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1.
Reliable land cover land use (LCLU) information, and change over time, is important for Green House Gas (GHG) reporting for climate change documentation. Four different organizations have independently created LCLU maps from 2010 satellite imagery for Malawi for GHG reporting. This analysis compares the procedures and results for those four activities. Four different classification methods were employed; traditional visual interpretation, segmentation and visual labelling, digital clustering with visual identification and supervised signature extraction with application of a decision rule followed by analyst editing. One effort did not report classification accuracy and the other three had very similar and excellent overall thematic accuracies ranging from 85 to 89%. However, despite these high thematic accuracies there were very significant differences in results. National percentages for forest ranged from 18.2 to 28.7% and cropland from 40.5 to 53.7%. These significant differences are concerns for both remote-sensing scientists and decision-makers in Malawi.  相似文献   

2.
In this study, we explored the spatial and temporal patterns of land cover and land use (LCLU) and population change dynamics in the St. Louis Metropolitan Statistical Area. The goal of this paper was to quantify the drivers of LCLU using long-term Landsat data from 1972 to 2010. First, we produced LCLU maps by using Landsat images from 1972, 1982, 1990, 2000, and 2010. Next, tract level population data of 1970, 1980, 1990, 2000, and 2010 were converted to 1-km square grid cells. Then, the LCLU maps were integrated with basic grid cell data to represent the proportion of each land cover category within a grid cell area. Finally, the proportional land cover maps and population census data were combined to investigate the relationship between land cover and population change based on grid cells using Pearson's correlation coefficient, ordinary least square (OLS), and local level geographically weighted regression (GWR). Land cover changes in terms of the percentage of area affected and rates of change were compared with population census data with a focus on the analysis of the spatial-temporal dynamics of urban growth patterns. The correlation coefficients of land cover categories and population changes were calculated for two decadal intervals between 1970 and 2010. Our results showed a causal relationship between LCLU changes and population dynamics over the last 40 years. Urban sprawl was positively correlated with population change. However, the relationship was not linear over space and time. Spatial heterogeneity and variations in the relationship demonstrate that urban sprawl was positively correlated with population changes in suburban area and negatively correlated in urban core and inner suburban area of the St. Louis Metropolitan Statistical Area. These results suggest that the imagery reflects processes of urban growth, inner-city decline, population migration, and social spatial inequality. The implications provide guidance for sustainable urban planning and development. We also demonstrate that grid cells allow robust synthesis of remote sensing and socioeconomic data to advance our knowledge of urban growth dynamics from both spatial and temporal scales and its association with population change.  相似文献   

3.
以钱塘江流域为研究区域,利用2010年ETM,MODIS和DEM多源数据,进行土地利用分类研究。在分析土地类型的光谱特性和植被指数年度变化基础上,运用光谱指数法和代数法从数据中提取各种土地覆被类型特征。利用WEKA软件平台下的C4.5决策树算法构建决策树分类模型,对钱塘江流域土地覆被类型进行分类研究,取得较高的分类精度。  相似文献   

4.
Wetlands provide vital wildlife habitat and ecosystem services, but changes in human land use has made them one of the world’s most threatened ecosystems. Although wetlands are generally protected by law, growing human populations increasingly drain and clear them to provide agricultural land, especially in tropical Africa. Managing and conserving wetlands requires accurately monitoring their spatial and temporal extent, often using remote sensing, but distinguishing wetlands from other land covers can be difficult. Here, we report on a method to separate wetlands dominated by papyrus (Cyperus papyrus L.) from spectrally similar grasslands dominated by elephant grass (Pennisetum purpureum Schumach.). We tested whether topographic, spectral, and temperature data improved land cover classification within and around Kibale National Park, a priority conservation area in densely populated western Uganda. Slope and reflectance in the mid-IR range best separated the combined papyrus/elephant grass pixels (average accuracy: 86%). Using a time series of satellite images, we quantified changes in six land covers across the landscape from 1984 to 2008 (papyrus, elephant grass, forest, mixed agriculture/bare soil/short grass, mixed tea/shrub, and water). We found stark differences in how land cover changed inside versus outside the park, with particularly sharp changes next to the park boundary. Inside the park, changes in land cover varied with location and management history: elephant grass areas decreased by 52% through forest regeneration but there was no net difference in papyrus areas. Outside the park, elephant grass and papyrus areas decreased by 61% and 39%, mostly converted to agriculture. Our method and findings are particularly relevant in light of social, biotic, and abiotic changes in western Uganda, as interactions between climate change, infectious disease, and changing human population demographics and distribution are predicted to intensify existing agricultural pressure on natural areas.  相似文献   

