Appraisal of zones of potential groundwater based on Photo-Geomorphic Study in Semi-Arid tract of Visakhapatnam District,Andhra Pradesh

Photo-geomorphic and hydrogeological studies over an area of 2020 sq km in the semi-arid tract of Visakhapatnam district, have enabled in identifying five zones of potential groundwater/hydromorphic units. Fluvial plain has the highest hydromorphic potential with a weight point score of 25, and coastal plain has poor to very poor potential with a score of 12. Wash plain, rolling/sandy plain, and piedmont plain have good to moderate to poor potential with scores of 20, 17 and 14 respectively. Geophysical surveys and the drilling of exploratory borewells along fractures/fracture traces and abandoned channels, revealed the existence of deep weathered and fractured zones capable of yielding large quantities of water.     

Desertification Vulnerability Assessment Model for a Resource Rich Region: A Case Study of Bellary District,Karnataka, India

Desertification is a global challenge being experienced across countries irrespective of their levels of development. Desertification is a complex negative process involving both natural and human components in terms of their socio-economic attainments. Hence, for identification and assessment of the process, pattern, magnitude and possible impacts of desertification, a multi-disciplinary approach with inter-disciplinary framework of analysis is essential. This study has made such an attempt to develop a comprehensive desertification vulnerability assessment Model on the basis of multi-variate Principal Component Analysis along with the Geographic Information System framework by using natural and socio-economic resources data inputs from census, satellite data and other sources. Bellary district, located in a rapidly growing southern state of India, Karnataka which is afflicted with various natural and development issues such as droughts, backwardness, haphazard mining, over irrigation, and associated effects of land degradation, siltation and water pollution has been chosen for the study. The inter-disciplinary framework based desertification vulnerability assessment model has assessed that 1379.198 km² area (15.55%) of Bellary district is prone to desertification (based on the satellite data IRS LISS III data of Dec 2005, Feb 2006, March 2006 and April 2006). In addition, 3229.337 km² (36.40%) is under moderate vulnerability which is fragile. Hence, unless proper development intervention and conservation measures are taken well in advance, almost more than half of Bellary district (51.95%) will be vulnerable to desertification. Spatially, the talukas that are seriously affected and that require development intervention on high priority are: Sandur, Kudligi, Hospet and Bellary which are the prime talukas of the district.     

Suitability Analysis of Groundwater Quality for Domestic and Irrigation Usage in Yamuna Nagar District, India: A GIS Approach

The main source to fulfill the enormous needs of water both for domestic and agricultural purposes in the densely cultivated region of Yamuna Nagar district of Haryana (India) is the water under earth. Since enough quantity of good quality water has been readily available, the water quality concerns are often neglected. In the present study analysis of the geochemical characteristics of groundwater to assess its suitability for domestic and irrigation purposes has been done. Fifty-five samples were collected in the months of June (pre-monsoon) and October (post-monsoon) from the bore wells. These samples were analysed for various parameters and were compared with various national and international standards to determine the suitability of water for domestic and irrigation use. The thematic maps for hydrogen ion concentration (pH), total dissolved solids (TDS), total hardness (TH), electric conductivity (EC), sodium adsorption ratio (SAR), percent sodium (Na%) and residual sodium carbonate (RSC) were prepared in GIS environment. These maps were further classified as per given standards to study the spatial variations of quality parameters and their suitability for drinking and irrigation purposes. Investigations revealed that groundwater in general was hard for domestic use. However it was within the safe limits for drinking. Furthermore groundwater quality was well within the desirable to permissible limits for irrigation purpose.     

Spatial and Temporal Variation of Groundwater Level and its Relation to Drainage and Intrusive Rocks in a part of Nalgonda District,Andhra Pradesh,India

Drainage and lineaments play an important role in the flow of groundwater. The objective of this study is to assess the groundwater level and its relation to drainage and lineaments in a hard rock region of a part of Nalgonda district, Andhra Pradesh, southern India. The region predominantly comprise of granites and gneisses. Groundwater level was measured in 42 representative wells in this study area from March 2008 to January 2010 once in every two months. Observed groundwater levels were compared with drainage and dyke density. Groundwater level fluctuation in low drainage density region is generally greater than those in moderate and high drainage density regions. The dykes do not act as barriers for groundwater flow as they are highly weathered. The quantity and flow of groundwater in this region is predominantly controlled by drainage density, intensity of weathering and presence of fractures. Thus the study indicate that the drainage density play a major role in groundwater level fluctuation and as the dykes are weathered, they do not affect the groundwater flow in this shallow unconfined aquifer.     

