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1.
Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a ‘best guess’ prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the sub-pixel scale, but only for simulated imagery. We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of small-scale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool for mapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of practical remotely sensed imagery at the sub pixel scale.  相似文献   

2.
This study investigates the Land Use & Land Cover (LULC) changes in a coastal area of the southwest part of Epirus region, called Preveza, situated in North-western Greece. Remote sensing imagery coming from the Enhanced Thematic Mapper (ETM+) sensor on board at the Landsat 7 satellite platform is used for this purpose. More specifically, we identified LULC changes in this environmentally sensitive coastal area, using Landsat image scenes for the dates of June 19th, 2000 and July 22nd, 2009. During this period, there was an increasing tourist activity and a high growth in the construction sector of the study area. The land-use changes were identified, examining several vegetation indices and band combinations, along with the implementation of different well-known classification techniques. The Normalized Difference Vegetation Index (NDVI) and the Brightness Index (BI) have proved to be the most suitable indices to successfully identify discrete land surface classes for this study area. Regarding the classifiers, a series of traditional and modern algorithms were tested. The Artificial Neural Networks (ANNs) and the Support Vector Machines (SVMs) gave improved results in comparison to other more traditional classification techniques. The best overall accuracy for the study area was achieved with the SVM classifier and reached 96.25% and 97.15% on the dates of June 19th, 2000 and July 22nd, 2009 respectively. The classification results depicted notable urbanization, small deforestation and important LULC changes in the agriculture sector, indicating a rapid coastal environment change in the region of interest.  相似文献   

3.
In this paper we discuss how low spatial resolution (1 km) ERS ATSR-2 and NOAA AVHRR satellite data were used to map and monitor changes in the grazing vegetation of the Badia region of Jordan. This area is typical of many arid zone grazing areas, comprising sparse vegetation and highly reflective soils. These two factors were found to severely limit the usefulness of satellite-derived vegetation indices that are frequently used to map and monitor vegetation in more temperate areas. Furthermore, the relationship between vegetation indices and percentage vegetation cover was found to be site-specific, thus reducing their application for large-scale vegetation monitoring. As an alternative, a hybrid geometric optical/empirically based model was developed for the area. This was based on the illumination geometry and reflectance values from the red and near-infrared scattergram of the satellite images. The output of the model was a series of maps indicating percentage vegetation cover for different dates and these were used to construct maps showing areas of vegetation change. Strong correlations (r2=0.837) were found between estimates of percentage vegetation cover derived from the model, and measurements made at a series of 16 field sites in the area. The use of geometric optical models based on satellite imagery improves the ability to map areas of grazing vegetation in arid areas such as the Badia and provides a good alternative to the use of vegetation indices.  相似文献   

4.
I.StduyAreaPUschRjdgeoftheSantaCatalinaMountains,CoronadONaionalForest,SoutheastArizona,wasselectedasastudyareafOrvegetationmopingandatestoftheroleOfGISinaidingrem0teIysenseddataclassificati0n.BeinganepitOmeoftheSantaCatalinaMountains,PUscllmdgeiscomprisedOf23O.65sqUarelQnoflandIocatedonthesouthwesternPOrti0noftheSantaCarelinaRangerDistrictOftheCoronadoNationalForest.ltprovidesasharPcontrastbebeenthenamralruggdnessOftheSantaCatalinaMountainsandtheCityOfTucson,Arizona,araPdl…  相似文献   

5.
Mapping ecosystem services (ES) over large scales is important for environmental monitoring but is often prohibitively expensive and difficult. We test a hybrid, low-cost method of mapping ES indicators over large scales in Pará State, Brazil. Four ES indicators (vegetation carbon stocks, biodiversity index, soil chemical quality index and rates of water infiltration into soil) were measured in the field and then summarized spatially for regional land-cover classes derived from satellite imagery. The regionally mapped ES values correlated strongly with independent and local measures of ES. For example, regional estimates of the vegetation carbon stocks are strongly correlated with actual measures derived from field samples and validation data (significant anova test – p-value = 4.51e?9) and differed on average by only 20 Mg/ha from the field data. Our spatially-nested approach provides reliable and accurate maps of ES at both local and regional scales. Local maps account for the specificities of an area while regional maps provide an accurate generalization of an ES’ state. Such up-scaling methods infuse large-scale ES maps with localized data and enable the estimation of uncertainty of at regional scales. Our approach is first step towards the spatial characterization of ES at large and potentially global scales.  相似文献   

