Weighted Overlay Analysis Research Articles

Site-suitability Analysis for Turmeric in Jaintia Hills of Meghalaya, India, using Analytical Hierarchical Process and Weighted Overlay Analysis:A Comparative Approach

India is the largest producer, consumer and exporter of turmeric ( Curcuma longa L.). The Lakadong variety of turmeric is endemic to Jaintia Hills of Meghalaya, India. It is considered as the best quality turmeric containing 7.5% curcumin, which is about three times higher than the other varieties (2–3%). This study identifies potential sites for turmeric cultivation in Jaintia Hills using geospatial techniques, viz. analytical hierarchical process (AHP) and weighted overlay analysis (WOA). WOA identified a total of 162,263.70 ha suitable for the expansion of Lakadong variety of turmeric in Jaintia Hills, of which 18% was highly suitable, 31% moderately suitable and 32% was marginally suitable. In the case of AHP, 21% area was found to be highly suitable, 25% moderately suitable and 45% marginally suitable.

GIS-based earthquake-triggered-landslide susceptibility mapping with an integrated weighted index model in Jiuzhaigou region of Sichuan Province, China

Abstract. A Mw=6.5 earthquake struck the Jiuzhaigou region of Sichuan Province, China, at 21:19 LT on Tuesday, 8 August 2017, and triggered a large number of landslides. For mitigating the damages of earthquake-triggered landslides to individuals and infrastructures of the earthquake-affected region, a comprehensive landslide susceptibility mapping was attempted with an integrated weighted index model by combining the frequency ratio and the analytical hierarchy process approaches under a GIS-based environment in the heavily earthquake-affected Zhangzha town of the Jiuzhaigou region. For this purpose, a total number of 842 earthquake-triggered landslides were visually interpreted and located from Sentinel-2A images acquired before and after the earthquake at first, and then the recognized landslides were randomly split into two groups to establish the earthquake-triggered landslide inventory, among which 80 % of the landslides were used for training the integrated model and the remaining 20 % for validation. Nine landslide controlling factors were considered including slope, aspect, elevation, lithology, distance from faults, distance from rivers, land use–land cover, normalized difference vegetation index and peak ground acceleration. The frequency ratio was utilized to evaluate the contribution of each landslide controlling factor to landslide occurrence, and the analytical hierarchy process was used to analyse the mutual relationship between landslide controlling factors. Finally, the landslide susceptibility map was produced by using weighted overlay analysis. Furthermore, an area under the curve approach was adopted to comprehensively evaluate the performance of the integrated weighted index model, including the degree of model fit and model predictive capability. The results demonstrated the reliability and feasibility of the integrated weighted index model in earthquake-triggered landslide susceptibility mapping at a regional scale. The generated map can help engineers and decision makers assess and mitigate hazards of the earthquake-triggered landslides to individuals and infrastructures of the earthquake-affected region.

An integrated approach to delineate the groundwater potential zones in Devdari watershed area of Akola district, Maharashtra, Central India

The present research work accentuates the hydrogeological evaluation for Devdari watershed of Maharashtra, Central India, using remote sensing, GIS, and multi influencing factor (MIF). The thematic layers of land use/land cover, groundwater depth, slope, drainage, flow direction, flow accumulation and geomorphology were prepared using IRS-LISS-III satellite data coupled with Shuttle Radar Topography Mission data on 23.50 and 30 m spatial resolution, respectively. The raster layers of these themes were estimated by employing ArcGIS software 10.3 and multi-influencing factor method and subsequently assigned with the relative weights as per their groundwater potential characteristics. For acknowledgement of the groundwater potential map, all the thematic layers and their respective weightage values were subjected to weighted overlay analysis (WOA) method. The evolved map demonstrates six groundwater potential zones in the study area, i.e., poor to nil (0.27 km2), very poor (0.95 km2), poor (17.67 km2), moderate (0.33 km2), good (9.51 km2), very good (14.665 km2) and excellent (1.84 km2). A field check survey was carried out to ascertain the validity of groundwater potential maps. The results of study area disclose that the area of watershed with poor, moderate and good-to-excellent groundwater potential zones is evaluated to allow precipitated water to infiltrate into subsurface and finally contribute to groundwater recharge in the watershed area.

English

Malaria is one of the most killer diseases in our planet earth. It is the primary cause of patient talks, admissions and demise every year in Ethiopia. It is important to reduce the transmission and effects of the problem identifying and mapping the malaria risk area using geospatial technologies. The general objective of the study is to analyze and map malaria prone areas using geospatial tools in Amibara and Gewanie Woredas of Afar Region. The specific objectives are to identify parameters that contribute to malaria hazard in the study area and to classify and map areas at risk of malaria. To achieve the stated objectives, the researchers employed spatial modeling technique particularly Weighted Overlay Analysis (WOA). Climatic data, topographical data and infrastructural data are the major data of the study. These data were processed and analyzed by ArcGIS, Erdas imagine, Idrisi, 3DEM terrain visualization and global mapper software. The result showed that the area is suitable moderately and marginally for malaria. From the total area of the study, 35 and 65% were moderately and marginally suitable for the occurrence of malaria respectively. Therefore, as malaria is one of the killer diseases the concerned bodies should use the technologies to prevent and control the transmission of malaria in the study area and there should be health package to prevent the diseases. Key words: Malaria mapping, geospatial tools.

