Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series

Satellite data holds considerable potential as a source of information on rice crop growth which can be used to inform agronomy. However, given the typical field sizes in many rice-growing countries such as China, data from coarse spatial resolution satellite systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) are inadequate for resolving crop growth variability at the field scale. Nevertheless, systems such as MODIS do provide images with sufficient frequency to be able to capture the detail of rice crop growth trajectories throughout a growing season. In order to generate high spatial and temporal resolution data suitable for mapping rice crop phenology, this study fused MODIS data with lower frequency, higher spatial resolution Landsat data. An overall workflow was developed which began with image preprocessing, calculation of multi-temporal normalized difference vegetation index (NDVI) images, and spatiotemporal fusion of data from the two sensors. The Spatial and Temporal Adaptive Reflectance Fusion Model was used to effectively downscale the MODIS data to deliver a time-series of 30 m spatial resolution NDVI data at 8-day intervals throughout the rice-growing season. Zonal statistical analysis was used to extract NDVI time-series for individual fields and signal filtering was applied to the time-series to generate rice phenology curves. The downscaled MODIS NDVI products were able to characterize the development of paddy rice at fine spatial and temporal resolutions, across wide spatial extents over multiple growing seasons. These data permitted the extraction of key crop seasonality parameters that quantified inter-annual growth variability for a whole agricultural region and enabled mapping of the variability in crop performance between and within fields. Hence, this approach can provide rice crop growth data that is suitable for informing agronomic policy and practice across a wide range of scales.     

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands,USA

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R² values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.     

2008—2018年中国冰川变化分析

调查冰川资源的分布与变化,对区域乃至全球的自然环境与经济社会发展都具有十分重要的意义。基于315景Landsat 8 OLI遥感影像,结合中国第二次冰川编目数据与Google Earth软件,通过人工目视解译等方法调查了2018年中国冰川的分布与变化。结果表明：中国现存冰川53 238条,总面积为（47 174.21±19.93） km²,72%的冰川面积<0.5 km²,规模在1~32 km²的冰川的面积占中国冰川总面积的60%。2008—2018年,中国冰川总面积减少1 393.97 km²,面积变化率为-0.43%?a^-1。冰川面积变化率表现出明显的空间差异,面积退缩最快的是冈底斯山,达-1.07%?a^-1;最慢的是羌塘高原,为-0.05%?a^-1。坡度上,各山系之间的冰川面积变化率差异较为明显。超过70%的山系位于正东和东南方向的冰川面积退缩快,2008—2018年退缩率为-5.0%;正北方向的冰川面积退缩相对缓慢,同时期退缩率为-3.8%。气温和降水变化率差异以及海拔、坡度、坡向等地形差异,共同影响中国冰川的变化。     

Characteristics of snow cover in the Hindukush,Karakoram and Himalaya region using Landsat satellite data

Estimation of snow cover characteristics (snow grain size, snow contamination, snow depth and liquid water content) from satellite data are important components for many hydrological models used for the water resource management. This research aimed to use Landsat ETM+ (Enhanced Thematic Mapper Plus) data to estimate the snow pack characteristics in northern Pakistan. The Normalized Difference Snow Index (NDSI), Snow Contamination Index (SCI) and Snow Grain Size Index (SGI) are applied to estimate the snow cover characteristics in northern Pakistan for the first time. Qualitative maps are generated to show the snow cover distribution, snow contamination concentration and snow grain size distribution over snow cover area. Our results show that NDSI, SCI and SGI can be effectively used to identify snow area, contaminated snow and ageing snow. Furthermore, the results of the current study indicate that in the HKH region 99.8% of the snow is least contaminated whereas 94.50% of the area has fine snow grain size. As no such attempt in the past has been made in northern Pakistan, it is envisaged that the results of this study will be helpful in planning remote sensing data for the water resource management and in characterizing the snow cover for the climate change applications in the region. Copyright © 2011 John Wiley & Sons, Ltd.     

