Delineation of groundwater potential zones using remote sensing and Geographic Information Systems(GIS)in Kadaladi region,Southern India

The primary objective of this research is to delineate potential groundwater recharge zones in the Kadaladi taluk of Ramanathapuram,Tamil Nadu,India,using a combination of remote sensing and Geographic Information Systems(GIS)with the Analytical Hierarchical Process(AHP).Various factors such as geology,geomorphology,soil,drainage,density,lineament density,slope,rainfall were analyzed at a specific scale.Thematic layers were evaluated for quality and relevance using Saaty's scale,and then inte-grated using the weighted linear combination technique.The weights assigned to each layer and features were standardized using AHP and the Eigen vector technique,resulting in the final groundwater potential zone map.The AHP method was used to normalize the scores following the assignment of weights to each criterion or factor based on Saaty's 9-point scale.Pair-wise matrix analysis was utilized to calculate the geometric mean and normalized weight for various parameters.The groundwater recharge potential zone map was created by mathematically overlaying the normalized weighted layers.Thematic layers indicating major elements influencing groundwater occurrence and recharge were derived from satellite images.2 Results indicate that approximately 21.8 km of the total area exhibits high potential for groundwater recharge.Groundwater recharge is viable in areas with moderate slopes,particularly in the central and southeastern regions.

Quantifying River Bank Erosion and Accretion Patterns along the Gorai River in Kushtia, Bangladesh: A Geospatial Analysis Utilizing GIS and Remote Sensing Techniques

River bank erosion is a natural process that occurs when the water flow of a river exceeds the bank’s ability to withstand it. It is a common phenomenon that causes extensive land damage, displacement of people, loss of crops, and infrastructure damage. The Gorai River, situated on the right bank of the Ganges, is a significant branch of the river that flows into the Bay of Bengal via the Mathumati and Baleswar rivers. The erosion of the banks of the Gorai River in Kushtia district is not a recent occurrence. Local residents have been dealing with this issue for the past hundred years, and according to the elderly members of the community, the erosion has become more severe activities. Therefore, the main objective of this research is to quantify river bank erosion and accretion and bankline shifting from 2003 to 2022 using multi-temporal Landsat images data with GIS and remote sensing technique. Bank-line migration occurs as a result of the interplay and interconnectedness of various factors such as the degree of river-related processes such as erosion, transportation, and deposition, the amount of water in the river during the high season, the geological and soil makeup, and human intervention in the river. The results show that the highest eroded area was 4.6 square kilometers during the period of 2016 to 2019, while the highest accreted area was 7.12 square kilometers during the period of 2013 to 2016. However, the erosion and accretion values fluctuated from year to year.

Land Use Land Cover Analysis for Godavari Basin in Maharashtra Using Geographical Information System and Remote Sensing

The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the land use and land cover (LULC) changes within the catchment area of the Godavari River, assessing the repercussions of land and water resource exploitation. Utilizing LANDSAT satellite images from 2009, 2014, and 2019, this research employed supervised classification through the Quantum Geographic Information System (QGIS) software’s SCP plugin. Maximum likelihood classification algorithm was used for the assessment of supervised land use classification. Seven distinct LULC classes—forest, irrigated cropland, agricultural land (fallow), barren land, shrub land, water, and urban land—are delineated for classification purposes. The study revealed substantial changes in the Godavari basin’s land use patterns over the ten-year period from 2009 to 2019. Spatial and temporal dynamics of land use/cover changes (2009-2019) were quantified using three Satellite/Landsat images, a supervised classification algorithm and the post classification change detection technique in GIS. The total study area of the Godavari basin in Maharashtra encompasses 5138175.48 hectares. Notably, the built-up area increased from 0.14% in 2009 to 1.94% in 2019. The proportion of irrigated cropland, which was 62.32% in 2009, declined to 41.52% in 2019. Shrub land witnessed a noteworthy increase from 0.05% to 2.05% over the last decade. The key findings underscored significant declines in barren land, agricultural land, and irrigated cropland, juxtaposed with an expansion in forest land, shrub land, and urban land. The classification methodology achieved an overall accuracy of 80%, with a Kappa Statistic of 71.9% for the satellite images. The overall classification accuracy along with the Kappa value for 2009, 2014 and 2019 supervised land use land cover classification was good enough to detect the changing scenarios of Godavari River basin under study. These findings provide valuable insights for discerning land utilization across various categories, facilitating the adoption of appropriate strategies for sustainable land use in the region.

