Mapping of wastelands of Kolar district using false colour composites of thematic mapper (TM) data

This study deals with the technique of remote sensing for identifying and deliniating wastelands in Kolar district of Karnataka. False colour composites of thematic mapper (TM) data supplemented by aerial photographs and toposheets wrere utiliesd for mapping wastelands. A map showing the geographic distribution of the wastelands in the districts was prepared on 1∶250,000 scales by compiling the individual wasteland sheets of 1∶50,000 scale. The seven different catagories of wastelands identified and mapped cover about 11.7% of the area in the district. A procedure for mapping wastelands has been worked out based on the experience gained in Kolar district which is a three phase system comprising image intrepretation of false colour composite of TM data, aerial photo interpretation and limited ground truth verification in the selected doubtful areas. This procedure was found to be adequate enough for mapping wastelands accurately in the shortest possible time with least expense and as such are recommended for mapping wastelands in other districts of the country.     

Colour infrared aerial photographs as data base for reconnaissance soil mapping and land suitability grouping

Colour infrared and panchromatic B & W aerial photographs at 1∶25,000 scale over part of Anantapur district of Andhra Pradesh were interpreted stereoscopically for delineating soilscape units. Soils and land properties were evaluated for suitability of the land for agriculture i.e. paddy and wheat. The results indicate that the relative case in delineating physiographic units offered by colour infrared air-photos does not commensurate with their cost. In the study area, 19.57 and 14.78 per cent area have been found to be suitable for paddy and wheat, respectively.     

Vegetation type discrimination on Landsat TM data in heterogeneous forested landscape of Western Ghats—Accuracy evaluation from large scale aerial photo maps

In the present study, forest type classification using Landsat TM False Colour Composite (FCC) bands 2, 3, 4 has been evaluated for mapping highly heterogeneous forest environment of Western Ghats (Kerala). Visual interpretation of Landsat TM FCC has been carried out to identify bioclimatic vegetation types. For accuracy estimation maps prepared from 1∶15,000 scale black-and-white aerial photographs have been used as ground check data. For comparison aerial photomap classes have been aggregated to match with Landsat-TM-derived map. The classification accuracy of ten major bioclimatic and landcover types was estimated using systematic sampling procedure. The overall classification accuracy of the forest types for the study area was 88.33%.     

Forest working plan inputs through high resolution space photographs—A case study in Dangs forest,Gujarat

For scientific management of forests, working plans are prepared for each forest division in India. Majority of forest type or density mapping in India has been carried out using space borne data at a scale of 1∶1 m or 1∶250,000. A forest compartment, (100–400 ha) the smallest management unit can be delineated atleast on 1∶50,000 or 1∶63,360 scale by using space borne data. In this paper, an attempt has been made to use high resolution MKF-6 and KATE-140 data obtained during SALYUT-7 overpass in April 1984 for providing information at compartment level. This paper describes mapping done for entire Dangs forest showing different density classes in different working circles and ranges. Classification accuracy was found to be 90% at 95 confidence limit.     

Relative performance of landsat MSS,TM and IRS LISS-I data for acreage estimation of Rabi sorghum

Acreage estimation of Rabi sorghum crop in Ahmadnagar, Pune and Solapur districts of central Maharashtra has been attempted using synchronously acquired Landsat MSS and TM data of 1987–88 season and IRS LISS-I data of 1988–89 season; in conjuction with near-synchronous ground truth data. The remote-sensing-based acreage estimations for the districts were compared with the respective estimates by Bureau of Economics and Statistics (BES). As the acreages were underestimated with the classification of standard four-band MSS data, the atmospheric correction of fourband MSS data and normalised differencing (ND) of the atmospheric-corrected MSS data were attempted. The main observations are: (1) the use of Landsat MSS data results in underestimation of sorghum acreage in comparison with BES estimation, (2) the atmospheric correction and ND transformation of MSS data are necessary for bringing acreage estimates in agreement with BES estimates, (3) Mid-IR data in band 1.55 to 1.75 μm are useful in improving the separability of land-use classes, and (4) remote sensing data with radiometric sensitivity comparable to LISS-I or Landsat TM and Signal-to-Noise ratios comparable to LISS-I data are suitable for accurate acreage estimation of sorghum.     