6.
Abstract

Development programmes in Sahelian Africa are beginning to use geographic information system (GIS) technology. One of the GIS and remote sensing programmes introduced to the region in the late 1980s was the use of seasonal vegetation maps made from satellite data to support grasshopper and locust control. Following serious outbreaks of these pests in 1987, the programme addressed a critical need, by national and international crop protection organizations, to monitor site-specific dynamic vegetation conditions associated with grasshopper and locust breeding. The primary products used in assessing vegetation conditions were vegetation index (greenness) image maps derived from National Oceanic and Atmospheric Administration satellite imagery. Vegetation index data were integrated in a GIS with digital cartographic data of individual Sahelian countries. These near-real-time image maps were used regularly in 10 countries for locating potential grasshopper and locust habitats. The programme to monitor vegetation conditions is currently being institutionalized in the Sahel.  相似文献   

7.
The Atlantic Forest biome has only 13 percent of its pristine vegetation cover left. This article analyzes the consequences of land changes on forest cover in the Paraíba Valley, São Paulo state, Brazil, from 1985 to 2011. Multitemporal satellite image classifications were carried out to map eight land use and land cover classes. The forest cover increased from 2,696 km2 in 1985 to 4,704 km2 in 2011, mostly over areas of degraded pastures. The highest rates of afforestation were observed within protected areas around eucalyptus plantations. On the other hand, deforestation processes were concentrated on areas covered by secondary forests. Socioeconomic changes taking place in particular Brazilian settings, such as industrialization and agricultural modernization, allied to the Paraíba Valley's natural biophysical constraints for agricultural production, have led the region to experience a remarkable case of forest transition.  相似文献   

8.
Traditionally, forest inventory and ecosystem mapping at local to regional scales rely on manual interpretation of aerial photographs, based on standardized, expert-driven classification schemes. These current approaches provide the information needed for forest ecosystem management but constrain the thematic and spatial resolution of mapping and are infrequently repeated. The goal of this research was to demonstrate the utility of an unsupervised, quantitative technique based on Light Detection And Ranging (LiDAR) data and multi-spectral satellite imagery for mapping local-scale ecosystems over a heterogeneous landscape of forested and non-forested ecosystems. We derived a range of metrics characterizing local terrain and vegetation from LiDAR and RapidEye imagery for Calvert and Hecate Islands, British Columbia. These metrics were used in a cluster analysis to classify and quantitatively characterize ecological units across the island. A total of 18 clusters were derived. The clusters were attributed with quantitative summary statistics from the remotely sensed data inputs and contextualized through comparison to ecological units delineated in a traditional expert-driven mapping method using aerial photographs. The 18 clusters describe ecosystems ranging from open shrublands to dense, productive forest and include a riparian zone and many wetter and wetland ecosystems. The clusters provide detailed, spatially-explicit information for characterizing the landscape as a mosaic of units defined by topography and vegetation structure. This study demonstrates that using various types of remotely sensed data in a quantitative classification can provide scientists and managers with multivariate information unique from that which results from traditional, expert-based ecosystem mapping methods.  相似文献   

9.
新疆荒漠地区植被覆盖度遥感估算模型十分缺乏,给荒漠化监测等相关工作带来很大不便,开展植被覆盖度遥感估算经验模型研究,对于促进和完善相关地区的生态监测及研究工作具有积极的现实意义。通过对阜康市北部沙漠南缘和克拉玛依市中部平原荒漠进行无人机航拍,利用无人机遥感提取（光合）植被信息,并将无人机航拍影像的植被覆盖度统计单元与高分辨率卫星影像像元在空间上直接相对应,获取在高分辨率卫星影像像元尺度上的植被盖度,然后通过植被覆盖度和空间上与其相对应的源自高分辨率卫星影像的NDVI数据的拟合关系,建立基于源自高分二号影像的NDVI的阜康北部沙漠植被覆盖度遥感估算线性模型以及基于源自ZY1-02C影像的NDVI的克拉玛依平原荒漠植被覆盖度遥感估算二次多项式模型。研究中所采用的无人机遥感与卫星遥感相结合、植被覆盖度统计单元与卫星像元在空间上直接对应的方法,可避免以往相关工作中常以点位测量数据代表卫星像元数据所带来的不确定性。由于所用卫星影像的NDVI数据稳定性相对不足等原因,所建立的遥感估算模型的估算精度尚相对偏低,有待于今后进一步的工作加以改进。  相似文献   