5.
Satellite-based wetland mapping faces challenges due to the high spatial heterogeneity and dynamic characteristics of seasonal wetlands. Although normalized difference vegetation index (NDVI) time series (NTS) shows great potential in land cover mapping and crop classification, the effectiveness of various NTS with different spatial and temporal resolution has not been evaluated for seasonal wetland classification. To address this issue, we conducted comparisons of those NTS, including the moderate-resolution imaging spectroradiometer (MODIS) NTS with 500?m resolution, NTS fused with MODIS and Landsat data (MOD_LC8-NTS), and HJ-1 NDVI compositions (HJ-1-NTS) with finer resolution, for wetland classification of Poyang Lake. Results showed the following: (1) the NTS with finer resolution was more effective in the classification of seasonal wetlands than that of the MODIS-NTS with 500-m resolution and (2) generally, the HJ-1-NTS performed better than that of the fused NTS, with an overall accuracy of 88.12% for HJ-1-NTS and 83.09% for the MOD_LC8-NTS. Future work should focus on the construction of satellite image time series oriented to highly dynamic characteristics of seasonal wetlands. This study will provide useful guidance for seasonal wetland classification, and benefit the improvements of spatiotemporal fusion models.  相似文献   

6.
Deforestation due to ever-increasing activities of the growing human population has been an issue of major concern for the global environment. It has been especially serious in the last several decades in the developing countries. A population-deforestation model has been developed by the authors to relate the population density with the cumulative forest loss, which is defined and computed as the total forest loss until 1990 since prior to human civilisation. NOAA-AVHRR-based land cover map and the FAO forest statistics have been used for 1990 land cover. A simulated land cover map, based on climatic data, is used for computing the natural land cover before the human impacts. With the 1990 land cover map as base and using the projected population growth, predictions are then made for deforestation until 2025 and 2050 in both spatial and statistical forms.  相似文献   

7.
郑瑜晗  黄麟  翟俊 《遥感学报》2020,24(7):917-932
陆表覆盖变化影响地表特征从而改变地表能量平衡是理解人类活动对全球气候变化影响的关键环节。选择国际气候谈判主要国家的美国、印度和巴西作为中国的对比国,对比分析不同国别、不同气候带典型陆表覆盖类型的地表反照率时空差异,进而模拟开垦和城市化等陆表覆盖变化对反照率的影响差异。结果表明:(1) 2000年—2015年,中国、美国的地表反照率年际变化存在明显的气候带空间分异特征,中国干旱半干旱区和美国中低纬湿润区表现出降低趋势,而中国亚热带湿润和美国高纬与中部干旱区则表现出明显的升高趋势,印度的地表反照率年际变化呈微弱下降趋势,而巴西为微弱上升趋势。(2)无雪覆盖时,耕地、林地、草地和人造地表反照率具有夏高、冬低的时间变化特征,干旱半干旱区反照率明显高于湿润区。4种类型的国别差异体现在,中国亚热带湿润区地表反照率均以上升为主,干旱半干旱区则相反;美国除耕地在干旱区呈较强的升高趋势外,其余类型基本为降低趋势;印度均表现为降低趋势;巴西则表现为略微升高趋势。(3)与无雪覆盖相比,有雪覆盖时不同陆表覆盖类型地表反照率均有所提高,林地提高幅度最小,约0.06—0.26,耕地提高最大,约为0.17—0.38,且中国林地反照率提高幅度略高于美国。(4)原陆表覆盖为林地时,开垦和城镇化均导致地表反照率升高,且干旱区升高幅度高于湿润区,湿润区的升高幅度随纬度降低而减弱;为草地时,开垦主要在巴西、印度和中、美亚热带湿润区引起地表反照率升高。而城镇化引起的反照率变化则受到原有地表覆盖、季节和气候背景影响存在较复杂的国别和气候带差异。  相似文献   

8.
MODIS data were used in conjunction with 600 ground survey points to create a 500 m resolution land cover product of Mali. It improves upon previously published land cover products for this region in resolution and accuracy. Of particular importance is the ability to detect small-scale, but important, wetland features such as rice cultivation areas. A combination of classical ground survey of vegetation type and structure, meteorological data, and remote sensing was used to quantify the relationship between vegetation and climate along the sensitive Sahel savanna—desert transition. The study demonstrates the effectiveness of using MODIS data for regional-scale studies.  相似文献   

