为了提高玉米的遥感长势监测的准确度,以河北省中部平原地区为研究区域,以MODIS遥感数据反演的条件植被温度指数(Vegetation Temperature Condition Index, VTCI)与叶面积指数(Leaf Area Index, LAI)作为玉米长势监测指标,通过灰色关联...为了提高玉米的遥感长势监测的准确度,以河北省中部平原地区为研究区域,以MODIS遥感数据反演的条件植被温度指数(Vegetation Temperature Condition Index, VTCI)与叶面积指数(Leaf Area Index, LAI)作为玉米长势监测指标,通过灰色关联度分析法确定玉米各生育时期(出苗—拔节期、拔节—抽雄期、抽雄—灌浆期与灌浆—成熟期)VTCI与LAI作为相应生育时期长势监测指标的权重值,以及4个生育时期的玉米长势在总体长势与产量形成中的权重值,并基于权重结果分别构建玉米在4个生育时期与主要生育期的长势综合监测指标,进而评估研究区域2011—2016年间的玉米长势。结果表明,各生育时期VTCI作为长势监测指标的权重值均大于LAI,且以拔节—抽雄期最大,抽雄—灌浆期次之,说明玉米各生育时期的长势与最终产量较易受到水分胁迫的影响,并以拔节—抽雄期与抽雄—灌浆期对水分胁迫最为敏感;而玉米长势综合监测指标在4个生育时期的权重值较为接近,并以灌浆—成熟期略大,说明该时期的玉米长势与最终产量之间的关系较为密切。研究区域5市的县域尺度玉米长势综合监测指标与单产之间的决定系数(R2)介于0.247～0.598之间,均达到了极显著水平(P<0.001),优于单一的VTCI或LAI指标,表明基于长势综合监测指标的玉米长势监测结果准确度较高。研究年份间该区域的玉米长势以2011年的长势最好,2014年与2015年长势最差,且西部长势优于东部。展开更多
Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegi...Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.展开更多
Land use and land cover are essential for maintaining and managing the natural resources on the earth surface. A complex set of economic, demographic, social, cultural, technological, and environmental processes usual...Land use and land cover are essential for maintaining and managing the natural resources on the earth surface. A complex set of economic, demographic, social, cultural, technological, and environmental processes usually result in the change in the land use/land cover change (LULC). Pokhara Metropolitan is influenced mainly by the combination of various driving forces: geographical location, high rate of population growth, economic opportunity, globalization, tourism activities, and political activities. In addition to this, geographically steep slope, rugged terrain, and fragile geomorphic conditions and the frequency of earthquakes, floods, and landslides make the Pokhara Metropolitan region a disaster-prone area. The increment of the population along with infrastructure development of a given territory leads towards the urbanization. It has been rapidly changing due to urbanization, industrialization and internal migration since the 1970s. The landscapes and ground patterns are frequently changing on time and prone to disaster. Here a study has been carried to study on LULC for the last 18 years (2000-2018). The supervised classification on Landsat Imagery was performed and verified the classification through computing the error matrix. Besides, the water bodies and vegetation area were extracted through the Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDWI) respectively. This research shows that during the last 18 years the agricultural areas diminishing by 15.66% while urban area is increasing by 13.2%. This research is beneficial for preparing the plan and policy in the sustainable development of Pokhara Metropolitan.展开更多
文摘为了提高玉米的遥感长势监测的准确度,以河北省中部平原地区为研究区域,以MODIS遥感数据反演的条件植被温度指数(Vegetation Temperature Condition Index, VTCI)与叶面积指数(Leaf Area Index, LAI)作为玉米长势监测指标,通过灰色关联度分析法确定玉米各生育时期(出苗—拔节期、拔节—抽雄期、抽雄—灌浆期与灌浆—成熟期)VTCI与LAI作为相应生育时期长势监测指标的权重值,以及4个生育时期的玉米长势在总体长势与产量形成中的权重值,并基于权重结果分别构建玉米在4个生育时期与主要生育期的长势综合监测指标,进而评估研究区域2011—2016年间的玉米长势。结果表明,各生育时期VTCI作为长势监测指标的权重值均大于LAI,且以拔节—抽雄期最大,抽雄—灌浆期次之,说明玉米各生育时期的长势与最终产量较易受到水分胁迫的影响,并以拔节—抽雄期与抽雄—灌浆期对水分胁迫最为敏感;而玉米长势综合监测指标在4个生育时期的权重值较为接近,并以灌浆—成熟期略大,说明该时期的玉米长势与最终产量之间的关系较为密切。研究区域5市的县域尺度玉米长势综合监测指标与单产之间的决定系数(R2)介于0.247～0.598之间,均达到了极显著水平(P<0.001),优于单一的VTCI或LAI指标,表明基于长势综合监测指标的玉米长势监测结果准确度较高。研究年份间该区域的玉米长势以2011年的长势最好,2014年与2015年长势最差,且西部长势优于东部。
基金Under the auspices of Key Program of Chinese Academy of Sciences(No.KZZD-EW-08-02)CAS/SAFEA(Chinese Academy of Science/State Administration of Foreign Experts Affairs)International Partnership Program for Creative Research Teams(No.KZZD-EW-TZ-07)Strategic Frontier Program of Chinese Academy of Sciences-Climate Change:Carbon Budget and Relevant Issues(No.XDA05050101)
文摘Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.
文摘Land use and land cover are essential for maintaining and managing the natural resources on the earth surface. A complex set of economic, demographic, social, cultural, technological, and environmental processes usually result in the change in the land use/land cover change (LULC). Pokhara Metropolitan is influenced mainly by the combination of various driving forces: geographical location, high rate of population growth, economic opportunity, globalization, tourism activities, and political activities. In addition to this, geographically steep slope, rugged terrain, and fragile geomorphic conditions and the frequency of earthquakes, floods, and landslides make the Pokhara Metropolitan region a disaster-prone area. The increment of the population along with infrastructure development of a given territory leads towards the urbanization. It has been rapidly changing due to urbanization, industrialization and internal migration since the 1970s. The landscapes and ground patterns are frequently changing on time and prone to disaster. Here a study has been carried to study on LULC for the last 18 years (2000-2018). The supervised classification on Landsat Imagery was performed and verified the classification through computing the error matrix. Besides, the water bodies and vegetation area were extracted through the Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDWI) respectively. This research shows that during the last 18 years the agricultural areas diminishing by 15.66% while urban area is increasing by 13.2%. This research is beneficial for preparing the plan and policy in the sustainable development of Pokhara Metropolitan.
