Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial a...Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.展开更多
Using CASA model, biomass within the Haihe River basin during 2002 -2007 was estimated based on remote sensing images, corresponding data of temperature, precipitation and solar radiation, and 1：400 000 0 maps of veg...Using CASA model, biomass within the Haihe River basin during 2002 -2007 was estimated based on remote sensing images, corresponding data of temperature, precipitation and solar radiation, and 1：400 000 0 maps of vegetation coverage in China. Variations in the biomass with vegetation type and vegetation coverage in 2007 were analyzed. Meanwhile, its temporal and spatial changes were discussed. The results validate the applicability of CASA model in the estimation of biomass within the Haihe River basin. During the past 6 years, annual average biomass within the basin was 405.5 Tg in total; annual average biomass in the basin was high in the southeast but low in the northwest, namely plains 〉 mountains 〉 plateaus.展开更多
植被净初级生产力及其对气候变化的响应研究是全球变化的核心内容之一。在利用内蒙古典型草原连续13年的地上生物量资料对基于遥感信息的生态系统碳循环过程CASA（Camegie-Ames-Stanford Approach）模型验证的基础上，分析了内蒙古典型...植被净初级生产力及其对气候变化的响应研究是全球变化的核心内容之一。在利用内蒙古典型草原连续13年的地上生物量资料对基于遥感信息的生态系统碳循环过程CASA（Camegie-Ames-Stanford Approach）模型验证的基础上，分析了内蒙古典型草原1982-2002年植被净初级生产力（Net primary productivity，NPP）的时间变异及其影响因子。结果表明：1）1982～2002年21年间内蒙古典型草原的平均年NPP为290．23 g C·m^-2．a^-1，变化范围为145．80～502．84 g C·m^-2·a^-1；2）内蒙古典型草原NPP呈增加趋势，但没有达到显著性水平，其中1982～1999年的18年间NPP呈现非常显著的增加趋势（P〈0．01），NPP增加的直接原因是由于生长旺季生长本身增强所致；3）内蒙古典型草原NPP与年降水量呈极显著的相关关系，年降水量显著影响NPP的变异，而NPP与年均温无显著相关关系。展开更多
为了揭示湖北省植被NPP的时空演变规律及驱动机制,基于CASA模型计算2000—2018年湖北省植被NPP,结合气象数据和土地利用数据,利用重心模型、相关性分析和贡献指数等方法分析植被NPP的时空变化及其影响因素。结果表明:(1)2000—2018年湖...为了揭示湖北省植被NPP的时空演变规律及驱动机制,基于CASA模型计算2000—2018年湖北省植被NPP,结合气象数据和土地利用数据,利用重心模型、相关性分析和贡献指数等方法分析植被NPP的时空变化及其影响因素。结果表明:(1)2000—2018年湖北省植被NPP年均值介于532.19~656.49 g C/(m^(2)·a),整体呈波动上升趋势;(2)湖北省植被NPP在空间分布上表现为由西北向东南递减的趋势,植被NPP重心迁移轨迹呈M型,西北地区的增量和增速较大高于东南地区。(3)湖北省植被NPP与年均气温呈正相关的区域面积占全省总面积的54.49%,主要分布在荆门、荆州地区以及宜昌东南部地区;年均NPP与年降水量呈正相关的面积高达87.65%,主要分布在随州、襄阳和孝感北部地区。(4)2000—2018年研究区域内NPP总量增加19.86×10^(-2)Tg C,在土地利用变化引起的NPP损益中,主要由其他土地类型向林地、耕地和草地转换引起;不同时期土地覆盖变化对NPP总量的贡献率有所差异,2000—2010年建设用地贡献率最高为53.81%,2010—2018年耕地贡献率最高为61.53%。展开更多
基金Under the auspices of the National Natural Science Foundation of China (No. 40571117), the Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX3-SW-338), Research foundation of the State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences (KQ060006)
文摘Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.
文摘Using CASA model, biomass within the Haihe River basin during 2002 -2007 was estimated based on remote sensing images, corresponding data of temperature, precipitation and solar radiation, and 1：400 000 0 maps of vegetation coverage in China. Variations in the biomass with vegetation type and vegetation coverage in 2007 were analyzed. Meanwhile, its temporal and spatial changes were discussed. The results validate the applicability of CASA model in the estimation of biomass within the Haihe River basin. During the past 6 years, annual average biomass within the basin was 405.5 Tg in total; annual average biomass in the basin was high in the southeast but low in the northwest, namely plains 〉 mountains 〉 plateaus.
文摘植被净初级生产力及其对气候变化的响应研究是全球变化的核心内容之一。在利用内蒙古典型草原连续13年的地上生物量资料对基于遥感信息的生态系统碳循环过程CASA（Camegie-Ames-Stanford Approach）模型验证的基础上，分析了内蒙古典型草原1982-2002年植被净初级生产力（Net primary productivity，NPP）的时间变异及其影响因子。结果表明：1）1982～2002年21年间内蒙古典型草原的平均年NPP为290．23 g C·m^-2．a^-1，变化范围为145．80～502．84 g C·m^-2·a^-1；2）内蒙古典型草原NPP呈增加趋势，但没有达到显著性水平，其中1982～1999年的18年间NPP呈现非常显著的增加趋势（P〈0．01），NPP增加的直接原因是由于生长旺季生长本身增强所致；3）内蒙古典型草原NPP与年降水量呈极显著的相关关系，年降水量显著影响NPP的变异，而NPP与年均温无显著相关关系。
文摘植被净初级生产力（net primary productivity,NPP）及其对气候变化的响应研究是全球变化的核心内容之一。基于地理信息系统和卫星遥感应用技术,利用CASA模型估算了2001-2008年甘南草地NPP,在模型验证的基础上,分析了甘南草地NPP空间分布格局和时间分布特征。结果表明,1）2001-2008年甘南草地多年平均NPP为483.41 g C/（m2.a）,大体呈现由西南向东北逐渐减少的趋势,单位面积多年平均NPP在海拔3 000~3 500 m最高,达到497.07 g C/（m2.a）;2）甘南草地植被生长季节变化明显,主要生长期集中在第177~240天;3）甘南草地NPP呈现增加趋势,增长趋势最明显的草地类型是低平地草甸类,而沼泽的变幅最小,通过与8年间温度和降水的分析可以看出,影响甘南草地NPP变化的主要驱动力是降水量。
文摘为了揭示湖北省植被NPP的时空演变规律及驱动机制,基于CASA模型计算2000—2018年湖北省植被NPP,结合气象数据和土地利用数据,利用重心模型、相关性分析和贡献指数等方法分析植被NPP的时空变化及其影响因素。结果表明:(1)2000—2018年湖北省植被NPP年均值介于532.19~656.49 g C/(m^(2)·a),整体呈波动上升趋势;(2)湖北省植被NPP在空间分布上表现为由西北向东南递减的趋势,植被NPP重心迁移轨迹呈M型,西北地区的增量和增速较大高于东南地区。(3)湖北省植被NPP与年均气温呈正相关的区域面积占全省总面积的54.49%,主要分布在荆门、荆州地区以及宜昌东南部地区;年均NPP与年降水量呈正相关的面积高达87.65%,主要分布在随州、襄阳和孝感北部地区。(4)2000—2018年研究区域内NPP总量增加19.86×10^(-2)Tg C,在土地利用变化引起的NPP损益中,主要由其他土地类型向林地、耕地和草地转换引起;不同时期土地覆盖变化对NPP总量的贡献率有所差异,2000—2010年建设用地贡献率最高为53.81%,2010—2018年耕地贡献率最高为61.53%。