9.
Sri Lanka is one of the biodiversity hotspots of the world. This study has utilized satellite remote sensing and GIS techniques to generate a nation-wide database on forests, forest types and land use/land cover of Sri Lanka. Spatial assessment of forest cover changes was carried out for the periods 1976–1985, 1985–1994, 1994–2005 and 2005–2014. The landscape fragmentation analysis has carried out to calculate the spatial and temporal patterns of forest. Land use/land cover map was prepared representing seven classes in 2014. The plantations occupy a large area (34.2%) followed by forests (33.4%) and agriculture (26.1%) in 2014. During the period of 1976–2014, the forest has been decreased by 5.5%. From 1976 to 1985 forest recorded a loss at an annual rate of 0.49%. This annual rate decreased to 0.01% during 2005–2014 indicates declining trend of deforestation and effective conservation measures. The study found deforestation hotspots in south east and northern most parts of the Sri Lanka. Total number of patches estimated has increased from 15193 in 1976 to 16136 in 2014. The study has found that main causes of deforestation in Sri Lanka were due to expansion of agriculture and plantations. The extent of change detected in the study through geospatial techniques has significance to the forest ecology and management of natural landscapes in Sri Lanka.  相似文献   

10.
Land use and land cover change are of prime concern due to their impacts on CO2 emissions, climate change and ecological services. New global land cover products at 300 m resolution from the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI LC) project for epochs centered around 2000, 2005 and 2010 were analyzed to investigate forest area change and land cover transitions. Plant functional types (PFTs) fractions were derived from these land cover products according to a conversion table. The gross global forest loss between 2000 and 2010 is 172,171 km2, accounting for 0.6% of the global forest area in year 2000. The forest changes are mainly distributed in tropical areas such as Brazil and Indonesia. Forest gains were only observed between 2005 and 2010 with a global area of 9844 km2, mostly from crops in Southeast Asia and South America. The predominant PFT transition is deforestation from forest to crop, accounting for four-fifths of the total increase of cropland area between 2000 and 2010. The transitions from forest to bare soil, shrub, and grass also contributed strongly to the total areal change in PFTs. Different PFT transition matrices and composition patterns were found in different regions. The highest fractions of forest to bare soil transitions were found in the United States and Canada, reflecting forest management practices. Most of the degradation from grassland and shrubland to bare soil occurred in boreal regions. The areal percentage of forest loss and land cover transitions generally decreased from 2000–2005 to 2005–2010. Different data sources and uncertainty in the conversion factors (converting from original LC classes to PFTs) contribute to the discrepancy in the values of change in absolute forest area.  相似文献   

11.
Land cover mapping forms a reference base for resource managers in their decision-making processes to guide rural/urban growth and management of natural resources. The aim of this study was to map land cover dynamics within the Upper Shire River catchment, Malawi. The article promotes innovation of automated land cover mapping based on remote sensing information to generate data products that are both appropriate to, and usable within different scientific applications in developing countries such as Malawi. To determine land cover dynamics, 1989 and 2002 Landsat images were used. Image bands were combined in transformations and indices with physical meaning; together with spatial data, to enhance classification accuracy. A maximum likelihood classification for each image was computed for identification of land cover variables. The results showed that the combination of spatial and digital data enhanced classification accuracy and the ability to categorise land cover features, which are relatively inhomogeneous.  相似文献   

12.
Changes in forest composition impact ecological services, and are considered important factors driving global climate change. A hybrid sampling method along with a modelling approach to map current and past land cover in Kunming, China is reported. MODIS land cover (2001–2011) data-sets were used to detect pixels with no apparent change. Around 3000 ‘no change points’ were systematically selected and sampled using Google Earth’s high-resolution imagery. Thirty-five per cent of these points were verified and used for training and validation. We used Random forests to classify multi-temporal Landsat imagery. Results show that forest cover has had a net decrease of 14385?ha (1.3% of forest area), which was primary converted to shrublands (11%), urban and barren land (2.7%) and agriculture (2.5%). Our validation indicates an overall accuracy (Kappa) of 82%. Our methodology can be used to consistently map the dynamics of land cover change in similar areas with minimum costs.  相似文献   

