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1.
Vegetation maps are essential tools for the conservation and management of landscapes as they contain essential information for informing conservation decisions. Traditionally, maps have been created using field-based approaches which, due to limitations in costs and time, restrict the size of the area for which they can be created and frequency at which they can be updated. With the increasing availability of satellite sensors providing multi-spectral imagery with high temporal frequency, new methods for efficient and accurate vegetation mapping have been developed. The objective of this study was to investigate to what extent multi-seasonal Sentinel-2 imagery can assist in mapping complex compositional classifications at fine spatial scales. We deliberately chose a challenging case study, namely a visually and structurally homogenous scrub vegetation (known as kwongan) of Western Australia. The classification scheme consists of 24 target classes and a random 60/40 split was used for model building and validation. We compared several multi-temporal (seasonal) feature sets, consisting of numerous combinations of spectral bands, vegetation indices as well as principal component and tasselled cap transformations, as input to four machine learning classifiers (Support Vector Machines; SVM, Nearest Neighbour; NN, Random Forests; RF, and Classification Trees; CT) to separate target classes. The results show that a multi-temporal feature set combining autumn and spring images sufficiently captured the phenological differences between the classes and produced the best results, with SVM (74%) and NN (72%) classifiers returning statistically superior results compared to RF (65%) and CT (50%). The SWIR spectral bands captured during spring, the greenness indices captured during spring and the tasselled cap transformations derived from the autumn image emerged as most informative, which suggests that ecological factors (e.g. shared species, patch dynamics) occurring at a sub-pixel level likely had the biggest impact on class confusion. However, despite these challenges, the results are auspicious and suggest that seasonal Sentinel-2 imagery has the potential to predict compositional vegetation classes with high accuracy. Further work is needed to determine whether these results are replicable in other vegetation types and regions.  相似文献   

2.
ABSTRACT

We propose a method for spatial downscaling of Landsat 8-derived LST maps from 100(30?m) resolution down to 2–4?m with the use of the Multiple Adaptive Regression Splines (MARS) models coupled with very high resolution auxiliary data derived from hyperspectral aerial imagery and large-scale topographic maps. We applied the method to four Landsat 8 scenes, two collected in summer and two in winter, for three British towns collectively representing a variety of urban form. We used several spectral indices as well as fractional coverage of water and paved surfaces as LST predictors, and applied a novel method for the correction of temporal mismatch between spectral indices derived from aerial and satellite imagery captured at different dates, allowing for the application of the downscaling method for multiple dates without the need for repeating the aerial survey. Our results suggest that the method performed well for the summer dates, achieving RMSE of 1.40–1.83?K prior to and 0.76–1.21?K after correction for residuals. We conclude that the MARS models, by addressing the non-linear relationship of LST at coarse and fine spatial resolutions, can be successfully applied to produce high resolution LST maps suitable for studies of urban thermal environment at local scales.  相似文献   

3.
System corrected multispectral imagery of the Central Afar region in Ethiopia provided by the ERTS-1 satellite was evaluated for the purposes of natural resource inventory under the headings of geology, vegetation, soils and land use. The methods and results of image interpretation are discussed in detail and the following general conclusions may be drawn. The ERTS-1 imagery provides a synoptic view of the region that is very nearly orthographic. A colour composite print of multispectral bands 4, 5 and 7 is superior to any of the individual black and white bands for natural resource interpretation. Exploratory soil, vegetation and land use maps and reconnaissance geological maps can be constructed rapidly. The small percentage of forest and agricultural land in this particular area enhances the geological value of the image. Satellite imagery is a valuable addition to the more conventional forms of aerial photography for agricultural studies provided that the study area covers at least 10 000 km2. Ground control was acquired between October 1972 and May 1973.  相似文献   

4.
This paper discusses the development and implementation of a method that can be used with multi-decadal Landsat data for computing general coastal US land use and land cover (LULC) maps consisting of seven classes. With Mobile Bay, Alabama as the study region, the method that was applied to derive LULC products for nine dates across a 34-year time span. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and Coastal Change and Analysis Program value-added products. Each classification’s overall accuracy was assessed by comparing stratified random locations to available high spatial resolution satellite and aerial imagery, field survey data and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall κ statistics ranging from 0.78 to 0.89. Accurate classifications were computed for all nine dates, yielding effective results regardless of season and Landsat sensor. This classification method provided useful map inputs for computing LULC change products.  相似文献   

