Assessment of Land use/land cover Change in the North-West District of Delhi Using Remote Sensing and GIS Techniques

Land is one of the prime natural resources. A city grows not only by population but also by changes in spatial dimensions. Urban population growth and urban sprawl induced land use changes and land transformation. The land transformation is a natural process and cannot be stopped but it can be regulated. Many geographical changes at the urban periphery are associated with the transfer of land from rural to urban purpose. There is an urgent need for fast growing areas like Delhi, which can be easily done by high-resolution remote sensing data. Land use/land cover of North West of Delhi has been analyzed for the time period of 1972?C2003. The remote sensing data used in study is Aster image of 2003 with a spatial resolution of 15?m and other data of 1972 Survey of India (SOI) toposheet at the scale of 1:50,000. Supervised digital classification using maximum likelihood classifier was applied for preparing land use/land cover. A change detection model was applied in ERDAS Imagine to find out the land use/land cover during 1972 to 2003. Eight land use classes was identified but main dominated classes were built up and agricultural land. A drastic change has been recorded during 30 years of time i. e. (1972-2003). In 1972, 92.06% of the land was under agricultural practice, which reduced to 64.71% in 2003. This shows 27.35% decrease in agricultural land in three decades. On the other hand built up area was 6.31% in 1972, which increased to 34% in 2003. One of the main cause of this land use change is the population growth due to the migration in the district from small cities and rural areas of Delhi.     

Analysing spatio-temporal footprints of urbanization on environment of Surat city using satellite-derived bio-physical parameters

Our study examines the relationships among various environmental variables in Surat city using remote sensing. Landsat Thematic Mapper satellite data were used in conjugation with geospatial techniques to study urbanization and correlation among satellite-derived biophysical parameters namely, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), normalized difference bareness index (NDBaI) and land surface temperature (LST). A modified NDWI (MNDWI) was used for extracting areas under water. Land use/land cover classification was performed using hierarchical decision tree classification technique using ERDAS IMAGINE Expert classifier with an accuracy of 90.4% for 1990 and 85% for 2009. It was found that city has expanded over 42.75 sq.km within two decades. Built-up, fallow and sediment land use classes exhibited high dynamics with increase of nearly 200% and 50% and decrease of 55% respectively from 1990 to 2009. Vegetation and water classes were less dynamic with 20% decrease and 15% increase. The transformation of land parcels from vegetation to built-up, vegetation to fallow and fallow to built-up has resulted in increase of LST by 5.5 ± 2.6°C, 6.7 ± 3°C and 3.5 ± 2.9°C, respectively.     

Land use mapping of kandi belt of jammu region

Digital image processing on IRS-1C-LISS-III data acquired on October 13, 1998 has been carried out to map the land use classes in part of the Kandi belt, the submontane tract lying in the Outer Himalaya of Jammu region of Jammu and Kashmir. Supervised classification has been combined with rule-based classification to delineate various land use classes. The various categories of land use in the area recognized are forest, agriculture, riverbed, urban, fallow, wasteland and water. Forest is dominant along the upper boundary of the Kandi belt (along Siwalik) and on ridges, whereas, agriculture land is mainly along the lower boundary (along Sirowal) of the study area.     

Application of multidate satellite imagery for land use planning and management in the drought prone areas of Karnataka

Based on visual interpretation of Multidate Landsat Imagery, the spatial distribution of land use/land cover over 45,000 sq.km, spread over the three drought prone districts of Bijapur, Belgaum and Dharwar in NW Karnataka, has been mapped. The land use/land cover is classified into five Level-I and twelve Level-II classes. The pattern of change in land use/land cover during the period October, 1980 and January, 1982 has been one of decline in all the land use classes (except for agricultural use, which is more due to seasonal change) which highlight the land use/land cover changes in the drought prone area. An optimum land use plan requires that all the cropland should be zoned for cultivation while marginal lands like scrub land and mixed barren land (from the view point of cultivation) should be zoned for pasture/grazing and animal husbandary. There is a case for flexibility here, depending upon the pressure of population on land. The accuracy level of the ‘information base’ of the thematic map(s) obtained from Landsat imagery is 94 percent.     

