河南省植被覆盖度时空变化及其原因分析

基于河南省2010—2019年MODIS NDVI数据,利用像元二分模型估算植被覆盖度,利用一元线性回归获取变化趋势,并利用Pearson相关系数法探究河南省的植被指数和植被覆盖度的时空变化原因,可为河南省生态现状、生态环境建设规划和布局提供参考。结果表明：(1)2010—2019年河南省年度最大NDVI均值存在波动,呈微弱下降趋势;(2)河南省较高和中等植被覆盖度占比较大,且存在中等植被覆盖度向高植被覆盖度和低或无植被覆盖度的转换,社会因素是中等分化到低或无植被覆盖度的主要因素;(3)不同类型植被对降水变化的敏感性存在差异,森林、降水丰富地区和以灌溉为主的农业区受降水变化影响较弱,城镇、乡村和以降水为主的农业区受降水影响较强。     

江苏沿海地区耕地分布格局及其变化特征

利用1990年、2000年和2010年的遥感解译土地利用数据提取耕地数据,运用耕地集中度指数、核密度计算等方法分析江苏沿海地区耕地资源空间分布格局及其变化特征.结果表明:①1990-2010年,江苏沿海地区耕地面积所占比重较高,但呈逐年降低趋势,耕地数量逐年减少.耕地类型以平原水田、平原旱地两类为主,呈整体交错分布、部分集聚的分布格局;②从耕地分布状况来看,呈中部、南部高,北部略低的分布特征,耕地分布较集中,且在时间序列上有进一步加强的趋势,耕地区域变化差异性不明显;③从耕地核密度分布状况来看,密度高值区呈现扩散趋势,密度低值区呈集聚趋势,且在进一步增强.耕地整体呈中西部、西南部耕地分布稀疏,中东部、北部分布密集的空间分布特征.     

喀什市城市植被及其覆盖度研究

针对国内外对城市植被及其覆盖度方面的研究不够深入的现状,该文以喀什市1990年、2000年及2010年3期Landsat TM/ETM+遥感影像为数据源,结合归一化植被指数(NDVI)与植被覆盖度估算方法,对喀什市植被覆盖区土地类型、面积变化等方面进行研究。结果表明:1990年至2010年,高覆盖区所占比例由1990年到2000年逐步增加,2010年稍有减少;中高覆盖区面积出现先减小后增加的变化趋势;中覆盖区面积逐年增加;低覆盖区呈先减小后增加的趋势;极低覆盖区变化最慢,2010年比1990年稍有增加。     

阿拉尔垦区近30年耕地变化及其驱动因子分析

耕地动态变化趋势及其驱动因子的明确,是确保国家粮食安全、水土资源合理开发利用和土地利用结构调整的重要依据。以南疆阿拉尔垦区为例,基于1990—2019年间7个重要时期的Landsat卫星遥感影像、人口、国内生产总值(gross domestic product,GDP)等数据,将波谱角(spectral angle mapper,SAM)、神经网络(artificial neural net,ANN)、最小距离(minimum distance classification,MDC)、最大似然(maximum likelihood classification,MLC)和支持向量机(support vector machine,SVM) 5种分类方法经全连接条件随机场(fully connected conditional random field,FC—CRF)处理后进行对比,从中筛选出最佳算法来解译遥感影像,利用解译结果分析耕地面积变化、类型转化和空间动态变化特征,并探讨耕地面积变化的主要驱动因子、作用路径和强度。结果表明,在5种分类算法中,SVM—CRF算法的分类精度最高,总体精度为0.95,Kappa系数为0.94,其他4类算法的总体精度为0.65～0.89,Kappa系数为0.58～0.86。研究区1990—2019年间耕地面积呈持续增长趋势,耕地面积净增长量为729.97 km~2(312.21%),耕地转入和转出分别呈现出向外扩张和向内收缩趋势。总人口、GDP、全社会固定资产投资、农业生产总值和棉花价格是耕地面积变化的5个主要驱动因子,其中GDP对耕地面积变化的直接影响最大,棉花价格的直接影响最小,除GDP对耕地面积表现为负向作用外,其他4个因子对耕地面积变化均表现为正向作用。     