5.
Abstract

Wildfire is a major disturbance agent in Mediterranean Type Ecosystems (MTEs). Providing reliable, quantitative information on the area of burns and the level of damage caused is therefore important both for guiding resource management and global change monitoring. Previous studies have successfully mapped burn severity using remote sensing, but reliable accuracy has yet to be gained using standard methods over different vegetation types. The objective of this research was to classify burn severity across several vegetation types using Landsat ETM imagery in two areas affected by wildfire in southern California in June 1999. Spectral mixture analysis (SMA) using four reference endmembers (vegetation, soil, shade, non‐photosynthetic vegetation) and a single (charcoal‐ash) image endmember were used to enhance imagery prior to burn severity classification using decision trees. SMA provided a robust technique for enhancing fire‐affected areas due to its ability to extract sub‐pixel information and minimize the effects of topography on single date satellite data. Overall kappa classification accuracy results were high (0.71 and 0.85, respectively) for the burned areas, using five canopy consumption classes. Individual severity class accuracies ranged from 0.5 to 0.94.  相似文献   

6.
This paper presents a novel methodological approach to countrywide vegetation mapping. We used green vegetation biomass over the year as captured by coarse resolution hyper-temporal NDVI satellite-imagery, to generate vegetation mapping units at the biome, ecoregion and at the next lower hierarchical level for Namibia, excluding the Zambezi Region. Our method was based on a time series of 15 years of SPOT-VGT-MVC images each representing a specific 10-day period (dekad). The ISODATA unsupervised clustering technique was used to separately create 2–100 NDVI-cluster maps. The optimal number of temporal NDVI-clusters to represent the information on vegetation contained in the imagery was established by divergence separability statistics of all generated NDVI-clusters. The selected map consisted of legend of 81 cluster-specific temporal NDVI-profiles covering each a 15-year period of averaged NDVI data representing all pixels classified to that cluster. Then, by legend-entry using the dekad-medians of all 15 annual repeats, we produced generalized legend-entries without year-specific anomalies for each cluster. Subsequently, a hierarchical cluster analysis of these temporal NDVI-profiles was used to produce a dendrogram that generated grouping options for the 81 legend-entries. Maps with cluster-groups of 8 and 4 legend-entries resulted. The 81-cluster map and its 65 legend-entries vector version have no equivalent in published vegetation maps. The 8 cluster-group map broadly corresponds with published ecoregion level maps and the 4 cluster-group map with the published biome maps in their number of legend units. The published vegetation maps varied considerably from our NDVI-profile maps in the location of mapping unit boundaries. The agreement index between our map and published biome maps ranges from 70−93. For the ecoregion level, the agreement index is much lower, namely 51−75. Our methodological approach showed a considerably higher discretionary power for hierarchical levels and the number of vegetation mapping units than the approaches applied to previously published maps. We recommended an approach to transform our three hyper-temporal NDVI-profiles based legend-entries into more specific vegetation units. This might be accomplished by re-analysis of available, spatially-comprehensive plant species occurrence data.  相似文献   

7.
This paper reports an investigation to determine the degree to which digitally processed Landsat TM imagery can be used to discriminate among vegetated lava flows of different ages in the Menengai Caldera, Kenya. Since Landsat data display vegetation parameters well, and plant communities vary with type and depth of soil development, selective digital processing techniques were applied to take advantage of these characteristics for discriminating relative age differences of the underlying volcanics. A selective series of five images, consisting of a color‐coded Landsat 5 classification and four color composites, were compared with geologic maps. These included a color coded, modified, unsupervised classification and contrast enhanced, color composite images using TM bands 3–2–1, 4–3–2 and 7–5–3, and the first 3 Karhunen‐Loeve transformation axes that had been generated using 7 Landsat TM bands.

The most recent of more than 70 post‐caldera flows within the caldera are trachytes, which are variably covered by shrubs and subsidiary grasses. Soil development evolves as a function of time, and as such, supports a changing plant community. Progressively older flows exhibit the increasing dominance of grasses over bushes. It was found that the Landsat images correlated well with geologic maps, but that the two mapped age classes could be further subdivided on the basis of different vegetation communities. It is concluded that field maps can be modified, and in some cases corrected by use of such imagery, and that digitally enhanced Landsat imagery can be a useful aid to field mapping in similar terrains.  相似文献   

8.
Abstract

The goal of this research was to explore the utility of very high spatial resolution, digital remotely sensed imagery for monitoring land‐cover changes in habitat preserves within southern California coastal shrublands. Changes were assessed for Los Penasquitos Canyon Preserve, a large open space in San Diego County, over the 1996 to 1999 period for which imagery was available.

