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1.
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
2.
Understanding the relationship between vegetation and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing vegetation indicators derived from remotely sensed imagery, we present an approach to forecast shifts in the future distribution of vegetation. Remotely sensed metrics representing cumulative greenness, seasonality, and minimum cover have successfully been linked to species distributions over broad spatial scales. In this paper we developed models between a historical time series of Advanced Very High Resolution Radiometer (AVHRR) satellite imagery from 1987 to 2007 at 1 km spatial resolution with corresponding climate data using regression tree modeling approaches. We then applied these models to three climate change scenarios produced by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity indices in 2065. Our results indicated that warming may lead to increased cumulative greenness in northern British Columbia and seasonality in vegetation is expected to decrease for higher elevations, while levels of minimum cover increase. The Coast Mountains of the Pacific Maritime region and high elevation edge habitats across British Columbia were forecasted to experience the greatest amount of change. Our approach provides resource managers with information to mitigate and adapt to future habitat dynamics. Forecasting vegetation productivity levels presents a novel approach for understanding the future implications of climate change on broad scale spatial patterns of vegetation. 相似文献
3.
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
4.
N. Sillero Luís Gonçalves-Seco 《International journal of geographical information science》2014,28(8):1709-1722
The analysis of the spatial structure of animal communities requires spatial data to determine the distribution of individuals and their limiting factors. New technologies like very precise GPS as well as satellite imagery and aerial photographs of very high spatial resolution are now available. Data from airborne LiDAR (Light Detection and Ranging) sensors can provide digital models of ground and vegetation surfaces with pixel sizes of less than 1 m. We present the first study in terrestrial herpetology using LiDAR data. We aim to identify the spatial patterns of a community of four species of lizards (Lacerta schreiberi, Timon lepidus, Podarcis bocagei, and P. hispanica), and to determine how the habitat is influencing the distribution of the species spatially. The study area is located in Northern Portugal. The position of each lizard was recorded during 16 surveys of 1 h with a very precise GPS (error < 1 m). LiDAR data provided digital models of surface, terrain, and normalised height. From these data, we derived slope, ruggedness, orientation, and hill-shading variables. We applied spatial statistics to determine the spatial structure of the community. We computed Maxent ecological niche models to determine the importance of environmental variables. The community and its species presented a clustered distribution. We identified 14 clusters, composed of 1–3 species. Species records showed two distribution patterns, with clusters associated with steep and flat areas. Cluster outliers had the same patterns. Juveniles and subadults were associated with areas of low quality, while sexes used space in similar ways. Maxent models identified suitable habitats across the study area for two species and in the flat areas for the other two species. LiDAR allowed us to understand the local distributions of a lizard community. Remotely sensed data and LiDAR are giving new insights into the study of species ecology. Images of higher spatial resolutions are necessary to map important factors such as refuges. 相似文献
5.
Jayson J. Murgoitio Rupesh Shrestha Lucas P. Spaete 《International journal of geographical information science》2013,27(10):1865-1883
Viewshed and line-of-sight are spatial analysis functions used in applications ranging from urban design to archaeology to hydrology. Vegetation data, a difficult variable to effectively emulate in computer models, is typically omitted from visibility calculations or unrealistically simulated. In visibility analyzes performed on a small scale, where calculation distances are a few hundred meters or less, ineffective incorporation of vegetation can lead to significant modeling error. Using an aerial LiDAR (light detection and ranging) data set of a lodgepole pine (Pinus contorta) dominant ecosystem in Idaho, USA, tree obstruction metrics were derived and integrated into a short-range visibility model. A total of 15 visibility plots were set at a micro-scale level, with visibility modeled to a maximum of 50 m from an observation point. Digital photographs of a 1 m2 target set at 5 m increments along three sightline paths for each visibility plot were used to establish control visibility values. Trunk obstructions, derived from mean vegetation height LiDAR data and processed through a series of tree structure algorithms, were factored into visibility calculations and compared to reference data. Results indicate the model calculated using trunk obstructions with LiDAR demonstrated a mean error of 8.8% underestimation of target visibility, while alternative methods using mean vegetation height and bare-earth models have an underestimation of 65.7% and overestimation of 31.1%, respectively. 相似文献
6.
