Expansion of Rural Settlements on High-Quality Arable Land in Tongzhou District in Beijing, China

Settlement expansion caused by urbanization is an important factor leading to the loss of arable land across the world. Due to various factors in China, such as institutional problems, the total number of rural settlements is decreasing, while the total area continues to increase. Rural settlements expand mainly into arable land, resulting in a significant loss of high-quality farmland, thus threatening long-term food security. However, research on this subject is relatively scarce. In this study, using KeyHole and RESURS F1 satellite remote sensing images, we examined the spatial expansion of rural settlements in Tongzhou District, Beijing, in 1972 and 1991. Then, the consumption of high-quality arable land by rural settlements expansion was assessed. It was found that the overall accuracy of the produced maps for 1972 and 1991 were 93% and 90%, respectively. The accuracy of mapped changes from 1972 to 1991 was as high as 90%. From 1972 to 1991 and from 1991 to 2015, the rural settlements in Tongzhou District expanded by 51.54% and 79.91% respectively, with 53.72% and 60.64% of the expanded rural settlements being on arable land. Rural settlements expanded mainly into high-quality arable land at the beginning of the study period, whereas later on, medium- and low-quality farmland was also occupied, albeit to a lesser degree.

Download Full-text

Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions

Remote Sensing ◽

10.3390/rs12010081 ◽

2019 ◽

Vol 12 (1) ◽

pp. 81 ◽

Cited By ~ 2

Author(s):

Xinghua Li ◽

Zhiwei Li ◽

Ruitao Feng ◽

Shuang Luo ◽

Chi Zhang ◽

...

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Spatial Resolution ◽

Satellite Imagery ◽

Satellite Remote Sensing ◽

Large Scale ◽

High Spatial Resolution ◽

Remote Sensing Images ◽

High Quality ◽

Geographical Maps

Urban geographical maps are important to urban planning, urban construction, land-use studies, disaster control and relief, touring and sightseeing, and so on. Satellite remote sensing images are the most important data source for urban geographical maps. However, for optical satellite remote sensing images with high spatial resolution, certain inevitable factors, including cloud, haze, and cloud shadow, severely degrade the image quality. Moreover, the geometrical and radiometric differences amongst multiple high-spatial-resolution images are difficult to eliminate. In this study, we propose a robust and efficient procedure for generating high-resolution and high-quality seamless satellite imagery for large-scale urban regions. This procedure consists of image registration, cloud detection, thin/thick cloud removal, pansharpening, and mosaicking processes. Methodologically, a spatially adaptive method considering the variation of atmospheric scattering, and a stepwise replacement method based on local moment matching are proposed for removing thin and thick clouds, respectively. The effectiveness is demonstrated by a successful case of generating a 0.91-m-resolution image of the main city zone in Nanning, Guangxi Zhuang Autonomous Region, China, using images obtained from the Chinese Beijing-2 and Gaofen-2 high-resolution satellites.

Download Full-text

A Method of Restoring Fuzzy Remote Sensing Image Based on Dark Pixel Prior

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001420540208 ◽

2019 ◽

Vol 34 (08) ◽

pp. 2054020

Author(s):

Guobin Chen ◽

Wei Dai

Keyword(s):

Remote Sensing ◽

A Priori ◽

Remote Sensing Image ◽

Remote Sensing Images ◽

High Quality ◽

Image Prior ◽

Pixel Value ◽

Dark Pixel ◽

Restoration Method

Remote sensing image deblurring is a long-term and challenging inverse problem. Among them, the ability to find the correct image prior is the key to recovering high-quality and clear images. Therefore, in order to recover high-quality clear images, this paper has found a new and effective image prior: The dark pixel a priori in remote sensing images and a fuzzy remote sensing image restoration method based on dark pixel prior is proposed. Since the dark pixels in the clear remote sensing image will increase the pixel value of the dark pixels in the blurred remote sensing image due to the weighted balance with the bright pixels around it, the sparsity of the dark pixels in the blurred remote sensing image is reduced. Therefore, by using this nonsparse feature of dark pixels in fuzzy remote sensing images, fuzzy remote sensing images and clear remote sensing images can be effectively distinguished, thus realizing the restoration of fuzzy remote sensing images. The experimental results show that the proposed method has obvious effects on the restoration effect and time.

Download Full-text

Analysis of the Coral Reef Evolution Based on Satellite Remote Sensing Images

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.1719 ◽

2013 ◽

Vol 333-335 ◽

pp. 1719-1723

Author(s):

Ming Xiao Xie ◽

Yin Cai ◽

Meng Guo Li

Keyword(s):

Remote Sensing ◽

Coral Reef ◽

Coral Reefs ◽

Satellite Remote Sensing ◽

Minimum Distance ◽

Remote Sensing Images ◽

Evolution Characteristics ◽

Biological Environment ◽

The Stability

Based on analysis of the ETM+ and TM remote sensing images of LandSAT satellites, the stability and evolution characteristics of the nearshore coral reefs at Changjiang, China was investigated. The results showed that the maximum distance from the outside edge of the coral reefs to the shoreline is 1.1km, and the corresponding minimum distance is 200m. From 1973 to 2013, the locations of coral reef chain are relatively stable with maximum variation 50m. Generally, the natural tidal currents and waves can not destroy the coral reefs, and the human activities do not change the biological environment of the coastal area. Therefore, the Changjiang coral reefs could keep stable in the long term.

