热带森林植被生物量遥感估算探讨

该文以我国云南省西双版纳的热带森林植被为例,对热带森林植被生物量的遥感地学估算进行初步探讨。研究表明,只用LANDSAT TM的波段数据建立生物量的回归估算模型时,其模型的复相关系数只有0．118,而利用其主成分或植被指数建立回归估算模型时,其模型的复相关系数不仅没有提高,反而在一定程度上有所降低。原始波段与其主成分结合能提高估算模型的复相关系数,其效果比原始波段与植被指数结合的效果要好。模型中如果考虑气象因子中的年平均降雨量,能在很大程度上提高其复相关系数。在此基础上引入地形因子,未能显著提高模型的复相关系数。有气象因子参与建立的遥感气象模型和遥感地学模型在0．01水平上回归显著。     

极干旱区稀疏荒漠植被地上生物量遥感估算

以库姆塔格沙漠南部阿尔金山北麓山前戈壁区为研究区,借助无人机影像数据准确提取植被覆盖区;采用高空间分辨率WorldView-3数据的估算结果对中空间分辨率Landsat-OLI数据的估算结果进行修正;选取红光反射率波段(RED)、近红外反射率波段(NIR)、比值植被指数(RVI)、归一化植被指数(NDVI)和修正土壤调...     

从光谱指数到融合数据集的全球植被遥感数据产品

遥感对地观测为理解陆地植被动态与全球环境变化规律提供了数据基础,基于卫星观测的全球植被遥感数据产品近年来层出不穷,但缺乏基于数据使用者视角的系统梳理。本文回顾了全球植被遥感数据产品的发展历程,梳理了相关卫星计划及对应数据产品,分析了从植被光谱指数到生物物理特征参量、传统光学遥感反演到叶绿素荧光及星载微波反演产品、从单一传感器生产到多数据源—多数据集融合产品的发展脉络,阐述了全球植被遥感数据产品的来源、特征与关联关系。认为当前全球植被遥感数据产品的生产与应用存在一定脱节,遥感产品精度制约了对地球系统的深入理解。全球植被遥感数据产品正从宏观状态监测向专业化、精细化、标准化转变,建议未来制备全球遥感数据产品应充分利用目前已积累的长时序观测数据,融合多源观测资料,提升现有数据集的时空分辨率、精度及连续性;注重提高特殊区域与特定类型生态系统的反演精度,加强多维植被特征的一体化监测;建立全球植被产品数据共享平台,提供标准的全流程数据处理与分发服务,将数据不确定性信息高效、清晰提供给用户。     

基于遥感和地面数据的景观尺度叶面积指数和生物量的模拟

The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper,The procedure was:(1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images;(2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated;(3) the relationship models between LAI and biomass were built and annual branch ,stem ,root and maximum leaf biomass over the landscape were simulated;(4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained.The simulation was based on spatial analysis module GRID in ArcoInfo software ,The method is laso a kind of scaling method from patch scale to landscape scale ,A case study of Changbai Mountain Nature Reserve was dissertated ,Aalysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.     

应用遥感数据研究中国植被生态系统与气候的关系

应用1982-1994年NOAA/AVHRR的归一化植被指数（NDVI）资料和587个气象台站的数据对我国不同类型植被生态系统和气候的关系进行研究，首先将我国的植被类型划分为21类，在此基础上分别研究了不同时间尺度下我国不同区域，不同植被类型和气候的关系。结果表明：在多年平均状态下，植被生态系统NDVI水平主要受水分条件的影响；年内变化上，温度对植被生态系统季相变化化起着比降水略大的作用，年降水量造成了植被季相响应的差异，在年际变化上，分别研究了4个季节和整个生长期尺度上的关系，一般情形为温度和降水对植被的年际波动起着大致相反的作用，不同植被类型在不同的生长时期（季节）对气候的变化响应方式也不同，发现在植被的生长期，我国南方和北方的植被生态系统对温度和降水的响应方式相反；同时存在2个植被-气候敏感区，分别为我国北方的典型草原到森林的过渡区和云南中部部分区域。     

应用Landsat ETM数据估算鄱阳湖湿生植被生物量

利用2000年的Landsat ETM数据,首次采用全数字化遥感定量方法对鄱阳湖湿生植被的生物量及其分布进行调查研究.首先,用该时相卫星数据制作假彩色合成图象,以该图象为主要依据之一,设计了野外生物量采样路线与样点,并在地形图和GPS的帮助下,实时地开展了湿生植被生物量的野外实地采样.然后,在室内将采样点坐标和Landsat ETM图象坐标进行几何纠正和匹配,将坐标统一转换为等积圆锥投影.再逐个坐标点比较采样数据与ETM4波段数据和NDVI、DVI和第一主成分数据之间的线性相关关系.统计分析的结果表明,采样数据与ETM 4波段数据有最好的正相关,其相关系数达到0.86.采样数据与DVI、NDVI数据的相关系数分别为0.83、0.80.采样数据与第一主成分数据之间的相关关系不显著,仅0.40.基于这一比较,建立了采样数据与ETM 4波段数据的线性相关模型.据此,用ETM 4波段计算出鄱阳湖4月份湿生植被的总生物量为3.8×109 kg,并编制了整个湖泊生物量的分布图.     