Multispectral, digital camera imagery from two summer dates, three years apart, was acquired using the Airborne Data Acquisition and Registration (ADAR) digital‐camera system. These very high resolution (VHR) image data (1m), composed of three visible and one near‐infrared wavebands (V/NIR), were the primary image input for assessing land cover change. Image‐derived datasets generated from georeferenced and registered ADAR imagery included multitemporal overlays and multitemporal band differencing with threshold selection. Two different multitemporal image classifications were generated from these datasets and compared. Single‐date imagery was analyzed interactively with image‐derived datasets and with information from field observations in an effort to discern change types. A ground sampling survey conducted soon after the 1999 image acquisition provided concurrent ground reference data.

Most changes occurring within the three‐year interval were associated with transitional phenological states and differential precipitation effects on herbaceous cover. Variations in air temperatures and timing of rainfall contributed to differences that the seven‐week image acquisition offset may have caused. Disturbance factors of mechanical clearing, erosion, potentially invasive plants, and fire were evident and their influence on the presence, absence, and type of vegetation cover were likely sources of change signals.

The multitemporal VHR, V/NIR image data enabled relatively fine‐scale land cover changes to be detected and identified. Band differencing followed by multitemporal classification provided an effective means for detecting vegetation increase or decrease. Detailed information on short‐term disturbance effects and long‐term vegetation type conversions can be extracted if image acquisitions are carefully planned and geometric and radiometric processing steps are implemented.  相似文献   

9.
This study presents a modified low-cost approach, which integrates the spectral angle mapper and image difference algorithms in order to enhance classification maps for the purpose of monitoring and analysing land use/land cover change between 2000 and 2015 for the Emirate of Dubai. The approach was modified by collecting 320 training samples from QuickBird images with a spatial resolution of 0.6 m, as well as carrying out field observations, followed by the application of a 3?×?3 Soble filter, sieving classes, majority/minority analysis, and clump classes of the obtained classification maps. The accuracy assessment showed that the targeted 2000, 2005, 2010 and 2015 classification maps have 88.1252%, 89.0699%, 90.1225% and 96.0965% accuracy, respectively. The results showed that the built-up area increased by 233.721?km2 (5.81%) between 2000 and 2005 and continues to increase even up and till the present time. The assessment of changes in the periods 2000–2005 and 2010–2015 confirmed that net vegetation area losses were more pronounced from 2000 to 2005 than from 2010 to 2015, dropping from 47,618 to 40,820?km2, respectively. This study is aimed to assist urban planners and decision-makers, as well as research institutes.  相似文献   

10.
Mapping a specific crop using single date multi-spectral imagery remains a challenging task because vegetation spectral responses are considerably similar. The use of multi-temporal images helps to discriminate specific crops as the classifier can make use of the uniqueness in the temporal evolution of the spectral responses of the different vegetated classes. However, one major concern in multi-temporal studies is the selection of optimum dates for the discrimination of crops as the use of all available temporal dates can be counterproductive. In this study this concern was addressed by selecting the best 2, 3, 4… combinations dates. This was done by conducting a separability analysis between the spectral response of the class of interest (here, sugarcane-ratoon) and non-interest classes. For this analysis, we used time series LISS-III and AWiFS sensors data that were classified using Possibilistic c-Means (PCM). This fuzzy classifier can extract single class sub-pixel information. The end result of this study was the detection of best (optimum) temporal dates for discriminating a specific crop, sugarcane-ratoon. An accuracy of 92.8 % was achieved for extracting ratoon crop using AWiFS data whereas the optimum temporal LISS-III data provided a least entropy of 0.437. Such information can be used by agricultural department in selecting an optimum number of strategically placed temporal images in the crop growing season for discriminating the specific crop accurately.  相似文献   