基于遥感GIS信息融合的测绘机器人滑模跟踪控制系统

测绘机器人是实现测绘自动化的执行设备,测绘机器人的工作空间更为复杂,给机器人的跟踪控制工作带来较大挑战;为提高测绘机器人跟踪控制效果,设计了基于遥感GIS信息融合的测绘机器人滑模跟踪控制系统;加设遥感信息采集器和GIS信息采集器,改装遥感GIS信息处理器以及滑模跟踪控制器,完成硬件系统的优化设计;考虑信息结构以及信息之间的逻辑关系,构建系统数据库,为遥感GIS信息提供充足的存储空间;根据测绘任务生成机器人滑模移动轨迹,作为机器人的控制目标;采集测绘机器人实时遥感与GIS信息,利用遥感GIS信息融合技术跟踪机器人实时位姿,比对位姿跟踪结果与生成的控制目标,计算滑模跟踪控制量,完成系统的测绘机器人滑模跟踪控制软件功能优化;系统测试结果表明:设计系统的控制误差平均值为1.9 m,抖振幅值为0.8 dB,具有较好的控制效果。

Study of coastal water zone ecosystem health in Zhejiang Province based on remote sensing data and GIS

The coastal ecosystem health assessment is a field of increasing importance.In this paper,a preliminary assessment of ecosystem health in Zhejiang coastal water zone was made,mainly based on remote sensing data and GIS technique.Its spatial and quantitative evaluation was facilitated by the progress of remote sensing and GIS technique development.Firstly,human activities,hydrology and ecosystem problems in the study area were discussed and analyzed.Secondly,from 4 aspects of human stress,physical,chemical and biological responses to anthropogenic activities and natural stress,several indicators such as water transparency（Secchi Disk Depth,SDD）,suspended substance concentration,dissolved inorganic nitrogen,active phosphate,chlorophyll,harmful algae bloom,as well as distribution of sewage,sea lanes and port were employed.Thirdly,the Analytic Hierarchical Process was used for indicator weight calculation,and the ecosystem health criteria were established according to the integrative analysis of national water quality criteria,similar coastal ecosystem health research in other places or data inherent properties.The results indicated that from 2005 to 2007 the coastal water ecosystem health value in Zhejiang Province was unhealthy and needs ecological restoration by human intervention.

Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS

Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.

Characterizing urban expansion of Korla City and its spatial-temporal patterns using remote sensing and GIS methods

Cities provide spatial contexts for populations and economic activities. Determining the spatial-temporal patterns of urban expansion is of particular significance for regional sustainable development. To achieve a better understanding of the spatial-temporal patterns of urban expansion of Korla City, we explore the urban expansion characteristics of Korla City over the period 1995-2015 by employing Landsat TM/ETM＋ images of 1995, 2000, 2005, 2010, and 2015. Urban land use types were classified using the supervised classification method in ENVI 4.5. Urban expansion indices, such as expansion area, expansion proportion, expansion speed, expansion intensity, compactness, and fractal dimension, were calculated. The spatial-temporal patterns and evolution process of the urban expansion （e.g., urban gravity center and its direction of movement） were then quantitatively analyzed. The results indicated that, over the past 25 years, the area and proportion of urban land increased substantially with an average annual growth rate of 15.18%. Farmland and unused land were lost greatly due to the urban expansion. This result might be attributable to the rapid population growth and the dramatic economic development in this area. The city extended to the southeast, and the urban gravity center shifted to the southeast as well by about 2118 m. The degree of urban compactness tended to decrease and the fractal dimension index tended to increase, indicating that the spatial pattern of Korla City was becoming loose, complex, and unstable. This study could provide a scientific reference for the studies on urban expansion of oasis cities in arid land.

Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin

Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation （RUSLE） integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm.ha-1hr-1/year, 0.10 to 0.44 t ha-1 -MJ-1.mm 1, 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002 2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin.

