scholarly journals Mapping Panax Notoginseng Plantations by Using an Integrated Pixel- and Object-Based (IPOB) Approach and ZY-3 Imagery

2021 ◽  
Vol 13 (11) ◽  
pp. 2184
Author(s):  
Zhiqi Yang ◽  
Jinwei Dong ◽  
Weili Kou ◽  
Yuanwei Qin ◽  
Xiangming Xiao
Keyword(s):  
Spatial Distribution ◽  
Yunnan Province ◽  
Vascular Diseases ◽  
Panax Notoginseng ◽  
Traditional Herbal Medicine ◽  
Target Class ◽  
Object Based ◽  
The Government ◽  
Level Scale ◽  
Iteration Analysis

Plantations of Panax notoginseng (PN), traditional herbal medicine for the prevention and treatment of vascular diseases, are expanding rapidly in China, especially in the Yunnan province of China, due to its increasing demands and prices and causing dramatic environmental concerns. However, existing information on its planting area and spatial distribution are limited. Here, we mapped the PN planting area by using a new integrated pixel- and object-based (IPOB) approach, the Random Forest (RF) classifier, and the high-resolution ZiYuan-3 (ZY-3) imagery. We improved the procedures of classification in three aspects: (1) a new spectral index—Normalized Difference PN Index (NDPI)—was proposed, (2) the efficiency and scale of segmentation were optimized by using the Bi-level Scale-sets Model (BSM), and (3) feature variables were selected through an iteration analysis from 99 feature variables (spectral, textural, geometric, and geographic). Compared with the pixel- and the object-based methods, the IPOB has the highest F1 score of 0.98 and also has high robustness in terms of user and producer accuracies (97% and 99%, respectively), following by the object-based method (F1 = 0.94) and the pixel-based method (F1 = 0.93). The high accuracy was expected since the target class has very distinctive spectral and textural characteristics. Although all three approaches showed reasonably high accuracies due to the application of the NDPI and optimized procedures, the result showed the outperformance of the proposed IPOB approach. The framework established in this study expects to apply for regional or national PN surveys extensively. The information on the area and spatial distribution of PN can guide the government on policy making for the planting and exporting of traditional Chinese medicine resources.

scholarly journals Concentration and Spatial Distribution of Potentially Toxic Elements in Surface Soil of a Peak-Cluster Depression, Babao Town, Yunnan Province, China

2021 ◽  
Vol 18 (6) ◽  
pp. 3122
Author(s):  
Hongyu Tian ◽  
Cheng Zhang ◽  
Shihua Qi ◽  
Xiangsheng Kong ◽  
Xiangfei Yue
Keyword(s):  
Spatial Distribution ◽  
Food Safety ◽  
Toxic Elements ◽  
Yunnan Province ◽  
Surface Soil ◽  
Agricultural Soils ◽  
Principal Component ◽  
Potentially Toxic Elements ◽  
Rice Grain ◽  
The Government

Potentially toxic elements (PTEs) in Chinese agricultural soils, including those in some heritage protection zones, are serious and threaten food safety. Many scientists think that these PTEs may come from parent rock. Hence, at a karst rice-growing agricultural heritage area, Babao town, Guangnan County, Yunnan Province, China, the concentrations of eight PTEs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) were determined in 148 surface soil, 25 rock, and 52 rice grain samples. A principal component analysis (PCA) and hierarchical cluster analysis were used to divide the surface soil into groups, and inverse distance weighting (IDW) was used to analyze the spatial distribution of PTEs. Soil pollution was assessed with the geoaccumulation index (Igeo). The results show that Cd, Hg, Zn, and Cr were polluting the soil (average Igeo > 0). The highest concentration of PTEs was distributed in the southwest of Babao town in the carbon rock area, which had the highest pH and soil total organic carbon (Corg), Mn, and TFe2O3 contents. PCA biplots of soil samples showed that the carbon rock area was associated with the most species of PTEs in the study area including Pb, Cd, Hg, As, and Zn. The clastic rock area was associated with Cu and Ni, and the lime and cement plants were associated with CaO, pH, Corg, TC, and aggravated PTE pollution around factories. In high-level PTE areas, rice was planted. Two out of 52 rice grain samples contained Cd and 4 out of 52 rice grain samples had Cr concentrations above the Chinese food safety standard pollutant limit (Cd 0.2 mg/kg; Cr 1 mg/kg). Therefore, the PTEs from parent rocks are already threatening rice safety. The government should therefore plan rice cultivation areas accordingly.

