scholarly journals Calibration and validation of a post-forest land use dynamic model based on timed automaton using a Markov model

2011 ◽  
Vol 20 (4) ◽  
pp. 274-279
Author(s):  
Venot Ratiarson ◽  
Dominique Hervé ◽  
Cyprien R. Rakotoasimbahoaka ◽  
Jean-Pierre Müller
Keyword(s):  
Land Use ◽  
Markov Model ◽  
Dynamic Model ◽  
Forest Land ◽  
Calibration And Validation ◽  
Model Based ◽  
Timed Automaton

scholarly journals Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework

2019 ◽  
Vol 8 (10) ◽  
pp. 454 ◽  
Author(s):  
Junfeng Kang ◽  
Lei Fang ◽  
Shuang Li ◽  
Xiangrong Wang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Cellular Automata ◽  
Markov Model ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Remote Sensing Images ◽  
Mapreduce Framework ◽  
Construction Land ◽  
Model Based

The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model. In this research, we designed a parallel CA-Markov model based on the MapReduce framework. The model was divided into two main parts: A parallel Markov model based on MapReduce (Cloud-Markov), and comprehensive evaluation method of land-use changes based on cellular automata and MapReduce (Cloud-CELUC). Choosing Hangzhou as the study area and using Landsat remote-sensing images from 2006 and 2013 as the experiment data, we conducted three experiments to evaluate the parallel CA-Markov model on the Hadoop environment. Efficiency evaluations were conducted to compare Cloud-Markov and Cloud-CELUC with different numbers of data. The results showed that the accelerated ratios of Cloud-Markov and Cloud-CELUC were 3.43 and 1.86, respectively, compared with their serial algorithms. The validity test of the prediction algorithm was performed using the parallel CA-Markov model to simulate land-use changes in Hangzhou in 2013 and to analyze the relationship between the simulation results and the interpretation results of the remote-sensing images. The Kappa coefficients of construction land, natural-reserve land, and agricultural land were 0.86, 0.68, and 0.66, respectively, which demonstrates the validity of the parallel model. Hangzhou land-use changes in 2020 were predicted and analyzed. The results show that the central area of construction land is rapidly increasing due to a developed transportation system and is mainly transferred from agricultural land.

MANAJEMEN DATA SPASIAL: PENGGUNAAN TANAH WILAYAH PEDESAAN DI SUMATERA BARAT

2019 ◽  
Vol 5 (2) ◽  
pp. 48-53
Author(s):  
Afrital Rezki, S.Pd., M.Si ◽  
Erna Juita ◽  
Dasrizal Dasrizal ◽  
Arie Zella Putra Ulni
Keyword(s):  
Land Use ◽  
Paddy Field ◽  
Secondary Forest ◽  
Water Bodies ◽  
Primary Forest ◽  
Land Uses ◽  
Forest Land ◽  
Land Use Patterns ◽  
Crop Fields ◽  
Mixed Plantations

Perkembangan penggunaan tanah bergerak horisontal secara spasial ke arah wilayah yang mudah diusahakan. Penggunaan tanah juga bergerak secara vertikal dalam rangka menaikkan mutunya. Penelitian ini bertujuan untuk menganalisis pola penggunaan lahan, bagaimana manajemen penggunaan lahan di satu wilayah berdasarkan batas Nagari. Metode yang digunakan adalah analsisis spasial dengan interpretasi citra penginderaan jauh, survey lapangan, dan analisis deskriptif. Pertumbuhan pemukiman Nagari Sungai Sariak Kecamatan VII Koto Kabupaten Padang Pariaman mengakibatkan pemanfaatan ruang menjadi tumpang tindih. Diperlukan cara-cara pengelolaan dan managemen penggunaan tanah dalam rangka pembangunan berkelanjutan yang menaikkan taraf hidup masyarakat dan tidak menimbulkan kerugian lingkungan.Terdapat 9 jenis penggunaan lahan yang ada di Nagari Sungai Sariak. Penggunaan lahan tersebut adalah Primary Forest, Secondary Forest, Paddy Field, Settlement, Mixed Plantations, Crop Fields, Water Bodies, Bushes, dan Plantations. Penggunaan lahan yang paling luas di Nagari Sungai Sariak adalah jenis penggunaan lahan Primary Forest, sebesar 48% dari total luas wilayah Nagari Sungai Sariak. Pada tahun 2011 sampai tahun 2016, penggunaan lahan paling luas terjadi pada penggunaan lahan jenis Primary Forest yang kemudian menjadi Mixed Plantations. Land use Changes moved horizontally spatially towards areas that are easily cultivated. The land use also moves vertically in order to increase its quality. This study aims to analyze land use patterns, how land use management in one area is based on Nagari boundaries. The method used is spatial analysis with interpretation of remote sensing images, field surveys, and descriptive analysis. The growth of Nagari Sungai Sariak in Kecamatan VII Koto, Kabupaten Padang Pariaman resulted in overlapping use of space. Management methods are needed and management of land use in the framework of sustainable development that raises the standard of living of the community and does not cause environmental losses. There are 9 types of land use in the Nagari Sungai Sariak. The land uses are Primary Forest, Secondary Forest, Paddy Field, Settlement, Mixed Plantations, Crop Fields, Water Bodies, Bushes, and Plantations. The most extensive land use in Nagari Sungai Sariak is the type of Primary Forest land use, amounting to 48% of the total area of the Nagari Sungai Sariak. From 2011 to 2016, the most extensive land use occurred in Primary Forest land uses which later became Mixed Plantations.