11.
The information content of flood extent maps can be increased considerably by including information on the uncertainty of the flood area delineation. This additional information can be of benefit in flood forecasting and monitoring. Furthermore, flood probability maps can be converted to binary maps showing flooded and non-flooded areas by applying a threshold probability value pF = 0.5. In this study, a probabilistic change detection approach for flood mapping based on synthetic aperture radar (SAR) time series is proposed. For this purpose, conditional probability density functions (PDFs) for land and open water surfaces were estimated from ENVISAT ASAR Wide Swath (WS) time series containing >600 images using a reference mask of permanent water bodies. A pixel-wise harmonic model was used to account for seasonality in backscatter from land areas caused by soil moisture and vegetation dynamics. The approach was evaluated for a large-scale flood event along the River Severn, United Kingdom. The retrieved flood probability maps were compared to a reference flood mask derived from high-resolution aerial imagery by means of reliability diagrams. The obtained performance measures indicate both high reliability and confidence although there was a slight under-estimation of the flood extent, which may in part be attributed to topographically induced radar shadows along the edges of the floodplain. Furthermore, the results highlight the importance of local incidence angle for the separability between flooded and non-flooded areas as specular reflection properties of open water surfaces increase with a more oblique viewing geometry.  相似文献   

12.
Abstract

The main objective of this study is to investigate and monitor the landuse and morphological changes in the floodplain part of the Talar River, northern parts of Iran. In the present study, the aerial photographs have been used to produce landuse maps of the floodplain for three periods including 1968, 1994, and 2013. The quantitative analysis of the produced landuse maps showed that the floodplain has undergone substantial landuse changes. Moreover, the sediment bar and the beach area have been decreased about 97 and 90%, respectively, during the 45-year period. Substantial increases of 192 and 622% have been observed for orchards and residential areas, respectively. On the other hand, not only the forest and riparian vegetation were decreased but also the average width of river was decreased about 25.5 m. In addition, flow length of the study reach increased about 8 m. The RNCI was about ?0.7 m per year indicating sedimentation process. During the period of 1968–2013, Caspian Sea has retreated about 150 m and the delta of Talar River was changed. This study showed that morphological actions during first 26 years (1968–1994) were the stable and last 19 years had the change period, especially sedimentation (bar).  相似文献   

13.
Land cover and land use change (LCLUC) is a global phenomenon, and LCLUC in urbanizing regions has substantial impacts on humans and their environments. In this paper, a semi-automatic approach to identifying the type and starting time of urbanization was developed and tested based on dense time series of Vegetation-Impervious-Soil (V-I-S) maps derived from Landsat surface reflectance imagery. The accuracy of modeled V-I-S fractions and the estimated time of initial change in impervious cover were assessed. North Taiwan, one of the regions of the island of Taiwan that experienced the greatest urban LCLUC, was chosen as a test area, and the study period is 1990 to 2015, a period of substantial urbanization. In total, 295 dates of Landsat imagery were used to create 295 V-I-S fraction maps that were used to construct fractional cover time series for each pixel. Root Mean Square Error (RMSE)s for the modeled Vegetation, Impervious, and Soil were 25 %, 22 %, 24 % respectively. The time of Urban Expansion is estimated by logistic regression applied to Impervious cover time series, while the time of change for Urban Renewal is determined by the period of brief Soil exposure. The identified location and estimated time for newly urbanized lands were generally accurate, with 80% of Urban Expansion estimated within ±2.4 years. However, the accuracy of identified Urban Renewal was relatively low. Our approach to identifying Urban Expansion with dense time series of Landsat imagery is shown to be reliable, while Urban Renewal identification is not.  相似文献   

14.
Abstract

Riparian vegetation has a fundamental influence on the biological, chemical and physical nature of rivers. The quantification of riparian landcover is now recognised as being essential to the holistic study of the ecosystem characteristics of rivers. Medium resolution satellite imagery is now commonly used as an efficient and cost effective method for mapping vegetation cover; however such data often lack the resolution to provide accurate information about vegetation cover within riparian corridors. To assess this, we measure the accuracy of SPOT multispectral satellite imagery for classification of riparian vegetation along the Taieri River in New Zealand. In this paper, we discuss different sampling strategies for the classification of riparian zones. We conclude that SPOT multispectral imagery requires considerable interpretative analysis before being adequate to produce sufficiently detailed maps of riparian vegetation required for use in stream ecological research.  相似文献   

15.
Results are presented of analysis of Landsat MSS imagery for the purpose of assessing damage to northern taiga and tundra vegetation caused by emissions generated by nonferrous metallurgy on northwest Russia's Kola Peninsula. Unlike earlier studies, the present project attempts to provide spatially comprehensive coverage of vegetation impacts, according to a standardized methodology for their assessment. A reduction in the number of feature classes identifiable upon a change from visual interpretation to automated classification based on spectral brightness values made it necessary to test alternative classification procedures (based on brightness ratios and the normalized vegetation index).  相似文献   

