Spatial Behavior of Soil Erodibility in the La Villa River Basin, Panama

Introduction: Soil erodibility is an important factor in understanding the erosion that takes place in a territory. This is a parameter that can behave erratically in small spaces, but that describes a trend in larger spaces. Aim: Determine the K factor of soil erodibility in the La Villa-Panama river basin. Place and Duration of Study: La Villa River Basin-Azuero Peninsula, Panama. 2010-2012. Methodology: 98 points of the La Villa river watershed were sampled. Factor K was calculated using the adaptation to the sol-erodibility nomogram. The percentage of organic matter, structure class (in the field), permeability (combination permeameter) and the percentages of sand, silt and very fine sand (Bouyoucos method) were determined. To obtain the most complete information possible on the distribution of erodibility, a superficial interpolation of the point values ​​corresponding to the soil samples taken was carried out. The software used was Arcview 3.3 and the Spatial Analyst extension. The interpolation method was IDW (Inverse Distance Weight). The erodibility values ​​were categorized into seven intervals in such a way that it was possible to observe the differences on the map. Results: The erodibility values ​​were influenced by the content of organic matter and coarse particles (percentage of sand and silt + very fine sand) of the soil. In the province of Herrera, 86% of the land surface and 76% in the province of Los Santos presents susceptibility to erosion in the ranges of 0.032 to 0.043 Ton ha h ha-1 Mj-1 mm-1. Conclusion: The results indicate that 80% of the soils of the La Villa river basin present a moderately high erodibility factor, with the highest values ​​being registered in the upper middle zone.

Using the Archydro tool for watershed delineationCase of the Kherzet Youcef mine, North-eastern Algeria

This research article is attempted on the study of the morphological characteristics of the oued Loussif sub-watershed, located in the Wilaya of Sétif, Algeria. This study is part of a more general study on the hydrogeological study of the Kherzet Youcef deposit. In all fields interested in the study of spatial phenomena, a need for automation is emerging, especially for geographical structures of the ‘network’ type, given their systemic organization of space that is not explained in databases of geographical data. In order to meet this need for automation, the use of Geographic Information Systems has proven to be cost-effective. Morphological characteristics such as flow accumulation, flow direction and stream network were extracted on the basis of the digital elevation model (DEM), and the results were interpreted and analyzed. The geographic information system (GIS) based approach with the use of DME facilitates the understanding of the different morphological features represented in the thematic matrix data maps, and the correlation between flow accumulations, flow direction, stream order and stream network has been well explored. The study represents the morphological characteristics extracted from the DEM. The software used to perform the global analysis was ESRI ArcGIS version 10.8 with the ESRI Spatial Analyst and ArcHydro extension. Morphological features are effective in understanding the spatial distribution of the watercourse network and identifying potential groundwater locations.

Identification of Areas for Sustainable Settlements in Highly Conflicted Protected Areas Using ArcGIS Spatial Analyst: A Case of Chobe District, Botswana

The increasing human settlements around protected areas is a significant cause of the shrinking size of conservation areas globally. This is an alarming situation, especially in countries where protected areas significantly contribute to the National economy. The use of new tools to solve Land use conflicts that exist around protected areas is needed. This study employed the weighted overlay analysis using ecological, social and economic factors to model suitability for developing settlements in Chobe District, an international tourist destination in Northern Botswana, using ArcGIS spatial analyst. The majority of the land (83.4%) in Chobe is not suitable for settlement, while suitable areas that could for settlement remain relatively small (0.3% of the land). This study suggests that more land for settling the increasing population be created out of Chobe District to avoid encroachment on the conservation areas. The study demonstrated that ArcGIS spatial analyst model builder could be integrated into the land resource planning process of protected areas, making it a handy tool for the analysis and the identification of ecological, economic and social factors, thus establishing an excellent area for further research, especially for sustainable management of protected areas.

