查看更多>>摘要：Surface upward longwave radiation (SULR) is one of the four com-ponents of the surface radiation budget,which is defined as the total surface upward radiative flux in the spectral domain of 4-100 μm.The SULR is an indicator of surface thermal conditions and greatly impacts weather,climate,and phenology.Big Earth data derived from satellite remote sensing have been an important tool for studying earth science.The Advanced Baseline Imager (ABI)onboard the Geostationary Operational Environmental Satellite(GOES-16) has greatly improved temporal and spectral resolution compared to the imager sensor of the previous GOES series and is a good data source for the generation of high spatiotemporal resolution SULR.In this study,based on the hybrid SULR estimation method and an upper hemisphere correction method for the SULR dataset,we developed a regional clear-sky land SULR dataset for GOES-16 with a half-hourly resolution for the period from 1st January 2018 to 30th June 2020.The dataset was validated against surface measurements collected at 65 Ameriflux radiation network sites.Compared with the SULR dataset of the Global LAnd Surface Satellite (GLASS) Iongwave radiation product that is generated from the Moderate Resolution Imaging Spectroradiometer (MODIS)onboard the polar-orbiting Terra and Aqua satellites,the ABI/GOES-16 SULR dataset has commensurate accuracy (an RMSE of 15.9 W/m2 vs 19.02 W/m2 and an MBE of-4.4 W/m2 vs-2.57 W/m2),coarser spatial resolution (2 km at nadir vs 1 km resolution),less spatial coverage (most of the Americas vs global),fewer weather conditions (clear-sky vs all-weather conditions) and a greatly improved temporal resolution (48 vs 4 observations a day).The published data are available at http://www.dx.doi.org/10.11922/sciencedb.j00076.00062.
查看更多>>摘要：Plant phenology is a key parameter for accurately modeling eco-system dynamics.Limited by scarce ground observations and ben-efiting from the rapid growth of satellite-based Earth observations,satellite data have been widely used for broad-scale phenology studies.Commonly used reflectance vegetation indices represent the emergence and senescence of photosynthetic structures(leaves),but not necessarily that of photosynthetic activities.Leveraging data of the recently emerging solar-induced chlorophyll fluorescence (SIF) that is directly related to photosynthesis,and the traditional MODIS Normalized Difference Vegetation Index (NDVI),we investigated the similarities and differences on the start and end of the growing season (SOS and EOS,respectively) of the Tibetan Plateau.We found similar spatiotemporal patterns in SIF-based SOS(SOSSIF) and NDVl-based SOS (SOSNDVI).These spatial patterns were mainly driven by temperature in the east and by precipitation in the west.Yet the two satellite products produced different spatial patterns in EOS,likely due to their different climate dependencies.Our work demonstrates the value of big Earth data for discovering broad-scale spatiotemporal patterns,especially on regions with scarce field data.This study provides insights into extending the definition of phenology and fosters a deeper understanding of ecosystem dynamics from big data.
查看更多>>摘要：Yellow rust (Puccinia striiformis f.sp.Tritici) is a frequently occurring fungal disease of winter wheat (Triticum aestivum L.).During yellow rust infestation,fungal spores appear on the surface of the leaves as yellow and narrow stripes parallel to the leaf veins.We analyzed the effect of the fungal spores on the spectra of the diseased leaves to find a band sensitive to yellow rust and established a new vegetation index called the yellow rust spore index (YRSI).The estimation accuracy and stability were evaluated using two years of leaf spectral data,and the results were compared with eight indices commonly used for yellow rust detection.The results showed that the use of the YRSI ranked first for estimating the disease ratio for the 2017 spectral data (R2 =0.710,RMSE =0.097) and outperformed the published indices (R2 =0.587,RMSE =0.120) for the validation using the 2002 spectral data.The random forest (RF),k-nearest neighbor (KNN),and support vector machine (SVM) algorithms were used to test the discrimination ability of the YRSI and the eight commonly used indices using a mixed dataset of yellow-rust-infested,healthy,and aphid-infested wheat spectral data.The YRSI provided the best performance.
查看更多>>摘要：Black-necked crane (Grus nigricollis,BNC),facing serious threats from human activities and habitat variations,is an endangered species classified as vulnerable under the revised IUCN Red List.In this article,we investigated and analyzed the population and nest-ing microhabitat of BNCs in the Longbao National Nature Reserve(NNR) from 1978 to 2016,and found the number of BNCs increased from 24 in 1978 to 216 in 2016.This establishment of the Longbao NNR represented the activities of protecting endangered animal species are effective.However,the land cover classification results of Landsat images showed that the marsh wetland,which was the BNC's primary habitat,decreased during 1978-2016,while artificial buildings increased,which affected the habitat of BNCs.The increase in average temperature over the past 40 years has also had an impact on the number of BNCs.BNCs preferred to nest in marsh wetlands or on islands with open water or star-like distribu-tions through observation.The results of the principal component analysis showed that the nearest distance between nests and habi-tat type were the primary factors influencing nesting site selection.To protect BNC,we suggest decreasing wetland fragmentation,reducing habitat degradation and providing an undisturbed habitat.
查看更多>>摘要：Large-scale projects,such as the construction of railways and high-ways,usually cause an extensive Land Use Land Cover Change(LULCC).The China-Central Asia-West Asia Economic Corridor(CCAWAEC),one key large-scale project of the Belt and Road Initiative (BRI),covers a region that is home to more than 1.6 billion people.Although numerous studies have been con-ducted on strategies and the economic potential of the Economic Corridor,reviewing LULCC mapping studies in this area has not been studied.This study provides a comprehensive review of the recent research progress and discusses the challenges in LULCC monitoring and driving factors identifying in the study area.The review will be helpful for the decision-making of sustainable devel-opment and construction in the Economic Corridor.To this end,350 peer-reviewed journal and conference papers,as well as book chapters were analyzed based on 17 attributes,such as main driv-ing factors of LULCC,data collection methods,classification algo-rithms,and accuracy assessment methods.It was observed that:(1)rapid urbanization,industrialization,population growth,and cli-mate change have been recognized as major causes of LULCC in the study area;(2) LULCC has,directly and indirectly,caused several environmental issues,such as biodiversity loss,air pollution,water pollution,desertification,and land degradation;(3) there is a lack of well-annotated national land use data in the region;(4) there is a lack of reliable training and reference datasets to accurately study the long-term LULCC in most parts of the study area;and (5) several technical issues still require more attention from the scientific community.Finally,several recommendations were proposed to address the identified issues.
NETL
NSTL
万方数据
维普