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1.
At the beginning of the new millennium, after a severe drought and destructive floods along the Yangtze River, the Chinese government implemented two large ecological rehabilitation and reforestation projects: the Natural Forest Protection Programme and the Sloping Land Conversion Programme. Using Landsat data from a decade before, during and after the inception of these programmes, we analyze their impacts along with other policies on land use, land cover change (LULCC) in southwest China. Our goal is to quantify the predominant land cover changes in four borderland counties, home to tens of thousands of ethnic minority individuals. We do this in three time stages (1990, 2000 and 2010). We use support vector machines as well as a transition matrix to monitor the land cover changes. The land cover classifications resulted in an overall accuracy and Kappa coefficient for forested area and cropland of respectively 91% (2% confidence interval) and 0.87. Our results suggest that the total forested area observed increased 3% over this 20-year period, while cropland decreased slightly (0.1%). However, these changes varied over specific time periods: forested area decreased between 1990 and 2000 and then increased between 2000 and 2010. In contrast, cropland increased and then decreased. These results suggest the important impacts of reforestation programmes that have accelerated a land cover transition in this region. We also found large changes in LULC occurring around fast growing urban areas, with changes in these peri-urban zones occurring faster to the east than west. This suggests that differences in socioeconomic conditions and specific local and regional policies have influenced the rates of forest, cropland and urban net changes, disturbances and net transitions. While it appears that a combination of economic growth and forest protection in this region over the past 20 years has been fairly successful, threats like drought, other extreme weather events and land degradation remain. 相似文献
2.
Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010 总被引：1，自引：0，他引：1
Liu Jinxun Sleeter Benjamin M. Zhu Zhiliang Heath Linda S. Tan Zhengxi Wilson Tamara S. Sherba Jason Zhou Decheng 《Carbon balance and management》2016,11(1):1-13
Human activities have diverse and profound impacts on ecosystem carbon cycles. The Piedmont ecoregion in the eastern United States has undergone significant land use and land cover change in the past few decades. The purpose of this study was to use newly available land use and land cover change data to quantify carbon changes within the ecoregion. Land use and land cover change data (60-m spatial resolution) derived from sequential remotely sensed Landsat imagery were used to generate 960-m resolution land cover change maps for the Piedmont ecoregion. These maps were used in the Integrated Biosphere Simulator (IBIS) to simulate ecosystem carbon stock and flux changes from 1971 to 2010. Results show that land use change, especially urbanization and forest harvest had significant impacts on carbon sources and sinks. From 1971 to 2010, forest ecosystems sequestered 0.25 Mg C ha?1 yr?1, while agricultural ecosystems sequestered 0.03 Mg C ha?1 yr?1. The total ecosystem C stock increased from 2271 Tg C in 1971 to 2402 Tg C in 2010, with an annual average increase of 3.3 Tg C yr?1. Terrestrial lands in the Piedmont ecoregion were estimated to be weak net carbon sink during the study period. The major factors contributing to the carbon sink were forest growth and afforestation; the major factors contributing to terrestrial emissions were human induced land cover change, especially urbanization and forest harvest. An additional amount of carbon continues to be stored in harvested wood products. If this pool were included the carbon sink would be stronger. 相似文献
3.
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
4.
5.
Minakshi P.K. Sharma Amandeep Kaur Vanita Shalley 《Journal of the Indian Society of Remote Sensing》2005,33(1):63-68
This study reveals the temporal changes in the land use/land cover of district Ludhiana from the years 1970 to 2001 and reports
on the change that has occurred in land use/land cover as a result of change in cropping pattern. The changes were analysed
through the data obtained from statistical abstract 1969–70, False Colour Composite (FCC) of IRS-IC LISS-III satellite data
of March 2001 and ground truth. There has been a decrease in agricultural land by 2100 ha. but still it occupies 83.76% of
the total geographical area (TGA). The wasteland shows a declining trend whereas forest cover has increased from 1.07 to 2.71%
of TGA. Area under non-agricultural uses has increased from 10.13 to 12.50% of TGA. There has also been a great change in
the cropping pattern of the district. Crops such as groundnut, gram and cotton have nearly disappeared and wheat and rice
dominate the region. This change has substantially resulted in the decrease of area under wastelands. 相似文献
6.