scholarly journals A Model-Based Tool for Assessing the Impact of Land Use Change Scenarios on Flood Risk in Small-Scale River Systems—Part 1: Pre-Processing of Scenario Based Flood Characteristics for the Current State of Land Use

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 102
Author(s):  
Frauke Kachholz ◽  
Jens Tränckner
Keyword(s):  
Land Use ◽  
River Flow ◽  
Land Use Changes ◽  
Small Rivers ◽  
Small Scale ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Model Based ◽  
Current State ◽  
The Impact

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.

scholarly journals Spatial-Temporal Change of Land Use and Its Impact on Water Quality of East-Liao River Basin from 2000 to 2020

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1955
Author(s):  
Mingxi Zhang ◽  
Guangzhi Rong ◽  
Aru Han ◽  
Dao Riao ◽  
Xingpeng Liu ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Point Source ◽  
Water Body ◽  
Forest Land ◽  
Point Source Pollution ◽  
Construction Land ◽  
Unused Land ◽  
Non Point Source Pollution

Land use change is an important driving force factor affecting the river water environment and directly affecting water quality. To analyze the impact of land use change on water quality change, this study first analyzed the land use change index of the study area. Then, the study area was divided into three subzones based on surface runoff. The relationship between the characteristics of land use change and the water quality grade was obtained by grey correlation analysis. The results showed that the land use types changed significantly in the study area since 2000, and water body and forest land were the two land types with the most significant changes. The transfer rate is cultivated field > forest land > construction land > grassland > unused land > water body. The entropy value of land use information is represented as Area I > Area III > Area II. The shift range of gravity center is forest land > grassland > water body > unused land > construction land > cultivated field. There is a strong correlation between land use change index and water quality, which can be improved and managed by changing the land use type. It is necessary to establish ecological protection areas or functional areas in Area I, artificial lawns or plantations shall be built in the river around the water body to intercept pollutants from non-point source pollution in Area II, and scientific and rational farming in the lower reaches of rivers can reduce non-point source pollution caused by farming.

scholarly journals Topographic Position, Land Use and Soil Management Effects on Soil Organic Carbon (Vineyard Region of Niš, Serbia)

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1438
Author(s):  
Snežana Jakšić ◽  
Jordana Ninkov ◽  
Stanko Milić ◽  
Jovica Vasin ◽  
Milorad Živanov ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Layer ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Compaction ◽  
Soil Management ◽  
Forest Land ◽  
Topographic Position