10.
We compared four remote sensing methods to detect changes in New Zealand's grasslands (image differencing, normalised difference vegetation index (NDVI) differencing post‐classification and visual interpretation). The visual interpretation resulted in the best classification results, with a 98% overall accuracy when compared with ground‐truthed data. The tests on automatic classification (image differencing, NDVI differencing) and post classification had much lower accuracies, ranging from 47% to 56%. In the New Zealand grassland landscape, automatic detection methods were not able to differentiate between variations of soil moisture and vegetation phenology from variations in land‐use change. This, in combination with topographic effects, which have hampered the automated mapping of vegetation, is the main reason why visual interpretation of high‐resolution imagery is still needed.  相似文献   

11.
We examine the selection criteria for satellite images and methods of processing them in the process of mapping underwater landscapes using remotely sensed data, discuss the interpretation principles and algorithms as well as some issues related to the support of observations with field material. It is shown that a detailed landscape mapping of shallow marine waters by methods of visual and automated interpretation requires multispectral superhigh spatial resolution images. Results of investigations made on underwater profiles by using lightweight diving outfits were employed to describe seven types of underwater landscapes, and echo sounder measurements were used in constructing the digital elevation model for the bottom of Srednyaya Bay. It is established that the regions for which it was possible to carry out a reliable interpretation of data from the IKONOS-2 spacecraft are in the range of depths between 0 and 10 m and make up about three-fourths of the area of the bay bottom. Ten facies were identified and put on the map, for each of which we determined the area, the range of depths and the mean depth of propagation. Remotely sensed data were used to assess the contribution (in the spatial structure of the geosystem) of algal vegetation on the littoral; the eelgrass fields were ranked according to the degree of projective cover. As a result of a clustering according to the similarity of spectral attributes, we identified ten groups of pixels of the image analyzed. An analysis is made of the agreement between the distribution of facies identified by expert interpretation and results of an automated classification of pixels, and the contours of landscape units were updated. The conclusion is drawn regarding integration of the computer-aided and visual approaches to interpretation of remotely sensed data for shallow marine waters leading to a “hybrid” express method of mapping landscapes of shallow marine waters.  相似文献   

12.
Landslides are frequent natural disasters in mountainous regions, particularly in the Himalayas in India during the southwest monsoon season. Although scientific study of landslides has been in progress for years, no significant achievement has been made to preclude landsliding and allay disasters. This research was undertaken to understand the areal distribution of landslides based on geological formations and geomorphological processes, and to provide more precise information regarding slope instability and mechanisms of failure. After completing a landslide inventory, prepared through field investigation and satellite image analysis, 493 landslides, comprising 131 investigated in the field and 362 identified from satellite imagery, were identified and mapped. The areal distribution of these landslides shows that sites more prone to landsliding have moderate to steep slopes, the lithology of the Lesser Himalayan formations, and excavations for road corridors. Landslide susceptibility zones were delineated for the area using the weight-of-evidence method on the basis of the frequency and distribution of landslides. Weights of selected variables were computed on the basis of severity of triggering factors. The accuracy of landslide susceptibility zones, calculated statistically (R2 = .93), suggests high accuracy of the model for predicting landsliding in the area.  相似文献   

13.
The critical need to consider all options in the search for groundwater in semi-arid areas has promoted work on the possible association of near-surface groundwater and vegetation characteristics using a combination of remote-sensing data and geographic information systems (GIS) techniques. Two vegetative criteria (dense woody cover and abundance of deep-rooting species) are identified as being indicative of near-surface groundwater, and their spatial distribution is tested against the location of aquifers in southeast Botswana. Vegetative criteria classes were combined in a GIS environment with the distribution of geomorphic units and bedrock geology to determine the degree of coincidence with assumed or known aquifers. Results indicate that the distribution of dense woody vegetation as mapped from Thematic Mapper imagery has some potential in identifying especially surficial but also bedrock near-surface groundwater sources in mostly naturally vegetated semi-arid areas. Dense woody cover classes tend to select aquifers in topographically higher areas while classes comprising some deep-rooting species tend to select low-lying aquifers such as those occurring in fossil valleys. Deep-rooting species, however, are less successful as a vegetative criterion. Although various technical refinements are suggested, this work shows that vegetative criteria mapping can however be used in conjunction with conventional geological/geophysical techniques to enhance the prospects for groundwater location in relatively undisturbed semi-arid areas.  相似文献   

