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A global land utilization and land cover sequence spatialization method integrating GCAM and CA

A sequence space, spatialization technology, applied in data processing applications, instruments, biological neural network models, etc.

Active Publication Date: 2019-04-23
南京泛在地理信息产业研究院有限公司 +1
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  • Application Information

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Problems solved by technology

Similarly, a country with the same geopolitical and socioeconomic conditions within its neighborhood still exhibits significant spatial heterogeneity in land use and land cover due to changes in climate, moisture, soil, or topography

Method used

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  • A global land utilization and land cover sequence spatialization method integrating GCAM and CA
  • A global land utilization and land cover sequence spatialization method integrating GCAM and CA
  • A global land utilization and land cover sequence spatialization method integrating GCAM and CA

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Embodiment Construction

[0027] A global land use and land cover sequence spatialization method integrating GCAM and CA, including the following steps:

[0028] (1) Considering agro-ecological zoning and geopolitical economic zoning, the global land is divided into 283 sub-regions, and the land use requirements of different land types in 283 sub-regions are obtained;

[0029] (2) Combining the driving factors of global land use change, obtain 12 spatial variables, use the neural network to obtain the initial land type transition probability, and obtain the transition rules between different land use types by region;

[0030] (3) Calculate the weight matrix of land type transformation in 283 sub-regions in the world;

[0031] (4) Calculate the comprehensive transition probability of 283 sub-regions in the world;

[0032] (5) Carry out spatialization based on the comprehensive transition probability of (4) step;

[0033] (6) According to the three future development scenarios in the world, the spatial...

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Abstract

The invention discloses a global land utilization and land cover sequence spatialization method integrating GCAM and CA. The GCAM model and the geographic CA are combined, global 283 subareas are achieved, global land use sequence spatial data products from 2010 years to 2100 years are achieved, the spatial resolution is 1 km, and the time resolution is 5 years. By integrating the initial probability of the neural network, the neighborhood influence, the ground class transformation weight matrix of each sub-region and a planning constraint condition, the comprehensive transformation probability of the ground class of each sub-region is obtained, and the land utilization and the land coverage of each sub-region is spatialized. The method is mainly applied to the global land utilization change and coverage modeling under different development scenes in the future, has the capability of producing high-resolution global LUCC products, and promotes the research on the construction of a high-resolution land utilization model under the global scale.

Description

technical field [0001] The invention relates to the field of cellular automaton land use modeling, in particular to a global land use and land cover sequence spatialization method integrating GCAM and CA. Background technique [0002] Global land use and land cover change (LUCC) is critical to understanding the interactions between human activities and global environmental changes such as biodiversity and the carbon cycle. Existing studies have shown that the construction of LUCC models has become an important tool to reveal the driving mechanism of global LUCC changes and to study the temporal and spatial changes of global LUCC in the past and future years. The global-scale LUCC model has become a tool for comprehensive evaluation of global issues. pivotal parts. Although global-scale LULC modeling is required in many situations, few global-scale LUCC models currently exist due to their complexity. [0003] At present, the existing models for global LUCC mainly include th...

Claims

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Application Information

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IPC IPC(8): G06Q50/26G06N3/02
CPCG06N3/02G06Q50/26Y02A90/10
Inventor 曹敏朱艳慧黄梦雪蔡博勤马尚靖
Owner 南京泛在地理信息产业研究院有限公司
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