Land use change detection based on multi‐date imagery from different satellite sensor systems

An empirical study was performed assessing the accuracy of land use change detection when using satellite image data acquired ten years apart by sensors with differing spatial resolutions. Landsat/Multi‐spectral Scanner (MSS) with Landsat/Thematic Mapper (TM) or SPOT/High Resolution Visible (HRV) multi‐spectral (XS) data were used as a multi‐data pair for detecting land use change. The primary objectives of the study were to: (1) compare standard change detection methods (e.g. multi‐date ratioing and principal components analysis) applied to image data of varying spatial resolution; (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice‐versa in the registration process: and (3) determine if Landsat/TM or SPOT/ HRV(XS) data provides more accurate detection of land use changes when registered to historical Landsat/MSS data.

Ratioing multi‐sensor, multi‐date satellite image data produced higher change detection accuracies than did principal components analysis and is useful as a land use change enhancement technique. Ratioing red and near infrared bands of a Landsat/MSS‐SPOT/HRV(XS) multi‐date pair produced substantially higher change detection accuracies (～10%) than ratioing similar bands of a Landsat/MSS ‐ Landsat/TM multi‐data pair. Using a higher‐resolution raster grid of 20 meters when registering Landsat/MSS and SPOTZHRV(XS) images produced a slightly higher change detection accuracy than when both images were registered to an 80 meter raster grid. Applying a “majority”; moving window filter whose size approximated a minimum mapping unit of 1 hectare increased change detection accuracies by 1–3% and reduced commission errors by 10–25%.     

Urban land use mapping and zoning of Bombay Metropolitan Region using remote sensing data

Bombay Metropolitan Region covering an area of about 4,360 sq. km. was selected for urban land use studies and for urban land use zoning. Urban land use mapping was carried out using SPOT multispectral linear array imagery on 1∶25,000 scale employing visual analysis tehcniques. Fifteen maps were prepared depicting the spatial distribution of various urban classes in the Greater Bombay and New Bombay regions. Sixteen urban land use maps were also prepared using Landsat TM data showing the distribution of land use pattern on 1∶50,000 scale for the entire metropolitan region. Urban land use zoning was carried out based upon suitability index on 1∶250,000 scale. This map provides information on the areas to be used for construction and areas to be kept under green belt in the metropolitan region. This study is a joint venture of Space Applications Centre with Bombay Metropolitan Development authority.     

Tea acreage estimation and condition assessment using satellite data in nilgiri district,tamilnadu

In the present study an attempt has been made to estimate acreage and condition of tea plantations by using satellite based digital remotely sensed data in visible, near infra-red and middle infra-red spectral regions, in the Nilgiri district of Tamilnadu state. Landsat MSS and TM data, acquired on Dec. 26, 1990 were used in the analysis, Different spectral band combinations, Landsat MSS (1234), TM (1234), TM (2345) and TM (123457) were used for identification of tea plantations. District-boundary-overlaying approach with complete enumeration of digital data was used for estimation of tea acreages. Condition assessment of tea plantations is based on the Greenness Index. Use of Landsat MSS data resulted in an underestimation of area under tea whereas the acreages estimated by using TM spectral band combinations 1234 and 2345 compared closely with the estimates of Department of Horticulture (DOH). The distribution pattern of various condition classes of tea plantations compared well with the prevailing ground conditions as observed during post-classification field survey in September 1992 in the district.     

Mapping Soil Resources in Part of Northern India Using Spaceborne Multispectral Data

Abstract

Spaceborne multispectral measurements have been found very useful tool in delineating soilscape boundaries. The Indian Remote Sensing Satellite (IRS 1B) Linear Imaging Self‐scanning Sensor (LISS‐II) data in the form of false colour composite (FCC) prints at 1:50,000 scale covering part of a complex terrain ‐ hard rock intermixed with the alluvium, were interpreted visually for mapping soil resources. The physiography and lithology of the terrain have been found to have a direct bearing on the occurrence of soils. The image elements which are the reflection of surface drainage, land use/land cover, wetness, etc have been helpful in segregating the broad physiographic units into their components. These sub‐divisions were ultimately found to be associated with the characteristic soils. The methodology and results are discussed in detail.     

