Estimation of net primary productivity in China using remote sensing data

It is significant to estimate terrestrial net primary productivity (NPP) accurately not only for global change research, but also for natural resources management to achieve sustainable development. Remote sensing data can describe spatial distribution of plant resources better. So, in this paper an NPP model based on remote sensing data and climate data is developed. And 1km resolution AVHRR NDVI data are used to estimate the spatial distribution and seasonal change of NPP in China. The results show that NPP estimated using remote sensing data are more close to truth. Total annual NPP in China is 2.645X109 tC. The spatial distribution of NPP in China is mainly affected by precipitation and has the trend of decreasing from southeast to northwest.

Improving remote sensing-based net primary production estimation in the grazed land with defoliation formulation model

Remote sensing(RS) technologies provide robust techniques for quantifying net primary productivity(NPP) which is a key component of ecosystem production management. Applying RS, the confounding effects of carbon consumed by livestock grazing were neglected by previous studies, which created uncertainties and underestimation of NPP for the grazed lands. The grasslands in Xinjiang were selected as a case study to improve the RS based NPP estimation. A defoliation formulation model(DFM) based on RS is developed to evaluate the extent of underestimated NPP between 1982 and 2011. The estimates were then used to examine the spatiotemporal patterns of the calculated NPP. Results show that average annual underestimated NPP was 55.74 gC·m^(-2)yr^(-1) over the time period understudied, accounting for 29.06% of the total NPP for the Xinjiang grasslands. The spatial distribution of underestimated NPP is related to both grazing intensity and time. Data for the Xinjiang grasslands show that the average annual NPP was 179.41 gC·m^(-2)yr^(-1), the annual NPP with an increasing trend was observed at a rate of 1.04 gC·m^(-2)yr^(-1) between 1982 and 2011. The spatial distribution of NPP reveals distinct variations from high to low encompassing the geolocations of the Tianshan Mountains, northern and southern Xinjiang Province and corresponding with mid-mountain meadow, typical grassland, desert grassland, alpine meadow, and saline meadow grassland types. This study contributes to improving RS-based NPP estimations for grazed land and provides a more accurate data to support the scientific management of fragile grassland ecosystems in Xinjiang.

Satellite remote sensing of ultraviolet irradiance on the ocean surface

Ultraviolet （UV） radiation has a significant influence on marine biological processes and primary productivity; however, the existing ocean color satellite sensors seldom contain UV bands. A look-up table of wavelength- integrated UV irradiance （280-400 nm） on the sea surface is established using the coupled ocean atmosphere radiative transfer （COART） model. On the basis of the look-up table, the distributions of the UV irradiance at middle and low latitudes are inversed by using the satellite-derived atmospheric products from the Aqua satellite, including aerosol optical thickness at 550 nm, ozone content, liquid water path, and the total precipitable water. The validation results show that the mean relative difference of the 10 d rolling averaged UV irradiance between the satellite retrieval and field observations is 8.20% at the time of satellite passing and 13.95% for the daily dose of UV. The monthly-averaged UV irradiance and daily dose of UV retrieved by satellite data show a good correlation with the in situ data, with mean relative differences of 6.87% and 8.43%, respectively. The sensitivity analysis of satellite inputs is conducted. The liquid water path representing the condition of cloud has the highest effect on the retrieval of the UV irradiance, while ozone and aerosol have relatively lesser effect. The influence of the total precipitable water is not significant. On the basis of the satellite-derived UV irradiance on the sea surface, a preliminary simple estimation of ultraviolet radiation＇s effects on the global marine primary productivity is presented, and the results reveal that ultraviolet radiation has a non-negligible effect on the estimation of the marine primary productivity.