Groundwater Prospect Zoning Using Remote Sensing and Geographical Information System: A Case Study in Dala-Renukoot Area, Sonbhadra District, Uttar Pradesh

In the present study, ground water prospect zones in Dala-Renukoot area, in Sonebhadra district. Uttar Pradesh, India have been delineated, through integration of various thematic maps using ARC/INFO GIS. Thematic maps in respect of geology, geomorphology. slope, drainage, land-use/land cover, lineament and lineament intersection frequency were prepared on 1:50,000 scale using remote sensing and conventional methods. These maps were scanned and registered with reference to a basemap and are input as separate layers using ARC/INFO GIS. Each theme was assigned a weightage depending on its influence on the movement and storage of groundwater and each unit in every theme map is assigned a knowledge based ranking from 1 to 5 depending on its significance to groundwater occurrence. All the themes are overlaid, two at a time and the resultant composite coverage is classified into five groundwater prospect categories. This output map is correlated with the groundwater data collected in the field.     

Estimation of LAI and above-ground biomass in deciduous forests: Western Ghats of Karnataka, India

This study demonstrates the potentials of IRS P6 LISS-IV high-resolution multispectral sensor (IGFOV  6 m)-based estimation of biomass in the deciduous forests in the Western Ghats of Karnataka, India. Regression equations describing the relationship between IRS P6 LISS-IV data-based vegetation index (NDVI) and field measured leaf area index (ELAI) and estimated above-ground biomass (EAGB) were derived. Remote sensing (RS) data-based leaf area index (PLAI) image is generated using regression equation based on NDVI and ELAI (r² = 0.68, p ≤ 0.05). RS-based above-ground biomass (PAGB) image was generated based on regression equation developed between PLAI and EAGB (r² = 0.63, p ≤ 0.05). The mean value of estimated above-ground biomass and RS-based above-ground biomass in the study area are 280(±72.5) and 297.6(±55.2) Mg ha⁻¹, respectively. The regression models generated in the study between NDVI and LAI; LAI and biomass can also help in generating spatial biomass map using RS data alone. LISS-IV-based estimation of biophysical parameters can also be used for the validation of various coarse resolution satellite products derived from the ground-based measurements alone.     

基于GIS的城镇建设用地发展适宜性评价——以常州市金坛区为例

为更加深入地了解村镇尺度城镇建设用地发展适宜性情况,提高土地利用综合效益,本文以常州市金坛区遥感影像数据和土地利用现状数据为基础,采用层次分析法和GIS空间分析技术,选择自然、区位、生态和土地转换适宜度四大类10个指标,建立了适用于平原地区的具有区域代表性的城镇建设用地发展适宜性评价指标体系,分析了金坛区城镇发展适宜区分布与空间自相关特征。研究结果能为城市规划、土地规划等提供依据,尤其在城镇建设用地发展布局上具有重要的现实意义。     

基于POI数据的广场功能研究——以兰州市城关区为例

基于ArcGIS中的网络分析法,选取兰州市城关区东方红广场、五泉下广场和万达广场构建沿不同等级交通线的1 min、1.5 min、3 min 3个缓冲区圈层,同时统计不同缓冲区内居住设施、公共管理与公共服务设施和商业设施三大类兴趣点(point of interest,POI)数据的数量与占比.结果显示,东方红广场的交...     

Assessment of Late Blight Induced Diseased Potato Crops: A Case Study for West Bengal District Using Temporal AWiFS and MODIS Data

Remote sensing technology becomes an effective and inexpensive technique for detecting disease in vegetation. In this study, an attempt has been done to discriminate healthy and late blight affected crop using remote sensing based indices such as NDVI and LSWI. NDVI and LSWI spectral profiles between healthy and late blight affected crop shows large difference. Mean difference in reflectance between two acquired dates Jan. 10 and 29, 2009 crop clusters varied from 31.28 % in red band, 7.7 % in NIR band and 6.23 % in SWIR bands in healthy crops while in late blight affected crops it is ?15.5 % in red, 44.4 % in NIR and ?14.61 % in SWIR bands. Negative percentage differences in reflectance indicate reflectance increases from Jan. 10, 2009 to Jan. 29, 2009, while positive difference indicate decrease in reflectance between the two dates. Since potato is an irrigated crop, these differences in reflectance are attributed to prevalent disease at that time. It is found that severely affected areas are Bardhman, Arambag, Bishnupur, Ghatal and Hugli taluka with crop damage areas are 4036.66, 1138.68, 2025.23, 469.15, and 380.08 ha, respectively.     