用SAR与TM数字复合图像编制1:5万～1:10万解译地质图的优点及精度分析

SAR与TM数字复合处理技术,能为地质解译及地质制图提供一份空间与波谱信息都比较丰富 的图像。复合图像的优点是：地物细节详尽,立体感强,图像上阴影又少,便于进行各种图像增 强处理和与其他地学资料对比分析、拟合。试验表明,除岩性解译能力较差外,其它地质体的解译能完全或基本满足中等(大)比例尺区域地质调查的要求。     

空间实验室图像的制图能力分析及其地学应用——以西藏日喀则地区和珠峰地区的试验为例

本文论述了空间实验室测量相机(MC)拍摄的彩色红外立体像对在中比例尺地形制图、正射影像地图以及土地资源调查中的应用可能性,给出1:10万和1:20万比例尺的制图例证,表明平面位置和高程精度能满足1:10万比例尺地形图规范要求;1:10万比例尺影像图可以满足专题制图精度要求。 应用数字图像处理技术,将二种来源(MC,MSS)的遥感数据做数字匹配,并进行信息提取、组合、增强和分类等处理,其结果与原始图像比较表明有独特的优越性,与MSS原始数据相比,图像的空间分辨率明显提高,各种类型界线更分明,可分辨类目增多;而与MC原始图像相比,其光谱特性获得改善且能保持原有的空间分辨率。土地利用类型解释精度与MSS和MC原始图像比较分别提高7—20％左右。     

The Utility of Very High Spatial Resolution Images to Identify Urban Objects

Abstract

Landsat MSS, TM and SPOT XS imageries were used in conjunction with unsupervised, supervised and hybrid classilication techniques to classify land cover types in semi‐arid savannas of Mathison Pastoral Station in the Katherine region of northern Australia. Accuracy assessment was based on field data from 246 ground survey sites over a 745‐km² study area. Of 14 land cover classes identified by traditional mapping means, all combinations of imageries and classification techniques differentiated at least seven land cover types. The overall accuracy for these classifications ranged between 43% and 67%. SPOT XS image delivered the best accuracy followed by TM and MSS; unsupervised classification performed better than supervised and hybrid methods. User's and producer's accuracy of individual land units ranged from 0% to 100%. Riparian woodlands, woodland on limestone slopes, shrubland on clay plains, woodland on limestone plains and shadows were the best‐mapped classes. The land units that were associated with undulating hills were not mapped accurately. However, incorporation of a digital elevation model (DEM) in a GIS improved the overall accuracy. The user's and producer's accuracy of dominant land cover types were also enhanced. The classification results and the efficacy of the techniques at Mathison were similar to those found for a nearby semi‐arid area (Kidman Springs) about 200 km from Mathison. However, the overall accuracy was lower at Mathison than at Kidman Springs. Spectral classification masks were developed from the SPOT XS and TM imageries at Kidman Springs, and were applied to classify SPOT XS and TM imageries at Mathison. Initial results showed that the classification mask could be successfully extrapolated to map dominant land cover types but only with moderate accuracy (50%).     

High spatial resolution image object classification for terrestrial oil spill contamination mapping in West Siberia

This work is a part of the OSCaR pilot study (Oil Spill Contamination mapping in Russia). A synergetic concept for an object based and multi temporal mapping and classification system for terrestrial oil spill pollution using a test area in West Siberia is presented. An object oriented image classification system is created to map contaminated soils, vegetation and changes in the oil exploration well infrastructure in high resolution data. Due to the limited spectral resolution of Quickbird data context information and image object structure are used as additional features building a structural object knowledge base for the area. The distance of potentially polluted areas to industrial land use and infrastructure objects is utilized to classify crude oil contaminated surfaces. Additionally the potential of Landsat data for dating of oil spill events using change indicators is tested with multi temporal Landsat data from 1987, 1995 and 2001. OSCaR defined three sub-projects: (1) high resolution mapping of crude oil contaminated surfaces, (2) mapping of industrial infrastructure change, (3) dating of oil spill events using multi temporal Landsat data. Validation of the contamination mapping results has been done with field data from Russian experts provided by the Yugra State University in Khanty-Mansiyskiy. The developed image object structure classification system has shown good results for the severely polluted areas with good overall classification accuracy. However it has also revealed the need for direct mapping of hydrocarbon substances. Oil spill event dating with Landsat data was very much limited by the low spatial resolution of Landsat TM 5 data, small scale character of oil spilled surfaces and limited information about oil spill dates.     

Mapping of tropical dry deciduous forest and landuse in part of Vindhyan range using satellite remote sensing

Forest vegetation of Vindhyan range located in the north of G.B. Pant Sagar (dam) has been subjected to degradation due to high biotic pressure caused by the installation of thermal power plants, coal mining, heavy cattle grazing etc. In the present study Landsat TM FCC of 1∶250,000 scale was visually analysed with respect to forest vegetation types, crown density and structure along with other landuse/land cover classes. ExceptShorea robusta (Sal) andLagerstroemia parviflora (Lendia) all forest vegetation types show higher percentage of degradation and under-stocked condition with respect to their areal extent under study. Overall classification accuracy of the forest types has been found to be 88.94%. This indicates that for obtaining reliable mapping accuracy in dry deciduous areas, satellite remote sensing data of appropriate season is essential.