利用星载微波辐射计SSM／I多通道、多时相亮温数据开展了中国陆地覆盖特征的季节变化研究。通过对国内外星载微波辐射应用研究分析，提出了归一化极化指数(NDPI)的概念。处理了1997年4月、7月、10月和1998年1月的(每月的20、24日各两天)多通道SSM／I数据，在此基础上计算形成了第一幅中国陆地区域的归一化微波极化指数图，开展了中国陆地区域覆盖特征随季节变化的研究。研究结果表明，不同的陆地覆盖特征有特征的NDPI值，NDPI随季节而变化，植被、水分是引起NDPI变化的主要因子。 相似文献
7.
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
8.
Mark Broich Matthew C. Hansen Peter Potapov Bernard Adusei Erik Lindquist Stephen V. Stehman 《International Journal of Applied Earth Observation and Geoinformation》2011
Monitoring loss of humid tropical forests via remotely sensed imagery is critical for a number of environmental monitoring objectives, including carbon accounting, biodiversity, and climate modeling science applications. Landsat imagery, provided free of charge by the U.S. Geological Survey Center for Earth Resources Observation and Science (USGS/EROS), enables consistent and timely forest cover loss updates from regional to biome scales. The Indonesian islands of Sumatra and Kalimantan are a center of significant forest cover change within the humid tropics with implications for carbon dynamics, biodiversity maintenance and local livelihoods. Sumatra and Kalimantan feature poor observational coverage compared to other centers of humid tropical forest change, such as Mato Grosso, Brazil, due to the lack of ongoing acquisitions from nearby ground stations and the persistence of cloud cover obscuring the land surface. At the same time, forest change in Indonesia is transient and does not always result in deforestation, as cleared forests are rapidly replaced by timber plantations and oil palm estates. Epochal composites, where single best observations are selected over a given time interval and used to quantify change, are one option for monitoring forest change in cloudy regions. However, the frequency of forest cover change in Indonesia confounds the ability of image composite pairs to quantify all change. Transient change occurring between composite periods is often missed and the length of time required for creating a cloud-free composite often obscures change occurring within the composite period itself. In this paper, we analyzed all Landsat 7 imagery with <50% cloud cover and data and products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify forest cover loss for Sumatra and Kalimantan from 2000 to 2005. We demonstrated that time-series approaches examining all good land observations are more accurate in mapping forest cover change in Indonesia than change maps based on image composites. Unlike other time-series analyses employing observations with a consistent periodicity, our study area was characterized by highly unequal observation counts and frequencies due to persistent cloud cover, scan line corrector off (SLC-off) gaps, and the absence of a complete archive. Our method accounts for this variation by generating a generic variable space. We evaluated our results against an independent probability sample-based estimate of gross forest cover loss and expert mapped gross forest cover loss at 64 sample sites. The mapped gross forest cover loss for Sumatra and Kalimantan was 2.86% of the land area, or 2.86 Mha from 2000 to 2005, with the highest concentration having occurred in Riau and Kalimantan Tengah provinces. 相似文献
9.
Lars T. Waser Markus Schwarz 《International Journal of Applied Earth Observation and Geoinformation》2006
Considerable efforts have recently resulted in the development of global land cover data at large spatial scales. The main objective of this study is a comparison of different AVHRR- and MODIS-based forest and land cover products at the scale of the European Alps: a large natural ecosystem that is exposed to both natural environmental threats and human impacts and exploitation. In a first test, the accuracy of land cover products in predicting the overall amount of forest across national boundaries was assessed using national forest inventory statistics. Both variants of forest class combinations resulted in a general overestimation of the forest area. The IGBP 2.0 cover performed best with an overall mean absolute error of 13% and a bias of 0%. In a second test, large-area land cover products were tested for accuracy in predicting 13 aggregated land cover types in a spatially explicit manner using CORINE land cover as reference dataset. Due to data inconsistencies, partly insufficient spatial resolution, steep terrain and land use heterogeneity of the European Alps, only partly satisfactory results were obtained. 相似文献
10.
