Ecological Environment Assessment of Mining Area by Using Moving Window-based Remote Sensing Ecological Index

2019 ◽  
Author(s):  
Dongyu ZHU ◽  
Tao CHEN ◽  
NIU Ruiqing ◽  
ZHEN Na
Keyword(s):  
Remote Sensing ◽  
Mining Area ◽  
Ecological Environment ◽  
Moving Window ◽  
Ecological Index ◽  
Environment Assessment

scholarly journals A Multi-Criteria Evaluation of the Urban Ecological Environment in Shanghai Based on Remote Sensing

2021 ◽  
Vol 10 (10) ◽  
pp. 688
Author(s):  
Yuxiang Yan ◽  
Xianwen Yu ◽  
Fengyang Long ◽  
Yanfeng Dong
Keyword(s):  
Remote Sensing ◽  
Evaluation Method ◽  
Projection Pursuit ◽  
Detection Methods ◽  
Ecological Environment ◽  
Ecological Index ◽  
Environment Quality ◽  
Shanghai City ◽  
Projection Pursuit Model ◽  
The Impact

The urban ecological environment is related to human health and is one of the most concerned issues nowadays. Hence, it is essential to detect and then evaluate the urban ecological environment. However, the conventional manual detection methods have many limitations, such as the high cost of labor, time, and capital. The aim of this paper is to evaluate the urban ecological environment more conveniently and reasonably, thus this paper proposed an ecological environment evaluation method based on remote sensing and a projection pursuit model. Firstly, a series of criteria for the urban ecological environment in Shanghai City are obtained through remote sensing technology. Then, the ecological environment is comprehensively evaluated using the projection pursuit model. Lastly, the ecological environment changes of Shanghai City are analyzed. The results show that the average remote sensing ecological index of Shanghai in 2020 increased obviously compared with that in 2016. In addition, Jinshan District, Songjiang District, and Qingpu District have higher ecological environment quality, while Hongkou District, Jingan District, and Huangpu District have lower ecological environment quality. In addition, the ecological environment of all districts has a significant positive spatial autocorrelation. These findings suggest that the ecological environment of Shanghai has improved overall in the past five years. In addition, Hongkou District, Jingan District, and Huangpu District should put more effort into improving the ecological environment in future, and the improvement of ecological environment should consider the impact of surrounding districts. Moreover, the proposed weight setting method is more reasonable, and the proposed evaluation method is convenient and practical.

scholarly journals Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke

2019 ◽  
Vol 11 (22) ◽  
pp. 6385 ◽  
Author(s):  
Qin Liu ◽  
Zhaoping Yang ◽  
Fang Han ◽  
Hui Shi ◽  
Zhi Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Ecological Status ◽  
Spatial Data Analysis ◽  
Ecological Environment ◽  
Species Structure ◽  
Heritage Sites ◽  
Environment Assessment ◽  
Heritage Site ◽  
Better Than

Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.

scholarly journals Research on Temporal and Spatial Resolution and the Driving Forces of Ecological Environment Quality in Coal Mining Areas Considering Topographic Correction

2021 ◽  
Vol 13 (14) ◽  
pp. 2815
Author(s):  
Xinran Nie ◽  
Zhenqi Hu ◽  
Qi Zhu ◽  
Mengying Ruan
Keyword(s):  
Remote Sensing ◽  
Coal Mining ◽  
Coal Mine ◽  
Ecological Environment ◽  
Topographic Correction ◽  
Ecological Index ◽  
Mining Areas ◽  
Environment Quality ◽  
Temporal And Spatial