Loktak notified Wetland ecosystem and its catchment

Conservation of wetland is considered paramount in view of its ecological significance. The availability of reliable and up-to-date data on seasonal water spread, tropic state of wetland and bio-physical parameters besides the landuse/cover of the catchment area is a prerequisite for ‘wise use’ of any wetland ecosystem. The present study is carried out to identify the above parameters of Loktak notified wetland through visual interpretation of 1RS IA/IB LISS II FCC of 1990 and 1994/95. It indicates that the water spread of the lake is showing a declining trend and an increasing trend for aquatic vegetation. In 1990 post-monsoon data water spread was 15441 ha which become 11166 ha in October 1994. The extent of water spread further decreases by pre-monsoon season and was found to be 7875 ha in the IRS LISS II data of March 1995. Like-wise area under aquatic vegetation and associated marshy/ swamps was 10499 ha in October 1990 and 13506 ha in October 1994. Catchment of Loktak lake (104872 ha) is highly degraded and forest covers only 7205 ha area. Agriculture is the main land use (35576 ha) in the catchment and substantial area is also under land with or without scrub. Thus, there is a need to rehabilitate the catchment by way of planting trees for reducing silt load in the Loktak lake and ensuring its ‘wise use’.     

结合高分遥感和多源数据的高原湖泊流域土地利用分析

高分一号卫星是为提升我国高分辨率数据自给率自主发射的卫星,在土地利用监测方面具有重要的应用价值。将GF-1卫星影像与多源数据影像进行对比能够挖掘各数据源在土地利用动态监测方面的差异性。本文以云南省杞麓湖流域为研究区,选取最新的Sentinel-2、GF-1和Landsat 8卫星遥感影像进行土地利用分类,以第二次全国土地利用调查数据为基期数据,结合野外实地调研和土地利用转移矩阵开展土地利用现状和演变分析,得出以下结论：①杞麓湖流域的水域、建设用地、耕地和林地自中心向外呈现出圈层分布的特征,与第二次全国土地调查结果相比,水域、耕地、林地3种类型的自然景观面积减少,而建设用地和其他用地受人类活动的影响,面积大幅增加,变化主要集中在杞麓湖周边的纳古镇和河西镇。②Sentinel-2卫星影像与GF-1卫星影像均具有较高的空间分辨率,二者对土地利用变化评估的结果相近,均优于Landsat 8卫星影像,其中GF-1卫星影像具有较高的应用价值。     

Studying Changes in Land Use Within the Poyang Lake Region

Poyang Lake is the largest freshwater lake in China. Because the lake is faced with a series of ecological and environmental problems, it is important and necessary to study the land use changes in the Poyang Lake region. In this study, Landsat images from 1976, 1989, 1999 and 2009, were used along with other evaluation methods (quantitative analysis of changes in land use, land use dynamic, degree and transfer matrix analyses) to investigate the changes in land use within the Poyang Lake region from 1976 to 2009. Land use was classified into seven types: cropland, woodland, grassland, the water body, construction land, bottomland and unused land. Areas of cropland, bottomland and the water body were decreasing although the area of the water body decreased relatively slowly. However, areas of construction land, grassland, woodland and unused land increased to a certain extent, with unused land increasing the most rapidly given its smaller proportion compared to the other types. All land types in the study region had different levels of conversion between other types of land. As a whole, the decrease in cropland and the increase in construction land, woodland and grassland were caused by human activities and the conservation policies such as Grain-for-Green and “returning farm to lake”. However, the decrease in the water body area was mainly influenced by natural factors and human activities. Changes in the area of bottomland were mainly influenced by water levels and human farming activities.     