Simulation of runoff in Baitarani basin using composite and distributed curve number approaches in HEC-HMS model

The present study was conducted in Baitarani basin up to Anandapur gauging station of Odisha covering an area of 8603.7 km2. Pre-processing of basin from digital elevation model (DEM) was done using HEC-Geo-HMS extension and spatial analyst tool in ArcGIS. These pre-processed files were then imported to HEC-HMS for simulating runoff. In this study, runoff simulation was done using two methods, viz., composite and distributed curve number (CN) approaches. SCS curve number method was used for computation of runoff volume, SCS UH method for direct runoff, constant- monthly varying base flow method for base flow and Muskingum method for flow routing. The model was calibrated and validated using both composite and distributed CN approaches. Data from 1st January, 2007 to 31st December, 2013 were used for calibration and 1st January, 2014 to 31st December, 2016 were used for validation. During the calibration period of composite CN approach, the statistical parameters like Nash-Sutcliffe efficiency (NSE), Coefficient of determination (R2), Percent bias (PBIAS) and RMSE-observations standard deviation ratio (RSR) were found to be 0.51, 0.63, 12.82 and 0.7, respectively and during the validation period they were found to be 0.53, 0.54, -19.73 and 0.7, respectively. In case of distributed CN approach, the statistical parameters like NSE, R2, PBIAS and RSR were found to be 0.62, 0.63, -8.64 and 0.6, respectively during the calibration period and 0.67, 0.66, -2.25 and 0.6, respectively during the validation period. The study indicated that distributed CN approach is more accurate than composite CN approach in simulation of runoff using HEC-HMS model.

Study on Spatial Imbalance and Determinants of E-Commerce Development in Zhejiang, China

As a world-famous and well-developed e-commerce region, the development of e-commerce in Zhejiang province has always attracted people’s wide attention. Based on publicly available e-commerce transaction-related data, basic geographic data, and regional economic and social development data, we use the Gini coefficient to measure the imbalance of e-commerce development in Zhejiang province during 2017–2019. With the help of spatial analyst tools in ArcGIS desktop, the cluster and outlier analysis method is used to study the spatial pattern of e-commerce development in the province at the district or county-level city scale. To explore the causes of spatial aggregation and imbalance of e-commerce in Zhejiang province quantitatively, the paper proposes a geographical weighted regression (GWR) model with 15 economic and social development-related indicators. GWR and ordinary least squares (OLS) analysis indicate that 5 of the 15 selected indicators are highly related to the development of regional e-commerce development in Zhejiang, China.

Regional Geotechnical Mapping Employing Kriging on Electronic Geodatabase

A regional geotechnical map was developed by employing kriging using spatial and s geostatistical analysis tools. Many studies have been carried out in the field of topography, digital elevation modeling, agriculture, geological, crop, and precipitation mapping. However, no significant contribution to the development of geotechnical mapping has been made. For the appraisal of a geotechnical map, extensive field explorations were carried out throughout the geotechnically diversified plateau spread over an area of approximately 23,000 km2. In total, 450 soil samples were collected from 75 data stations to determine requisite index properties and soil classification for the subsequent allowable bearing capacity evaluation. The formatted test results, along with associated geospatial information, were uploaded to ArcMap, which created an initial input electronic database. The kriging technique of geostatistical analysis was determined to be more feasible for generating a geotechnical map. The developed map represents the distribution of soil in the region as per the engineering classification system, allowable bearing capacity, and American Association of State Highway and Transportation Officials (AASHTO) subgrade rating for 1.5-, 3.0-, and 4.5-m depths. The accuracy of the maps generated using kriging interpolation technique under spatial analyst tools was verified by comparing the values in the generated surface with the actual values measured at randomly selected validation points. The database was primarily created for the appraisal of geotechnical maps and can also be used for preliminary geotechnical investigations, which saves the cost of soil investigations. In addition, this approach allows establishing useful correlations among the geotechnical properties of soil.

Spatial Visualization of Geochemical Data: Application to the Chichinautzin Volcanic Field, Mexico