scholarly journals Analysis of Spatial Distribution of PM2.5 and Human Behavior on Air Pollution in Jakarta

2021 ◽  
Vol 940 (1) ◽  
pp. 012018
Author(s):  
K I Solihah ◽  
D N Martono ◽  
B Haryanto
Keyword(s):  
Air Pollution ◽  
Spatial Distribution ◽  
Human Behavior ◽  
Urban Areas ◽  
Descriptive Analysis ◽  
Air Pollution Control ◽  
Linear Regression Models ◽  
Raising Awareness ◽  
Knowledge And Attitude ◽  
The Government

Abstract Particulate matter is one of the threatening pollutants harmful to health. Currently, many researchers focus on the problem of PM2.5 concentrations in urban areas. This study aims to estimate the spatial distribution of PM2.5, and identify human behavior on air pollution in Jakarta. The method used were Spline with Tension to build the PM2.5 models, and multiple linear regression models to analyze human behavior on air pollution. The results showed that the annual average of PM2.5 in the last two years tends to be high in western, southern, and eastern parts of Jakarta. In addition, there was a decrease of PM2.5 concentration in 2020 compared to 2019 assumed as a result of Covid-19 Pandemic restrictions. Besides, analysis results showed a significant association between knowledge and attitude aspects on the action aspect. Based on descriptive analysis, people have good knowledge of air pollution and also concern to reduce air pollution. However, the actions for air pollution control are still not maximized which may cause high PM2.5 concentrations in Jakarta. We conclude that to reduce air pollution, the government should focus on the border areas of Jakarta and it can be done by increasing public knowledge and raising awareness for air pollution.

scholarly journals Spatial Structure Characteristics of Slope Farmland Quality in Plateau Mountain Area: A Case Study of Yunnan Province, China

2020 ◽  
Vol 12 (17) ◽  
pp. 7230
Author(s):  
Zhengfa Chen ◽  
Dongmei Shi
Keyword(s):  
Spatial Distribution ◽  
Spatial Structure ◽  
Yunnan Province ◽  
Hot Spot ◽  
Mountain Region ◽  
Cold Spot ◽  
Structure Characteristics ◽  
Spot Area ◽  
Slope Farmland ◽  
Southern Fringe

As an important part of farmland, the slope farmland is widely distributed in the central and western plateau mountain region in China. It is necessary to scientifically evaluate the slope farmland quality (SFQ) and analyze the spatial structure characteristics of SFQ to ensure reasonable utilization and partition protection of slope farmland resources. This paper takes the typical plateau mountain region—Yunnan Province in China—as an example and systematically identifies the leading factors of SFQ. The sloping integrated fertility index (SIFI) is adopted to reflect the SFQ. The evaluation system is built to quantitatively evaluate the SFQ and the spatial structure characteristics of SFQ were analyzed by a geostatistical model, autocorrelation analysis and spatial cold–hot spot analysis. The results show that the SFQ indexes in Yunnan Province are between 0.36 and 0.81, with a mean of 0.59. The SFQ grade is based on sixth-class, fifth-class, seventh-class and fourth-class land. The SFQ indexes present a normal spatial distribution, and the Gaussian model fits well with the semi-variance function of the spatial distribution of SFQ indexes. Furthermore, the spatial distribution of SFQ indexes is moderately autocorrelated. The structural factors play a major role in the spatial heterogeneity of SFQ indexes, but the influence of random factors should not be ignored. The spatial distribution of SFQ grades has a significant spatial aggregation characteristic, and the types of local indicators of spatial association (LISA) are based on high–high (HH) aggregation and low–low (LL) aggregation. The cold spot and hot spot distributions of SFQ grades display the significant spatial difference. The hot spot area is mainly distributed in Central Yunnan and the Southern Fringe, while the cold spot area mainly distributes in the Northeastern Yunnan, Northwestern Yunnan and Southwestern Yunnan. This study could provide a scientific basis for SFQ management and ecological environment protection in the plateau mountain region.