Spatio-temporal Pattern of Ecosystem Pressure in Countries Along the Belt and Road: Combining Remote Sensing Data and Statistical Data

Building a Green Silk Road by integrating the Sustainable Development Goals(SDGs) is one of the Belt and Road Initiative(BRI) visions, but the BRI faces enormous challenge that is the conflict between economic development and ecological sustainability.Understanding the current scale and trend of the impact of human activities on the ecosystem is the preliminary work to ensure that human activities do not exceed the ecological carrying capacity under the BRI. This study evaluated the ecosystem pressure in countries along the Belt and Road(B&R) from 2000–2017 based on the supply-consumption balance relationship of ecological resources. Net primary productivity(NPP) is taken as the measure of ecological resources, and the supply level and consumption intensity of ecological resources is estimated based on remote sensing data and statistical data, respectively. Results show that thirteen countries with overconsumed ecological resources concentrated in the West Asia/Middle East. Although the intensity of the ecological resource consumption correlated with ecological resource endowments, the ecosystem pressure was determined by social development dependence on the ecological resources at the same ecological resource endowments level. Nearly 80% of countries along the B&R suffered from significantly increased(P < 0.05) ecosystem pressure during 2000–2017, since most of the countries along the B&R were developing countries,and their economic development was highly dependent on ecological resources. Some West Asia/Middle East countries successfully mitigated the ecosystem pressure by importing feed for livestock. Likewise, the Southeast Asian islands benefitted from the import of agricultural products. The results highlight that the BRI should reduce the dependence of social development demands on local ecological resources by international trade for ensuring the increasing ecosystem pressure trend within the ecological carrying capacity.

Remote Sensing Data Application to Monitor Snow Cover Variation and Hydrological Regime in a Poorly Gauged River Catchment—Northern Pakistan

Snow- and glacier-nourished river basins located in the Himalaya-Karakoram-Hindukush (HKH) ranges supply a significant amount of discharge in River Indus upstream Tarbela Dam. It is, hence, important to comprehend the cryosphere variation and its relationship to the stream flow in these high-altitude river catchments. The MODIS remotely sensed database of snow products was chosen to examine the average annual snow and glacier cover (cryosphere) variations in the Shigar River basin (poorly gauged mountainous sub-catchment of the Indus River). Hydrological regime in the area was investigated through monthly database of observed stream fluxes and climate variables (precipitation and mean temperature) for the Shigar River catchment. Analysis indicated the usefulness of remote sensing techniques for estimation of the snow cover variation in the poorly or un-gauged high-elevation catchments of the HKH zone. Results also showed that Shigar River discharge was influenced mainly by the seasonal and annual snow cover area (SCA) variation and the temperature seasonality. Moreover, it is important to uncover such inter-relationship of stream flow, climate variables and snow cover in the poorly gauged high-altitude catchments of Karakoram region for better water resource management and accurate flood hazards predictions at Tarbela.

Significant discrepancies of land surface daily net radiation among ten remotely sensed and reanalysis products

Land surface all-wave net radiation(R_(n))is crucial in determining Earth’s climate by contributing to the surface radiation budget.This study evaluated seven satellite and three reanalysis long-term land surface R_(n)products under different spatial scales,spatial and temporal variations,and different conditions.The results showed that during 2000-2018,Global Land Surface Satellite Product(GLASS)-Moderate Resolution Imaging Spectroradiometer(MODIS)performed the best(RMSE=25.54 Wm^(-2),bias=-1.26 Wm^(-2)),followed by ERA5(the fifth-generation of European Centre for Medium-Range Weather Forecast Reanalysis)(RMSE=32.17 Wm^(-2),bias=-4.88 Wm^(-2))and GLASS-AVHRR(Advanced Very-High-Resolution Radiometer)(RMSE=33.10 Wm^(-2),bias=4.03 Wm^(-2)).During 1983-2018,GLASS-AVHRR and ERA5 ranked top and performed similarly,with RMSE values of 31.70 and 33.08 Wm^(-2)and biases of-4.56 and 3.48 Wm^(-2),respectively.The averaged multi-annual mean R_(n)over the global land surface of satellite products was higher than that of reanalysis products by about 10~30 Wm^(-2).These products differed remarkably in long-term trends variations,particularly pre-2000,but no significant trends were observed.Discrepancies were more frequent in satellite data,while reanalysis products showed smoother variations.Large discrepancies were found in regions with high latitudes,reflectance,and elevation which could be attributed to input radiative components,meteorological variables(e.g.,cloud properties,aerosol optical thickness),and applicability of the algorithms used.While further research is needed for detailed insights.