森林生态系统遥感监测技术研究进展

森林是陆地生态系统的主体,森林生态系统监测技术是实现森林可持续利用与全球变化研究的重要支撑与信息保障。从4个方面概述了遥感技术在森林生态系统监测中的应用研究进展：森林遥感分类及变化监测、森林植被参数遥感反演、森林蓄积量与生物量遥感估算、森林干扰遥感监测等。结合遥感技术的发展,总结了森林生态系统监测中使用的多源遥感数据和各类模型,提出集成地面调查数据、高分地-空雷达扫描监测技术,以及多源光学遥感建模技术和生态系统过程模型,构建多维度、多尺度、高时间密度的森林生态系统监测平台的研究展望。     

地学应用中的遥感图像处理若干问题的分析

遥感技术在地理学应用中是如何从遥感影像上直观、准确的得到所需的信息,为本专业服务。文章从地学应用部门在进行遥感影像处理时遇到的几个问题:多光谱数据的选取与合成;多源信息的复合;新型图像分类器的应用;专题提取的精度等方面的进展作了分析。     

青海湖环湖地区草地植被生物量遥感监测模型

利用青海湖环湖地区2000年陆地卫星TM遥感图像数据和同期野外实测的34处样方产草量数据,分析了遥感植被指数与草地植被生物量之间的相关关系,进而分别建立了遥感植被指数与草地植被生物量的一元线性回归模型和非线性回归模型。研究表明,遥感植被指数与草地生物量之间存在较好的相关性,但不同遥感植被指数与草地植被生物量相关性程度存在一定差别。此外,所建遥感植被指数与草地植被生物量的非线性回归模型在拟合精度上优于一元线性回归模型,且由三次方程得到的非线性回归模型最适用于监测青海湖环湖地区的草地植被生物量。     

Wetland vegetation biomass estimation and mapping from Landsat ETM data: a case study of poyang lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18–28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.     

Wetland vegetation biomass estimation and mapping from Landsat ETM data:a case study of Poyang Lake

Poyang Lake is the largest freshwater lake in China. This paper conducted a digital and rapid investigation of the lake’s wetland vegetation biomass using Landsat ETM data acquired on April 16, 2000. First, utilizing the false color composite derived from the ETM data as one of the main references, the authors designed a reasonable sampling route for field measurement of the biomass, and carried it out on April 18-28, 2000. Then after both the sampling data and the ETM data were geometrically corrected to an equal-area projection of Albers, linear relationships among the sampling data and some transformed data derived from the ETM data and the ETM 4 were calculated. The results show that the sampling data is best relative to the band 4 data with a high correlation coefficient of 0.86, followed by the DVI and NDVI data with 0.83 and 0.80 respectively. Therefore, a linear regression model, which was based on the field data and band 4 data, was used to estimate the total biomass of entire Poyang Lake, and then the map of the biomass distribution was compiled.     

2001-2013年华北地区植被覆盖度与干旱条件的相关分析

基于MODIS-NDVI遥感数据以及地表气象数据,计算了2001-2013年华北地区的修正Palmer干旱指数（Palmer Drought Severity Index,PDSI）和植被覆盖度,总结出植被覆盖度以及PDSI的年际变化规律,从华北地区生态分区的角度分析了二者的相关关系。结果表明：① 华北平原的植被覆盖度呈南高北低、中部高四周低的分布特点,最低为内蒙古高原草原生态区的0.61,最高为淮阳丘陵地区的0.84;② 2001-2013年,华北平原整体植被覆盖度主要呈上升趋势,其中华北的北部、西部、南部山区及丘陵地带植被覆盖度主要呈上升趋势,而华北平原农业区以及京津唐城郊地带植被覆盖度呈下降趋势;③ 华北地区的东北部有变潮湿的趋势,南部则有变干旱的趋势,其他地区干旱条件变化不明显;④ 华北地区植被覆盖度与气候干旱程度的平均相关系数为0.20,73.37%的地区相关系数为正,正相关关系最为明显的地区为华北地区的西北部,而北京、天津、以及河北省与河南省一级、二级城市的城郊地区相关系数多为负值。⑤ 在华北大部分地区,夏季和秋季的气候干旱条件对植被覆盖度的影响最为明显。     