Soil productivity in the Yunnan province: Spatial distribution and sustainable utilization

2015 ◽  
Vol 147 ◽  
pp. 10-19 ◽  
Author(s):  
Duan Xingwu ◽  
Rong Li ◽  
Zhang Guangli ◽  
Hu Jinming ◽  
Fang Haiyan
Keyword(s):  
Spatial Distribution ◽  
Yunnan Province ◽  
Soil Productivity ◽  
Sustainable Utilization

scholarly journals Spatial Distribution of Leptospirosis and Land Use in Bantul District, 2010-2018

2020 ◽  
Vol 4 (1) ◽  
pp. 31
Author(s):  
Nur Lathifah Syakbanah
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Spatial Analysis ◽  
Environmental Changes ◽  
Distribution Patterns ◽  
Effective Control ◽  
Residential Areas ◽  
Populations At Risk ◽  
Surveillance Programs ◽  
The Government

Land use is an important environmental factor in the dynamics of human health. In the case of leptospirosis, environmental transmission cycles are caused by rat transition, environmental changes and populations at risk. Utilization of GIS-based spatial analysis may help detecting distribution patterns of leptospirosis cases, allocating resources and planning effective control and surveillance programs in endemic areas. This study aims to analyze the spatial distribution of leptospirosis based on land use and stream flow in Bantul District, 2010-2018. This ecological study was conducted in Bantul District, Yogyakarta for 9 years. Spatial analysis overlays processed data on leptospirosis cases per village and land use maps of 2016 using QGIS 3.0. Spatial distribution of 12 of high leptospirosis villages (18-35 cases) are in residential areas, tributaries, croplands, irrigated fields, rain-fed rice fields, and plantations. Those villages was crossed by major river basin which is potentially as transmission media of leptospirosis cases after heavy rainfall. It is suggested to increase the Early Awareness and Alert (EAA) system by active surveillance of early case finding from the government and endemic villagers.

scholarly journals Measuring And Mapping The State Of Food Insecurity In Rajasthan, India

2021 ◽  
Vol 14 (1) ◽  
pp. 33-40
Author(s):  
Rajput Swati ◽  
Arora Kavita
Keyword(s):  
Spatial Distribution ◽  
Food Security ◽  
Food Insecurity ◽  
Four Dimensions ◽  
Multiple Factors ◽  
Global Issue ◽  
The Government ◽  
High Level ◽  
The Relationship ◽  
Very High

Food insecurity is a global issue that persists at various scales and intensity. It is linked to irregularity or uncertainty of food, water and fuel and can develop under the influence of multiple factors. Food availability, accessibility, consumption and stability are the four broad dimensions of food security. This paper analyses the relationship between these four dimensions and food insecurity for 33 districts in Rajasthan, India, using the data collected from the published documents, periodicals and websites of the government or other authentic sources. To analyse the link between these four dimensions, several indicators were taken into consideration. The collected data was used to rank the districts based on their level of food insecurity. Thus, the results include categorization of the districts into four zones based on the values of the variables. The results are presented through maps, which show the spatial distribution of food insecurity. It can be concluded, that the districts of Banswara, Dungarpur, Udaipur, Bharatpur, Rajsamand, Dhaulpur and Jalore have a very high level of food insecurity.

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