14.
生态环境遥感综合系列制图方法   总被引：16，自引：0，他引：16  
廖克 《地理学报》2005,60(3):479-486
提出生态环境遥感综合系列制图方法, 采用GPS、RS、GIS相结合, 在野外综合考察与遥感影像综合判读的基础上, 利用GPS定位和GIS数据采集、分析与处理的方法技术, 在室内先生成综合性的生态环境单元轮廓界线图, 并列表记录其类型及其编码, 然后自动演绎派生出生态环境类型图及各要素专题地图。全文包括三个部分:1生态环境遥感综合系列制图的科学依据与基本方法;2生态环境遥感综合系列制图的具体方法和步骤;3结论。该方法不仅保证了生态环境综合系列地图的统一协调和科学质量, 而且大大加快了成图速度, 使系列地图更好地反映生态环境各要素之间的相互联系, 便于各地图的比较分析与综合评价, 尤其为生态环境信息系统和其他地理信息系统基本单元及其数据库的建立提供了最有效的方法。  相似文献   

15.
The weights-of-evidence model (a Bayesian probability model) was applied to the task of evaluating landslide susceptibility using GIS. Using landslide location and a spatial database containing information such as topography, soil, forest, geology, land cover and lineament, the weights-of-evidence model was applied to calculate each relevant factor's rating for the Boun area in Korea, which had suffered substantial landslide damage following heavy rain in 1998. In the topographic database, the factors were slope, aspect and curvature; in the soil database, they were soil texture, soil material, soil drainage, soil effective thickness and topographic type; in the forest map, they were forest type, timber diameter, timber age and forest density; lithology was derived from the geological database; land-use information came from Landsat TM satellite imagery; and lineament data from IRS satellite imagery. Tests of conditional independence were performed for the selection of factors, allowing 43 combinations of factors to be analysed. For the analysis of mapping landslide susceptibility, the contrast values, W + and W -, of each factor's rating were overlaid spatially. The results of the analysis were validated using the previous landslide locations. The combination of slope, curvature, topography, timber diameter, geology and lineament showed the best results. The results can be used for hazard prevention and land-use planning.  相似文献   

16.
Quantification of landscape-based vegetation structural variation and pattern is a significant goal for a variety of ecological, monitoring and biodiversity studies. Vegetation structural metrics, derived from airborne laser scanning (ALS or aerial light detection and ranging—LiDAR) and QuickBird satellite imagery, were used to establish the degree of plot-based vegetation variation at a hillslope scale. Topographic position is an indicator of energy and water availability, and was quantified using DEM-based insolation and topographic wetness, respectively, stratifying areas into hot-warm-cold and wet-moist-dry topographic classes. A range of vegetation metrics—maximum and modal canopy height, crown cover, foliage cover, NDVI and semivariance—were compared among randomly selected plots from each topographic class. NDVI increases with increasing landscape wetness, whereas ALS-derived foliage cover decreases with increasing insolation. Foliage cover is well correlated with crown cover (R 2 =0.65), and since foliage cover is readily calculable for whole-of-landscape application, it will provide valuable and complementary information to NDVI. Between-plot heterogeneity increases with increasing wetness and decreasing insolation, indicating that more sampling is required in these locations to capture the full range of landscape-based variability. Pattern analysis in landscape ecology is one of the fundamental requirements of landscape ecology, and the methods described here offer statistically significant, quantifiable and repeatable means to realise that goal at a fine spatial grain.  相似文献   