Kamleshan Pillay Naeem Hoosen Agjee Srinivasan Pillay 《Journal of the Indian Society of Remote Sensing》2014,42(1):51-60
Land is the basic resource that is needed by man in order to survive: It provides humans with living space, nutrition and energy resources. The rapid growth of the human population, climate change and pollution on a catastrophic scale has caused the quality of land resources to be compromised. Remote sensing is a useful tool in land cover change detection providing information to decision makers. The aim of this study was to evaluate land cover changes in the Mtunzini area in South Africa over the past 18 years; determine why changes have occurred and predict land cover patterns for future years. In this study a supervised classification was used to detect land cover classes of the Mtunzini area from 1992 to 2009 using four Landsat images in the time series analysis. The supervised classification had an accuracy of 80.80 % which was used to model land cover changes. Commercial sugar cane and forest plantation classes increased throughout the time series. It was estimated in the modelling procedure that bushland (42.11 %) and bare soil (35 %) would be changed to commercial sugar cane. This is indicative of the expanding agriculture sector in Mtunzini. Natural vegetation is predicted to be disturbed: 18 % of bushland and 15.07 % of dense bush are expected to be replaced by rural dwellings. This is owing to a potential increase in the rural population and a reduced local economic growth. This study highlights the need for increased vigilance of the forestry industry and commercial sugar cane farms which may be encroaching on natural vegetation and livelihoods of local residents. Strategic planning and proper management of natural vegetation types is needed as these land cover types are decreasing rapidly. 相似文献
11.
中国陆地生态系统脆弱带遥感模型 总被引：4，自引：0，他引：4
本研究通过对我国陆地生态系统8个典型样地的植被指数取样实验和图像计算结果发现，这8个样地植被指数随着水、热因子的季节变化，在时间和空间上具有一定的“绿波推移”和“景观更替”规律。在中国东部湿润的季风区（样地1－3），随着纬度的增高，其月平均植被指数与月平均气温有较大的相关。发现降水相对丰沛的地带，热量和光照条件的变化成为植被生长和变化的自然限制因子；而在中国北方森林－森林草原－典型昌原－荒漠草原－荒漠地带上，随着从东部（湿润地区）到西部（干旱地区）干湿条件的更替，月平均植被指数与降水多寡有较大的正相关关系。在8个样地上都呈现出共同的规律，即定向风的分布与植被指数的分布在时间和空间上具有逆相分布的“套合关系”。尤其在时间上有相逆套合关系，这正是中国北方沙尘暴和沙漠化加剧的自然原因。本研究定量地给出了我国陆地不同经纬度带生态系统脆弱季节和累积时间的分布。 相似文献
12.
Zhi-Hua Shi Lu Li Wei Yin Lei Ai Nu-Fang Fang Yan-Tun Song 《International Journal of Applied Earth Observation and Geoinformation》2011
Recently there have been reports of forest regrowth occurring in different regions across the world. There is also a growing recognition of the potential beneficial impact that secondary forests may have on the global environment: providing crucial ecosystem services such as soil conservation, stabilization of hydrological cycles, carbon sequestration, and support for forest dependent communities. Consequently, there is a growing awareness of the need to recognize that landscapes are complex shifting mosaics wherein forest clearing and reforestation take place. In this study, the rates of reforestation, deforestation, forest regrowth and degradation were measured using multi-temporal Landsat images of Danjiangkou, China. Landsat data from 1990, 1999 and 2007 were (1) classified as dense forest, open forest and non-forest areas and (2) compared between years to identify forest cutting, regeneration and degradation. The results showed that there was a net gain of 29,315 ha of forest area (including dense and open forest) from 1990 to 2007, showing a clear trend of reforestation in the study area. Forest modification (degradation and regrowth) and change categories (deforestation and reforestation) occurred simultaneously during the observation time period. Socioeconomic data from public statistics and environmental attributes allowed the assessment of the socioeconomic factors and the environmental conditions that caused these changes using non-metric multidimensional scaling (NMDS). The research showed that the socioeconomic factors due to different policies were major driving forces of forest transition, whereas environmental attributes of the underlying landscape constrained forest cover changes. These findings have led to a better understanding of forest transition at a local scale in our study region. Comprehensive knowledge of these relationships may be useful to reconstruct past forest transitions and predict future changes, and may help to enhance sustainable management practices aimed at preserving essential ecological functions. 相似文献
13.
Modelling for prediction of global deforestation based on the growth of human population 总被引：1，自引：0，他引：1
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
14.
G. Singh M. S. Sarkar A. Pandey S. Lingwal I. D. Rai B. S. Adhikari G. S. Rawat R. S. Rawal 《Journal of the Indian Society of Remote Sensing》2018,46(10):1625-1635
Effective quantification of land cover changes remains a challenge in Himalayan hills and mountains, and has a colossal value addition for natural resource management. Here we present a new robust method for classifying land cover vegetation at physiognomic scale along steep elevational gradients from ~?200 to ~?7000 masl in the Kailash Sacred Landscape, Western Himalaya, India along with four decades of land use and land cover changes (1976–2011) using remote sensing techniques coupled with intensive ground surveys. Results show that forest cover loss was minimum ca 7.14% of existing forest in 1976; but, however forest fragmentation is high especially in montane broad-leaved and subtropical needle leaved forests. This change largely impacted the quality of valuable tree species such as Quercus spp. Post 1976, continuous migration forced conversion of high altitude agricultural lands into grasslands and scrublands. Human settlement expansion was high especially in low altitudinal range valleys between 1000 and 2000 masl and has increased 6.76 fold since 1976, leading to high forest fragmentation in spite of reduced agriculture area in the landscape. Our physiognomic level classified land cover map will be a key for forest managers to prioritize conservation zones for protecting this unique forest land. 相似文献
15.
