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%.     

Relative utility of Landsat-TM and MSS data small scale soil mapping

The Landsat MSS and TM data in the form of false colour composite (FCC) prints at 1∶250,000 scale over parts of Mirzapur (U.P.) and Rohtas district of (Bihar) were interpreted monoscopically in concert with the collateral data and limited field check for soilscape boundary delineation. The study has revealed that at the mapping scale, except for improved image contrast and capturing features of relatively smaller dimensions, no additional advantage has been noticed with TM data over MSS data with respect to exhibition of soilscape boundaries. However, the capability of TM data to withstand enlargement upto 1∶50,000 which is not feasible with MSS data is an additional feature from soil mapping viewpoint.     

遥感技术在深圳-大亚湾沿海高速公路工程地质调查及选线中的应用

应用计算机增强和特征信息提取技术,结合航空摄影图像的立体观察对比,对卫星TM数字图像地学信息进行解译研究,并通过野外调查验证,对深圳-大亚湾沿海高速公路沿线工程地质环境进行了迅速评价,经计算机不同处理方法处理获得的TM专题信息图像在进行地质构造解译和岩土体分类中均起到重要作用,而航片在地质体边界圈定和详细定位以及灾害地质现象分析方面效果较好。在不到两个月的时间里就完成了该项目从图像处理、解译到野外调查和成图及报告编写的全过程工作,节约勘察资金50%以上,满足了公路勘查前期工作的需要,也充分体现了遥感技术的优越性。遥感解译研究与常规地质调绘方法相结合,可取得事半功倍的效果,也是公路勘察手段现代化的标志和必经之路。     

Mapping and monitoring of urban landuse of Hisar Town,Haryana using remote sensing techniques

Aerial photographs for the year 1965 and 1975 and Landsat TM (FCC) 1986 data on 1:50,000 scale were used to map and monitor the pattern of growth and development of Hisar Town during the last 20 years. The different landuse categories identified are residential, commercial, industrial, recreational, vacant lands etc. The original shape of the town was nucleated one, but presently it is star-shaped, which is due to extension of the urban centre along the radiating roads. It has mainly elongated itself along the Delhi and Rajgarh roads. The presence of Government Livestock Farm (GLF), Equine Breeding Farm and HAU Farm towards North-west of the town has completely checked its growth on these sides. The total residential-cum-commercial area has nearly doubled during 1965–1975 and trebled by 1986. The change in net area under different types of urban land-use categories, described above has also been calculated. Degraded scrub lands and sandy wasteland on the fringes of the town have been identified where further development can be planned to avoid encroachment on good agricultural lands. Recommendations have been given for future urban planning of the town.     

Improved geological mapping using landsat-5 TM data in Weixi area,Yunnan province China

Different image processing algorithms have been evaluated in the context of geological mapping using Landsat TM data. False color composites, the principal component imagery, and IHS decorrelation stretching method for Landsat-5 TM data have been found useful for delineating the regional geological features, mainly to provide the maximum geological information of the studied area. The study testifies that using which image processing yields best results for geological mapping in arid and semiarid regions by preserving morphological and spectral information. Generally, the studied area can be divided into three main geological units: Basaltic intrusive rocks, Metamorphic with varying intensities and Sedimentary rocks.     

Multi‐Temporal Study and Detailed Photogeological Mapping of the Armero Debris Flow (Colombia), Using Landsat TM 5 Images

Abstract

On November the 13^th of 1985, the City of Armero (Colombia) was destroyed by debris flows generated by a reactivation of the Nevado del Ruiz Volcano. The flows ocurred in at least three principal pulses, as was observed by the disater's survivors. Landsat TM 5 data processing was carried out in subscenes taken before and after the lahar sedimentation.

False color composites were generated and combined with the geological information available in order to visualize the magnitude of the catastrophe and the flow characteristics. Taking advantage of Landsat TM 5 images with high spectral resolution, a detailed photogeological mapping of the three principal pulses of the debris flows was carried out. Landsat TM 5 proved to be a powerful complementary source of information for hazard assesment of these catastrophic debris flows. The images were used in addition to ground‐based information, and were an easy way to help ordinary people and decision makers understand such hazardous volcanic situations.     

Improved geological mapping using landsat-5 TM data in Weixi area, Yunnan province China

Different image processing algorithms have been evaluated in the context of geological mapping using Landsat TM data. False color composites, the principal component imagery, and IHS decorrelation stretching method for Landsat-5 TM data have been found useful for delineating the regional geological features, mainly to provide the maximum geological information of the studied area . The study testifies that using which image processing yields best results for geological mapping in arid and semiarid regions by preserving morphological and spectral information. Generally, the studied area can be divided into three main geological units: Basaltic intrusive rocks, Metamorphic with varying intensities and Sedimentary rocks.     

Monitoring of forest cover type and landuse classes through remote sensing techniques

Ranikhet tahsil being situated in mountaineous region of the Himalaya has been influenced by fast changes in forest cover and landuse during the recent past. Remote sensing technique has been employed to monitor the changes in forest cover and imporant landuse classes. Landsat MSS (FCC) and Landsat TM (FCC) of 1972 and 1986 respectively has been visually interpreted. The study highlights the potential of remote sensing techniques for monitoring the changes in forest cover and land use classes.     