近30年长江中下游平原典型区耕地覆盖变化

以长江中下游平原苏皖边界的10个县市为研究区,利用1984,1990,1995,2000,2005和2010年6期的TM/ETM+图像提取土地覆盖信息,从时间和空间2个方面研究耕地覆盖变化。结果表明:①从时间变化来看,研究区近30 a耕地总体呈减少趋势,经历了快速减少、缓慢减少和急剧减少3个过程,1984—1990年、1990—2000年及2000—2010年耕地分别减少了374.10 km2,66.09 km2及1 724.33 km2,主要表现为城镇和水体侵占耕地,但林地开垦使耕地增加;②从空间变化上看,沿江城市周围大面积耕地转变为建设用地,以1984年的南京市区、马鞍山市区和芜湖市区为主,且城镇化速度在加快;1990年以来沿石臼湖和固城湖周边地区的部分耕地转变成养殖塘,其西部地区转换较频繁;1984—2000年耕地沿山体和耕地交界处增加,2000年之后又因实施退耕还林和营造经济林而有所减少。     

基于OMAP平台的近30年辽东湾植被指数时空变化特征分析

为了明确辽东湾植被长势的时空变化特征,本文针对传统的遥感影像信息提取速度缓慢、效率较低等问题,基于奥维互动地图(Ovid interactive map, OMAP)平台,利用Landsat遥感影像提取1990—2019年辽东湾生长季NDVI数据,采用一元线性回归对NDVI时空变化特征进行讨论。结果表明：1)以2010年为转折点,近30年来,辽东湾地表植被NDVI呈现先增后减再增的变化趋势,植被覆盖总面积变化较小,但中高植被覆盖区(0.6相似文献   

Landsat时序数据支持下的藏东南植被时空变化监测

本文利用GEE平台和1990—2019年巴宜区Landsat遥感影像，采用像元二分模型、相关性分析等方法分析了巴宜区植被覆盖度的时空变化特征与驱动力。研究结果表明：①1990—2019年巴宜区植被覆盖度总体呈稳中有增的趋势，其中，河谷区域增加明显，而高海拔区域相对稳定；②1990—2019年巴宜区气温呈显著升高，降水略有下降，总体呈“暖干化”，气温较降水量对植被覆盖变化更明显，但气候变化对植被覆盖变化影响总体不明显；③1990—2019年巴宜区植被覆盖变化与人类活动有很好的相关性，其中，低、中低、中、中高植被覆盖区域，呈显著的负相关，而高植被覆盖区域呈正相关。本文基于遥感大数据和地理云计算的植被覆盖监测动态监测和定量分析方法，能对高山峡谷区生态评估和演替分析提供一定的技术支撑和科学数据。     

基于RS/GIS的耕地资源变化特征分析

以黑龙江省嫩江县为研究区,综合运用RS/GIS手段,分析1984~2011年近30年研究区耕地资源在数量和空间上的变化特征,结果表明:研究区耕地利用数量发生了一定变化,总体上耕地面积减少,主要转向林地、建设用地以及草地;耕地资源在空间变化上具有一定的特征,表现为南部变化较大,中部和西部变化居中,北部和东部变化最小;各乡镇耕地相对变化率的总体差异不大,相对比较均衡。研究成果可以为研究区耕地保护提供一定的参考。     

近40年椒江—台州湾滩涂围垦土地利用变化的遥感调查

利用1971年和1981年2版次地形图数据以及1981年、1990年、2001年和2011年4期遥感影像数据对近40 a来椒江—台州湾的滩涂围垦土地利用变化进行了调查。依据上述资料,利用GIS空间分析功能,获得了5期滩涂围垦土地利用现状及各期次之间的滩涂围垦土地利用变化转移矩阵。调查结果表明,近40 a来,椒江—台州湾滩涂围垦总体上呈增加趋势,土地利用变化的类型逐渐增多。1971—1990年间滩涂围垦土地利用类型多为耕地、养殖场和围垦用地;1990年以后,滩涂处于围垦开发利用热潮,光滩及围垦用地等多向耕地、居住用地、港口码头及养殖场等类型转化,而原本耕地及养殖场用地则多转化为居住用地。2001—2011年间,有80.77%的滩涂转化为围垦用地,光滩面积减少程度大,椒江—台州湾滩涂围垦扩张速度达到各时期最大值。     

2009—2017年北京市土地利用变化时空特征

对北京市土地利用类型、城市扩张程度和植被覆盖度进行时空特征分析,为合理制定城市空间规划和土地利用管理提供科学依据。以北京市全域为研究对象,基于2009、2013和2017年Landsat遥感影像基础,利用非监督分类方法得到土地类型图,计算城市扩张指数和植被覆盖度指数,并进行环路地类动态变化分析。结果表明：1)2009—2017年北京市绿地/耕地面积减少746.22 km²,建筑用地面积增加601.36 km²,两者面积变化表现出此消彼长的趋势;2)绿地/耕地及建筑用地的空间消长特点存在明显的环路差异;3)高植被覆盖度区域面积剧烈减少;4)土地利用类型和植被覆盖度变化在2009—2013年和2009—2017年两阶段内差异明显。可见北京市城市扩张速度有所减缓,绿地/耕地面积相对减少率高,城市土地利用变化存在明显的时空差异。     