13.
Measuring and progressing toward international goals of curbing deforestation and improving livelihoods of people who depend on forests requires nuanced understanding of forests and the processes surrounding deforestation and degradation. Despite rapid improvements in Earth Observation technology, monitoring of tropical forests remains hindered by persistent cloud cover, heterogeneous landscapes, long wet seasons, and small and ephemeral clearings masked by rapid growth. A hybrid method is presented that combines elements of both time-series and compositing approaches to best overcome these obstacles to map forest cover and change in the Republic of Panama based on Landsat imagery. The resulting Panama Vegetation-Cover Time-Series (PVCTS) maps depict forest cover in Panama from 1990 to 2016 at 30 m resolution. Acknowledging the fuzzy boundary between forest and non-forest classes, these maps employ a hierarchical classification scheme that reflects the natural process of regeneration and can accommodate different definitions of forest and deforestation. Classification accuracy is 97–98 % between forest/non-forest categories and 76–81 % for deforestation events. The maps show a slight greening of Panama from 1990 to 2016 caused by expansion of young secondary growth. The annual rate of deforestation in mature forest has remained around -0.6 %/yr, although young forests have matured at a similar rate such that there is no net loss of forest. While estimates of total forest cover are similar to official national estimates depending on forest definition, there is little agreement in location of deforestation events.  相似文献   

14.
Cash crop expansion has been a major land use change in tropical and subtropical regions worldwide. Quantifying the determinants of cash crop expansion should provide deeper spatial insights into the dynamics and ecological consequences of cash crop expansion. This paper investigated the process of cash crop expansion in Hangzhou region (China) from 1985 to 2009 using remotely sensed data. The corresponding determinants (neighborhood, physical, and proximity) and their relative effects during three periods (1985–1994, 1994–2003, and 2003–2009) were quantified by logistic regression modeling and variance partitioning. Results showed that the total area of cash crops increased from 58,874.1 ha in 1985 to 90,375.1 ha in 2009, with a net growth of 53.5%. Cash crops were more likely to grow in loam soils. Steep areas with higher elevation would experience less likelihood of cash crop expansion. A consistently higher probability of cash crop expansion was found on places with abundant farmland and forest cover in the three periods. Besides, distance to river and lake, distance to county center, and distance to provincial road were decisive determinants for farmers’ choice of cash crop plantation. Different categories of determinants and their combinations exerted different influences on cash crop expansion. The joint effects of neighborhood and proximity determinants were the strongest, and the unique effect of physical determinants decreased with time. Our study contributed to understanding of the proximate drivers of cash crop expansion in subtropical regions.  相似文献   

15.
Developing countries are vulnerable to tropical cyclones due to climatic variability and the frequency and magnitude of some extreme weather and disaster events is likely to increase. Cities and towns situated along the coastal belt of Visakhapatnam district experienced severe damage because of Hudhub cyclone (12 October 2014). The main objective of this research was to identify and quantify the damage to agriculture and vegetation caused by Hudhud cyclone. In this study, landsat-8 satellite data-sets acquired before and after the cyclone have been used; image processing techniques have been carried out to assess the changes of pre- and post-cyclone condition. Economic loss of agriculture crops has been assessed using crop production loss per hectare and total economic loss for agriculture crops in the study area was calculated. Classification results and land use land cover change analysis show that 13.25% of agriculture-Kharif and 31.1% of vegetation was damaged. Crop Biomass was estimated with aid of crop conversion factor for pre- and post-cyclone conditions. Total ‘Above ground biomass’ of the agriculture crop area was estimated at 31.57 t/ha and total loss of biomass was assessed to be 4.2 t/ha. Carbon stock was found to be varying from 0.3 to 8.3 t.C/ha in specific agriculture crops. From the results, it was concluded that Hudhud has done significant damage to the rural and urban areas of Visakhapatnam. The outcome of this study can be used by decision-makers for the release of post disaster relief fund to affected areas.  相似文献   

16.
Cropland is one of the essential elements of our ecological systems for producing agricultural products. In developing countries, urban expansion is a frequently appearing phenomena, which is a type of land cover land use (LCLU) change. This change can drastically alter the features on the land surface including croplands. It can lead to detrimental consequences which has considerable effects on the social-ecological systems when croplands are lost. Argentina is an extremely agricultural intense developing country, and Buenos Aires province is a top agricultural production site and has been urbanizing during the last 30 years. Thus studying and analyzing the metropolitan area of this province will contribute to our understanding of the relationship between urban expansion and its effect on croplands. So far, no research has used measurable quantitative methodologies on the Buenos Aires metropolitan region (BAMR) to reveal the relationship between urbanization and cropland. By using 30-meter resolution Landsat images of June 1985 and July 2015, this study finds urban land has expanded from 937.16?km2 to 1835.47?km2, and 30.28% of the new urban lands comes from existing croplands.  相似文献   