红外遥感相机成像参数优化研究

为了更好地优化红外遥感相机成像参数,文章首次提出信噪比-动态范围积相机性能综合评价指标。建立了红外遥感相机的噪声电压模型并深入分析噪声影响,当恒定噪声电压项远大于时变噪声电压项时噪声电压模型可以近似简化为线性模型。进而建模分析了积分电容和积分时间对信噪比和动态范围的影响,并首次提出信噪比-动态范围积作为相机性能评价的指标。信噪比-动态范围积随着积分时间同步增大,积分时间较小时增速较快,积分时间较大时增速迅速下降;信噪比-动态范围积随着积分电容的增大先增加后减小,存在极值。研究结果对红外遥感相机的参数优化设计具有重要作用。

基于遥感和通量观测的实际蒸散发时空变化特征——以黄河流域水源涵养区为例

蒸散发是地表水热平衡的关键要素,分析蒸散发的时空分布特征及其影响因素,对于深入理解区域水文循环与生态系统过程至关重要。基于通量观测站数据,评估GLEAM、MTE、GLDAS和AVHRR共4种蒸散发产品在黄河流域水源涵养区的适用性,利用水量平衡方法验证其在流域尺度上的精度,并探讨实际蒸散发的影响因素。结果表明:在站点尺度上,GLEAM蒸散发产品精度最高;在流域尺度上,校正后的GLEAM蒸散发产品与实际蒸散发的相对误差在渭河南山支流区最小,其次是兰州以上地区;1982—2015年黄河流域水源涵养区实际蒸散发整体呈增加趋势,空间分布上自西到东逐渐增加;不同植被类型年均蒸散发差异较大,阔叶林的蒸散发最大(575.2 mm),其次是农田(504.3 mm),高山草甸的蒸散发最小(358.2 mm);实际蒸散发变化主要受到太阳辐射与气温的影响。

基于向量叉乘标签分配的遥感图像目标检测算法

近年来遥感图像目标检测受到了广泛的关注,主流的遥感图像目标检测器通过预设锚框与真实框之间的交并比(IoU)进行正负样本的划分。为了解决基于IoU的标签分配方法在遥感图像小而密集目标中存在复检和漏检的问题,本文提出了一种基于向量叉乘标签分配的遥感图像目标检测算法YOLOXR。首先,提出了一种标签粗分配策略,通过向量叉乘的方法判断特征图的像素点是否在旋转目标内或者目标中心点附近的旋转正方形框内,从而确定其是否为候选正样本。其次,为了降低边缘低质量候选正样本对标签分配的影响,提出了旋转中心度量方法,通过向量叉乘判断像素点距离中心点的远近程度进而赋予不同的权重。最后,基于最优传输的方法(sim OTA)选取真实框和样本点的最优匹配对,使得总体代价最小,进而为旋转目标分配合适的标签。此外,为了解决旋转IoU损失不可导以及Smooth L1损失难以权衡旋转框各个参数的问题,通过计算真实框和预测框二维高斯分布的Kullback-Leibler散度(KLD)来替代IoU。在公开的遥感图像目标检测数据DOTA、HRSC 2016和UCAS-AOD上的大量实验表明,所提方法优于目前绝大多数旋转目标检测算法。

Principles and methods for the validation of quantitative remote sensing products

We first discuss the relativity of "true value and homogeneity" for quantitative remote sensing products (QRSPs), and then propose the definitions of "eigenaccuracy" and "eigenhomogeneity" under practical conditions. The eigenaccuracy and eigenhomogeneity for land surface crucial parameters such as albedo, leaf area index (LAI), and surface temperature are analyzed based on a series of experiments. Secondly, we point out the differences and similarities between the scale-free phenomena of the QRSPs and the measurements of the coastline length (1-dimensional) and the curved surface area (2-dimensional). An information fractal algorithm for the QRSPs is presented. In a case study for the LAI, when the fractal dimension is 2.16, the ratio of the LAI retrieval values obtained respectively from remote sensing data of 30 m and 6 km pixel resolution can actually reach as high as 2.86 for the same 6 km pixel using the same retrieval model. Finally, we propose an operational validation method "one test and two matches" and multipoint observation when the real situation does not allow carrying out scanning measurement without gap and overlap on the ground surface.

