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.

An Appraisal of Land Use/Land Cover Change Scenario of Tummalapalle, Cuddapah Region, India—A Remote Sensing and GIS Perspective

The study was aimed at appraising the changing land use/land cover scenario of Tummalapalle region in Cuddapah district of Andhra Pradesh using Remote sensing data and GIS technology. The region is considered as it has rich uranium reserves and is experiencing a remarkable expansion in recent times. The land use/land cover change analysis was carried out using IRS P6 LISS-III and LANDSAT-8 OLI multitemporal data pertaining to the years 2006 and 2016. The image classification resulted in five major land use/land cover classes namely built-up, agricultural, forest, wasteland and water bodies. The study noticed that the areas under built-up and agricultural classes are found increased from 0.94 km2 (0.84%) to 2.75 km2 (2.44%) and 61.68 km2 (54.84%) to 63.91 km2 (56.82%), respectively during 2006-2016. Area under forest, wasteland and water bodies are found decreased considerably from 3.09 km2 (2.75%) to 0.86 km2 (0.76%), 43.71 km2 (38.56%) to 42.60 km2 (37.88%) and 3.05 km2 (2.71%) to 2.35 km2 (2.09%), respectively. The study recommends development of industrial based economy by optimally utilizing the existing land resource (scrub and wasteland classes) and simultaneously extending the agricultural practices to other possible areas to make them more productive.

IMPROVING THE EFFECT OF GREENING ON HEAT ISLAND IN URBAN RESIDENTIAL DISTRICTS BASED ON REMOTE SENSING AND GIS ANALYSIS

Analyzing the thermal distribution on plane conditions objectively is difficult due to lack of enough meteorological observation stations within urban residential areas. In this paper satellite observations synchronous or quasi-synchronous with ground observations are adopted, and a teleconnection model is built between the satellite spectral and surface temperature for quantitative retrieval of temperature. Furthermore, by combining the satellite data with other multiple factors, a GIS comprehensive analysis model and a functional evaluation method for urban residential districts are established, which are used to study the relation between the air temperature and media characteristics on ground as well as the greening cooling effect in recent years in Shanghai. The results show that the air temperature in greened urban residential districts is generally lower than the average temperature and much less than the highest one. In general,the average air temperature in the greened area is at most 1.19℃ lower than the maximum temperature in the districts,which is 0.67℃ and 0.55℃ lower than that of the highest for buildings and roads respectively. The temperature is inversely proportional with greening fraction but is directly proportional with the ratio of roads and buildings. The higher the greening fraction in internal residential districts, the lower the temperature, and the higher the ratio of road and building is, the higher the temperature.

Identification of groundwater potential in hard rock aquifer systems using Remote Sensing, GIS and Magnetic Survey in Veppanthattai, Perambalur, Tamilnadu

Water is an essential natural resource without which life wouldn’t exist.The study aims to identify groundwater potential areas in Vepapanthattai taluk of Perambalur district,Tamil Nadu,India,using analytic hierarchy process(AHP)model.Remote sensing and magnetic parameters have been used to determine the evaluation indicators for groundwater occurrence under the ArcGIS environment.Groundwater occurrence is linked to structural porosity and permeability over the predominantly hard rock terrain,making magnetic data more relevant for locating groundwater potential zones in the research area.NE-SW and NW-SE trending magnetic breaks derived from reduction to pole map are found to be more significant for groundwater exploration.The lineaments rose diagram indicates the general trend of the fracture to be in the NE-SW direction.Assigned normalised criteria weights acquired using the AHP model was used to reclassify the thematic layers.As a result,the taluk’s low,moderate,and high potential zones cover 25.08%,25.68%and 49.24%of the study area,respectively.The high potential zones exhibit characteristics favourable for groundwater infiltration and storage,with factors as gentle slope of<3°,high lineament densities,magnetic breaks,magnetic low zones as indicative of dykes and cracks,lithology as colluvial deposits and land surface with dense vegetation.The depth of the fracture zones was estimated using power spectrum and Euler Deconvolution method.The groundwater potential mapping results were validated using groundwater level data measured from the wells,which indicated that the groundwater potential zoning results are consistent with the data derived from the real world.

