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This study takes the Zhouyuan site region, which is the most representative Western Zhou Dynasty (1046 BC-771BC) large city-site in China, as an example. Based on the interpretation results of satellite remote sensing images from 1973 to 2021, the paper systematically analyzed the evolution of landscape patterns in the Zhouyuan site region spanning for about 50 years using 4 methods, including land use classification, land use transfer matrix, landscape pattern distribution gravity center model and landscape pattern index. Additionally, the results show that nowadays Zhouyuan site is still in a period of accelerated invasion and destruction by natural and human factors, which indicates that the protection of the Zhouyuan site has been inadequate or even unsuccessful for a long time. For the purpose of making more accurate and better protection of the Zhouyuan site, four challenges and six protection recommendations have been put forward. Based on remote sensing and geographic information system (GIS), this paper contributed a method combining 4 models to analyze the spatial-temporal evolution characteristics of landscape pattern of ancient large city-sites, in order to provide more basis for the formulation of cultural relic protection strategies. [ABSTRACT FROM AUTHOR]

Based on the improved Tapio decoupling model and geographic information system spatial analysis technology, this paper studied the spatial and temporal pattern evolution law of the decoupling relationship between innovation capability and resource consumption in 283 cities in China. The non-residual complete decomposition model was used to decompose the rebound effect of resource consumption in China's urban innovation development. We found (1) during the study period, innovation capability and resource consumption in Chinese cities showed a weak decoupling state. (2) Regions with significant decoupling showed a trend of spatial agglomeration, and the gap in the degree of urban decoupling gradually narrowed. (3) The increase in urban population growth and innovation intensity in China have a positive pull effect on resource consumption. The improvement in resource efficiency has an inhibitory effect on resource consumption, but this inhibition is less than the effect of population scale and innovation intensity on resource consumption. [ABSTRACT FROM AUTHOR]

This paper empirically visualizes the spatial patterns of the inter-provincial electricity flows in relation to the distribution of gross domestic product (GDP) per capita using spatial geographical information system (GIS) and cartograms. It highlights how developed provinces in eastern China are net importers of electricity from western and central China, which creates a west-east power transmission pattern and helps deepen the regional economy disparity. [ABSTRACT FROM AUTHOR]

The new round of the Grain for Green Project (GGP) has unified the subsidy standards for economic and ecological forests. However, due to the difference between the afforestation density effect and management effect, the project's ecological effect is different. Uniform payment standards may decouple afforestation investment from its ecological benefits, consequently affecting the cost-effectiveness of investment. This study combines a geographic information system and remote sensing technology to explore the optimal forest types investment structure of the GGP from the cost-effectiveness perspective. We used dynamic panel models to estimate the number of lag periods for species investment and an individual fixed-effects model to estimate the optimal structure of species investment. The conclusions are as follows: The lag period of the effect of ecological forest investment on the normalized difference vegetation index (NDVI) is shorter than that of economic forest investment. When the proportion of ecological forest investment is 53%−62%, the unit investment in afforestation leads to the largest NDVI. This study promotes the process of vegetation restoration effects from phenomenological analysis to mechanism analysis and incorporates forest types characteristics and natural meteorological factors into the afforestation investment efficiency evaluation system, providing a theoretical basis for GGP optimization. [ABSTRACT FROM AUTHOR]

Geographical information systems (GIS) are essential tools for mineral prospectivity modeling (MPM). Three-dimensional (3D) MPM is able to learn the association between geological evidence and mineralization in shallow zones and thereby build a prospectivity model for deep zones, making it a desirable technique to target deep-seated orebodies. However, existing 3D MPM methods directly generalize the model learned in shallow zones to the deep zones without attention to model transferability caused by the different metallogenic mechanisms between the two zones. In this study, we aim to robustly transfer the prospectivity model learned from shallow zones to deep zones. We cast the 3D MPM as a domain adaptation problem, which is an important realm of transfer learning. Because the metallogenic mechanism can be closely associated with spatial locations, we specifically focus on domain adaption concerning the spatial locations that are ignored by conventional domain adaptation methods. To measure the spatial-associated domain discrepancy, we propose a novel spatial-associated maximum mean discrepancy (SAMMD), which compares the joint distributions of features and spatial locations across domains. Based on the SAMMD criterion, a deep neural network, referred to as the spatial-associated domain adaptation network, is devised to learn cross-domain but mineralization-indicative features for building prospectivity model that is transferable to deep zones. A case study of the world-class Sanshandao gold deposit, in eastern China, was carried out to validate the effectiveness of the proposed methods. The results show that compared with other leading MPM methods and other domain adaption variants, the proposed method has superior prediction accuracy and targeting efficiency, demonstrating the effectiveness and robustness of the proposed method in targeting deep-seated orebodies in areas with different metallogenic mechanisms and no labeled data. [ABSTRACT FROM AUTHOR]

Flash floods are one of the most serious mountain disasters in Linzhi, China, pose a grave threat to the lives and property of the residents. However, the current regional vulnerability research cannot meet the needs of refined disaster prevention and mitigation in mountainous areas. Therefore, to address this knowledge gap, this study presented a vulnerability assessment framework base on spatialization technique along with the triangular fuzzy number-based analytic hierarchy process (TFN-AHP) and random forest (RF) model. To achieve this goal, an assessment system containing 12 indicators was constructed from the three perspectives of exposure, susceptibility and coping capacity. Firstly, factor spatialization is introduced in data preprocessing. Then TFN-AHP and the RF model were used to calculate the exposure, susceptibility, and coping capacity. Finally, the spatial distribution of the vulnerability throughout Linzhi was obtained. According to the results, the exposure, susceptibility and coping capacity in most areas are extremely low and low, accounting for 74.1%, 99% and 99%, respectively. The vulnerability is similar to the exposure that most of the regions have extremely low vulnerability and low vulnerability, accounting for 83.5%. The moderate vulnerability regions account for 8.5%, and the high vulnerability regions account for only 1%. The assessment results show that highexposure areas mainly exhibit a linear distribution, and mainly include river valleys, cultivated land, and residential areas. Obviously, these areas are mainly distributed in the population and economic agglomeration areas and on low-altitude terrain. The distribution of high and comparatively high vulnerability zones, where economic and human activities are considerably high, are closely to the topography of the catchment. Thus, the results of this study provide scientific and technological evidence for resettlement, population distribution adjustment, and prevention and mitigation of flash floods in Linzhi. [ABSTRACT FROM AUTHOR]

We first predicted the potential climate suitability of food crops with geographical indications (GIs) using the maximum entropy (MaxEnt) model and eight bioclimatic predicators under three shared socioeconomic pathway (SSP) scenarios during 2021-2040. The results showed that highly suitable rice, wheat, and corn areas increased in the three scenarios. Specifically, the growth rate under the SSP2-4.5 scenario was higher than that under the other scenarios. The potentially suitable area of wheat GIs was the largest with the most dramatic change. In contrast, the highly suitable area of millet and soybean GIs decreased under the SSP2-4.5 scenario but increased under the SSP1-2.6 and SSP3-7.0 scenarios. The increased greenhouse gas concentrations and radiative forcing under various scenarios had different effects on the dominant factors, changing the highly suitable areas of various food crop GIs. This study provides scientific evidence for the future cultivation of food crop GIs. [ABSTRACT FROM AUTHOR]