黄土丘陵干旱区地下水资源遥感调查研究

以宁夏固原县东部的黄土丘陵干旱地区为研究区，利用ETM的热红外波段进行地下水资源遥感调查，识别对地下水资源和水环境有重要影响的地形地貌、岩性构造、土壤植被、水系特征等综合自然体的遥感特征，分析研究地表水与地下水联系的环境条件，提取遥感找水信息异常，圈定找水靶区，为探水井设计及施工提供重要依据，取得了良好的应用效果。     

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.     

Landsat TM及JERS－1 SAR数据在金矿探测中的应用研究

金矿遥感探测之关键在于成矿构造及铁氧化物、含羟基蚀变矿物的信息提取。ＪＥＲＳ—１ＳＡＲ在构造探测方面具有很大的优势，可通过噪斑消除及边缘增强的空间滤波来提取构造信息。ＬａｎｄｓａｔＴＭ可通过主成分变换，比值分析－主成分变换来提取蚀变矿物波谱信息、抑制植被波谱干扰。这两种遥感数据的复合处理可综合蚀变与构造信息。     

Spatiotemporal characteristics of white mold and impacts on yield in soybean fields in South Dakota

ABSTRACT

White mold of soybeans is one of the most important fungal diseases that affect soybean production in South Dakota. However, there is a lack of information on the spatial characteristics of the disease and relationship with soybean yield. This relationship can be explored with the Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 and a fusion of Landsat 8 and the Moderate Resolution Imaging Spectroradiometer (MODIS) images. This study investigated the patterns of yield in two soybean fields infected with white mold between 2016 and 2017, and estimated yield loss caused by white mold. Results show evidence of clustering in the spatial distribution of yield (Moran’s I = 0.38; p < 0.05 in 2016 and Moran’s I = 0.45; p < 0.05 in 2017) that can be explained by the spatial distribution of white mold in the observed fields. Yield loss caused by white mold was estimated at 36% in 2016 and 56% in 2017 for the worse disease pixels, with the most accurate period for estimating this loss on 21 August and 8 September for 2016 field and 2017 field, respectively. This study shows the potential of free remotely sensed satellite data in estimating yield loss caused by white mold.     

青藏高原非均匀地表区域能量通量的研究

卫星遥感在研究青藏高原非均匀地表区域能量通量和蒸发（蒸散）量时有其独到的作用。本文介绍了基于NOAA-14 AVHRR和Landsat TM资料推算藏北高原地区区域地表特征参数、植被参数及区域地表热通量的方案，并把其用于GAME／Tibet（全球能量水循环之亚洲季风青藏高原试验研究）和CAMP／Tibet（“全球协调加强观测计划（CEOP）亚澳季风之青藏高原试验研究”）试验区。并指出了此方法估算青藏高原非均匀地表区域地表能量通量和蒸发（蒸散）量时存在的难点问题和解决问题的可能途径。     

从ASTER和Landsat／TM卫星数据反演日本千叶地区地表反射率和气溶胶光学厚度分布

在卫星遥感大气研究中，已有的精确反演海洋表面反射率和其上空气溶胶光学厚度分布的算法，由于陆地地表像元反射率的不均一性，使得这些方法在应用于陆地表面反射率的反演中具有一定的局限性。而利用三步校正法可以去除地表邻近像元的影响，从而消除这种局限性。文中介绍了三步校正的算法，并对日本千叶地区ASTER卫星数据进行了大气和地表邻近像元的影响校正，精确地反演了该地区的地表反射率，通过地表反射率和气溶胶光学厚度之间的关系计算得到了气溶胶光学厚度的分布。同时证明了在洁净天反演的地表反射率可以应用于反演同一季节中非洁净天的气溶胶光学厚度分布，这样不但减小了气溶胶模式选择的影响，而且实现了在缺少太阳辐射计数据情况下获得气溶胶光学厚度分布的目的。