     

无人机航摄技术在大比例尺测图中的应用研究

以无人机航摄技术在大比例尺(1∶1 000、1∶500)地形图测绘中的应用为研究目的,采用固定翼无人机平台,搭载非量测型数码相机,于河北某矿区进行航摄大比例尺地形图制作实验,通过外业实测点位数据对测图高程及平面精度进行评估。实验结果表明:通过严控误差影响因素无人机航摄技术可以满足1∶1 000比例尺测图精度要求,1∶500比例尺测图精度无法满足。最后,基于精度评定数据对误差产生的原因进行了深入分析与探讨,为无人机航摄技术测绘大比例尺地形图应用的可行性及可靠性提供了经验。     

Soil erosion assessment and mapping of the algar river watershed (uttar pradesh) using remote sensing technique

This study was undertaken to prepare an inventory on soil erosion of a hilly river watershed — the Aglar watershed, part of Tehri Garhwal and Dehradun districts (U.P.), using terrain physiography and soil survey data obtained from interpretation and analysis of Landsat TM FCC (1:62,500 scale) and limited ground investigations. The watershed is divided into four broad physiographic units viz. higher Himalayas (> 2000m elevation); lower Himalayas (< 2000m elevation); river terraces and flood plains. Each physiographic unit has been further divided into subunits on the basis of aspects and landuse. Three major orders of soils viz. Inceptisols, Mollisols and Entisols were found in different physiographic units. Soil, and land properties of soilscape units viz. soil depth, texture, structure, slope, landuse and soil temperature regime were evaluated for soil-erosion hazard. The results indicate that in the whole watershed 19.13%, 45.68%, 26.51% and 7.92% areas have been found to be under none to slight, moderate, severe and very severe soil erosion hazard categories, respectively.     

基于数字化技术的1∶250000地形图制图研究

全国1∶250 000数据库是国家基础地理信息系统的重要组成部分,在许多部门得到广泛应用。随着科技进步和用户使用的不断深入,数据库的横向应用要求越来越多,进行新一轮的1∶250 000地形图制图工作势在必行。地图制图的数字化是计算机及自动化技术在地图制图学领域渗透发展的产物。本文主要介绍利用现有1∶250 000地形要素数据库成果,进行数字地图制图的工作要点。     

关于公主岭市1∶1000比例尺地形图成果现状及长远发展问题的探讨

公主岭市依靠得天独厚的地缘优势和优惠的投资政策,使近十年的建设得到了迅速发展。房地产开发、城市路网改造、招商引资工程建设对测绘工作提出了更高的要求。公主岭市现有的1∶1 000比例尺地形图是1993年测绘的聚脂薄膜蒙绘图,测绘面积小,已使用了11年,现势性比较差。现以施测吉林华润生化黄龙工业园1∶1 000比例尺地形图为例,探讨如何满足规划设计急需和城市长远发展的问题。     

基于NDVI背景场的雪盖制图算法探索

NDSI算法提取MSS雪盖面积时,受到MSS影像缺少短波红外波段的局限。为充分精确提取MSS影像的雪盖面积,本文探索一种以NDVI为背景场的雪盖制图新思路。该方法首先在辐射校正时利用6S模型反演地表反射率,然后根据各地物的光谱特性差异和NDVI特性差异,在ENVI软件SPECTRAL模块中创建冰雪光谱阈值查找表。通过ETM＋和TM影像的三个例证,详细阐明该算法流程以及查找表的创建,并以NDSI对其雪盖制图进行精度验证。结果一致表明,与常规的分类方法（最大似然法）相比较,本文探索的NDVI背景场算法有更高的总体精度和Kappa系数。     

Landsat TM versus MSS data for forest type identification

Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) data were digitally analyzed for forest type identification in the Kisatchie Ranger District, Kisatchie National Forest, Louisiana. Ground‐verification maps were produced from field surveys and interpretation of 1.12,000 and 1: 58,000 color‐infrared (CIR) aerial photography of nine compartments. Stand boundary and soils maps were input to a digital Geographic Information System (GIS) with the Landsat and ground‐verification data.

‐ Unsupervised classifications of the Landsat data did not identify the above cover types well. Supervised classifications were tested by stand agreement to the ground verification. The highest four‐class agreement was obtained for the TM classification (76 percent). Three‐class (open, pine, and hardwoods) stand agreements (81 (MSS) and 85 (TM) percent) were not significantly different as tested by analysis of variance (alpha level 0.1).