Yingchun Zhou Sunil Narumalani William J. Waltman Sharon W. Waltman Michael A. Palecki 《International journal of geographical information science》2013,27(5):445-462
Growing concerns about global climate change, biodiversity maintenance, natural resources conservation, and long-term ecosystem sustainability have been responsible for the transformation of traditional single resource management approaches into integrated ecosystem management models. Eco-regions are large ecosystems of regional extent that contain smaller ecosystems of similar response potential and resource production capabilities. They can be used as a geographical framework for organizing and reporting resource information, setting bioecological recovery criteria, extrapolating site-level management, and monitoring global change. The objective of this research is to develop a quantitative, multivariate regionalization model that is capable of delineating eco-regions at multiple levels from remotely sensed information and other environmental and natural resources spatial data. The Spatial Pattern Analysis Model developed in this study uses a region-growing algorithm to generate spatially contiguous regions from primitive polygonal land units. The algorithm merges the most similar pair of neighbouring units at each iteration, based on satisfying certain similarity criteria until all units are grouped into one. This model was utilized to develop an eco-region map of Nebraska with three hierarchical levels. In the mapping process, the STATSGO data set was used to build the primitive map units. Environmental parameters included in the model were multi-temporal AVHRR data, soil rooting depth, organic matter content, available water capacity, and long-term annual averages of water balance and growing degree day totals. Development of the model provides a new and useful approach to eco-region mapping for resource managers and researchers. The method is automated and efficient, reduces the judgement biases and uncertainty of manual analyses, and can be replicated for other regions or for the regionalization of other themes. 相似文献
7.
A. J. Tatem H. G. Lewis P. M. Atkinson M. S. Nixon 《International journal of geographical information science》2013,27(7):647-672
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
8.
基于RS与GIS的通化地区景观格局动态变化 总被引：10，自引：0，他引：10
在RS、GIS技术的支持下,利用MSS及TM影像数据对照地形图提取了通化地区1980、1995以及2000年景观生态格局信息,并利用景观多样性、景观优势度、斑块面积变异指数、景观破碎度、斑块形状指数等对该区的整体景观格局和各县(包括县级市)景观格局以及其动态进行了定量分析。结果表明在全区范围内,各种景观类型对应景观指数存在显著差异;通过对各县级行政单位的景观指数计算表明,它们的景观格局存在明显差异;从时间序列上看,无论是整个研究区、还是各县的景观格局在1995年与1980、2000年差异较大,而1980与2000年景观格局相似。 相似文献
9.
Gentile Francesco Ficetola Anna Bonardi Caspar A. Mücher Niels L.M. Gilissen Emilio Padoa-Schioppa 《International journal of geographical information science》2014,28(8):1723-1739
At the local spatial scale, land-use variables are often employed as predictors for ecological niche models (ENMs). Remote sensing can provide additional synoptic information describing vegetation structure in detail. However, there is limited knowledge on which environmental variables and how many of them should be used to calibrate ENMs. We used an information-theoretic approach to compare the performance of ENMs using different sets of predictors: (1) a full set of land-cover variables (seven, obtained from the LGN6 Dutch National Land Use Database); (2) a reduced set of land-cover variables (three); (3) remotely sensed laser data optimized to measure vegetation structure and canopy height (LiDAR, light detection and ranging); and (4) combinations of land cover and LiDAR. ENMs were built for a set of bird species in the Veluwe Natura 2000 site (the Netherlands); for each species, 26–214 records were available from standardized monitoring. Models were built using MaxEnt, and the best performing models were identified using the Akaike’s information criterion corrected for small sample size (AICc). For 78% of the bird species analysed, LiDAR data were included in the best AICc model. The model including LiDAR only was the best performing one in most cases, followed by the model including a reduced set of land-use variables. Models including many land-use variables tended to have limited support. The number of variables included in the best model increased for species with more presence records. For all species with 33 records or less, the best model included LiDAR only. Models with many land-use variables were only selected for species with >150 records. Test area under the curve (AUC) scores ranged between 0.72 and 0.92. Remote sensing data can thus provide regional information useful for modelling at the local and landscape scale, particularly when presence records are limited. ENMs can be optimized through the selection of the number and identity of environmental predictors. Few variables can be sufficient if presence records are limited in number. Synoptic remote sensing data provide a good measure of vegetation structure and may allow a better representation of the available habitat, being extremely useful in this case. Conversely, a larger number of predictors, including land-use variables, can be useful if a large number of presence records are available. 相似文献
10.