Multispectral imaging systems for airborne remote sensing to support agricultural production management

This study investigated three different types of multispectral imaging systems for airborne remote sensing to support management in agricultural application and production.The three systems have been used in agricultural studies.They range from low-cost to relatively high-cost,manually operated to automated,multispectral composite imaging with a single camera and integrated imaging with custom-mounting of separate cameras.Practical issues regarding use of the imaging systems were described and discussed.The low-cost system,due to band saturation,slow imaging speed and poor image quality,is more preferable to slower moving platforms that can fly close to the ground,such as unmanned autonomous helicopters,but not recommended for low or high altitude aerial remote sensing on fixed-wing aircraft.With the restriction on payload unmanned autonomous helicopters are not recommended for high-cost systems because they are typically heavy and difficult to mount.The system with intermediate cost works well for low altitude aerial remote sensing on fixed-wing aircraft with field shapefile-based global positioning triggering.This system also works well for high altitude aerial remote sensing on fixed-wing aircraft with global positioning triggering or manually operated.The custom-built system is recommended for high altitude aerial remote sensing on fixed-wing aircraft with waypoint global positioning triggering or manually operated.

Spatial scaling of net primary productivity model based on remote sensing

Spatial scaling for net primary productivity （NPP） refers to the transferring process of establishing quantitative correlation between simulated NPP derived from data at different spatial resolutions. How to transfer NPP at one scale by the algorithm with smaller error to at another is the urgent problem. Nonlinearity and effects from land cover type are two main problems in NPP scaling. In this paper, the contextural approach based on mixed pixels and support vector machine （SVM） algorithm are used to make the scaling model from the fine resolution （TM） to the coarse resolution （MODIS）. Spatial scaling from NPP retrieved from fine resolution data to NPP derived from coarse resolution images is performed, and the correction of scale effect to NPP retrieved from coarse resolution data of MODIS is accomplished. The result shows that the correlation between Rj_coereted of the correction factor for scale effect and 1-Fmiddle dessity grassland estimated by SVM regression model is higher （R2=0.81）. Before the correction for scale effect, the correlation between NPPMODIS and NPPTM is lower （R2=0.69; RMSE=3.47）, while the correlation between NPPTM and corrected NPPMODIS_corrected is higher （R2=0.84; RMSE= 1.87）. Therefore, NPP corrected for scale effect has been greatly improved in both correlation and error.

卫星遥感赋能旱情监测:进展与展望

我国干旱灾害发生频繁,造成的损失严重。传统的干旱监测主要基于气象和水文数据,在监测面上的旱情时存在局限。基于新质生产力开展旱情监测迫在眉睫,也是新时期干旱灾害防御工作的重要着力点。近年来,随着卫星遥感技术快速发展,大范围、高精度、高频次、全天候对地观测能力基本形成,旱情遥感监测由早期的模型研究向业务化应用方向发展,多源遥感星地协同旱情监测、精细化旱情综合评估以及遥感、水文气象耦合的旱情预警是未来发展趋势。

Development and evaluation of low-altitude remote sensing systems for crop production management