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.

     

Use of remote sensing techniques for detailed hydrogeological investigations in parts of Narmada Sagar command area,MP

Of late, airphoto interpretation and Landsat imagery analysis play a vital role in geological mapping for detailed hydrogeological investigations for ground water prospecting. Certain obscure features like lineaments/fracture zones which are masked by surface soil and cultivated lands are easily visible. In hard rocks like granites and basalts the occurrence and movement of ground water are controlled by the fracture pattern. Delineation of potential zones of ground water for successful exploration is possible by the study and analysis of aerial photographs, visual interpretation of Landsat imagery and interactive data analysis system through computer techniques and applications. These techniques constitute for data integration with conventional methods of hydrogeological investigations and exploratory drilling. As a case study an area of 1500 sq km in part of the Narmada river basin of Madhya Pradesh and also forming a portion of Narmada Sagar area covered under topo sheets 46 N/12 and 46 N/16 was taken up. Aerial photographs pertaining to the area of study and Landsat imagery of band 5 and 7 in scale blown upto 1∶250,00 were scanned and analysed. It was observed that the successful artesian wells are located in pominent lineament/fractured zones in the study area. It is also recommended after through analysis different hyddromorphic zonations for future exploration of ground water.     

Growing stock estimation through stratified sampling on satellite remote sensing data

Aerial photographs are being extensively used for forest surveys i.e. forest cover type mapping, assessment of growing stock, estimation of area, vegetation studies, etc. Satellite remote sensing technology offers new possibilities and scope for achieving some of the above applications with higher accuracy and reliability. The assessment of growing stock through subjective stratification has also become possible with increase in spatial and spectral resolution. In the present study, the LANDSAT TM FCC (1966) has been visually interpreted on the basis of tonal characteristics. Stratified random sampling method has then used for determination of number of sample units for collection of ground Inventory data. Using regression equations, the volume per hectare of individual forest cover types were calculated. Satellite remote sensing data has been used for initial stratification, distribution of sample plots and calculation of area under various forest cover types. Estimate has been made for available commecial and non-commercial growing stocks in the study area.     

Monitoring of salt affected soils — A case study using aerial photographs,salyut‐7 space photographs,and landsat TM data

Soils of part of Ukai‐kakarapar Command area, Gujarat (India) have been mapped at 1:25, 000 scale using aerial photographs of December 1977. It was observed that about 36.3% of the area was affected by soil salinity/alkalinity. The test area has been remapped using Salyut‐7 space photographs taken during Indo‐Soviet joint flight in April, 1984. The area affected by soil salinity/alkalinity was found to be substantially higher (80.3%). The earlier mapping using aerial photographs was done when the soil surface was compartively moist (December 1977) as compared to date of Salyut‐7 photography (April 1984), when the soil surface was likely to be devoid of moisture and the salts moved to the surface. To have easy comparision with the map prepared by using aerial photographs, Landsat TM data of December, 1985 was used in which 45.7% of the total area was mapped as salt affected. The extent of area delineated using Landsat TM was higher than that of 1977 but much lesser than the area delineated using Salyut‐7 (MKF‐6M) photographs. This indicated that the increase in the extent of salt affected area in the map prepared using the MKF‐6M photographs might be partly due to actual increase in the salinity/alkalinity and partly due to the seasonal affects. Among the various bands of MKF‐6M, band ‐4 was found to be the best for delineating the salt affected soils. The boundaries were sharper in the FCC and band No.4 of MKF‐6M than in the aerial photographs.     

Landsat 8 vs. Landsat 5: A comparison based on urban and peri-urban land cover mapping

An image dataset from the Landsat OLI spaceborne sensor is compared with the Landsat TM in order to evaluate the excellence of the new imagery in urban landcover classification. Widely known pixel-based and object-based image analysis methods have been implemented in this work like Maximum Likelihood, Support Vector Machine, k-Nearest Neighbor, Feature Analyst and Sub-pixel. Classification results from Landsat OLI provide more accurate results comparing to the Landsat TM. Object-based classifications produced a more uniform result, but suffer from the absorption of small rare classes into large homogenous areas, as a consequence of the segmentation, merging and the spatial parameters in the spatial resolution (30 m) of Landsat images. Based exclusively on the overall accuracy reports, the SVM pixel-based classification from Landsat 8 proved to be the most accurate for the purpose of mapping urban land cover, using medium spatial resolution imagery.     