Spatial distribution of soil organic carbon (SOC) is the result of a combination of various factors related to both the natural environment and anthropogenic activities. The aim of this study was to examine (i) the state of SOC in topsoil and subsoil of vineyards compared to the nearest forest, (ii) the influence of soil management on SOC, (iii) the variation in SOC content with topographic position, (iv) the intensity of soil erosion in order to estimate the leaching of SOC from upper to lower topographic positions, and (v) the significance of SOC for the reduction of soil’s susceptibility to compaction. The study area was the vineyard region of Niš, which represents a medium-sized vineyard region in Serbia. About 32% of the total land area is affected, to some degree, by soil erosion. However, according to the mean annual soil loss rate, the total area is classified as having tolerable erosion risk. Land use was shown to be an important factor that controls SOC content. The vineyards contained less SOC than forest land. The SOC content was affected by topographic position. The interactive effect of topographic position and land use on SOC was significant. The SOC of forest land was significantly higher at the upper position than at the middle and lower positions. Spatial distribution of organic carbon in vineyards was not influenced by altitude, but occurred as a consequence of different soil management practices. The deep tillage at 60–80 cm, along with application of organic amendments, showed the potential to preserve SOC in the subsoil and prevent carbon loss from the surface layer. Penetrometric resistance values indicated optimum soil compaction in the surface layer of the soil, while low permeability was observed in deeper layers. Increases in SOC content reduce soil compaction and thus the risk of erosion and landslides. Knowledge of soil carbon distribution as a function of topographic position, land use and soil management is important for sustainable production and climate change mitigation.

scholarly journals Historic and Simulated Desert-Oasis Ecotone Changes in the Arid Tarim River Basin, China

2021 ◽  
Vol 13 (4) ◽  
pp. 647
Author(s):  
Fan Sun ◽  
Yi Wang ◽  
Yaning Chen ◽  
Yupeng Li ◽  
Qifei Zhang ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Markov Model ◽  
River Basin ◽  
Arable Land ◽  
Current Trend ◽  
Ecological Crisis ◽  
Tarim River ◽  
Tarim River Basin ◽  
Desert Oasis

The desert-oasis ecotone, as a crucial natural barrier, maintains the stability of oasis agricultural production and protects oasis habitat security. This paper investigates the dynamic evolution of the desert-oasis ecotone in the Tarim River Basin and predicts the near-future land-use change in the desert-oasis ecotone using the cellular automata–Markov (CA-Markov) model. Results indicate that the overall area of the desert-oasis ecotone shows a shrinking trend (from 67,642 km2 in 1990 to 46,613 km2 in 2015) and the land-use change within the desert-oasis ecotone is mainly manifested by the conversion of a large amount of forest and grass area into arable land. The increasing demand for arable land for groundwater has led to a decline in the groundwater level, which is an important reason for the habitat deterioration in the desert-oasis ecotone. The rising temperature and drought have further exacerbated this trend. Assuming the current trend in development without intervention, the CA-Markov model predicts that by 2030, there will be an additional 1566 km2 of arable land and a reduction of 1151 km2 in forested area and grassland within the desert-oasis ecotone, which will inevitably further weaken the ecological barrier role of the desert-oasis ecotone and trigger a growing ecological crisis.

scholarly journals Dynamic Markov Model: Password Guessing Using Probability Adjustment Method

2021 ◽  
Vol 11 (10) ◽  
pp. 4607
Author(s):  
Xiaozhou Guo ◽  
Yi Liu ◽  
Kaijun Tan ◽  
Wenyu Mao ◽  
Min Jin ◽  
...  
Keyword(s):  
Markov Model ◽  
Repetition Rate ◽  
Random Sampling ◽  
High Probability ◽  
Deterministic Algorithm ◽  
High Repetition Rate ◽  
Generation Process ◽  
Dynamic Distribution ◽  
Model Based ◽  
Optimal Adjustment

In password guessing, the Markov model is still widely used due to its simple structure and fast inference speed. However, the Markov model based on random sampling to generate passwords has the problem of a high repetition rate, which leads to a low cover rate. The model based on enumeration has a lower cover rate for high-probability passwords, and it is a deterministic algorithm that always generates the same passwords in the same order, making it vulnerable to attack. We design a dynamic distribution mechanism based on the random sampling method. This mechanism enables the probability distribution of passwords to be dynamically adjusted and tend toward uniform distribution strictly during the generation process. We apply the dynamic distribution mechanism to the Markov model and propose a dynamic Markov model. Through comparative experiments on the RockYou dataset, we set the optimal adjustment degree α. Compared with the Markov model without the dynamic distribution mechanism, the dynamic Markov model reduced the repetition rate from 75.88% to 66.50% and increased the cover rate from 37.65% to 43.49%. In addition, the dynamic Markov model had the highest cover rate for high-probability passwords. Finally, the model avoided the lack of a deterministic algorithm, and when it was run five times, it reached almost the same cover rate as OMEN.

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.

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