17.
While aerial photography and satellite imagery are the usual data sources used in remote sensing, land based oblique photographs can also be used to measure ecological change. By using such historical photographs, the time frame for change detection can be extended into the late 1800s and early 1900s, predating the era of aerial imagery by decades. Recent advancements in computing power have enabled the development of techniques for georeferencing oblique angle photographs. The WSL Monoplotting Tool is a new piece of software that opens the door to analyzing such photographs by allowing for extraction of spatially referenced vector data from oblique photographs. A very large repeat photography collection based on the world's largest systematic collection of historical mountain topographic survey images, the Mountain Legacy Project, contains >6000 high resolution oblique image pairs showing landscape changes in the Rocky Mountains of Alberta between ca. 1900 – today. We used a subset of photographs from this collection to assess the accuracy and utility of the WSL Monoplotting Tool for georeferencing oblique photographs and measuring landscape change. We determined that the tool georeferenced objects to within less than 15 m of their real world 3D spatial location, and the displacement of the geographic center of over 121 control points was less than 3 m from the real world spatial location. Most of the error in individual object placement was due to the angle of viewing incidence with the ground (i.e., low angle/highly oblique angles resulted in greater horizontal error). Simple rules of control point selection are proposed to reduce georeferencing errors. We further demonstrate a method by which raster data can be rapidly extracted from an image pair to measure changes in vegetation cover over time. This new process permits the rapid evaluation of a large number of images to facilitate landscape scale analysis of oblique imagery.  相似文献   

18.
A survey of the vegetation of the North York Moors identified nine vegetation associations, one of which has not been recognized in other British uplands; callunetum vulgaris sub-association juncetosum squarrosi. The vegetation associations occur in a mosaic too detailed for mapping at any practical scale, so seven map classes based largely on terrain patterns were mapped from black-and-white aerial photographs.The map classes provide a suitable basis for assessing the extent to which a system of areas managed specifically for conservation might represent the biota of the North York Moors.  相似文献   

19.
This article evaluates the potential of 1-m resolution, 128-band hyperspectral imagery for mapping in-stream habitats, depths, and woody debris in third- to fifth-order streams in the northern Yellowstone region. Maximum likelihood supervised classification using principal component images provided overall classification accuracies for in-stream habitats (glides, riffles, pools, and eddy drop zones) ranging from 69% for third-order streams to 86% for fifth-order streams. This scale dependency of classification accuracy was probably driven by the greater proportion of transitional boundary areas in the smaller streams. Multiple regressions of measured depths (y) versus principal component scores (x1, x2,…, xn) generated R2 values ranging from 67% for high-gradient riffles to 99% for glides in a fifth-order reach. R2 values were lower in third-order reaches, ranging from 28% for runs and glides to 94% for pools. The less accurate depth estimates obtained for smaller streams probably resulted from the relative increase in the number of mixed pixels, where a wide range of depths and surface turbulence occurred within a single pixel. Matched filter (MF) mapping of woody debris generated overall accuracies of 83% in the fifth-order Lamar River. Accuracy figures for the in-stream habitat and wood mapping may have been misleadingly low because the fine-resolution imagery captured fine-scale variations not mapped by field teams, which in turn generated false “misclassifications” when the image and field maps were compared.The use of high spatial resolution hyperspectral (HSRH) imagery for stream mapping is limited by the need for clear water to measure depth, by any tree cover obscuring the stream, and by the limited availability of airborne hyperspectral sensors. Nonetheless, the high accuracies achieved in northern Yellowstone streams indicate that HSRH imagery can be a powerful tool for watershed-wide mapping, monitoring, and modeling of streams.  相似文献   

20.
Supervised classification of digital Landsat satellite images was used to locate seabird nesting habitats in the Russian High Arctic archipelago of Franz Josef Land, a region where the avifauna is poorly known and ecologically vulnerable. Major seabird nesting colonies are readily identifiable in Landsat Thematic Mapper (TM) imagery of the region due primarily to the distinctive spectral signature of vegetation on ornithogenically altered soils below bird cliffs. Supervised image classification was used to pinpoint areas displaying spectral characteristics typical of documented seabird nesting habitats. A total of 101 seabird nesting colony locations identified in Russian and Western literature from 1898 to 1996 was used as training sites to develop spectral signatures from a summer TM image mosaic for use in a supervised maximum likelihood classification. The classified image was thresholded and compared to a map of documented nesting locations. Of the 101 field-documented nesting sites, 96 were clearly identified in the classified image. An inventory was produced of all undocumented seabird habitats suggested by the classification, totalling over 300 sites. The methodology used may be applicable to other arctic regions and is intended as a first step when planning ecological protection zones in remote and inaccessible arctic regions.  相似文献   

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