利用改进型MODIS火点探测算法实现河北省秸秆焚烧火点识别

为准确地了解河北省秸秆焚烧火点的空间分布,为秸秆焚烧监测的实现、禁烧工作的开展、环境质量改善提供支持.基于MODIS L1B数据、MODIS标准火点产品MOD14、全国秸秆焚烧火点日报数据为基础,采用改进型MODIS火灾探测算法,并通过IDL语言实现,得到秸秆焚烧火点空间分布信息,并进行空间与定量精度分析.研究表明:火点大部分位于河北省南部的一些地区,其中尤以邢台、石家庄、邯郸火点数量最为突出;该算法运算速度快,获取的秸秆焚烧火点数据具有一定检测精度和可靠性,对秸秆焚烧的监测具有一定的实用价值.     

澳大利亚北方领地矿产资源管理制度和政策研究

全球矿业市场呈现低迷态势,但其糜态难以抑制各国对矿产资源的需求,本文以资源禀赋较好的澳大利亚北方领地为例,分析了当前澳大利亚北方领地的矿产资源禀赋以及矿产资源的管理制度和矿权的一些费用问题.另外,本文还分析了澳大利亚北方领地的投资优劣势,为我国企业在澳大利亚北方领地投资矿产资源、开展地质勘查提供便利.     

A stochastic model for active fire detection using the thermal bands of MODIS data

Active fire detection using satellite thermal sensors usually involves thresholding the detected brightness temperature in several bands. Most frequently used features for fire detection are the brightness temperature in the 4-/spl mu/m wavelength band (T/sub 4/) and the brightness temperature difference between 4- and 11-/spl mu/m bands (/spl Delta/T=T/sub 4/-T/sub 11/). In this letter, the task of active fire detection is examined in the context of a stochastic model for target detection. The proposed fire detection method consists of applying a decorrelation transform in the (T/sub 4/,/spl Delta/T) space. Probability density functions for the fire and background pixels are then computed in the transformed variable space using simulated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal data under different atmospheric humidity conditions and for cases of flaming and smoldering fires. The Pareto curve for each detection case is constructed. Optimal thresholds are derived by minimizing a cost function, which is a weighted sum of the omission and commission errors. The method has also been tested on a MODIS reference dataset validated using high-resolution SPOT images. The results show that the detection errors are comparable with the expected values, and the proposed method performs slightly better than the standard MODIS absolute detection method in terms of the lower cost function.     

Satellite-based automated burned area detection: A performance assessment of the MODIS MCD45A1 in the Brazilian savanna

Burnings, which cause major changes to the environment, can be effectively monitored via satellite data, regarding both the identification of active fires and the estimation of burned areas. Among the many orbital sensors suitable for mapping burned areas on global and regional scales, the moderate resolution imaging spectroradiometer (MODIS), on board the Terra and Aqua platforms, has been the most widely utilized. In this study, the performance of the MODIS MCD45A1 burned area product was thoroughly evaluated in the Brazilian savanna, the second largest biome in South America and a global biodiversity hotspot, characterized by a conspicuous climatic seasonality and the systematic occurrence of natural and anthropogenic fires. Overall, September MCD45A1 polygons (2000–2012) compared well to the Landsat-based reference mapping (r² = 0.92) and were closely accompanied, on a monthly basis, by MOD14 and MYD14 hotspots (r² = 0.89), although large omissions errors, linked to landscape patterns, structures, and overall conditions depicted in each reference image, were observed. In spite of its spatial and temporal limitations, the MCD45A1 product proved instrumental for mapping and understanding fire behavior and impacts on the Cerrado landscapes.     