Land use change is the result of the interplay between socioeconomic, institutional and environmental factors, and has important
impacts on the functioning of socioeconomic and environmental systems with important tradeoffs for sustainability, food security,
biodiversity and the vulnerability of people and ecosystems to global change impacts. Based on the results of the First Land
Use Survey in Tibet Autonomous Region carried out in the late 1980s, land use map of Lhasa area in 1990 was compiled for the
main agricultural area in Lhasa valley using aerial photos obtained in April, May and October 1991 and Landsat imagery in
the late 1980s and 1991 as remotely sensed data sources. Using these remotely sensed data, the land use status of Lhasa area
in 1991, 1992, 1993, 1995, 1999 and 2000 were mapped through updating annual changes of cultivated land, artificial forest,
grass planting, grassland restoration, and residential area and so on. Land use map for Lhasa area in 2007 was made using
ALOS AVNIR-2 composite images acquired on October 24 and December 26, 2007 through updating changes of main land use types.
According to land use status of Lhasa area in 1990, 1995, 2000 and 2007, the spatial and temporal land use dynamics in Lhasa
area from 1990 to 2007 are further analyzed using GIS spatial models in this paper. 相似文献
11.
Land use change is the result of the interplay between socioeconomic, institutional and environmental factors, and has important impacts on the functioning of socioeconomic and environmental systems with important tradeoffs for sustainability, food security, biodiversity and the vulnerability of people and ecosystems to global change impacts. Based on the results of the First Land Use Survey in Tibet Autonomous Region carried out in the late 1980s, land use map of Lhasa area in 1990 was compiled for the main agricultural area in Lhasa valley using aerial photos obtained in April, May and October 1991 and Landsat imagery in the late 1980s and 1991 as remotely sensed data sources. Using these remotely sensed data, the land use status of Lhasa area in 1991, 1992, 1993, 1995, 1999 and 2000 were mapped through updating annual changes of cultivated land, artificial forest, grass planting, grassland restoration, and residential area and so on. Land use map for Lhasa area in 2007 was made using ALOS AVNIR-2 composite images acquired on October 24 and December 26, 2007 through updating changes of main land use types. According to land use status of Lhasa area in 1990, 1995, 2000 and 2007, the spatial and temporal land use dynamics in Lhasa area from 1990 to 2007 are further analyzed using GIS spatial models in this paper. 相似文献
12.
Land use/cover, landforms and fragmentation patterns in a tropical dry forest in the southern Pacific region of Mexico 总被引：1，自引：0，他引：1
Leopoldo Galicia Alba Esmeralda Zarco-Arista Karla Ivette Mendoza-Robles José Luis Palacio-Prieto Arturo García-Romero 《Singapore journal of tropical geography》2008,29(2):137-154
In spite of widely documented studies of deforestation rates and land use/cover changes in tropical dry forests in Mexico, relatively little is known about fragmentation patterns in such forests. This study defines the spatial distribution of landforms and land use/cover types the lower Papagayo River basin and examines their influence on fragmentation patterns and biological diversity in a tropical dry forest in that southern Pacific region. The land use/cover map was constructed from aerial photographs, Landsat TM imagery (2000) and fieldwork. Landform units were defined based on altitude, slope, lithology and morphology. Landscape fragmentation parameters were obtained using FRAGSTATS (version 3.3) considering the numbers of patches, mean, minimum and maximum patch size, edge density, total edge and connectivity. Results show tropical dry forest to be remnant vegetation (~11 per cent), characterized by isolation and low connectivity. Land use/cover types have different effects on fragmentation patterns. Agriculture and cattle raising produce similar numbers of patches, but with a different mean size; and human settlements have a scattered distribution pattern. The abandonment of rural agricultural livelihoods has favoured the expansion of secondary tropical dry forest characterized by continuity and high connectivity, which suggests a high regeneration potential from land abandonment. It can be concluded that tropical dry forest fragmentation and recovery at regional scales depend on such landscape attributes as lithology, slope, geomorphology and management. 相似文献
13.
14.
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
15.
1 Introduction Arid western China stretches from west of Helan Mountains to south of the piedmont of Kunlun Mountains, covering about 2.50×106 km2 or 26.08% of the total territorial area of China. Its unique geographic location in the hinterland of Euras… 相似文献
16.
Danny Redo J.O. Joby Bass Andrew C. Millington 《Applied geography (Sevenoaks, England)》2009,29(1):91-110
Analyses of landscape change using remotely sensed satellite imagery constitute a large component of forest transition research, allowing for assessments of large areas. In the western highlands of Honduras is an area of complex forest dynamics (～45,000 ha) that has seen significant forest regeneration in recent years. However, analysis of the larger region (～500,000 ha) shows net forest loss. The comparative aspects highlight the importance of site selection and scale in forest transition analysis, a process often ignored in the land-use and land-cover change (LULCC) and forest transition literature. Results also highlight the importance of analyzing human-induced fragmentation at a variety of selected sites and a range of spatial scales, and producing quality, accurate forest cover and change maps. 相似文献
17.
