Study on Mechanism of Scale Effect on Measurement of Land Use Classification Area
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Based on the analysis of the scale effect on land use classification area of land use survey,this paper puts forward the calculation method of the areal difference of the same land types under different scales,so as to lay the theoretical basis for the further study of the areal difference of the current situation of large scale land use survey.Cite
This paper analyzed the determining factors Of land use and its spatial dependency in China, and through statistical and multi-scale GIS techniques investigated the spatial patterns of land use. Correlation and regression analysis was used to identify the most important explanatory variables from a large set of candidate determining factors. We found that the distribution of all land use types in China will be best described by a combination of different biophysical and socio-economic factors. Specific attention was given to the influence of scale and the spatial distribution of arable land. The results will provide some reference for the land use planning and spicy-making of sustainable utilization of land resources.
Arable land
Land Cover
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Based on remote sensing and geographical information system,land use database of 1998 and 2002 in Xinjian County were established.Two commonly used prediction models,which are Markov model based on transformation matrix and GM(1,1) based on Grey theory respectively were applied to predict land use change direction in the future.The results indicated that coincidence degree between two prediction models was very high.Arable land and unused land will decrease persistently.Forest land and construction land showed acceleration tendency.Grassland and water body will be leveling-off in the future.Furthermore,driving forces of land use change are analyzed in this paper.The research results could provide scientific basis for land use planning and land use policy constitution.
Arable land
Land information system
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The purpose of this paper is to overcome the problem that the uniform classification model cannot be used to improve the accuracy of land use classification effectively,and to provide a method with high precision and efficiency to extract qualitative and quantitative information of land use/cover.In this paper,two extraction methods,i.e.,the hierarchical information extraction method and the method based on knowledge and rule,are combined.The hierarchical information extraction method can create a cleaner extracting environment when extracting specific types of land use/cover.The method based on knowledge and rule can give full play to the role of priori knowledge and experience,and reference diverse assistant information comprehensively.The purpose of combining the two methods is to further improve the classification accuracy.Taking the metropolitan area of Nanjing as an example,a set of land use information hierarchical extraction process is designed and put into effect.In the extraction process,TM image spectrum information and the temporal and spatial characteristics of land use in study area are fully considered.Using different ways and data such as water extraction index model,Ratio Resident-area Index(RRI),NDVI,DEM data and the urban built-up area boundary,we extracted eight types of land use/cover,i.e.,water,urban build-up area,rural build-up area,mining land,bare land,woodland,farmland,and urban green land.Specially,we constructed a build-up and quarry discrimination index(BQDI)to efficiently distinguish build-up area from mining/bare land,and make full use of elevation and slope information to extract woodland from vegetation coverage area.In addition,the urban build-up area boundary plays an important role in distinguishing urban build-up area and rural build-up area,farmland and urban green land,mining land and bare land.The results showed that the overall accuracy(OA)reached 88.67%,and the Kappa index reached 0.85 when extracting the land use/cover information of 2012 in study area.Besides,the overall accuracy on other years' information extraction were all higher than 87%,and the Kappa index were all more than 0.84.We concluded that the hierarchical land use information extraction method based on knowledge and rule possesses high precision and wide applicability.The method has a good reference value to land use/cover extraction practice in other regions.Further research should be undertaken to increase the degree of automation in information extraction process,the efficiency and accuracy of extraction in the future.
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Land use and land cover change (LUCC) is one of the most important aspects within the scope of global change. As a critical portion of LUCC study, classification of land use and land cover types not only affects the classification results, but also determines applications of relevant data. In the paper, studies of land use and land cover classification systems were reviewed. It could be concluded that the land use and land cover classification laid more emphasis on the land use classification before the 1970s. The land use classification system emphasized the differences between land functions and was mainly applied to land use inventory investigation and land use mapping. After then, the classification system based on land cover rapidly developed due to the development of satellite remote sensing and computer technology. This classification system emphasized the differences between land categories and was mainly applied to land cover change studies. The review shows that almost all current land use and land cover classification systems tend to be suitable only for a specific research purpose at a certain scale. The incompatibility amongst the current classification systems has resulted in numerous inconveniences and difficulties in the courses of aggregation, analysis, and sharing of land use and land cover data due to the absence of consistent standards. Therefore, a standardized classification system is extremely warranted. However, a universal classification system suitable for all kinds of research purposes is neither possible nor necessary. The reasons lie in that on the one hand, the minimum classification unit could be dependent on the mapping scale as well as the spatial resolution of remote sensing data; on the other hand, land use and land cover types of varying detailed degrees are required for different research purposes. Furthermore, it would be probable that some special land use and land cover types existed in specific regions, for example, the Qinghai-Tibet Plateau in China. At last, this review states that a standardized classification system should be hierarchically organized and could be extended. The land use and land cover types of higher hierarchy could be directly identified from remote sensing images without auxiliary information, which would make it convenient for data comparison and sharing. The land use and land cover types of lower hierarchy could be defined in terms of a specific study purpose, which could satisfy the specific study needs.