珠三角地区长时间序列气溶胶时空变化特征分析

本文通过对2000年—2013年长时间序列的MODIS气溶胶产品进行统计,分析了珠三角地区气溶胶光学厚度(AOD)和细粒子光学厚度(FAOD)的空间分布特征以及年度和季节变化特点,有助于深入研究珠三角地区颗粒物污染水平变化及颗粒物的排放与输送等。研究结果显示珠三角地区中部为AOD高值区,东西两翼地区为AOD低值区。AOD和FAOD的最高值通常分别出现在春季和秋季,最低值则通常都出现在冬季。2006年之后,珠三角地区大气气溶胶总消光虽在部分年份仍有反弹上升的现象出现,但已有明显降低。然而,该地区细粒子消光在2000年—2012年期间则呈逐年增加的趋势,且其空间差异性也越加显著,细颗粒物污染仍需进一步控制。     

Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data

ABSTRACT

Monitoring the structural and functional dimensions of natural vegetation is a critical issue to ensure effective management of biodiversity. While coarse-resolution satellite image time-series have been used extensively to monitor vegetation physiognomies, their potential to describe plant species composition remains understudied. The objective of this study is to assess the potential of annual time-series of MODIS images to discriminate combinations of plant communities, called “vegetation series,” and characterize their structural and functional dimensions at the landscape scale. Twelve vegetation series were mapped in a 16 574 ha study area in a Mediterranean context located in Corsica (France). First, the structural dimension of vegetation series was examined using a random forest (RF) model calibrated with a reference field map to (i) measure the importance of each MODIS image in discriminating vegetation series; (ii) quantify the influence of the number of dates on model accuracy; and (iii) map the vegetation series with the optimal subset of MODIS images. Second, the functional dimension of vegetation series was analyzed by ordinating three functional indices through principal component analysis. These indices were the annual sum of normalized difference vegetation index (NDVI), the annual amplitude of NDVI, and the date of maximum NDVI, considered as a proxy for annual primary production, seasonality of carbon fluxes, and vegetation phenology, respectively. Results showed that (i) vegetation series were mapped accurately (median Kappa index 0.70, median overall accuracy 0.76), preferably using images acquired from February to August; (ii) at least 10 MODIS images were required to achieve sufficient accuracy; and (iii) a functional gradient was detected, ranging from high annual net primary production with low seasonality of carbon fluxes and early phenology in Mediterranean vegetation series to low annual net primary production with high seasonality of carbon fluxes and late phenology in alpine vegetation series.     

The geopotential to (14, 14) from a combination of satellite and gravimetric data

A set of2261 5°×5° mean anomalies were used alone and with satellite determined harmonic coefficients of the Smithsonian' Institution to determine the geopotential expansion to various degrees. The basic adjustment was carried out by comparing a terrestrial anomaly to an anomaly determined from an assumed set of coefficients. The (14, 14) solution was found to agree within ±3 m of a detailed geoid in the United States computed using1°×1° anomalies for an inner area and satellite determined anomalies in an outer area. Additional comparisons were made to the input anomaly field to consider the accuracy of various harmonic coefficient solutions. A by-product of this investigation was a new γ_E=978.0463 gals in the Potsdam system or978.0326 gals in an absolute system if −13.7 mgals is taken as the Potsdam correction. Combining this value of γ_E withf=1/298.25, KM=3.9860122·10 ²² cm ³ /sec ² , the consistent equatorial radius was found to be6378143 m.     

Seasonal trend analysis (STA) of MODIS vegetation index time series for the mangrove canopy of the Teacapan-Agua Brava lagoon system,Mexico

Monthly time series, from 2001 to 2016, of the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) from MOD13Q1 products were analyzed with Seasonal Trend Analysis (STA), assessing seasonal and long-term changes in the mangrove canopy of the Teacapan-Agua Brava lagoon system, the largest mangrove ecosystem in the Mexican Pacific coast. Profiles from both vegetation indices described similar phenological trends, but the EVI was more sensitive in detecting intra-annual changes. We identified a seasonal cycle dominated by Laguncularia racemosa and Rhizophora mangle mixed patches, with the more closed canopy occurring in the early autumn, and the maximum opening in the dry season. Mangrove patches dominated by Avicennia germinans displayed seasonal peaks in the winter. Curves fitted for the seasonal vegetation indices were better correlated with accumulated precipitation and solar radiation among the assessed climate variables (Pearson’s correlation coefficients, estimated for most of the variables, were r ≥ 0.58 p < 0.0001), driving seasonality for tidal basins with mangroves dominated by L. racemosa and R. mangle. For tidal basins dominated by A. germinans, the maximum and minimum temperatures and monthly precipitation fit better seasonally with the vegetation indices (r ≥ 0.58, p < 0.0001). Significant mangrove canopy reductions were identified in all the analyzed tidal basins (z values for the Mann-Kendall test ≤ ?1.96), but positive change trends were recorded in four of the basins, while most of the mangrove canopy (approximately 87%) displayed only seasonal canopy changes or canopy recovery (z > ?1.96). The most resilient mangrove forests were distributed in tidal basins dominated by L. racemosa and R. mangle (Mann-Kendal Tau t ≥ 0.4, p ≤ 0.03), while basins dominated by A. germinans showed the most evidence of disturbance.     