One challenge facing spatial scientists trying to support public health outreach and intervention in challenging environments is the lack of fine scale spatial data. These data are required to gain a better understanding of both physical and social systems; why disease occurs where it does, and how to disrupt it. While data options exist, including high resolution aerial imagery, remotely sensed data, and even online mapping products like Google Street View, these all come with limitations. One option that has previously been utilized to assess cholera risk is spatial video. Here it is used to map potential mosquito breeding sites in an endemic Dengue and Chikungunya, and emerging Zika impacted community. We show how this method can provide mapping support in the hands of non-specialist public health workers who, working in collaboration with out-of-area geographic information systems (GIS) teams, can identify where to target limited intervention resources. We use a case study of an impoverished informal style Nicaraguan community suffering from a high disease burden to show spatial variation in potential mosquito breeding habitats. A field team collected street-by-street spatial video data to produce fine scale risk maps of standing water and trash locations, which, when interpreted with the associated spatial video imagery, were used to suggest where intervention strategies should be targeted. We also discuss how these same data layers can be used to address other health concerns traditionally found in informal settlements. 相似文献
18.
Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare soil and water are unmixed, using the remote sensing spectral mixture analysis. We try the method to unmix the canopy funation structure of arid land cover in order to avoid the differentiation of regional vegetation system and the disturbance of environmental background. We developed a modified production efficiency model NPP-PEM appropriate for the arid area at regional scale based on the concept of radiation use efficiency. This model refer to the GLO-PEM and CASA model was driven with remotely sensed observations, and calculates not just the conversion efficiency of absorbed photosynthetically active radiation but also the carbon fluxes that determine net primary productivity (NPP). We apply and validate the model in the Kaxger and Yarkant river basins in arid western China. The NPP of the study area in 1992 and 1998 was estimated based on the NPP-PEM model. The results show that the improved PEM model, considering the photosynthetical activation of heterogeneous functional vegetation, is in good agreement with field measurements and the existing literature. An accurate agreement (R2 = 0.85, P<0.001) between the estimates and the ground-based measurement was obtained. The spatial distribution of mountain-oasis-desert ecosystem shows an obvious heterogeneous carbon uptake. The results are applicable to arid ecosystem studies ranging from characterizing carbon cycle, carbon flux over arid areas to monitoring change in mountain-oasis-desert productivity, stress and management. 相似文献
19.
The U.S. state of Maryland needs to monitor land use change in order to address land management objectives. This paper presents a change detection method that, through automation and standard geographic information system (GIS) techniques, facilitates the estimation of landscape change via photointerpretation. Using the protocols developed, we show a net loss of forest land, with losses due primarily to urban development and most gains in forest land coming from agricultural land conversions. This study indicates that about 75,000 photo plots would be needed to estimate land use change in Maryland at the county-level, assuming a uniform sampling intensity and a maximum desired county-level sampling error of 20 percent, with an estimated time requirement of 125 h. The protocol we present for designing, planning and conducting a photointerpretation-based land use change procedure can be used by other regions and is well suited for land use change monitoring, assuming that analysis of opportunity costs suggests that existing or new remotely sensed imagery classifications do not meet user needs. 相似文献
20.
塔里木河干流植被遥感监测时空多尺度协同分析方法 总被引：3，自引：1，他引：2
利用遥感植被指数、典型植被样方和地面观测信息进行塔里木河干流植被监测是目前的主要方法。由于塔里木河干流具有流域下垫面均匀性差,自然植被随机分布的特点,使得现有研究方法局限在特定的时间和空间尺度,很难使用地面的观测数据和不同尺度的遥感数据进行植被生长状态的协同分析。针对这些问题,本文提出了利用不同分辨率遥感数据和地面观测数据进行多尺度协同分析的方法MSSA(Multiple Scale Synergy Analysis)。该方法包括以下几个步骤:①通过低空间分辨率的遥感数据构建时间序列的塔里木河干流植被指数分布图像,在分析图像特征的基础上划分塔里木河遥感监测单元;②对监测单元内部不同组分的时间和空间状态参数进行量化与率定;③根据几何光学模型原理和植被随机分布特性,采用线性混合模型模拟单元植被指数;④根据模拟结果和遥感数据的对比分析,获得地面植被参量的可靠估计。该方法将地面组分的状态参量和遥感数据通过模拟模型相关联,实现了不同时空尺度遥感数据以及地面样方或者点观测数据的协同分析,为塔里木河干流植被监测进行长期、细致的研究建立了海量数据综合分析的方法体系。 相似文献