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Land information system
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Classification scheme
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The indicator selection is the basis of the performance evaluation of land use.Many scholars established performance evaluation index system of land use and provided the theoretical foundation for land use evaluation.However,to build performance evaluation index system of land-use is still an important task of academia.Some existing evaluation index of urban land use ignore the spatial scale and their target,hierarchy and regional feature had a little obvious.In this paper,the establishment of performance evaluation index system of urban land-use for two spatial scales—built-up areas and municipal districts.
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Land use change is one of the main research subjects of global environmental change and sustainable development.Land use models are useful for disentangling complex socio-economic and biophysical factors that influence the rate and spatial pattern of land use change,and for estimating the impacts of land use changes.Furthermore,models can support the exploration of future land use change under different scenarios and conditions.Taking the Chongqing metropolitan area as a case,we used 120 m ×120mraster data and the SPSS and ArcGIS 10.1software to construct a dynamic simulation model in different scenarios of land use/cover change.The CLUE-S model,which is based on comprehensive considerations on the basis of natural and human factors,can simulate small-scale land use change scenarios with characteristics of integrity,openness,spatiality and competitive efficiency.Firstly,6key driving factors,including elevation,slope(0°-5°,5°-15°and 15°),distance to rivers,distance to roads,distance to local financial revenue and so on,were identified by using logistic stepwise regression method;Secondly,land use data in 2000 and 2005 were used respectively to simulate the spatial pattern of land use in 2005 and 2010for the main city of Chongqing.Lastly,the simulated land use map in2010 was compared with the actual land use map in 2010 to validate simulation results.The model considers various macro driving factors and the relationship between the land use change and consider the various driving factors of land use/cover change.The SPSS software is used to determine the various factors from the regression model,in this way the precision of the simulation results are improved.The overall simulation accuracy was achieved to more than 86%,suggesting that the CLUE-S model has a good applicability in simulating land use change in the main city of Chongqing and can be used to predict future land use change.The CLUE-S model can provide a scientific basis for land-use planning and urban planning in the future.The simulation results show that,by 2030,wetland,artificial land,forest,cultivated land and other land present a decreasing trend.In contrast,grassland is slightly growing in all scenarios.Cultivated land and artificial land present the most significant changes.With time,cultivated land and forest land area are increasingly close in terms of total area.
Land Cover
Driving factors
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The Markov-cellular automata is suitable to study complex spatial-temporal geographic system, especially for regional land use, and it has been an important tool and research focus for regional land use change modeling. Previous researchers focused on a few kind of land use type at the regional scale and the data resolution was cursory because land use maps were usually derived from TM image. Few researchers involved precise scale of land use change within a region. To solve this problem, we took the data of land-use survey as a data source maps that include detailed multiple land use types. The case study area was Changping District, which is a rapidly growing area of Beijing. We select the land use map of 2001 and 2005 which include the multiple land use types as data source to simulate the land use of 2012. The results of simulation show that simulation accuracy of multiple land use types is better than them of cursory scale land use types, although it takes a substantial amount of time to run. The statistical result derived from Moran's I and fractal parameter indicates that simulation shows the high spatial stability. The simulation results showed that the number of cropland is keeping on decrease from 2005 to 2012 without the holistic sustainable development measures and severe land policy. This paper represents a good try to local land use change modeling as shown combined Markov chain analysis and cellular automata models. The simulated future land use changes have significant environmental and socioeconomic implications for sustainable region land detailed planning in the study area.
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The study on land use change is a frontier and hotspot in global environmental change study. Taking land use change of Xiji County in 1980s as an example, the methods of researching land use change are discussed. The result shows that applying land use maps with different scale and different land use classification system studies land use change is feasible. Main processes of operation are as follows: (1) conversion of land use classification system; (2) spatial overlay analysis; (3) determining probability conversion matrix of land use change; (4) attribute database analysis.
Hotspot (geology)
Global Change
Frontier
Change analysis
Spatial change
Environmental change
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Based on the first national land survey and the second land survey data, this paper uses GIS technology, mathematical and statistical analysis techniques, and combines with related theory to research on land use / land cover change (LUCC) study through various types of data processing in the sample area-Weifang City, Shandong Province. According to land use change model, it makes a comprehensive analysis of the 1997-2007 years, the quantity and speed changes in land use, and also indicates land use change rule. What's more, it can predict future changes of land use by means of Markov model. Finally, it points out the strategies and measures to reasonably develop and use land resource according to present conditions of land use.
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Land information system
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Suitable land-cover/land-use information is rarely available in most developing countries, particularly when newness, accuracy, relevance, and compatibility are used as evaluation criteria. In Indonesia, various institutions developed their own maps with considerable differences in classification schemes, data sources and scales, as well as in survey methods. Redundant land-cover/land-use surveys of the same area are frequently carried out to ensure the data contains relevant information. To overcome this problem, a multidimensional land-use classification system was developed. The system uses satellite imagery as main data source, with a multi-dimensional approach to link land-cover information to land-use-related categories. The land-cover/land-use layers represent image-based land-cover (spectral), spatial, temporal, ecological and socio-economic dimensions. The final land-cover/land-use database can be used to derive a map with specific content relevant to particular planning tasks. Methods for mapping each dimension are described in this paper, with examples using Quickbird satellite imagery covering a small part the Semarang area, Indonesia. The approaches and methods used in this study may be applied to other countries having characteristics similar to those of Indonesia
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Land information system
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