly experienced many changes in land use. Changes in land use in Ambarawa District are dominated by changes in agricultural land to non-agricultural land. This is because the land in Ambarawa District is influenced by the role of its inhabitatns in utilizing the land so that it has an impact on land use change. This study aims to determine changes in land use, the factors that influence land use changes, the direction of development and what types of use changes are most dominant in Ambarawa District, Pringsewu Regency. The method used in this research is survei and image interpretation by looking at changes in land use in each area. The population used in this study were all villages in Ambarawa District, totaling 8 villages which were suspected of experiencing changes in land use. Collecting data in this study is a descriptive geospatial approach through the overlay technique of land use spatial data. The results showed that there was a change in land use in Ambarawa District year 2014-2019 covering an area of 2.195,8 ha (70,83%), which was caused by social and economic factors, namely the increase in population and workers and the direction of land use changes to the west and east.

Traffic analysis zone level crash estimation models based on land use characteristics

2013 ◽  
Vol 50 ◽  
pp. 678-687 ◽  
Author(s):  
Srinivas S. Pulugurtha ◽  
Venkata Ramana Duddu ◽  
Yashaswi Kotagiri
Keyword(s):  
Land Use ◽  
Traffic Analysis ◽  
Estimation Models
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