南京幕燕山地森林植被恢复重建研究

在大量野外工作的基础上,借助AutoCAD技术,运用植被生态学、恢复生态学的原理与方法,对幕燕山地森林植被的恢复与重建进行了研究。建立了幕燕山地植被分类系统,包括3个植被型组、5个植被型、5个植被亚型、8个群系组、12个群系,绘制了幕燕山地1∶5000植被群系图,计算了幕燕山地各群系的面积。分析了南京地区山地森林植被10个主要群系(青冈+栓皮栎林,枫香林,白栎林,栓皮栎林,麻栎林,黄连木+黄檀林,朴树+构树林,刺槐林,马尾松林,黑松林)间的演替关系,构建了南京地区森林植被次生演替模式。根据上述研究结果,提出了幕燕山地森林植被恢复重建的关键措施,预测了上述措施实施后幕燕山地植被类型构成的变化,并绘制了幕燕山地森林植被恢复重建规划图(1∶5000)。     

基于遥感数据的伊宁市城市扩展及其驱动力分析

以新疆伊犁哈萨克自治州直属市-伊宁市为例,以1990-2015年的 Landsat TM/ETM+/OLI遥感影像为数据来源,采用最大似然法提取土地利用信息,通过城市用地扩展的变化分析、城市土地利用的动态度分析、城市用地的转移特征分析、转移矩阵特征分析、土地利用变化率分析、单一土地利用动态度分析等方法,对伊宁市城市信息和城市扩展及其驱动力进行回归分析和相关性分析。结果表明：（1）1990-2015年间建设用地扩展速率和扩展强度的变化趋势基本一致,最大值分别为7.85%、18.64%,出现在2000-2005年间。（2）研究期间建设用地重心总体上向西北方向转移2 087.79 m。（3）建设用地扩展空间主要来自于耕地、未利用地、林地。（4）经济发展、人口增长是伊宁市建设用地扩展的主要驱动因子,两个因素的相关性达到0.988和0.996。本项研究成果为更准确、更快捷地掌握伊宁市城市扩展变化的规律、合理布局城市改造及其未来发展方向提供客观的科学依据。     

Assessment of biophysical properties of Royal Belum tropical forest,Malaysia

The Royal Belum forest reserve is one of the oldest tropical rainforests in the world and it is one of the largest virgin forest reserves in Malaysia. However, not many studies have been conducted to understand the ecology of this forest. In this study we estimated the aboveground biomass (AGB) of the forest using diameter at breast height (DBH) and height of trees (h ), tree species and hemispherical photographs of tree canopy. We estimated AGB using five allometric equations. Our results demonstrated that the AGB given by the one tree species specific allometric equation does not show any significant differences from the values given by the non‐tree species specific allometric equations at tree and plot levels. The AGB of Intsia bijuga species, Koompassia malaccensis species and Shorea genera were comparatively higher, owing to their greater wood density, DBH and h. This has added importance because some of these species are categorized as threatened species. Our results demonstrated that mean AGB values in this forest (293.16 t ha^‐1) are the highest compared to some studies of other areas in Malaysia, tropical Africa and tropical Bazilian Amazonia, implying that the Royal Belum forest reserve, is an important carbon reservoir.     

The use of Landsat imagery to assess large-scale forest cover changes in space and time,minimizing false-positive changes

A new approach, based on the application of multi-spectral remote sensing data of Landsat imagery, is introduced to determine large-scale spatiotemporal variations of forest cover changes quantitatively and with a high degree of precision. The test area covers about 837,330.5 ha of a mountainous region in Central Italy. The approach employs several multi-temporal Landsat acquisitions to account for forest cover changes larger than 0.5 ha for the period from March 2002 to July 2011. In contrast to automated approaches that strongly curtail mapping time, the approach introduced here allowed us to map only the real forest cover change, based on a robust validation and rectification of the detected forest change. Derived high spatial resolution data of forest change estimates indicate that about 5.7% (47,670.5 ha) of the observed forest area was subject to human-induced change between 2002 and 2011. Moreover, the detected forest cover changes, most of which are identifiable as timber harvesting, are considerably larger than those reported in the official statistics and often fall within the perimeter of restricted areas (i.e., national parks and natural reserves).     

Assessment of spatial and temporal dynamics of tropical forest cover: A case study in Malkangiri district of Orissa, India

Tropical forests have been recognized as having global conservation importance. However, they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa, India, during 1973–2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest, open forest, scrub land, agriculture, barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation, shifting cultivation, dam and road construction, unregulated management actions, and social pressure. A significant increase of 1222.8 km2 agriculture area (1973–2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences, including decline in forest cover, soil erosion, and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests, which are rapidly being deforested.     

热带森林覆被的时空动态评价——以印度Malkangiri district of Orissa为例

Tropical forests have been recognized as having global conservation importance. However,they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa,India,during 1973-2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973),Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest,open forest,scrub land,agriculture,barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation,shifting cultivation,dam and road construction,unregulated management actions,and social pressure. A significant increase of 1222.8 km2 agriculture area (1973-2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences,including decline in forest cover,soil erosion,and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests,which are rapidly being deforested.