Fuzzy Criteria based Recognition of Groundwater Prospective Zones using GIS and Remote Sensing

Singh Priyamvada*, Hasnat Mariya and Singh Pitam

The objective of the present study is to provide a model for groundwater prospective zones based on different geological properties, i.e. soil type geomorphology, geology, land use, lineament and drainage using remote sensing and fuzzy criteria under GIS environment. Different groundwater indicators on thematic maps are given membership grades and ranking on the basis of their groundwater holding property. All of the thematic maps are combined with the fuzzy overlay operation.

On the basis of given fuzzy membership grade and ranking, different groundwater prospective zones have been delineated in the study area. Different types of five categories of groundwater prospective zones as excellent (1131.30 km2), very good (1026.42 km2), good (498.16 km2), moderate (719.29 km2) and poor (735.54 km2) have been demarcated. A major portion of the study area has excellent to moderate prospects while a few spotted areas have poor prospects of groundwater.

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Assessing Factors that affect Selection of Adaptation Strategies for Small-Scale Fishing Communities

Syafei Arie*, Wardhani Ayu, Aisyah Dinesta, Ciptaningayu Tresta, Assomadi Abdu, Boedisantoso Rachmat, Slamet Agus and Hermana Joni

Climate change is a global phenomenon that impacts nature. One of the impacts is the increase in the earth’s surface temperature that increases the sea level and causing a reduction in coastlines. In addition, fishermen's productive physical capital such as vessels, jetties and fishing gear, are vulnerable to the changing climate. Therefore, fishermen need to use adaptation strategies to survive in coastal areas. This study was undertaken in Tambakrejo, Sumbermanjing, Malang. Data were collected using surveys (questionnaires). Their understanding of climate change affects their choice of adaptation strategies.

Our findings reveal that fishermen's understanding of climate change, perceived feelings of impacts and their characteristics are important variables when choosing adaptation strategies. Perceived feeling of sea level increases and changes of fish species are significant factors that affect them in selecting adaptation strategies such as create new mangrove area, construction of breakwater and the use of new fishing technologies. The limitation of fishermen's knowledge of climate change should lead to active promotion and education from stakeholders and/or government for successful implementation of any adaptation strategies.

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Variable Importance Assessment for Colorization of Grayscale Aerial Images based on Random Forest, Adaptive Boosting and Stochastic Gradient Boosting

Jee Hee Koo, Dae Kyo Seo and Yang Dam Eo*

Colorization is a process of assigning colors to pixels of grayscale images. In the case of aerial images, this technique is essential for improving visual appeal of images and for city monitoring. However, it is difficult to select the variables for optimal results because the aerial images are composed of complex structures influenced by factors such as solar elevation angle, season and sensor parameters. In this study, variables affecting the colorization of grayscale aerial images are selected using random forest (RF), adaptive boosting (AdaBoost) and stochastic gradient boosting (SGB), which clarify the importance of variables. In the case of RF, the variable importance is determined by evaluating the decrease in accuracy which is performed by measuring the prediction accuracy by randomly permuting the variable.

In the cases of AdaBoost and SGB, extended the existing decision tree method, the sum of all decreases in Gini impurity for a given variable is calculated and the result is then normalized by the number of iterations or the number of trees. The selected variables are intensity; gray-level co-occurrence matrix (GLCM) obtained through angular second moment (ASM), contrast, correlation and entropy; speed-up robust features (SURF) reduced to 32 dimensions through principal component analysis (PCA): mean and variance. The importance of variables evaluation revealed that the importance of intensity is dominant whereas SURF used for common colorization methods has no effect on grayscale aerial image colorization. Furthermore, colorization is performed on the basis of important variables only which results in no difference from the colorization result obtained by using all variables.

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An approach to delineate groundwater potential zones in Orenburg, Russia

Choudhary K.*, Boori M.S. and Kupriyanov A.

Groundwater is one of the valuable natural resources determining the health of a human being in an area. The present research investigated the hydrogeological determinants to assess the sensitivity of each factor to the intrusion pattern and to map the regional groundwater potential zone for the dry humid continental watershed in Orenburg, Russia using a geographic information system (GIS) and satellite remote sensing. In the context of considerable change in the use of groundwater pattern, particularly with continuously increasing demand for groundwater due to growing population, expansion of area under irrigation and economic progress, groundwater potential zones are demarcated by integrating the highly impacting thematic layers such as land use, slope, soil, drainage density, geomorphology etc. The thematic layers are prepared from the remote sensing satellite images, ground truth data and secondary data. CartoDEM (30 m), SOI toposheet, Landsat 8 (30 m) and high-resolution satellite images from Google Earth were used for the preparation of thematic maps. ArcGIS software was utilized to manipulate these data sets. Weight is assigned to each class for each thematic map according to their characteristic and interrelationship with groundwater.

All the thematic layers are unified into a GIS domain and assigned weight values are added for each polygon in the attribute table. Weights were assigned to all above factors according to their effectiveness, sensitivity and relevance to groundwater potentiality. Furthermore, the resulting groundwater potential map has been classified into five classes such as very high, high, moderate, low and very low based on hydro geomorphological condition. The results provide significant information and can be used by local authorities for groundwater management.

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