遥感解译与地理国情相结合的石漠化监测

考虑到地表石漠化的复杂性，借鉴林业部门的石漠化状况与程度评定方法，充分利用地理国情地表覆盖与DEM成果，结合遥感监测技术，计算地表的基岩裸露度与植被综合盖度，以野外实地调查为佐证，获取研究区域石漠化监测评定因子，确定研究区域石漠化的状况与程度，构建一套基于遥感解译的石漠化监测技术方法。结果表明，研究区自2008-2016年，石漠化发生率明显下降，区域生态环境逐步恢复；本文研究的技术方法可行，在节约人力资源的基础上，可快速获取石漠化状况与程度。     

石屏县土地更新调查的影像解译结果分析

利用2005年SPOT-5高分辨率卫星影像,运用RS、GIS、GPS等新的技术手段,分析、提取了石屏县土地利用变化信息。结果显示,石屏县新的土地控制面积为3 041.37km2,与2004年变更调查统相比较,现有辖区面积增加0.53km2。土地利用类型以农业用地为主,面积达25.40 536×104hm2,占总土地面积的83.53%。通过以高分辨率卫星影像进行更新调查,有效掌握石屏县土地利用状况和动态变化,查清土地利用结构,调整土地供应,有效利用土地资源提供了翔实的基础资料和科学依据。     

运用NDVI-Albedo特征空间提取石漠化信息

石漠化是西南喀斯特地貌地区面临的最主要生态环境问题之一,对石漠化进行监测是其防治的一项重要工作。本文以威宁西部典型的石漠化研究区斗古乡为例,基于Landsat 8 OLI遥感数据,计算了研究区归一化植被指数(NDVI)和地表反照率(Albedo),通过NDVI-Albedo特征空间构建石漠化差值指数(RSDDI),对石漠化信息进行提取并对其进行精度验证。研究表明:基于NDVI-Albedo特征空间法构建的石漠化差值指数能够较为准确且便捷地对石漠化信息进行提取与分级,在中度石漠化及重度石漠化的制图精度均达到89%以上,提取效果较好,有利于西南喀斯特地貌地区对石漠化的定量评估与监测。     

利用遥感影像进行植被分布分析

植被是生态环境的重要组成要素,它与一定的地形条件相适应。本文以吴起县遥感影像及地形数据为基础,集成使用RS,GPS及GIS技术,以NDVI植被指数计算为核心完成了植被覆盖度的动态监测及分析,植被群落已基本恢复成能与环境相适应的稳定群落,封禁效果基本稳定,林地面积、植被覆盖度等指标明显上升。植被覆盖度面积逐年增加,部分地区还出现了较为明显的逆转现象,整个研究区的生态环境呈现良性发展态势。     

黄河流域土地荒漠化动态变化遥感研究

利用1975年MSS、1990年TM和2000年ETM 3期遥感数据提取黄河流域土地荒漠化动态变化信息。调查结果表明,黄河流域土地荒漠化具有明显的地域性,主要分布在流域西北部。荒漠化土地面积变化总体呈增加趋势,从1975年~2000年增加了10 653.22 km2,平均每年增加426.12 km2。黄河流域地质背景和气候条件决定了荒漠化的总体分布和变化趋势,不合理的人类活动加速了荒漠化进程。     

Using Landsat Thematic Mapper records to map land cover change and the impacts of reforestation programmes in the borderlands of southeast Yunnan,China: 1990–2010

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.     

Evaluation of global land cover maps for cropland area estimation in the conterminous United States

Global land cover data could provide continuously updated cropland acreage and distribution information, which is essential to a wide range of applications over large geographical regions. Cropland area estimates were evaluated in the conterminous USA from four recent global land cover products: MODIS land cover (MODISLC) at 500-m resolution in 2010, GlobCover at 300-m resolution in 2009, FROM-GLC and FROM-GLC-agg at 30-m resolution based on Landsat imagery circa 2010 against the US Department of Agriculture survey data. Ratio estimators derived from the 30-m resolution Cropland Data Layer were applied to MODIS and GlobCover land cover products, which greatly improved the estimation accuracy of MODISLC by enhancing the correlation and decreasing mean deviation (MDev) and RMSE, but were less effective on GlobCover product. We found that, in the USA, the CDL adjusted MODISLC was more suitable for applications that concern about the aggregated county cropland acreage, while FROM-GLC-agg gave the least deviation from the survey at the state level. Correlation between land cover map estimates and survey estimates is significant, but stronger at the state level than at the county level. In regions where most mismatches happen at the county level, MODIS tends to underestimate, whereas MERIS and Landsat images incline to overestimate. Those uncertainties should be taken into consideration in relevant applications. Excluding interannual and seasonal effects, R² of the FROM-GLC regression model increased from 0.1 to 0.4, and the slope is much closer to one. Our analysis shows that images acquired in growing season are most suitable for Landsat-based cropland mapping in the conterminous USA.     