Precision agriculture accounts for within-field variability for targeted treatment rather than uniform treatment of an entire field.It is built on agricultural mechanization and state-of-the-art technologies of geographical information systems(GIS),global positioning systems(GPS)and remote sensing,and is used to monitor soil,crop growth,weed infestation,insects,diseases,and water status in farm fields to provide data and information to guide agricultural management practices.Precision agriculture began with mapping of crop fields at different scales to support agricultural planning and decision making.With the development of variable-rate technology,precision agriculture focuses more on tactical actions in controlling variable-rate seeding,fertilizer and pesticide application,and irrigation in real-time or within the crop season instead of mapping a field in one crop season to make decisions for the next crop season.With the development of aerial variable-rate systems,low-altitude airborne systems can provide high-resolution data for prescription variable-rate operations.Airborne systems for multispectral imaging using a number of imaging sensors(cameras)were developed.Unmanned aerial vehicles(UAVs)provide a unique platform for remote sensing of crop fields at slow speeds and low-altitudes,and they are efficient and more flexible than manned agricultural airplanes,which often cannot provide images at both low altitude and low speed for capture of high-quality images.UAVs are also more universal in their applicability than agricultural aircraft since the latter are used only in specific regions.This study presents the low-altitude remote sensing systems developed for detection of crop stress caused by multiple factors.UAVs,as a special platform,were discussed for crop sensing based on the researchers'studies.

Assessing the Response of Seasonal Variation of Net Primary Productivity to Climate Using Remote Sensing Data and Geographic Information System Techniques in Xinjiang

Net primary productivity （NPP） is a key component of energy and matter transformation in the terrestrial ecosystem, and the responses of NPP to global change locally and regionally have been one of the most important aspects in climatevegetation relationship studies. In order to isolate causal climatic factors, it is very important to assess the response of seasonal variation of NPP to climate. In this paper, NPP in Xinjiang was estimated by NOAA/AVHRR Normalized Difference Vegetation Index （NDVI） data and geographic information system （GIS） techniques. The impact of climatic factors （air temperature, precipitation and sunshine percentage） on seasonal variations of NPP was studied by time lag and serial correlation ageing analysis. The results showed that the NPP for different land cover types have a similar correlation with any one of the three climatic factors, and precipitation is the major climatic factor influencing the seasonal variation of NPP in Xinjiang. It was found that the positive correlation at 0lag appeared between NPP and precipitation and the serial correlation ageing was 0 d in most areas of Xinjiang, which indicated that the response of NPP to precipitation was immediate. However, NPP of different land cover types showed significant positive correlation at 2 month lag with air temperature, and the impact of which could persist 1 month as a whole. No correlation was found between NPP and sunshine percentage.

Remote sensing monitoring on regional crop water productivity in the Haihe River Basin

Crop water productivity （CWP） agricultural development in water scarcity is one of the important indicators for sustainable area. There is serious conflict between water sup- ply and requirement in the Haihe River Basin. CWP of winter wheat and summer maize from 2003 to 2007 in the Haihe River Basin is estimated based on large-scale evapotranspiration （ET） and crop yield obtained by remote sensing technology. Spatial and temporal distribution of CWP of winter wheat and summer maize is investigated in this study. Results show that CWP of winter wheat in most parts of the study area varies from 1.02 kg/m3 to 1.53 kg/m3, and CWP of summer maize varies from 1.31 kg/m3 to 2.03 kg/m3. Multi-year averaged CWP of winter wheat and summer maize in the study area is about 1.19 kg/m3 and 1.59 kg/m3. CWP results show certain promotion potential to alleviate the water shortage in the Haihe River Basin. Correlation analysis of CWP, crop yield and ET shows that there is great potential for crop yield promotion without the growth in irrigation water. Large-scale CWP estimated by remote sensing technology in this study shows spatial distribution features, which could be used to real-time agricultural water resource management combined with crop yield and ET.

Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin

Understanding of crop water productivity (WP) over large scale, e.g., river basin, has significant impli-cations for sustainable basin development planning. This paper presents a simplified approach to combine remote sensing, census and weather data to analyze basin rice and wheat WP in Indo-Gangetic River Basin, South Asia. A crop dominance map is synthesized from ground truth data and three existing LULC maps. National statistics on crop area and production information are collected and the yield is interpolated to pixel level using moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI). Crop evapotranspiration is mapped using simplified surface energy balance (SSEB) model with MODIS land surface temperature products and meteorological data collected from 56 weather stations. The average ET by rice and wheat is 368 mm and 210 mm respectively, accounting for only 69% and 65% of potential ET, and 67% and 338% of rainfall of the crop growth period measured from Tropical Rainfall Measurement Mission (TRMM). Average WP for rice and wheat is 0.84 and 1.36 kg/m3 respectively. WP variability generally follows the same trend as shown by crop yield disregarding climate and topography changes. Sum of rice-wheat water productivity, however, exhibits different variability leading to better understanding of irrigation water management as wheat heavily relies on irrigation. Causes for variations and scope for improvement are also analyzed.