Over the last few years, under the combined effects of climate change and human factors, the ecological environment of coal mining areas has undergone tremendous changes. Therefore, the rapid and accurate quantitative assessments of the temporal and spatial evolution of the ecological environment quality is of great significance for the ecological restoration and development planning of coal mining areas. This study applied the ecological environment index after topographic correction to improve the remote sensing ecological index (RSEI). Based on a series of Landsat images, the ecological environment quality of Yangquan Coal Mine in Shanxi Province from 1987 to 2020 was monitored and evaluated by an improved remote sensing ecological index. The results show that after topographic correction, the topographic effect of the remote sensing ecological index was greatly reduced, and its practicability was improved. From 1987 to 2020, the ecological environment quality of Yangquan Coal Mine was improved, and the mean of the RSEI increased from 0.4294 to 0.6379. The ecological environment quality of the six coal mines in the study area was improved. Among the six coal gangue dumps, the ecological environmental quality of D1, D2, D3, and D4 has improved, and the ecological environment quality of D5 and D6 worsened. The percentages of improved, unchanged, and degraded ecological environment quality in the entire coal mining area were 77.08%, 0.99%, and 21.93%, respectively. The global Moran’s index was between 0.7929 and 0.9057, and it was shown that there was a strong positive correlation between the ecological environmental qualities of the study area, and that its spatial distribution was clustered rather than random. The LISA cluster map showed that the aggregation and dispersion degree of ecological environment quality was mainly high–high clustering and low–low clustering over the whole stage. During the study period, temperature and precipitation had limited impacts on the ecological environment quality of Yangquan Coal Mine, while the coal mining activities and urbanization construction seriously affected the local ecological environment quality and the implementation of ecological restoration policies, regulations, and measures was the main reason for the improvement of the ecological environment quality.

scholarly journals CONSTRUCTION AND APPLICATION OF ENHANCED REMOTE SENSING ECOLOGICAL INDEX

2018 ◽  
Vol XLII-3 ◽  
pp. 1809-1813
Author(s):  
X. Wang ◽  
C. Liu ◽  
Q. Fu ◽  
B. Yin
Keyword(s):  
Remote Sensing ◽  
Natural Disasters ◽  
Vegetation Index ◽  
Principal Component ◽  
Hainan Island ◽  
Weight Coefficient ◽  
Ecological Environment ◽  
Ecological Index ◽  
Environment Quality

In order to monitor the change of regional ecological environment quality, this paper use MODIS and DMSP / OLS remote sensing data, from the production capacity, external disturbance changes and human socio-economic development of the three main factors affecting the quality of ecosystems, select the net primary productivity, vegetation index and light index, using the principal component analysis method to automatically determine the weight coefficient, construction of the formation of enhanced remote sensing ecological index, and the ecological environment quality of Hainan Island from 2001 to 2013 was monitored and analyzed. The enhanced remote sensing ecological index combines the effects of the natural environment and human activities on ecosystems, and according to the contribution of each principal component automatically determine the weight coefficient, avoid the design of the weight of the parameters caused by the calculation of the human error, which provides a new method for the operational operation of regional macro ecological environment quality monitoring. During the period from 2001 to 2013, the ecological environment quality of Hainan Island showed the characteristics of decend first and then rise, the ecological environment in 2005 was affected by severe natural disasters, and the quality of ecological environment dropped sharply. Compared with 2001, in 2013 about 20000 square kilometers regional ecological environmental quality has improved, about 8760 square kilometers regional ecological environment quality is relatively stable, about 5272 square kilometers regional ecological environment quality has decreased. On the whole, the quality of ecological environment in the study area is good, the frequent occurrence of natural disasters, on the quality of the ecological environment to a certain extent.

scholarly journals REMOTE SENSING EVALUATION OF ECOLOGICAL ENVIRONMENT OF ANQING CITY BASED ON REMOTE SENSING ECOLOGICAL INDEX

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 733-737
Author(s):  
X. Niu ◽  
Y. Li
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Environmental Quality ◽  
Ecological Environment ◽  
Mountainous Area ◽  
Ecological Change ◽  
Ecological Quality ◽  
Ecological Index ◽  
Use Of Resources