A STUDY ON DESERTIFICATION OF WEST JILIN PROVINCE BASED ON REMOTE SENSING AND GIS TECHNIQUES

'West Jilin Province' in this paper means Zhenlai, Baicheng, Taonan, Da'an,Tongyu, Fuyu, Songyuan, Qian'an, Changling, also includes Gongzhuling, Shuangliao, Lishu, Siping andNong' an which have been suffered from desertification. In west Jilin Province there are three sandzones passing through, they are Xiang (Xianghai) -Wu (Ulan Tug) sand zone, Hai-Feng sand zone, andTao'er River right bank sand zone. The desertification area of west Jilin Province is 819 100 ha,making up 12. 5% of the total land area. Among desertification types, in Jilin Province lightdesertification is the major, then is medium decertification, hevey desertification is the least.According to the comparison of the interpretation results of the Landsat images of the 1980s and the1990s by remote sensing and GIS techniques, it can be seen that the desertification area in westJilin Province basically didn't change on the whole, only increased 6130 ha, making up 0. 8% of thedesertification area, change scale is less than 1%. Evidently, desertification is controlled mostly,but some areas are continuing deterioration. The desertification process of China can be dividedinto three types according to origin nature, they are sandy steppe desertification, fixed sandarea(sand land) activation and dunes transfer invasion. Reasons of desertification of West JilinProvince are analyzed, they include natural factors (such as material source factors, chimatefactors) and artificial factors (such as destroying grass to reclaim, steppe decreasing greatly,illegally feeling shelter forest stands, constructing reservoir to influence eco-environment etc. ).Some suggestions are put forward as follows: establishing the social project for ecologicalreconstruction of degenerated land; intensifying planning and management of land use, revertingfarmland into forestland or pasture in a planned way. The key desertification control is to dependmainly on policy and management, then control techniques.

SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai Xizang(Tibet)Plateau of China. The melt water from the snow cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter-snow cover area can be computed by satellite images from multi platform, multi temporal and multi spectral. A cluster of snow cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two objective reality situations in China, so they should be considered in simulation and forecast. Apart from dividing, the derivation of snow cover area from satellite images would decide the results of calculating runoff. Field investigation for selection of the learning samples of different snow patterns is basis for the classification.

Land Use/Land Cover (LULC) Dynamics in a Semi-Arid Watershed in Eastern Rajasthan, India Using Geospatial Tools

Land use/land cover (LULC) change analysis has become a unique approach in determining the extent of degradation of natural resources within a given period of time. Remote sensing and GIS techniques have proved to be efficient tools for mapping and analyzing LULC changes over the last few decades. LULC change analysis has been carried out in Ruparel watershed which is situated in Alwar district, Eastern Rajasthan, India, based on visual image interpretation and change detection analysis of multi-temporal satellite data pertaining to IRS-P6 LISS III data of 2004 (Path-Row 95:52), IRS-P6 LISS III of 2014 (Path-Row 95:52) and IRS-R2A LISS III data of 2021. Visual image interpretation led to the delineation of 13 LULC classes using ArcGIS 10.5 software and include categories such as cultivated land, fallow land dense forest, open forest, degraded forest, open scrub, gullied/ravenous land, settlement/built-up land, River/waterbody, dry waterbody/dry river, plantation, barren/rocky/stony waste, and stone quarry. Results of the analysis depict significant LULC changes that have taken place in the area from 2004 to 2021. LULC categories such as cultivated land and settlement/built-up land have reported major changes in terms of their increase with 56.42 km2 (4.63%) and 31.9 km2 (2.63%) respectively primarily because of an increase in population. Likewise, the dense forest has reported a decrease of 33.78 km2 (2.78%) in its area and has been converted into degraded forest i.e., 32.04 km2 (2.64%) and open forest 2.85 km2 (0.24%) due to increased human exploitation of forest resources and mining activities taking place within the forested area. The study area needs the immediate attention of policymakers and stakeholders as the study area being part of the National Capital Region (NCR) will see excessive in-migration of the population in coming years which will further deplete the precious resources in the area.

Remote Sensing approach to evaluate anthropogenic influences on Forest Cover of Palamau Tiger Reserve,Eastern India

Background:Tropical forests have been experiencing remarkable rates of transformation over the past century as they are getting degraded or decimated to a great extent by anthropogenic activities.This study aims at investigating the long-term forest cover transformation in Palamau Tiger Reserve(PTR),Jharkhand,India,using Landsat TM,ETM+,and OLI satellite images during 1975-2015.The forest cover was delineated utilizing various keys of visual interpretation techniques.Results:The forest cover was primarily decreased in the north-eastern and north-western parts in PTR.In order to identify the anthropogenic disturbance in the forest reserve,human settlement density was mapped using highresolution Google Earth imagery.The results showed a positive correlation between human population density and settlement density.Five major affected sites with an outer buffer of 2 km were demarcated in order to deduce the anthropogenic influences in major non-forested sites in PTR.It was observed that the forest change was maximum at site 3(Ranidah,area 61.06 km^(2),−6.47%change)followed by site 2(Saidup,area 124.38 km^(2),−7.65%change),where settlement units were also high(2638 and 2621 settlement units,respectively).At site 1(Barkheta,area 81.59 km^(2)),−1.99%change was observed,and at site 4(Samadh Tola,area 9.15 km^(2)),1.03% change was observed having moderate settlement units(2422 and 1892 settlement units,respectively).Areas with the low level of human settlements(1038 settlement units)observed the least change,i.e.,at site 5(Netarhat,area 48.52 km^(2)),0.58%change was observed mainly during the years.Conclusions:The forest cover exhibited an overall decrease of 14.55 km^(2)(−1.34%change)with episodic variation during 1975-2015 in PTR,Eastern India.A significant forest disturbance occurred primarily in the north-eastern and north-western parts of PTR along the forest fringe due to the high population and settlement density.The study highlighted the potential use of freely available multi-temporal satellite observations in forest management.