多源潜在蒸散发产品在雅鲁藏布江流域的适用性评估与融合

基于2001—2018年监测站点观测的蒸发皿数据,分别在站点尺度和流域尺度上对GLEAM、MOD16A2、GLDAS_Noah和ERA5共4种遥感潜在蒸散发产品进行评估,选出适应性较好的3种遥感产品,运用Triple Collocation方法进行融合,并分析其时空变化特征。结果表明:在站点尺度上,ERA5遥感产品相关性较为显著(相关系数CC=0.72),精确度最高(相对偏差Bias=-22.48%,均方根误差RMSE=39.24 mm/月),更适用于雅鲁藏布江流域,MOD16A2和GLDAS_Noah次之;MOD16A2、GLDAS_Noah和ERA5分别占融合数据PET_(TC)的31.12%、30.64%和38.24%,对比PET_(TC)与3种遥感产品,PET_(TC)融合数据在流域内精度有所提高;融合数据PET_(TC)的潜在蒸散发峰值出现在2009年,雅鲁藏布江流域多年平均潜在蒸散发呈现从中部向上、下游逐渐减小的趋势,在流域东南角出现潜在蒸散发量最大值。在雅鲁藏布江流域内获得更精准的潜在蒸散发并揭示其变化规律,可为研究流域水资源的供需平衡和生态系统的稳定性提供数据支撑。

水利遥感数据规模化加工处理平台框架研究

以卫星遥感为代表的地表信息空天获取手段是支撑新时期智慧水利建设的重要途径。当前,遥感数据获取能力与处理服务能力之间出现了失衡,大量的对地观测卫星遥感数据被获取,而能够支撑水利业务的遥感数据产品即时服务能力和动态更新频次仍然存在瓶颈,“卫星数据量大、处理流程复杂、产品服务不足”的现状长期存在,制约着水利行业遥感应用的质量和效率。本文通过调研当前国内外遥感大数据加工处理进展,分析了面向智慧水利建设的水利遥感数据处理平台需求,设计了一种水利遥感数据规模化加工处理平台的框架,用于海量卫星遥感数据产品全链路自动化处理,以提升水利遥感数据产品处理质量和服务效率。该平台可以实现超过30种多源高分遥感数据全流程处理,通过动态分配GPU和CPU计算缓存,实现卫星遥感数据正射校正、融合、镶嵌、质检以及水利遥感专题信息提取等流程规模化、并行化和自动化处理,生产满足数字孪生流域建设的卫星遥感专题产品,支撑新时期智慧水利建设的遥感深度应用。

基于贝叶斯模型平均的2003–2015年青海三江源地区地表蒸散发数据集

蒸散发(Evapotranspiration,ET)是陆地水、碳和能量交换的重要组成部分。基于不同模型和不同遥感数据估算的ET,存在不同程度的不确定性。贝叶斯模型平均(Bayesian model averaging,BMA)提供了降低不确定性的一种途径。本研究采用中国三江源地区水热通量观测数据,以ARTS、PT-JPL、MOD16和SSEBop遥感蒸散发产品为基础,进行了BMA集成研究,生成了三江源地区2003–2015年250 m空间分辨率的年均地表蒸散发数据集。通过验证各输入模型和BMA集成模型结果,发现基于BMA的ET与通量观测数据相关性达0.94,能够解释观测数据季节变化的89%,优于单个模型的性能。说明BMA模型集成能够整合不同模型内在优势,降低结果估算的不确定性,从而获得更可靠的估算结果。本数据集可为三江源区域水热变化研究和生态系统调节功能评估提供更精确的数据支持。