Entropy Approach for Assessment of Urban Growth: A Case Study of Jaipur,INDIA

In India the last 30 years had witnessed a radical transformation of urban scene. In particular, during this period, the one lakh cities and million plus cities began to grow rapidly. In the present study, urban growth of Jaipur city in the last 31 years (1975–2006) was assessed. Jaipur ranks 11th in India with a total population of 2.3 million and has shown a consistent increase in the past 50 years. It is one of the fastest growing mega cities of the country with an annual average growth rate of 4.5% which is quite high from the national urban growth rate. Remote sensing and GIS have been used to extract the information related to urban growth-built up area and its spatial and temporal variation. The Shannon’s entropy at two levels (city as a whole and ward wise) is computed in order to quantify the form and patterns of urban growth using built up area as spatial phenomena. Further, multivariate statistical techniques have been used to establish the relationship between the urban growth and its causative and determining factors. Results of this study reveal that the growth rate of built up in Jaipur has outstripped the rate of population growth. Shannon’s entropy quantifies as dispersed form of urban growth till 2000 and after it, there is relative compactness in 2006.     

基于GIS的平原区雨水资源潜力估算与利用研究--以崂山区为例

针对目前水资源问题的越发严重,雨水资源的利用受到越来越多的关注和重视。充分利用雨水资源可以补给城市水源,涵养地下水,防治雨洪灾害。平原区作为人类活动的主要区域,雨水的利用更具有研究意义。本文以崂山区的平原区为例,估算了雨水资源总量、雨水资源理论潜力和雨水资源实际潜力,然后根据实际情况对雨水资源的利用进行了研究分析。     

矿业城市景观格局时空演变分析——以淮南市潘集区为例

以淮南市潘集区2005、2009和2013年3期遥感影像为数据源,以景观生态学理论为基础,结合遥感与地理信息系统技术,定量分析了潘集区近10年来土地利用动态变化和景观格局时空演变特征。结果表明,2005—2013年间潘集区建设用地面积大幅度增加,景观多样性随时间推移整体呈下降趋势。研究区内由于煤炭资源开发等人类活动的影响,出现了大量采空区积水,使得区域内景观格局变化十分复杂。本文试图探讨矿业城市人类活动影响下景观格局变化的一般规律,为相关政府部门城市规划及科学决策提供参考。     

基于空间抽样的上海市GlobeLand302020数据精度评估

针对上海GlobeLand302020土地覆盖产品,应用顾及空间异质性的类别-异质性分层抽样方法进行抽样,将研究区各地图类别划分为匀质区和异质区子类,按照内曼分配方法布设验证样本,在研究区域内抽取2500个验证像素,并参考同时期多源Google Earth高分遥感影像数据进行样本判读,获得参考分类即真实类别信息,对区域...     

城市建筑水平特征对城市热环境效应的影响——以大连市中山区为例

以大连市中山区的遥感和建筑等多源数据为基础,结合单窗算法和相关分析方法,研究分析了2002—2014年研究区的地表温度空间分异特征及地表温度与建筑密度的相关性。研究结果表明:(1)2002—2014年地表温度高温区域多分布在中山区西北部、解放路和中南路的沿线,且温度增加明显,东北部由于填海造陆温度明显升高;(2)高密度和较高密度的地块主要分布在青泥洼天津街商业区,大部分低、较低、中密度地块分布在解放路和中南路沿线;(3)2002年、2014年,地表温度与建筑密度呈现中等相关性,相关系数分别为0.514、0.537。     

基于GIS技术的居住区级公共服务设施配置研究——以沈阳市沈水新城为例

以沈阳市沈水新城为例,对居住区公共服务设施布局进行研究。应用GIS技术在空间布局和综合评价方面的优势对公共服务设施进行定性、定量、定位评价分析,建立公共服务设施规划选址评价体系,达到了通过定量指标选址的目的,增强了规划的科学性,提高了公共服务设施选址的效率。为地理信息技术应用在公共服务设施配置选址领域提供了技术、方法和理论支持。     

基于GIS的学校型应急避难场所空间布局与优化——以汕头市濠江区为例

学校是一种重要的应急避难场所资源,对城市应急救援和防灾管理发挥了重要的作用。本文以濠江区为例,从可达性、服务面积、服务人口比、服务缺口4个指标,结合叠加分析等空间分析工具评价其学校型应急避难场所空间布局合理性。结果表明:目前濠江区学校避难场所的总体规划布局不合理,服务范围无法基本覆盖,可达性相对较差,服务缺口相对较大。     

Landslide Mapping and Assessment by Integrating Landsat-8, PALSAR-2 and GIS Techniques: A Case Study from Kelantan State,Peninsular Malaysia