Monitoring the Cultivated Slope Land in the Three Gorges Reservoir Area Based on Remote Sensing and GIS

By means of combining auto-extraction with manual interpretation, the current distribution information about cultivated land is obtained. The distribution information of 1992 is extracted from the dynamic polygons of 2002. The monitoring mini-system of the cultivated slope land is established. In the system, detailed surveys, focused on the resources of cultivated slope land, are carried out. The results indicate that the area of the cultivated slope land is very large. Meanwhile, there are lots of cultivated steep slopes with gradient above 35°. The areas of steep land cultivated had been slowly reduced from 1992 to 2002. At the same time, the pressures of returning farm land to forestry are great in all counties. The conflicts between population growth, insufficient grain supply and stagnant economic development sharpen increasingly. It is inevitable to improve the agricultural structure.

Remote Sensing &GIS Based Spatio-Temporal Change Analysis of Wetland in Dhaka City, Bangladesh

Landscape of Dhaka city—one of the fastest growing mega cities in the world, is continuously changing due to un-planned urbanization. For example, the wetlands of the city have been shrinking. This study evaluates wetland changes in Dhaka Metropolitan Area (DMA), Bangladesh, between 1978 and 2009. Spatial and temporal dynamics of wetland changes were quantified using four Landsat images, a supervised classi?cation algorithm and the post-classi?cation change detection technique in GIS environment. Accuracy of the Landsat-derived wetland maps ranged from 87% to 92.5%. The analysis revealed that area of wetland and Rivers & Khals in Dhaka city decreased significantly over the last 30 years by 76.67% and 18.72% respectively. This changing trend of wetlands makes the drainage system of Dhaka City vulnerable, creating water logging problems and their consequences. Land filling and encroachment were recognized to be the main reasons for shrinking of the wetlands in the city. Development and alteration of the existing water bodies should consider the natural hydrological conditions.

Urbanization and Quality of Urban Environment Using Remote Sensing and GIS Techniques in East Delhi-India

An explosive increase of urban population, practically in all major cities and towns, has the consequent strain on the existing system manifested in an environmental chaos. The phenomena of accelerated urbanisation is the main culprit, wherein besides bringing higher standard of living, it has also brought problems, as growth of dense and unplanned residential areas, environmental pollution, non-availability of services and amenities, solid waste etc. Remote sensing satellite data is suitable for urban land use mapping to get detail and up- to-date information for environmental management. Where as GIS helps in developing database system for urban information, which supports decision making process. Development of digital database on all aspects of land use and urban planning is the next crucial task for the future in which remote sensing based informa-tion is going to play a major role. In Delhi, rise in population and growth in economic activity has led to en-vironmental degradation. With this view an attempt has been made to study the quality of urban environment in the East district of Delhi, which is experiencing very high urban growth with 98.75% urban population in 2001. For this study Landsat ASTER (MSS) data of year 2001 (15 m Ground resolution), Guide map of the year 1982 and demographic and environmental data has been used. Eight parameters were selected, which affect the urban environmental quality, namely built-up area, open spaces, household density, occupancy ra-tio, population density, accessibility to roads, noise and smell affected area. The study shows that the quality of environment has been degraded when we compare 1982 and 2003 data. Most of the East district was in a better state of environment in 1982, but in 2003 things have been changed and now 50% area is in very good, fair and desirable condition. The public participation and involvement should be encouraged planning and decisions making for the improvement in better urban environmental quality.

Using GIS-Based Weighted Linear Combination Analysis and Remote Sensing Techniques to Select Optimum Solid Waste Disposal Sites within Mafraq City, Jordan

Landfill siting was determined within Mafraq City, Jordan, through the integration of geographic information system (GIS), weighted linear combination (WLC) analysis, and remote sensing techniques. Several parameters were collected from various sources in vector and raster GIS formats, and then, used within the GIS-based WLC analysis to select optimum solid waste disposal sites. Namely, urban areas, agricultural lands, access roads, surface aquifers, groundwater table, fault system, water wells, streams, and land slope were considered in this research. Also, the trend of urban expansion within the study area was monitored using the Landsat data of 1989, 1999, and 2009 to support the selection process of disposal sites. It is found that about 84% of the study area was within “most suitable” to “moderately suitable” classes for landfill sites, while the rest of the study area was within “poorly suitable” and “unsuitable” classes. Based on the analysis of Landsat satellite data the urban area was expanded of more than 240% during the last three decades, mainly toward south, and southwest, except the villages near the existing disposal site, where the trend was toward east and northeast. Finally, three sites were suggested as alternatives to the existing disposal site taking into the consideration the environmental, biophysical, and economical variables applied in the GIS-based WLC analysis.