A land use suitability model for rainfed farming by Multi-criteria Decision-making Analysis (MCDA) and Geographic Information System (GIS)

This study was carried out to analyze the land use suitability of Golestan Province, located in the northeast of Iran, for rainfed farming performance using Geographic Information System (GIS) and Multi-criteria Decision-making Analysis (MCDA) in 2016. First, thematic maps of several environmental variables including soil, climate and topographic variables were obtained. After preparing the raster layers, the environmental requirements of rainfed farming were identified from a comprehensive literature review and asking local experts’ opinions; then they were classified according to FAO (Food and Agriculture Organization of the UN) requirements. In the next step, AHP (Analytic Hierarchy Process)-acquired weights were assigned to the criteria. Then, digital layers were overlaid using Weighted Overlay Analysis (WOA) in ArcGIS. According to the results of land suitability analysis, development of rainfed farming is possible for up to 56 percent of the current land of Golestan Province (about 396,550.5 ha) in the southern and central areas as a long belt from east to west. The results showed that some climatic variables such as temperature, annual rainfall, and sunshine hours were not limiting factors for rainfed farming in this region. However, other environmental variables such as salinity, organic matter, soil erosion, soil texture classes, and the autumn, spring, May and June rainfalls were identified as limiting factors for rainfed farming performance in the northern and northeastern regions of Golestan Province. We also found that slope was a limiting cause in the southern part of this province. Generally, the use of specific management practices such as increasing soil organic matter, saline reduction of lands, conservation tillage, and supplementary irrigation canimprove the quality class of low capability lands to higher suitability classes and increase the quality of environmental resources.

Appraisal of Drinking Water Quality in Lahore Residence, Pakistan

A comprehensive study for the spatial distribution of drinking water quality had been conductedfor residential area of Lahore, Pakistan. The study had made use of the geographic information system(GIS) for geographical representation and spatial analysis of groundwater quality. Physicochemicalparameters including electric conductivity, pH, TDS, Cl, Mg, Ca, alkalinity and bicarbonates from 73 ofthe water samples had been included in the analysis. Water quality data had been geo-referenced followedby its interpolation using inverse distance weighted (IDW) for each of the parameters. Very high alkalinityand bicarbonates values were observed in most parts of the area. For the comprehensive view, water qualityindex map had been prepared using weighted overlay analysis (WOA). The water quality index map wasclassified into five zones of excellent, good, poor, very poor and unfit for drinking as per WHO standardsof drinking water. 21% region had excellent quality of the underground water and 50% was found goodfor drinking. Poor quality of water was found in southeastern part, covering 27% of the study area. Only2% of the area was found under the very poor and unfit water quality conditions for drinking.

Predicting runoff induced mass loads in urban watersheds: Linking land use and pyrethroid contamination

Pyrethroid pesticide mass loadings in the Ballona Creek Watershed were calculated using the volume-concentration method with a Geographic Information Systems (GIS) to explore potential relationships between urban land use, impervious surfaces, and pyrethroid runoff flowing into an urban stream. A calibration of the GIS volume-concentration model was performed using 2013 and 2014 wet-weather sampling data. Permethrin and lambda-cyhalothrin were detected as the highest concentrations; deltamethrin, lambda-cyhalothrin, permethrin and cyfluthrin were the most frequently detected synthetic pyrethroids. Eight neighborhoods within the watershed were highlighted as target areas based on a Weighted Overlay Analysis (WOA) in GIS. Water phase concentration of synthetic pyrethroids (SPs) were calculated from the reported usage. The need for stricter BMP and consumer product controls was identified as a possible way of reducing the detections of pyrethroids in Ballona Creek. This model has significant implications for determining mass loadings due to land use influence, and offers a flexible method to extrapolate data for a limited amount of samplings for a larger watershed, particularly for chemicals that are not subject to environmental monitoring. Offered as a simple approach to watershed management, the GIS-volume concentration model has the potential to be applied to other target pesticides and is useful for simulating different watershed scenarios. Further research is needed to compare results against other similar urban watersheds situated in mediterranean climates.

Sea Level Rise Flood Zones: Mitigating Floods in Surabaya Coastal Area

Sea level rise (SLR) brings with it a negative impact towards Surabaya's coastal area as this particular part of the city is situated only 0-3 meters above sea level. The amount of damage due to the floods indicates the city's level of readiness in facing threats from the flood. With flood height up to 90 centimeters, it is necessary to classify flood risk levels in an attempt to reduce the impact that will occur.This paper identify sea level rise by using least square regression, which generates the trend and prediction of sea level rise. The next analysis is the identification of a potentially disaster due to sea level rise by using multinomial logistic regression. Identification of flood hazard characteristics through weighted-overlay analysis using flood height and duration as variables. It also identifies factors influencing vulnerability using Delphi analysis. AHP Expert is then employed to calculate the weight of each factor. Vulnerable zones are determined using overlay-weighted-sum on each vulnerable factor. These results are then mapped using Raster Calculator method, placing emphasis on risk functions influenced by hazard and vulnerability.The final result is a flood risk zone map which identifies 5 risk levels according to the National Disaster Mitigation Guidance.

석면 공간지식베이스 구축을 통한 석면 노출위험도 작성

Asbestos is a toxic material that can lead to lung cancer and other diseases. There is no information regarding areas in Korea that contain asbestos in nature; consequently we need to manage such areas with care. The purpose of this study was to construct a local graded map of asbestos exposure risk based on the natural occurrence of asbestos in rocks. We first developed a means of evaluating the asbestos exposure risk and produced thematic maps based on a field survey. In addition, we constructed a knowledge base for asbestos through analysis, representation and processes about asbestos data and prepare for the development of an evaluation model for asbestos exposure risk. The spatial analysis of asbestos exposure risk is based on a weighted-overlay analysis using expert opinion and the literature, and a fuzzy-overlay analysis using the uncertainty in the data. The map of asbestos exposure risk, compiled according to the weighted and fuzzy operations, is expected to be used to ensure safety and to reduce the risk of exposure to asbestos.