Multiple factors influence the consistency of cropland datasets in Africa

Accurate geo-information of cropland is critical for food security strategy development and grain production management, especially in Africa continent where most countries are food-insecure. Over the past decades, a series of African cropland maps have been derived from remotely-sensed data, existing comparison studies have shown that inconsistencies with statistics and discrepancies among these products are considerable. Yet, there is a knowledge gap about the factors that influence their consistency. The aim of this study is thus to estimate the consistency of five widely-used cropland datasets (MODIS Collection 5, GlobCover 2009, GlobeLand30, CCI-LC 2010, and Unified Cropland Layer) in Africa, and to explore the effects of several limiting factors (landscape fragmentation, climate and agricultural management) on spatial consistency. The results show that total cropland area for Africa derived from GlobeLand30 has the best fitness with FAO statistics, followed by MODIS Collection 5. GlobCover 2009, CCI-LC 2010, and Unified Cropland Layer have poor performances as indicated by larger deviations from statistics. In terms of spatial consistency, disagreement is about 37.9 % at continental scale, and the disparate proportion even exceeds 50 % in approximately 1/3 of the countries at national scale. We further found that there is a strong and significant correlation between spatial agreement and cropland fragmentation, suggesting that regions with higher landscape fragmentation generally have larger disparities. It is also noticed that places with better consistency are mainly distributed in regions with favorable natural environments and sufficient agricultural management such as well-developed irrigated technology. Proportions of complete agreement are thus located in favorable climate zones including Hot-summer Mediterranean climate (Csa), Subtropical highland climate (Cwb), and Temperate Mediterranean climate (Csb). The level of complete agreement keeps rising as the proportion of irrigated cropland increases. Spatial agreement among these datasets has the most significant relationship with cropland fragmentation, and a relatively small association with irrigation area, followed by climate conditions. These results can provide some insights into understanding how different factors influence the consistency of cropland datasets, and making an appropriate selection when using these datasets in different regions. We suggest that future cropland mapping activities should put more effort in those regions with significant disagreement in Sub-Saharan Africa.     

Studying Changes in Land Use Within the Poyang Lake Region

Poyang Lake is the largest freshwater lake in China. Because the lake is faced with a series of ecological and environmental problems, it is important and necessary to study the land use changes in the Poyang Lake region. In this study, Landsat images from 1976, 1989, 1999 and 2009, were used along with other evaluation methods (quantitative analysis of changes in land use, land use dynamic, degree and transfer matrix analyses) to investigate the changes in land use within the Poyang Lake region from 1976 to 2009. Land use was classified into seven types: cropland, woodland, grassland, the water body, construction land, bottomland and unused land. Areas of cropland, bottomland and the water body were decreasing although the area of the water body decreased relatively slowly. However, areas of construction land, grassland, woodland and unused land increased to a certain extent, with unused land increasing the most rapidly given its smaller proportion compared to the other types. All land types in the study region had different levels of conversion between other types of land. As a whole, the decrease in cropland and the increase in construction land, woodland and grassland were caused by human activities and the conservation policies such as Grain-for-Green and “returning farm to lake”. However, the decrease in the water body area was mainly influenced by natural factors and human activities. Changes in the area of bottomland were mainly influenced by water levels and human farming activities.     

清水河流域1978-2010年土地利用变化时空特征

通过对1978年、1998年和2010年3期遥感影像目视解译获得3期土地利用数据,分析清水河流域1978－2010年土地利用变化时空特征。研究表明：清水河流域1978－2010年期间,农用地、难利用地面积持续减少,林地、建设用地面积持续增加,草地面积先有所减少后增多,除林地以外其它土地类型变化幅度后期都较前期大;流域土地利用转移方向主要是农用地转为低、中、高覆盖度草地、林地和建设用地,中覆盖度草地转为低、高覆盖度草地和林地,低覆盖度草地转为中、高覆盖度草地、林地。结果表明,近年来清水河流域水土保持措施效果明显。