Integration of satellite remote sensing data and GIS techniques is an applicable approach for landslide mapping and assessment in highly vegetated regions with a tropical climate. In recent years, there have been many severe flooding and landslide events with significant damage to livestock, agricultural crop, homes, and businesses in the Kelantan river basin, Peninsular Malaysia. In this investigation, Landsat-8 and phased array type L-band synthetic aperture radar-2 (PALSAR-2) datasets and analytical hierarchy process (AHP) approach were used to map landslide in Kelantan river basin, Peninsular Malaysia. Landslides were determined by tracking changes in vegetation pixel data using Landsat-8 images that acquired before and after flooding. The PALSAR-2 data were used for comprehensive analysis of major geological structures and detailed characterizations of lineaments in the state of Kelantan. AHP approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index, land cover, distance to drainage, precipitation, distance to fault, and distance to the road were extracted from remotely sensed data and fieldwork to apply AHP approach. The excessive rainfall during the flood episode is a paramount factor for numerous landslide occurrences at various magnitudes, therefore, rainfall analysis was carried out based on daily precipitation before and during flood episode in the Kelantan state. The main triggering factors for landslides are mainly due to the extreme precipitation rate during the flooding period, apart from the favorable environmental factors such as removal of vegetation within slope areas, and also landscape development near slopes. Two main outputs of this study were landslide inventory occurrences map during 2014 flooding episode and landslide susceptibility map for entire Kelantan state. Modeled/predicted landslides with a susceptible map generated prior and post-flood episode, confirmed that intense rainfall throughout Kelantan has contributed to produce numerous landslides with various sizes. It is concluded that precipitation is the most influential factor for landslide event. According to the landslide susceptibility map, 65% of the river basin of Kelantan is found to be under the category of low landslide susceptibility zone, while 35% class in a high-altitude segment of the south and south-western part of the Kelantan state located within high susceptibility zone. Further actions and caution need to be remarked by the local related authority of the Kelantan state in very high susceptibility zone to avoid further wealth and people loss in the future. Geo-hazard mitigation programs must be conducted in the landslide recurrence regions for reducing natural catastrophes leading to loss of financial investments and death in the Kelantan river basin. This investigation indicates that integration of Landsat-8 and PALSAR-2 remotely sensed data and GIS techniques is an applicable tool for Landslide mapping and assessment in tropical environments.     

Landslide Hazard Assessment Using Random SubSpace Fuzzy Rules Based Classifier Ensemble and Probability Analysis of Rainfall Data: A Case Study at Mu Cang Chai District,Yen Bai Province (Viet Nam)

Landslide hazard assessment at the Mu Cang Chai district; Yen Bai province (Viet Nam) has been done using Random SubSpace fuzzy rules based Classifier Ensemble (RSSCE) method and probability analysis of rainfall data. RSSCE which is a novel classifier ensemble method has been applied to predict spatially landslide occurrences in the area. Prediction of temporally landslide occurrences in the present study has been done using rainfall data for the period 2008–2013. A total of fifteen landslide influencing factors namely slope, aspect, curvature, plan curvature, profile curvature, elevation, land use, lithology, rainfall, distance to faults, fault density, distance to roads, road density, distance to rivers, and river density have been utilized. The result of the analysis shows that RSSCE and probability analysis of rainfall data are promising methods for landslide hazard assessment. Finally, landslide hazard map has been generated by integrating spatial prediction and temporal probability analysis of landslides for the land use planning and landslide hazard management.     

Remote Sensing and GIS Based Landslide Susceptibility Assessment using Binary Logistic Regression Model: A Case Study in the Ganeshganga Watershed, Himalayas

A comprehensive Landslide Susceptibility Zonation (LSZ) map is sought for adopting any landslide preventive and mitigation measures. In the present study, LSZ map of landslide prone Ganeshganga watershed (known for Patalganga Landslide) has been generated using a binary logistic regression (BLR) model. Relevant thematic layers pertaining to the causative factors for landslide occurrences, such as slope, aspect, relative relief, lithology, tectonic structures, lineaments, land use and land cover, distance to drainage, drainage density and anthropogenic factors like distance to road, have been generated using remote sensing images, field survey, ancillary data and GIS techniques. The coefficients of the causative factors retained by the BLR model along with the constant have been used to construct the landslide susceptibility map of the study area, which has further been categorized into four landslide susceptibility zones from high to very low. The resultant landslide susceptibility map was validated using receiver operator characteristic (ROC) curve analysis showing an accuracy of 95.2 % for an independent set of test samples. The result also showed a strong agreement between distribution of existing landslides and predicted landslide susceptibility zones.