Remote sensing and GIS application in the detection of environmental degradation indicators

The main aim of this research is to highlight the environment change indicators during the last 20 years in a representa-tive area of the southern part of Iraq(Basrah Province was taken as a case) to understand the main causes which led to widespread environment degradation phenomena using a 1:250000 mapping scale.Remote sensing and GIS’s 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 land,sand land,urban area,unused land,and water bodies.Supervised classification and Normalized Difference Vegetation Index(NDVI),Normalized Difference Build-up Index(NDBI),Normalized Difference Water Index(NDWI),Normalized Difference Salinity In-dex(NDSI),and Topsoil Grain Size Index(GSI) were adopted in this research and used respectively to retrieve its class boundary.The results showed a clear deterioration in vegetative cover(514.9 km2) and an increase of sand dune accumulations(438.6 km2),accounting for 10.1,and 10.6 percent,respectively,of the total study area.In addition,a decrease in the water bodies’ area was de-tected(228.9 km2).Sand area accumulations had increased in the total study area,with an annual increasing expansion rate of(33.7 km2·yr·1) during the thirteen years covered by the study.It is therefore imperative that Iraqi government undertake a series of pru-dent actions now that will enable to be in the best possible position when the current environmental crisis ultimately passes.     

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.     

陆地卫星TM数据用于辽东地区铅锌矿产预测的方法探索

本文详细地介绍了笔者近期完成的一项试验研究, 目的在于将遥感、地质及物化探等综合地 质信息用于矿产预测, 建立相应的数学模型, 为找矿圈定靶区。在研究工作中, 引人数学地质的 “区域化变量”概念, 利用线性构造信息及与区内铅锌矿产密切相关的岩性单元进行统计分析； 提取出与矿化有关的地质因子, 并利用二项分布函数, 以6km × 6km的网距, 计算出至少含一个 铅锌矿化点的概率值。最终, 得到一张反映区内至少含有一个矿化点的概率等值线图。它为区内 成矿地质条件评价及找矿远景区的选择提供了定量数据, 并为了一步将要进行的综合信息矿产预 测提供了重要的基础资料。野外验证期间, 在根据概率分析所圈定的异常区内, 发现了新的铅锌 矿化现象, 其评价工作还在进行之中。     

Evaluation of Landsat TM data for forest cover type and landuse classification in subtropical forests of Kumaon Himalaya (U.P.)

LANDSAT-TM has been evaluated for forest cover type and landuse classification in subtropical forests of Kumaon Himalaya (U.P.) Comparative evaluation of false colour composite generated by using various band combinations has been made. Digital image processing of Landsat-TM data on VIPS-32 RRSSC computer system has been carried out to stratify vegetation types. Conventional band combination in false colour composite is Bands 2, 3 and 4 in Red/Green/Blue sequence of Landsat TM for landuse classification. The present study however suggests that false colour combination using Landsat TM bands viz., 4, 5 and 3 in Red/Green/Blue sequence is the most suitable for visual interpretation of various forest cover types and landuse classes. It is felt that to extract full information from increased spatial and spectral resolution of Landsat TM, it is necessary to process the data digitally to classify land cover features like vegetation. Supervised classification using maximum likelihood algorithm has been attemped to stratify the forest vegetation. Only four bands are sufficient enough to classify vegetaton types. These bands are 2,3,4 and 5. The classification results were smoothed digitaly to increase the readiability of the map. Finally, the classification carred out using digital technique were evaluated using systematic sampling design. It is observed that forest cover type mapping can be achieved upto 80% overall mapping accuracy. Monospecies stand Chirpine can be mapped in two density classes viz., dense pine (<40%) with more than 90% accuracy. Poor accuracy (66%) was observed while mapping pine medium dense areas. The digital smoothening reduced the overall mapping accuracy. Conclusively, Landsat-TM can be used as operatonal sensor for forest cover type mapping even in complex landuse-terrain of Kumaon Himalaya (U.P.)     

Comparison of reconnaissance soil maps prepared by conventional method and landsat imagery interpretation

Landsat images have been used in conjunction with topographical and geological information to prepare soil map of Mudhol taluk in Bijapur district, Karnataka state. The map has been compared with the reconnaisance map prepared by conventional method using 1:63,360 scale Survey of India toposheets. The study reveals that more accurate soil maps in terms of boundary delineation and composition of soil mapping units could be prepared by interpretation of Landsat images with adequate ground data. The method can thus be used in revising and improving many of the existing reconnaissance soil maps prepared by conventional method.     

The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna

Multi-sensor image fusion using the wavelet approach provides a conceptual framework for the improvement of the spatial resolution with minimal distortion of the spectral content of the source image. This paper assesses whether images with a large ratio of spatial resolution can be fused, and evaluates the potential of using such fused images for mapping the Brazilian Savanna. Three types of wavelet transforms were used to perform the fusion between MODIS and Landsat TM images. Five quality measures were defined to assess the quality of the fused images. The results showed that it was possible to perform the fusion of MODIS and TM images and the pyramidal in Fourier space wavelet transform provided the best quality measures for the fused images. Classification results showed that fused images could be used for mapping the Brazilian Savanna with an accuracy level comparable to the Landsat TM image.     

利用TM数据识别二道沟金矿地表地质特征

卫星TM数据以其丰富的光谱和连续的空间信息以及合理的市场价格被广泛地应用在中、小比例尺的金矿勘查中。利用TM数据所提供的信息指导大比例尺的矿区勘查和进行危机矿山外围找矿尚属探索性工作。本课题在利用TM数据对辽宁二道沟金矿地表矿床地质特征的识别就是这方面研究的一个尝试,并取得了很好的效果。