Study of landforms,land use and land units of a part of Krishna district,Andhra Pradesh,from aerial photographs

Utilising aerial photographs as the chief source of information an attempt has been made to study the land units, land use, land capability and limitations in relation to geomorphology of an area of about 350 sq. kms. in Krishna district of Andhra Pradesh. Besides identifying major individual landforms, the area is divided into four geomorphic environments each characterised by dominant landform pattern and relief. Each form and unit is described. Nine types of land units based on amount of slope and six land use classes were chosen after preliminary interpretation and a reconnaissance field check. The estimated range in slope is given for each land unit. The land’s capability and limitations are brought out from consideration of landforms, land units (slopes), nature of soil and water resources. Soil samples were collected from each geomorphic unit and analysed. The results are presented in the form of 3 maps and 2 tables, which may be of use for planning and development of the area.     

Delineation of soil associations for a part of tamil nadu by digital processing of landsat multispectral data

The utility of Landsat multispectral data for small scale soil mapping has been demonstrated in this study. The scene used for the study has path-row number 153-054 of Landsat-1 dated 26th February, 1973 covering parts of Ramnad, Tirunelveli and Kanyakumari districts of Tamil Nadu. Associations of sub groups have been delineated on 1 : 250,000 scale using computer-aided multispectrcl data analysis system (M-DAS). Soil map prepared using the computer has been found to be camparable with the soil map prepared by conventional methods at the same scale. Apart from the soil associations, other land use/land cover classes like water bodies forest/scrub/hiliy areas, crcps etc. were also categorised in the colour coded soil map.     

环境遥感信息分析法在干旱区找水中的应用——以内蒙锡林浩特地区为例

从研究干旱区域地下水与植被关系入手,通过植被遥感信息分析,推断出浅层地下水的富水区;根据干旱区地表水主要受地下水补给这一规律,应用多时相遥感资料通过对区内巴彦布拉格湖水水域面积的动态分析,指出呼吉尔湖水接受深层地下水补给。上述解译成果为本区找水提供了方向,已得到后续物探、钻探工程证实。     

Mapping and Identification of Homegardens as a Component of the Trees Outside Forests Using Remote Sensing and Geographic Information System

The homegardens represent an important component of the trees outside forests (TOF) in the rural ecosystem which fulfill a range of subsistence and economic needs besides providing many environmental services. The present work was focused on the identification and mapping of rural homegardens as a component of the trees outside forests in the larger landscape of the three districts—Cachar, Hailakandi and Karimganj, of Barak Valley, Assam, northeast India. Mapping and identification of homegardens and other dominant land use/land cover classes was done with IRS-P6 LISS-IV data using on-screen visual interpretation technique in a geographic information system environment. Two major TOF classes could be identified from the satellite data and homegardens were found to be the dominant TOF class with the highest percentage coverage of the total geographical area in the three districts. The study reveals that high resolution satellite data of IRS-P6 LISS-IV can be successfully used for classification and mapping of different land use/land cover classes including the homegardens with an overall classification accuracy of 91 %. The land use/land cover map generated for the three districts shows the distribution of the homegardens in relation to other land use/land cover classes and can be used in future for proper identification of homegardens and resource management planning.     

Application of Remotely-Sensed Data to Estimate a Water Budget for Data-Scarce Endorheic Basins: A Case Study of Lake Urmia basin,Iran

Estimating the water budgets of large basins is a challenge because of the lack of data and information. It becomes more complicated in endorheic basins that consist of separate land and water phases. The application of remotely-sensed data is one solution in this regard. The present study addresses this issue and develops a modeling framework to evaluate a water budget based on remotely-sensed data for endorheic basins. To explore the methodology, Lake Urmia basin was selected as a case study. The lake water level has declined steeply since 1995 and stakeholders have agreed to allocate 3100 MCM of water per year to the lake. This makes it necessary to monitor river inflow into the lake to fulfill the agreement. Gauging stations have been employed around the lake, but they could not account for shortages such as water uptake below the stations. To do this, separate water budgets for the water body and the land were required. More specifically, it was necessary to estimate actual evapotranspiration (ET _a ) from freshwater (E _f ) and saltwater (E _s ) estimated using the SEBAL model. Different methods were applied to estimate soil moisture, groundwater exploitation, and surface-groundwater inflow into the lake. A comparison of the observed and estimated amounts showed good agreement. For instance, the coefficient of determination for the observed/reported and estimated ET _a and E _f were 0.83 and 0.84, respectively. The average annual inflow was estimated to be 2.2 BCM/year for 2002–2008 using the RS model, which is about 84 % of the total inflow from the last recording stations before the lake and shows influence of water exploitation after these stations. Future study should focus on increasing temporal and spatial resolution of the method     