Download Full-text

Crop rotations with clover and their productivity

Multifunctional adaptive feed production № 23 (71) ◽

10.33814/mak-2020-23-71-38-42 ◽

2020 ◽

Author(s):

Ol'ga Gladysheva ◽

Oksana Artyuhova ◽

Vera Svirina

Keyword(s):

Forest Soil ◽

Crop Rotation ◽

Gray Forest Soil ◽

Arable Land ◽

Perennial Grasses ◽

Crop Rotations ◽

Field Crop ◽

Pure Steam ◽

Positive Effect

The results of long-term research in experiments with crop rotations with different clover saturation are presented. It is shown that the cluster has a positive effect on the main indicators of vegetation of dark-gray forest soil. The introduction of two fields of perennial grasses into the six-field crop rotation significantly increases both the humus reserves and increases the productivity of arable land by 1.5–2 times compared to the crop rotation with a field of pure steam.

Download Full-text

ANALYSIS OF ABDOMINAL TYPHOID INCIDENCE IN THE SOUTH REGION OF THE KYRGYZ REPUBLIC

Natural resources of the Earth and environmental protection ◽

10.26787/nydha-2713-203x-2020-1-10-11-12-43-48 ◽

2020 ◽

pp. 43-48

Author(s):

Zakirova J.S. ◽

Nadirbekova R.A. ◽

Zholdoshev S.T.

Keyword(s):

Drinking Water ◽

Typhoid Fever ◽

Risk Groups ◽

The Body ◽

Kyrgyz Republic ◽

Radiation Factor ◽

High Quality ◽

Two Generations ◽

Immunological Deficiency

The article analyze the long-term morbidity, spread of typhoid fever in the southern regions of the Kyrgyz republic, and remains a permanent epidemic focus in the Jalal-Abad region, where against the low availability of the population to high-quality drinking water, an additional factor on the body for more than two generations and radiation factor, which we confirmed by the spread among the inhabitants of Mailuu-Suu of nosological forms of the syndrome of immunological deficiency, as a predictor of risk groups for infectious diseases, including typhoid fever.

Download Full-text

Reports From the Field: “Vini Ansanm” Come Together for Inclusive Community Music Development in Port-au-Prince, Haiti

The Oxford Handbook of Social Media and Music Learning ◽

10.1093/oxfordhb/9780190660772.013.17 ◽

2020 ◽

pp. 273-289

Author(s):

Donald DeVito ◽

Gertrude Bien-Aime ◽

Hannah Ehrli ◽

Jamie Schumacher

Keyword(s):

Social Media ◽

Inclusive Education ◽

Children With Disabilities ◽

Small Population ◽

Significant Loss ◽

Community Music ◽

Music Learning ◽

Loss Of Life

Haiti has experienced a series of catastrophic natural disasters in recent decades, resulting in significant loss of life and long-term damage to infrastructure. One critical outcome of these disasters is that there are approximately 400,000 orphans in the small population of just over 10 million. Throughout Haiti, children with disabilities are often considered cursed, and thus are rejected by the community in which they live. Haitian children with disabilities need creative and educational activities that will help them grow, develop, enjoy their lives, and become accepted members of the community. This chapter on the Haitian Center for Inclusive Education presents a case study of social media engagement and music learning, with an emphasis on social justice that has contributed to sustainable efforts.

Download Full-text

A small attentional YOLO model for landslide detection from satellite remote sensing images

Landslides ◽

10.1007/s10346-021-01694-6 ◽

2021 ◽

Author(s):

Libo Cheng ◽

Jia Li ◽

Ping Duan ◽

Mingguo Wang

Keyword(s):

Remote Sensing ◽

Satellite Remote Sensing ◽

Remote Sensing Images

Download Full-text

A Disparity Refinement Algorithm for Satellite Remote Sensing Images Based on Mean-Shift Plane Segmentation

Remote Sensing ◽

10.3390/rs13101903 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1903

Author(s):

Zhihui Li ◽

Jiaxin Liu ◽

Yang Yang ◽

Jing Zhang

Keyword(s):

Remote Sensing ◽

Satellite Remote Sensing ◽

Stereo Matching ◽

Mean Shift ◽

Segmentation Method ◽

Remote Sensing Images ◽

Edge Matching ◽

Refinement Method ◽

Initial Segmentation ◽

Refinement Algorithm

Objects in satellite remote sensing image sequences often have large deformations, and the stereo matching of this kind of image is so difficult that the matching rate generally drops. A disparity refinement method is needed to correct and fill the disparity. A method for disparity refinement based on the results of plane segmentation is proposed in this paper. The plane segmentation algorithm includes two steps: Initial segmentation based on mean-shift and alpha-expansion-based energy minimization. According to the results of plane segmentation and fitting, the disparity is refined by filling missed matching regions and removing outliers. The experimental results showed that the proposed plane segmentation method could not only accurately fit the plane in the presence of noise but also approximate the surface by plane combination. After the proposed plane segmentation method was applied to the disparity refinement of remote sensing images, many missed matches were filled, and the elevation errors were reduced. This proved that the proposed algorithm was effective. For difficult evaluations resulting from significant variations in remote sensing images of different satellites, the edge matching rate and the edge matching map are proposed as new stereo matching evaluation and analysis tools. Experiment results showed that they were easy to use, intuitive, and effective.

Download Full-text