Investigating the Use of Remote Sensing and GIS Techniques to Detect Land Use and Land Cover Change: A Review

The accuracy of change detection on the earth’s surface is important for understanding the relationships and interactions between human and natural phenomena. Remote Sensing and Geographic Information Systems (GIS) have the potential to provide accurate information regarding land use and land cover changes. In this paper, we investigate the major techniques that are utilized to detect land use and land cover changes. Eleven change detection techniques are reviewed. An analysis of the related literature shows that the most used techniques are post-classification comparison and principle component analysis. Post-classification comparison can minimize the impacts of atmospheric and sensor differences between two dates. Image differencing and image ratioing are easy to implement, but at times they do not provide accurate results. Hybrid change detection is a useful technique that makes full use of the benefits of many techniques, but it is complex and depends on the characteristics of the other techniques such as supervised and unsupervised classifications. Change vector analysis is complicated to implement, but it is useful for providing the direction and magnitude of change. Recently, artificial neural networks, chi-square, decision tree and image fusion have been frequently used in change detection. Research on integrating remote sensing data and GIS into change detection has also increased.

Using Remote Sensing and GIS Techniques to Study Soil Degradation Processes in North Shaanxi Province,China

Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1∶250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and ArcView softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility ( SE ) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation, physical degradation and salinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33.75 % of the total land area (120.330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29.41 % of the total land area has slight or moderate desertification and 37.465 % is facing severe desertification.

Combined Remote Sensing and GIS Techniques for Studying the Large Roman Urban System Expansion during the Last Twenty Years

Several factors may contribute to on-going challenges for spatial planning and policy in megacities such as Rome, including rapid population shifts, poorly organized areas, and lack of data through which monitoring urban growth and land use change. This research was conducted to examine past and current effects of the urbanization process, occurred over the large Roman urban system, on the basis of multi-source and multi-temporal optical remote sensing (RS) data, collected between 1990 and 2013. These changes were then validated via Geographic Information System (GIS) techniques, in a particular procedure applied to urban land/agricultural transformations. The proposed approach, based on geo-statistical methods, was used to calculate the index of innovative space (AP Index), useful for the monitoring of the urban sprawl phenomenon. Strong evidence of urban expansion over the north-eastern quarter of the city, accompanied by environmental degradation and loss of biodiversity, is provided. Urban infill developments are expected to emerge in the south-eastern areas too, and these might increase urban pressure as well. In conclusion, RS and GIS technologies together with ancillary data can be used to assist decision makers in preparing future plans to find out appropriate solutions to urbanization encroachment.

Dynamics of Soil Erosion in Xingguo County, China, Determined Using Remote Sensing and GIS

The spatial and temporal dynamics of soil erosion in Xingguo County, Jiangxi Province, China were studied using multi-period remote sensing images and GIS. The results indicated that the soil erosion status of the region has been improving, particularly since the 1980s, with the erosion rate showing an evident decline over the past 30 years. The improvement showed not only in the decline of eroded soil area, but also with the reduction in the extent of erosion. The extent of erosion mainly changed by one level, and the change primarily occurred with the severely or moderately eroded soil types. However, in general, soil erosion was still an overriding problem in the region with some areas becoming more serious, especially those with large quantities of granite.

Geomorphometric Characterization of Upper South Koel Basin, Jharkhand: A Remote Sensing &GIS Approach

The quantitative analysis of drainage system is an important aspect of characterization of watersheds. Morphometry is measurement and mathematical analysis of landforms. The present study is an attempt to evaluate the drainage morphometrics of Upper South Koel Basin using Remote Sensing and GIS approach. A morphometric analysis was carried out to describe the topography and drainage characteristics of Upper South Koel watershed. The stream numbers, orders, lengths and other morphometric parameters like bifurcation ratio, drainage density, stream frequency, shape parameters etc. were measured. The drainage area of Upper South Koel watershed is 942.4 sq km and the drainage pattern is dentritic. The watershed was classified as 6th order drainage basin. The low values of bifurcation ratio and drainage density suggest that the area has not been much affected by structural disturbances. The study reveals that the different geomorphic units in the study area i.e. Structural hills, Pediments, Valley fills, Pediplains formed under the influence of permeable geology, are moderate to nearly level plains, with medium to low drainage density (<2.0) & low cumulative length of higher order streams . Such studies can be of immense help in planning and management of river basins.