Land use indicators of a watershed in arid region, western Rajasthan using Remote Sensing and GIS

The vegetation dynamics and land use/land cover types of Birantiya Kalan watershed located in the arid tracts of western Rajasthan have been characterized and evaluated using Remote Sensing and Geographical Information System (GIS). The watershed under study falls in the transitional plain of Luni Basin and is characterized by Aravali ranges in the eastern half and vast alluvial plains in the west. The land use/land cover types, as identified are cropland, fallow, forest, land with scrub, land without scrub, sandy area and the water body. Land with scrub occupied maximum area (39% area of the watershed) in 1996 in place of crop land which was dominant (43% of total area) in the year 1988. During eight years period, seasonal fallow land increased significantly and the areal extent of water body decreased to almost half. Vegetation vigour types have been classified into very poor, poor. moderate, good and very good categories. Moderate vigour type reduced from 62 to 27% and poor type increased from 34 to 68% during the period 1988 to 1996. Other vegetation vigour types have not shown any significant changes. To quantify the changes over the years in both vegetation and land use/land cover, weightages have been given to each type and composite values of both vegetation vigour and land use types for 1996 and 1988 have been calculated. It has been observed that the ratio for vegetation vigour has been found to be 0.85 showing that the overall vegetation have not improved after the treatment. The ratio for land use is found to be 1.01, which indicates negligible change in land use.     

煤炭开采对泥河小流域土地利用及景观格局的影响

以淮南煤矿区泥河小流域1987、1994、2000、2006、2009、2013、2017年7期多源遥感影像为数据源,结合纹理和光谱特征,利用支持向量机（SVM）对遥感影像进行分类,在此基础上分析了煤炭开采对泥河小流域近30年土地利用和景观格局变化的影响。结果表明：煤炭开采影响下流域的土地利用变化最显著的特征是耕地和建设用地的相互转变及耕地向塌陷水体的转变,30年间塌陷水体和建设用地分别增加了2 281.05、14 741.73 hm²,耕地减少了15 044.67 hm²。采煤驱动下,流域景观格局变化特征体现在以2006年为转折点,前期呈现破碎化、不规则化、异质化和低连通性变化的特征,之后呈现连续化、规则化、均衡化及高连通性变化的特征。建设用地、耕地和塌陷水体经历了不断破碎化到景观逐渐完善的过程;耕地、建设用地和自然水体斑块形状较为复杂;耕地优势性逐渐减弱,最大斑块指数由79.706 0降为38.745 5,塌陷水体和建设用地的优势性增强。     

利用改进的归一化差异水体指数（MNDWI）提取水体信息的研究

在对M cfeeters提出的归一化差异水体指数(NDWI)分析的基础上,对构成该指数的波长组合进行了修改,提出了改进的归一化差异水体指数MNDWI(M odified NDWI),并分别将该指数在含不同水体类型的遥感影像进行了实验,大部分获得了比NDWI好的效果,特别是提取城镇范围内的水体。NDWI指数影像因往往混有城镇建筑用地信息而使得提取的水体范围和面积有所扩大。实验还发现MNDWI比NDWI更能够揭示水体微细特征,如悬浮沉积物的分布、水质的变化。另外,MNDWI可以很容易地区分阴影和水体,解决了水体提取中难于消除阴影的难题。     

Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines – SVM), and hybrid (unsupervised–supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different depending on land use/cover classes. Early-growth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land use/cover classes were mapped with producer's and user's accuracies of ∼90%. Our classification approach seems very well suited to accurately map land use/cover of heterogeneous landscapes, thus having great potential to contribute to climate change mitigation schemes, conservation initiatives, and the design of management plans and rural development policies.     