Abstract. Figuring out the regional ecological environment quality and ecological change is critical for ecological environment monitoring and management and urban construction planning. Based on the remote sensing ecological index (RESI), we evaluate the ecological quality and ecological change from 1999 to 2019 of Anqing city. Multi-temporal Landsat images are used to extract the four indicators of humidity, vegetation, heat and dryness, respectively. Then the RSEI is calculated by principal component analysis. The results show that the ecological quality of Anqing city declined from 1999 to 2019 and then grew slowly from 2009 to 2019. The eco-environmental quality of Anqing city dropped slightly from 1999 to 2019, and the regions with worse quality grades exceeded those becoming better. Particularly, we find that from 1999 to 2009, the area where the ecological quality became better made up 18.31% of the urban area, while the worse ecological area accounted for 29.68% of the urban area; from 2009 to 2019, the area of improved ecological environment reached 24.35%, while the area of degraded quality constituted 41.36%. Land-use changes dominated eco-environmental quality. The areas of poor eco-environmental quality expanded in residential regions and eco-environmental quality of mountainous area improved since returning cultivated land in steep hills into forest. The RSEI results are expected to provide a quantitative foundation for planning sustainable development and the rational use of resources in Anqing city.

Spatiotemporal evolution of ecological environment quality in arid areas based on the remote sensing ecological distance index: A case study of Yuyang district in Yulin city, China

2021 ◽  
Vol 13 (1) ◽  
pp. 1701-1710
Author(s):  
Liangyan Yang ◽  
Lei Shi ◽  
Jing Wei ◽  
Yating Wang
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Northwest China ◽  
Ecological Environment ◽  
Arid Areas ◽  
Upward Trend ◽  
Ecological Index ◽  
Environment Quality ◽  
Grade Classification ◽  
Surrounding Areas

Abstract The ecological environment in arid areas of Northwest China has undergone considerable changes under the combined effects of climate change and human factors. Therefore, exploring the spatial and temporal evolution of the ecological environment quality is of great significance for the protection and management of the ecological environment in arid areas of Northwest China. This study adopted Yuyang district as the study area. Landsat Thematic Mapper/Operational Land Imager images from 1993 to 2018 were selected as the data source for the retrieval of important surface indicators and the construction of the remote sensing distance ecological index. The spatial distribution, trend, and grade classification of the ecological environment quality were monitored and analyzed. The results showed that (1) the ecological environment quality of Yuyang district from 1993 to 2018 showed an overall upward trend, mainly manifested as a sharp decline in the area of poor ecological environment from 84.81 to 53.36%. (2) The spatiotemporal changes in the ecological environment quality showed a downward trend in the central urban area and an upward trend in the noncentral urban area. (3) In general, rainfall and temperature had limited impact on the ecological environment quality. Urbanization seriously affected the local ecological environment quality and the implementation of the ecological restoration policies, regulations, and measures were the main drivers of the improvement to the ecological environment quality in other surrounding areas.

scholarly journals Construction and application research of ecological evaluation platform based on Cesium

2020 ◽  
Author(s):  
Yao Fu ◽  
Guize Luan ◽  
Jingzhi Cai ◽  
Yuchen Li ◽  
Fei Zhao
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Evaluation Model ◽  
Principal Component ◽  
Heterogeneous Data ◽  
Ecological Environment ◽  
Vegetation Coverage ◽  
Lake Area ◽  
Ecological Evaluation ◽  
Ecological Index

Abstract In this study, Sentinel 2A and Landsat series remote sensing images were used to determine the weights of vegetation coverage, humidity, dryness and heat by using the principal component analysis method. The remote sensing ecological index evaluation model was used to evaluate the ecology of the Fuxian Lake area from 2013 to 2018. Environmental quality in the study area is monitored and analyzed. By developing a unified organization and management module of spatio-temporal data in the collaborative production of multi-source heterogeneous data, the mapping relationship between data and parameters is established. The 3D-web data integration decision platform is constructed. Based on the Cesium engine real-time rendering and interactive visualization network 3D platform, real-time calculation and visualization of the ecological evaluation of the Fuxian Lake area between 2013 and 2018 is realized. The ecological environment of the study area continued to deteriorate from 2013 to 2015, improved slightly in 2016, and improved significantly in 2017–2018. The platform has the functions of searching, selecting the base map, measuring on the map, and positioning the coordinates, which can achieve the real-time ecological analysis function and show the change process of the ecological environment and natural resources.

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