The presence of spatial magma heterogeneities in volcanic monogenetic fields is a major observation discussed as well synthesized for worldwide volcanic fields. Magma heterogeneities still have not been visualized in the form of detailed spatial analyst tools, which could further help structuring works of geological mapping, volcanic hazard, and geoheritage evaluations. Here we synthetized 32 published datasets with a novel geochemical mapping model inspired by sub-disciplines of geomatic in one of the most documented monogenetic fields on earth: the Chichinautzin Volcanic Field (CVF) in Mexico. The volcanic units from CVF are covering the 2500 km2 area, and its neighbor stratovolcanoes are bordering the limit of most volcanic centers (Popocatepetl, Iztaccihuatl, and Nevado de Toluca). The results illustrate polygons and point map symbols from geochemical markers such as Alkalis vs SiO2, Sr/Y, and Ba/Nb. The geochemical heterogeneity of the CVF monogenetic bodies decreases as it approaches the Popocatepetl-Iztaccihuatl stratovolcanoes. This alignment is not observed in the occidental CVF portion near the flank of Nevado de Toluca, but geochemical anomalies associated to markers of continental crust interaction such as Sr/Y follow elongated patterns that are not strictly following structural lines and faults mapped on surface.

Determination of tree height according to data of raster images different resolution

The collection of information on the growth and development of trees is the basis for planning forestry and horticulture, while the relevance and reliability of such data defines the quality of forest and park inventory outputs. Currently in Ukraine, the height of growing trees and shrubs is measured mostly by clinometer. The enhancement of unmanned aerial vehicles (UAVs) and methods of processing the collected information allow to amplify the level of quality and accuracy of the collected data. Our goal was to consider the possibility of determining the height of trees based on aerial photography materials obtained by UAVs and to assess the accuracy of measured indicators modeling crown height at different spatial resolutions. Here we used methods of creating a digital canopy height model (CHM) from aerial photographs obtained by UAVs. We produced 8 digital elevation and terrain models for the calculation of CHM. Raster image analysis was performed using the ArcGIS software and Spatial Analyst toolkit using the Focal statistics filter. We have confirmed the possibility of CHM utilization to measure the height of trees in structurally homogeneous stands. Here we have shown the change of height values of Scots pine trees (Pinus sylvestris L.) and the deviation of the arithmetic mean value of the height for model trees applying the raster images with different spatial resolutions. Predicted tree heights were compared with the empirical values, which were obtained directly measuring the felled sample trees with the addition of stump height. CHM analysis with a cell size of 0.04 m2 and 0.1 m2 shows the smallest height deviations for model trees in the stand. The deviations relative to arithmetic mean were 2.3 % and 2.6 %. Raster images with a more coarse resolution (more than 1 m2) are not recommended in forest practice, since their utilizing entails a measurement error of 17% and higher, and thus exceeding the permissible deviations in tree height measurements according to the forest inventory guidelines currently applied in Ukraine.

Assessment of the Catastrophic Asia Floods and Potentially Affected Population in Summer 2020 Using VIIRS Flood Products

Since 2 June 2020, unusual heavy and continuous rainfall from the Asian summer monsoon rainy season caused widespread catastrophic floods in many Asian countries, including primarily the two most populated countries, China and India. To detect and monitor the floods and estimate the potentially affected population, data from sensors aboard the operational polar-orbiting satellites Suomi National Polar-Orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration (NOAA)-20 were used. The Visible Infrared Imaging Radiometer Suite (VIIRS) with a spatial resolution of 375 m available twice per day aboard these two satellites can observe floodwaters over large spatial regions. The flood maps derived from the VIIRS imagery provide a big picture over the entire flooding regions, and demonstrate that, in July, in China, floods mainly occurred across the Yangtze River, Hui River and their tributaries. The VIIRS 5-day composite flood maps, along with a population density dataset, were combined to estimate the population potentially exposed (PPE) to flooding. We report here on the procedure to combine such data using the Zonal Statistic Function from the ArcGIS Spatial Analyst toolbox. Based on the flood extend for July 2020 along with the population density dataset, the Jiangxi and Anhui provinces were the most affected regions with more than 10 million people in Jingdezhen and Shangrao in Jiangxi province, and Fuyang and Luan in Anhui province, and it is estimated that about 55 million people in China might have been affected by the floodwaters. In addition to China, several other countries, including India, Bangladesh, and Myanmar, were also severely impacted. In India, the worst inundated states include Utter Pradesh, Bihar, Assam, and West Bengal, and it is estimated that about 40 million people might have been affected by severe floods, mainly in the northern states of Bihar, Assam, and West Bengal. The most affected country was Bangladesh, where one third of the country was underwater, and the estimated population potentially exposed to floods is about 30 million in Bangladesh.