土地利用现状空间数据库拓扑关系分析及基于规则的高效检测

为了提高土地利用现状空间数据库空间数据检测效率,实现要素类拓扑关系的智能检测,在分析详查要素拓扑关系的基础上,提出基于拓扑规则的拓扑关系验证方法。并采用GIS开发平台ArcEngine,基于RSTT质检模型,研制了空间数据质检系统LR_Checker。经大量土地利用现状空间数据的测试表明,采用LR_Checker可显著提高数据检测效率,通过规则的逻辑组合,不仅实现要素类内拓扑关系检测,还支持不同要素类间拓扑关系检测。证明了基于拓扑规则的拓扑关系验证方法的正确性、有效性和合理性。     

遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文)

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km² in 1990 to 3 794.9 km² in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China).     

基于多级决策树分类的土地利用与覆盖信息提取

结合Landsat-8遥感数据,采用多级决策树分类方案,利用归一化植被指数、波段比值、主成分分量等光谱特征参数并融合其他非遥感知识,对黄河三角洲地区土地利用与覆盖的信息展开了全面的提取、研究与分析,获得了该地区5个一级类、12个二级类地物的分布情况,分类总体精度93.88%,优于传统监督分类。同时采用聚类、分类叠加和人机交互等分类后处理操作以获得更贴近地面实际的制图效果,开展基于海岸线的缓冲区分析以获得各地物特别是距离海岸线10 km、20 km范围内地物类型的空间分布并完成相关制图与分析,为黄河三角洲地区滨海土地的利用与开发提供了数据支持。     

Integration of remote sensing and GIS in monitoring the dynamics of land cover in Oroba-Kibos catchment area, Kenya

Land cover in Kenya is in a state of fl ux at different spatial and temporal scales. This compromises environmental integrity and socioeconomic stability of the population hence increasing their vulnerability to the externalities of environmental change. The Oroba-Kibos catchment area in western Kenya is one locality where rapid land use changes have taken place over the last 30 years. The shrubs, swamps, natural forests and other critical ecosystems have been converted on the altar of agriculture, human settlement, fuel wood and timber. This paper presents the results of a study that aimed at providing spatially-explicit information for effective remedial response through (a) Mapping the land cover; (b) Identifying the spatial distribution of land cover changes; (c) Determining the nature, rates and magnitude of the land cover changes, and; (d) Establishing the drivers of land use leading to land cover changes in Oroba-Kibos catchment area. Bi-temporal Landsat TM imagery, fi eld observation, household survey and ancillary data were obtained. Per-fi eld classifi cation of the Landsat TM imagery was performed in a GIS and the resultant land cover maps assessed using the fi eld observation data. Post-classifi cation comparison of the maps was then done to detect changes in land cover that had occurred between 1994 and 2008. SPSS was used to analyze the household survey data and attribute the detected land cover changes to their causes. The fi ndings showed that 9 broad classes characterize the catchment area including the natural forests, swamps, natural water bodies, woodlands, shrublands, built-up lands, grasslands, bare lands and croplands. Croplands are dominant and accounted for about 65% (57122 ha) of the total land in 1994, which increased at the rate of 0.89% to 73% (64772 ha) in 2008, while natural water bodies has the least spatial coverage accounting for about 0.6% (561 ha) of the total land in 1994, which diminished at the rate of 3.57% to 0.3% (260 ha) in 2008. Climate, altitude, access and rights to land, demographic changes, poverty, political governance, market availability and economic returns are the interacting mix of proximate and underlying factors that drive the land cover changes in Oroba-Kibos catchment area.