基于MODIS产品影像及陆面能量平衡系统(SEBS)的河北平原区域蒸散估算

地表蒸散是区域水文循环的重要组成部分之一,传统的地表蒸散估算一般基于点上的气象观测数据,当用于区域地表蒸散评价时,具有一定的局限性.随着遥感技术的发展,利用遥感影像能够对大区域进行观测的优势进行区域地表蒸散估算已成为可能.地表能量平衡系统(SEBS)是根据地表能量平衡估算地表蒸散量的一种方法,该方法由于提出了地表能量传输过程中关键制约因素热传导粗糙度的估算模型而在遥感蒸散计算方面具有较高的精度.本文在SEBS模型的基础上,以河北平原为例,采取中分辨率成像光谱辐射仪(MODIS)产品影像,根据研究区下垫面的实际情况进行了参数估算,进行了区域实际蒸发蒸腾量计算及模型精确度评价,并在SEBS模型的基础上,提出了新的"标准化温度差-反照率"特征空间分析方法,对研究区内地表土壤水分现状进行了评价;最后,对河北平原地表蒸散时空分布进行了分析.计算结果表明,在所选取的晴空乌云条件下,根据SEBS模型计算所得的地表蒸散与研究区内利用大型承重式蒸渗仪所测量的地表实际蒸散量具有很好的一致性,说明SEBS模型在遥感蒸散计算方面据有较高的可信度.然而,由于地表蒸散的遥感估算是以所获取的遥感影像单元为基础,计算误差不可避免,尤其是使用低分辨率遥感影像的时候,每个影像单元所反映的地表蒸散为单元内各种地表覆盖的综合反映,当与只反映一种地表覆盖蒸散的大型承重式蒸渗仪测量结果进行比较时,误差是显而易见的,因此,若着重考虑模型精度验证,尚需在以后的研究中考虑使用高分辨率的遥感影像.地表土壤水分或湿度状况是地表能量交换及蒸散发生的主要控制因素.利用地表温度与植被指数的关系对区域地表湿度状况进行监测在实践中被广泛利用,然而,由于不用地区地表属性的千差万别,当利用这种方法进行区域地表湿度评价时,"地表温度-植被指数"特征空间的边界很难确定.本文在SEBS模型的基础上,提出新的"标准化温度差-反照率"特征空间分析方法,对研究区内地表土壤水分现状进行评价,结果显示,由于在SEBS模型中考虑了干限和湿限两种极端情况下的能量平衡,"标准化温度差.反照率"特征空间的边界问题很容易被确定,利用修正的特征空间,可以对区域土壤水分或湿度状况进行客观的评价.下垫面的几何特征参数的精确反演是进行地表能量平衡模拟的基础,目前多根据有关经验公式利用遥感影像进行下垫面几何特征参数估算,由于已有的经验公式多基于不同研究区域获得,当应用到新的研究区时,其具体参数需要进一步调整,以获得对下垫面的几何特征的精确描述.由于缺乏相关实测资料,本研究中利用经验公式进行下垫面几何特征参数,误差不可避免,需要在以后的研究中进行深入探索.另外,地表蒸散的计算只是进行区域水资源评价、农业节水措施评价以及全球变化等研究的一个中间环节,需要在以后的研究中根据具体研究目的进行进一步研究.     