Geological mapping and mining prospecting in the Aouli inlier(Eastern Meseta,Morocco)based on remote sensing and geographic information systems(GIS)

Landsat 8 Oli,ASTER,and Sentinel 2A satellite images processing was used to map geological formations,lineaments and hydrothermal alteration minerals in the Aouli inlier,as a case study to illustrate the application of digital images processing and Geographic Information System(GIS)in geological mapping and mining prospecting.Principal Component Analysis(PCA)applied to the Landsat images allowed good lithological discrimination and contributed to the updating of available geological maps.The Automatic lineament extraction from Sentinel images revealed the main tectonic structures affecting Aouli inlier.The ratio bands(b5+b7)/b6 and the false color composite(b4/b6,b2/b1,b3/b2)allowed the hydrothermal alteration minerals mapping from Aster images.Combined with available geological data and field observations,the satellite derived data were integrated and analyzed in a GIS software to establish mining prospecting guides.The results showed that the anomaly zones are intimately linked to NNE-SSW and NW-SE oriented faults and to highly fractured areas developing argillic and Fe rich alterations.Verified via field survey,this approach was successfully applied to the Aouli inlier to rapidly target potential areas to be explored in the tactical phase.This provides a model for future prospecting efforts for similar mineral deposits in other areas.

Land-Use/Land-Cover Dynamics in Calabar Metropolis Using a Combined Approach of Remote Sensing and GIS

This paper assessed the dynamics in the land use/land cover (LULC) within patterns of the land use/land cover (LULC) in Calabar metropolis. The thermal imageries for 2002, 2006, 2008, 2010, 2012, 2014 and 2016 were obtained and processed using remote sensing and Arc GIS software package in order to determine the changes that have occurred in the LULC in study area. The result of the LULC thematic maps overall accuracies was computed above 80 percent, which indicates an almost perfect agreement. The findings of this study reveal that, LULC classes by the year 2016 have assumed different dimensions of change from the sizes of their previous sizes in comparison to their current sizes. Land-use pattern changes in the study area were characterized by an increase in the built up class, waterbody (though with a slightly negative change from 2010 to 2012) and a predominant negative trend in dense vegetation and bare land classes;thus, indicating that the future changing trends will pose a depleting threat to the overall LULC. This study has shown that, the changing land use pattern of the area is capable affecting certain characteristics of the environment such as surface temperature. The study recommends that effort should be made by the government to increase urban vegetation around city centers and outliers by embarking on reforestation.

INTEGRATED VEGETATION CLASSIFICATION AND MAPPINGUSING REMOTE SENSING AND GIS TECHNIQUES

NOAA-AVHRR data have been more and more used by scientists because of its short temporal resolution,large scope, inexpensive cost and broad wave bands. On macro and middle scale of vegetation remote sensing, NOAAAVHRR possesses an advantage when compared with other satellites. However, because NOAA-AVHRR also problem of low resolution, data distortion and geometrical distortion, in the area of application of NOAA-AVHRR in largescale vegetation - mapping, the accuracy of vegetation classification should be improved. This paper discuss the feasibilityof integrating the geographic data in GIS(Geographical Information System) and remotely sensed data in GIS. Under theenvironment of GIS, temperature, precipitation and elevation, which serve as main factors affecting vegetation growth,were processed by a mathematical model and qualified into geographic image under a certain grid system. The geographicimage were overlaid to the NOAA-AVHRR data which had been compressed and processed. In order to evaluate the usefulness of geographic data for vegetation classification, the area under study was digitally classified by two groups of interpreter: the proposed methodology using maximum likelihood classification assisted by the geographic database and a conventional maximum likelihood classification only. Both result were compared using Kappa statistics. The indices to both theproposed and the conventional digital classification methodology were 0. 668(yew good) and 0. 563(good), respetively.The geographic database rendered an improvement over the conventional digital classification. Furthermore, in this study,some problems related to multi-sources data integration are also discussed.