C. Sudhakar Reddy G. Manaswini C. S. Jha P. G. Diwakar V. K. Dadhwal 《Journal of the Indian Society of Remote Sensing》2017,45(5):825-836
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
16.
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
17.
Inaccurate information on forest resources could hamper forest conservation, reforestation and sustainable management. Remote-sensing products have emerged as key tools in forest cover monitoring. The Global Forest Watch (GFW) dataset as an interactive remote sensing product, is now applied by more than 2 million users including researchers, conservationists and local communities for analyzing forest cover changes. The quality of this product varies spatially, and local validations are recommended before using the data for inventory and management tasks. Our study evaluated the accuracy and suitability of the GFW dataset for analyzing China’s forest cover. We conducted a validation based on a streamlined visual interpretation procedure using high-resolution optical imagery on Google Earth to map the uncertainties and inaccuracies of GFW Tree Cover 2000 in China. We then estimated China’s forest area after considering the data uncertainty, made a comparison with the data reported by the National Forest Inventory of China (CNFI) to understand where and how the land-based inventory differs from the presence/absence-based remote sensing data. The results showed that the overall accuracy of the GFW Tree Cover 2000 data reached 94.5 %. The user’s and producer’s accuracy of forest classification was 89.26 % and 82.13 %. The sample-based area estimation using GFW showed a larger forest area than the figure reported by CNFI in mainland China, while data discrepancy varied at provincial levels. The study provides a detailed performance assessment of GFW in terms of accuracy of defining forest, and we advise the consideration of data uncertainty in forest cover estimates for future forest management. 相似文献
18.
KennedyOkelloWERE 《遥感学报》2010,14(1):180-196
<正>Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources. 相似文献
19.
Prioritization of sub-watersheds based on morphometric and land use analysis using remote sensing and GIS techniques 总被引：2，自引：0，他引：2
Akram Javed Mohd Yousuf Khanday Rizwan Ahmed 《Journal of the Indian Society of Remote Sensing》2009,37(2):261-274
Watershed prioritization has gained importance in natural resources management, especially in the context of watershed management.
Morphometric analysis has been commonly applied to prioritization of watersheds. The present study makes an attempt to prioritize
sub-watersheds based on morphometric and land use characteristics using remote sensing and GIS techniques in Kanera watershed
of Guna district, Madhya Pradesh. Various morphometric parameters, namely linear and shape have been determined for each sub-watershed
and assigned ranks on the basis of value/relationship so as to arrive at a computed value for a final ranking of the sub-watersheds.
Land use/land cover change analysis of the sub-watersheds has been carried out using multi-temporal data of IRS LISS II of
1989 and IRS LISS III of 2001. The study demonstrates the significant land use changes especially in cultivated lands, open
scrub, open forest, water bodies and wastelands from 1989 to 2001. Based on morphometric and land use/land cover analysis,
the sub-watersheds have been classified into three categories as high, medium and low in terms of priority for conservation
and management of natural resources. Out of the seven sub-watersheds, two sub-watersheds viz., SW1 and SW6 qualify for high
priority, whereas SW7 has been categorised as medium priority based on the integration of morphometric and land use change
analysis. 相似文献
20.
北京周边地区是近一二十a环境退化较严重的地区，特别是由于资源过度开发利用所引起的土地利用和土地覆被变化的生态
环境问题十分突出。以遥感技术、地理信息系统和全球定位系统技术为手段，利用1991或1992年、2001或2002年2期的遥感影像为
基础，辅以土地利用现状图及与生态建设等相关资料，通过外业调查验证，快速、准确地获取北京周边地区51个县级辖区，总土地
面积为23万km2的土地利用现状和近10a的土地利用动态变化及与生态环境相关的土地退化，以反映生态建设工程的实施效果，为
北京周边地区资源合理利用和生态环境建设与规划提供了科学依据。 相似文献