Remote detection of geological structures: an application to the Aravalli region,western India

Optical and microwave remote sensing data are used in conjunction with a digital elevation model to map lineaments in the central parts of the Aravalli region, Rajasthan, western India. Lineament maps interpreted from each data-set are subsequently combined to derive a composite lineament map of the area. Rose plots are used to identify the prominent trends of the lineaments and compared with published structural map of the study area. Three major trends are identified, namely, the NE–SW, NNE–SSW and EW, which are interpreted to be, related to the DF1, DF2 and DF4 deformation phases identified by the previous workers through field studies. The lineaments are classified as fold axes or faults, and a total of 10-fold axes and 30 faults mapped in the area.     

Assessment of the abnormal growth of floating macrophytes in Winam Gulf (Kenya) by using MODIS imagery time series

The objective of this research study is to assess the capability of time-series of MODIS imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the abnormal growth of the floating macrophytes in order to support monitoring and management action of Lake Victoria water resources.The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the high infestation of water hyacinth with significant socio-economic impact on riparian populations.In this paper, we describe an approach based on the time-series of MODIS to derive the temporal behaviour, the abundance and distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria) and its possible links to the concentrations of the main water constituencies.To this end, we consider the NDVI values computed from the MODIS imagery time-series from 2000 to 2009 to identify the floating macrophytes cover and an appropriate bio-optical model to retrieve, by means of an inverse procedure, the concentrations of chlorophyll a, coloured dissolved organic matter and total suspended solid.The maps of the floating vegetation based on the NDVI values allow us to assess the spatial and temporal dynamics of the weeds with high time resolution.A floating vegetation index (FVI) has been introduced for describing the weeds pollution level.The results of the analysis show a consistent temporal relation between the water constituent concentrations within the Winam Gulf and the FVI, especially in the proximity of the greatest proliferation of floating vegetation in the last 10 years that occurred between the second half of 2006 and the first half of 2007.The adopted approach will be useful to implement an automatic system for monitoring and predicting the floating macrophytes proliferation in Lake Victoria.     

Assessment of satellite ocean color products of MERIS,MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)

The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance R_rs(λ) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APD_m) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr⁻¹, whereas the R_rs(λ) uncertainty at 412 nm is the highest (APD_m 47–62%, RMS 0.0027–0.0041 sr⁻¹). The uncertainties of the aerosol optical thickness (AOT) τ_a, diffuse attenuation coefficient for downward irradiance at 490 nm K_d(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of K_d(490), SPM, and Chl-a may decrease significantly to the level of 20–30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task.     

Predicting the spatial distribution of hunted and non-hunted Sable antelope (Hippotragus niger niger) using remotely sensed woody cover in a Southern African savanna

From remotely sensed woody cover, we tested whether sables under hunting pressure preferred closed woodland habitats and whether those not under hunting preferred more open woodland habitats. We applied a two factorial logistic regression analysis to model the probability of occurrence of sable antelope in hunted and non-hunted areas of northwest Zimbabwe as a function of vegetation cover density (estimated by a normalized difference vegetation index (NDVI)). We validated the results by high-spatial resolution imagery derived tree canopy area. We subsequently compared the predictions from the two models in order to compare sable cover selection between hunted and non-hunted areas. Our results suggest that hunted sables are likely to select closed woodland, while non-hunted ones would prefer more open woodland habitats. We also established a significant positive relationship between NDVI and tree canopy cover, thus emphasizing the importance of remote sensing in studies that measure the impact of hunting on habitat selection of targeted species.     

The use of MODIS data to derive acreage estimations for larger fields: A case study in the south-western Rostov region of Russia

Recent developments in remote sensing technology, in particular improved spatial and temporal resolution, open new possibilities for estimating crop acreage over larger areas. Remotely sensed data allow in some cases the estimation of crop acreage statistics independently of sub-national survey statistics, which are sometimes biased and incomplete. This work focuses on the use of MODIS data acquired in 2001/2002 over the Rostov Oblast in Russia, by the Azov Sea. The region is characterised by large agricultural fields of around 75 ha on average. This paper presents a methodology to estimate crop acreage using the MODIS 16-day composite NDVI product. Particular emphasis is placed on a good quality crop mask and a good quality validation dataset. In order to have a second dataset which can be used for cross-checking the MODIS classification a Landsat ETM time series for four different dates in the season of 2002 was acquired and classified. We attempted to distinguish five different crop types and achieved satisfactory and good results for winter crops. Three hundred and sixty fields were identified to be suitable for the training and validation of the MODIS classification using a maximum likelihood classification. A novel method based on a pure pixel field sampling is introduced. This novel method is compared with the traditional hard classification of mixed pixels and was found to be superior.     