17.
With the high deforestation rates of global forest covers during the past decades, there is an ever-increasing need to monitor forest covers at both fine spatial and temporal resolutions. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat series images have been used commonly for satellite-derived forest cover mapping. However, the spatial resolution of MODIS images and the temporal resolution of Landsat images are too coarse to observe forest cover at both fine spatial and temporal resolutions. In this paper, a novel multiscale spectral-spatial-temporal superresolution mapping (MSSTSRM) approach is proposed to update Landsat-based forest maps by integrating current MODIS images with the previous forest maps generated from Landsat image. Both the 240 m MODIS bands and 480 m MODIS bands were used as inputs of the spectral energy function of the MSSTSRM model. The principle of maximal spatial dependence was used as the spatial energy function to make the updated forest map spatially smooth. The temporal energy function was based on a multiscale spatial-temporal dependence model, and considers the land cover changes between the previous and current time. The novel MSSTSRM model was able to update Landsat-based forest maps more accurately, in terms of both visual and quantitative evaluation, than traditional pixel-based classification and the latest sub-pixel based super-resolution mapping methods The results demonstrate the great efficiency and potential of MSSTSRM for updating fine temporal resolution Landsat-based forest maps using MODIS images.  相似文献   

18.
Abstract

Land use/land cover monitoring and mapping is crucial to efficient management of the land and its resources. Since the late 1980s increased attention has been paid to the use of coarse resolution optical data. The Moderate Resolution Imaging Spectroradiometer (MODIS) has features, which make it particularly suitable to earth characterization purposes. MODIS has 10 products dedicated mainly to land cover characterization and provides three kinds of data: angular, spectral and temporal. MODIS data also includes information about the data quality through the ‘Quality Assessment’ product. In this paper, we review how MODIS data are used to map land cover including the preferred MODIS products, the preprocessing and classification approaches, the accuracy assessment, and the results obtained.  相似文献   

19.
Driven by various natural and anthropogenic factors, Poyang Lake, the largest freshwater lake in China, has experienced significant land use/cover changes in the past few decades. The aim of this study is to investigate the spatial–temporal patterns of abrupt changes and detect their potential drivers in Poyang Lake, using time-series Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day maximum value composite vegetation indices between 2000 and 2012. The breaks for additive seasonal and trend (BFAST) method was applied to the smoothed time-series normalized difference vegetation index (NDVI), to detect the timing and magnitude of abrupt changes in the trend component. Large part of Poyang Lake (98.9% for trend component) has experienced abrupt changes in the past 13 years, and the change patterns, including the distributions in timing and magnitudes of major abrupt trend changes between water bodies and land areas were clearly differentiated. Most water bodies had abrupt increasing NDVI changes between 2010 and 2011, caused by the sequential severe flooding and drought in the two years. In contrast, large parts of the surrounding land areas had abrupt decreasing NDVI changes. Large decreasing changes occurred around 2003 at the city of Nanchang, which were driven by urbanization. These results revealed spatial–temporal land cover changing patterns and potential drivers in the wetland ecosystem of Poyang Lake.  相似文献   

20.
Abstract

Global land cover is one of the fundamental contents of Digital Earth. The Global Mapping project coordinated by the International Steering Committee for Global Mapping has produced a 1-km global land cover dataset – Global Land Cover by National Mapping Organizations. It has 20 land cover classes defined using the Land Cover Classification System. Of them, 14 classes were derived using supervised classification. The remaining six were classified independently: urban, tree open, mangrove, wetland, snow/ice, and water. Primary source data of this land cover mapping were eight periods of 16-day composite 7-band 1-km MODIS data of 2003. Training data for supervised classification were collected using Landsat images, MODIS NDVI seasonal change patterns, Google Earth, Virtual Earth, existing regional maps, and expert's comments. The overall accuracy is 76.5% and the overall accuracy with the weight of the mapped area coverage is 81.2%. The data are available from the Global Mapping project website (http://www.iscgm.org/). The MODIS data used, land cover training data, and a list of existing regional maps are also available from the CEReS website. This mapping attempt demonstrates that training/validation data accumulation from different mapping projects must be promoted to support future global land cover mapping.  相似文献   

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