16.
Abstract

The objective of this study was to explore the utility of multi‐temporal, multi‐spectral image data acquired by the IKONOS satellite system for monitoring detailed land cover changes within shrubland habitat reserves. Sub‐pixel accuracy in date‐to‐date registration was achieved, in spite of the irregular relief of the study area and the high spatial resolution of the imagery. Change vector classification enabled features ranging in size from tens of square meters to several hectares to be detected and six general land cover change classes to be identified. Interpretation of the change vector classification product in conjunction with visual inspection of the multi‐temporal imagery enabled identification of specific change types such as: vegetation disturbance and associated increase in soil exposure, shrub removal, urban edge vegetation clearing and fire maintenance, increase in vegetation cover, spread of invasive plant species, fire scars and subsequent recovery, erosional scouring, trail and road development, and expansion of bicycle disturbances.  相似文献   

17.
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).  相似文献   

18.
Monitoring ecological indicators is important for assessing impacts of human activities on ecosystems. A means of identifying and applying appropriate indicators is a prerequisite for: environmental assessment; better assessment and understanding of ecosystem health; elucidation of biogeochemical trends; and more accurate predictions of future responses to global change, particularly those due to anthropogenic disturbance. The challenge is to derive meaningful indicators of change that capture the complexities of ecosystems yet can be monitored consistently over large areas and across time. In this study, methods for monitoring indicators of land cover (LC) and forest change were developed using multi-sensor Landsat imagery. Mapping and updating procedures were applied to the Humber River Basin (HRB) in Newfoundland and Labrador, one of four test sites in Canada selected for testing the development of national-scale methods. Procedures involved unsupervised clustering and labeling of baseline imagery, followed by image-to-image spectral clustering to derive binary change masks within which new LC types were classified for non-baseline imagery. Updated maps were compatible with the baseline map and reflected change in LC for three time periods: 1976–1990, 1990–2001, and 2001–2007. From the LC products, several change indicators were quantified including: forest depletion, forest regeneration, forest change, net forest change, and annual rates of change. The procedures were validated using field plots to assess the accuracy of the 2007 LC product (74.2% for 10 LC classes) and change classes observed from 2001 to 2007 (87.8% for four change classes: depletion, regeneration, non-treed class no change, and treed class no change). Methods were considered to be highly efficient and operationally feasible over large areas spanning multiple Landsat scenes. Specific results for the test site provided trend information supporting land and resource management in the HRB region.  相似文献   

19.
In perennial and natural vegetation systems, monitoring changes in vegetation over time is of fundamental interest for identifying and quantifying impacts of management and natural processes. Subtle changes in vegetation cover can be identified by calculating the trends of a vegetation density index over time. In this paper, we apply such an index-trends approach, which has been developed and applied to time series Landsat imagery in rangeland and woodland environments, to continental-scale monitoring of disturbances within forested regions of Australia. This paper describes the operational methods used for the generation of National Forest Trend (NFT) information, which is a time-series summary providing visual indication of within-forest vegetation changes (disturbance and recovery) over time at 25 m resolution. This result is based on a national archive of calibrated Landsat TM/ETM+ data from 1989 to 2006 produced for Australia's National Carbon Accounting System (NCAS). The NCAS was designed in 1999 initially to provide consistent fine-scale classifications for monitoring forest cover extent and changes (i.e. land use change) over the Australian continent using time series Landsat imagery. NFT information identifies more subtle changes within forested areas and provides a capacity to identify processes affecting forests which are of primary interest to ecologists and land managers. The NFT product relies on the identification of an appropriate Landsat-based vegetation cover index (defined as a linear combination of spectral image bands) that is sensitive to changes in forest density. The time series of index values at a location, derived from calibrated imagery, represents a consistent surrogate to track density changes. To produce the trends summary information, statistical summaries of the index response over time (such as slope and quadratic curvature) are calculated. These calculated index responses of woody vegetation cover are then displayed as maps where the different colours indicate the approximate timing, direction (decline or increase), magnitude and spatial extent of the changes in vegetation cover. These trend images provide a self-contained and easily interpretable summary of vegetation change at scales that are relevant for natural resource management (NRM) and environmental reporting.  相似文献   

20.
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.  相似文献   

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