Discharge and suspended sediment flux estimated along the mainstream of the Amazon and the Madeira Rivers (from in situ and MODIS Satellite Data)

Water and suspended sediment fluxes are considered during the period 2000–2008 in a region including the full Amazon River from the confluence of the Negro River to Santarém, the end part of the Solimões River, and the lower part of the Madeira River. Three types of data are used: water discharge estimated from field measurements, and suspended sediment obtained from field measurements and derived from MODIS satellite data. A generalized least square method including a propagating term is developed in order to propagate the signal upward and downward the river. The approach is introduced and tested. Several experiments are considered in order, first, to estimate the ability to propagate the signal from stations located before the confluences of Negro and Madeira Rivers to stations located on the Amazon River; second to investigate the possibility to propagate the signal along the Amazon River which dynamics is coupled with floodplains dynamics; and third to produce optimal solutions of water and sediment fluxes. For each experiment, the influence of field and satellite data is compared. The approach is efficient in the upper part of the region of study where the Solimões, the Negro and the Madeira Rivers meet and fails in the lower part of the region where interactions between Amazon River and floodplains play an important role on the fluxes’ dynamics. The optimal experiment includes in situ and satellite data from all the stations available and is used to analyse the recent evolution of suspended sediment flux along the Amazon River and its interaction with the large coupled floodplains. A high accumulation rate is observed during the 2000–2002 period, followed by decreasing rates until 2005 and by increasing values in 2006 and 2007. Our results suggest that floodplains extending along a river reach of 390 km-long between Itacoatiara and Óbidos trap about 15% of the suspended sediment flux passing at Óbidos. The simulated deposition rate is of about 0.3 Mt km⁻¹ yr⁻¹ corresponding to an accretion rate of about 27 mm yr⁻¹.     

A Method to Upscale the Leaf Area Index (LAI) Using GF-1 Data with the Assistance of MODIS Products in the Poyang Lake Watershed

A leaf area index is a key parameter reflecting the growth changes of vegetation and one of the most important canopy structural parameters for performing quantitative analyses of many ecological and climate models. Although using high-resolution satellite data and the radiative transfer model (RTM) can be used to generate high resolution LAI products, the RTM method has some problems because its temporal resolution is low, the input parameters are more appropriate for a physics model, and some parameters are difficult to obtain. Problems that urgently need to be solved include improving the temporal-spatial resolution for LAI products and localizing LAI products. To explore an applicable method for the high-resolution LAI products in a small basin and to improve the inversion accuracy, we propose an approach for GF-1 WFV LAI retrieval using MOD15A2 data and the measured LAI of the Poyang Lake watershed. Empirical models were used to retrieve high resolution LAI values, and the results show that these models are well designed for analyzing time-series satellite data. Good correlations were obtained between the NDVI of the GF-1 WFV data, the retrieved LAI values and the MODIS LAI data from samples acquired in both summer and winter. The exponential NDVI model obtained the best LAI value estimation results from the GF-1 WFV data (R2 = 0.697, RMSE = 1.100); the best synthetic validation of the RMSE is 0.883, close to the optimum model. Therefore, the retrieval results more fully reflect the growth process of the different features. This study proposed an upscale method for developing a high spatial resolution GF-1 satellite standard LAI products retrieval model using MODIS data. The proposed method will be helpful for efficiently improving the temporal-spatial resolution of LAI products to benefit the extraction of vegetation parameter information and dynamic land use monitoring.     

Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using MODIS and field reflectance data

Monitoring turbidity and Surface Suspended Sediment Concentration (SSSC) of inland waters is essential to address several important issues: erosion, sediment transport and deposition throughout watersheds, reservoir siltation, water pollution, human health risks, etc. This is especially important in regions with limited conventional monitoring capacities such as West Africa. In this study, we explore the use of Moderate Resolution Imaging Spectroradiometer data (MODIS, MOD09Q1 and MYD09Q1 products, red (R) and near infrared (NIR) bands) to monitor turbidity and SSSC for the Bagre Reservoir in Burkina Faso. High values ​​of these parameters associated with high spatial and temporal variability potentially challenge the methodologies developed so far for less turbid waters. Field measurements (turbidity, SSSC, radiometry) are used to evaluate different radiometric indices. The NIR/R ratio is found to be the most suited to retrieve SSSC and turbidity for both in-situ spectoradiometer measurements and satellite reflectance from MODIS.The spatio temporal variability of MODIS NIR/R together with rainfall estimated by the Tropical Rainforest Measuring Mission (TRMM) and altimetry data from Jason-2 is analyzed over the Bagre Reservoir for the 2000–2015 period. It is found that rain events of the early rainy season (February-March) through mid-rainy season (August) are decisive in triggering turbidity increase. Sediment transport is observed in the reservoir from upstream to downstream between June and September. Furthermore, a significant increase of 19% in turbidity values is observed between 2000 and 2015, mainly for the July to December period. It is especially well marked for August, with the central and downstream areas showing the largest increase. The most probable hypothesis to explain this evolution is a change in land use, and particularly an increase in the amount of bare soils, which enhances particle transport by runoff.     

Derivation of a Tidal Inundation Model to Support Environmental Research in Roebuck Bay (Western Australia)

A method for deriving mean inundation times for a large expanse of intertidal mudflats is presented. Image processing techniques are used to extract waterlines from two Landsat Thematic Mapper scenes at approximately high and low tides, respectively. Along with data based on standard tidal predictions, the waterlines are utilised to derive an initial Digital Elevation Model (DEM) for the tidal flat within a GIS environment. As the model fails to fully cover the mean spring tidal range, a routine is developed to linearly extrapolate this surface to the elevation of the mean spring low tide. Tidal interpolation equations are then utilised to generate an inundation time in hours for each cell on this extrapolated DEM. Output from the generalised model is a series of maps showing isolines of inundation for both the mean spring and neap tidal cycles, as well as sets of point data that may be integrated with existing biological sample data. These data will be used to support an ongoing geologic and biologic investigation of the bay and its ecology.     

Bathymetrical influences on spatial and temporal characteristics of chlorophyll-a concentrations in the Southern Ocean from 2002 to 2012 (October to March) using MODIS

Phytoplankton blooms, particularly in the Southern Ocean, can have significant impact on global biogeochemistry cycling. To investigate the accuracy of chlorophyll-a distribution, and to better understand the spatial and temporal dynamics of phytoplankton biomass, we examine chlorophyll-a estimates (October–March from 2002 to 2012) derived from Moderate Resolution Imaging Spectrometer (MODIS) data following the ocean chlorophyll-a 3 model (OC3M) algorithm. Noticeable seasonality occurs in the temporal distribution of chlorophyll-a concentrations, which shows the highest value in December and January and an increasing tendency during the 2002–2012 period. The spatial distribution of chlorophyll-a varies greatly with latitude, as higher latitudes experience more phytoplankton blooms (chlorophyll-a concentration larger than 1 mg/m³) and marginal seas (Ross Sea and Amundsen Sea) show different bloom anomalies caused by two dominant algae species. Areas at higher latitudes and shallow water (<500 m) experience the shorter ice-free periods with greater seasonality. A noticeable bathymetry gradient exists at 2500-m isobaths, while water at the 500–2500-m depth experiences quite long ice-free periods with a stable water environment. Blooms generally occur near topographic features where currents have strong interactions when the water depth is more than 2500 m. Based on these findings, we can classify the Southern Ocean into two bloom subregions, 0–500 m as an enhanced bloom zone (EBZ), and 500–2500 m as a moderate bloom zone (MBZ). The EBZ has a quite high-bloom probability of about 30%, while the MBZ has only 10%.