The expansion of tree-based boom crops in mainland Southeast Asia: 2001 to 2014

Over the past half century, countries of Mainland Southeast Asia (MSEA) – Cambodia, Laos, Myanmar, Thailand, and Vietnam – have witnessed increases in commercialized agriculture with rapid expansions of boom-crop plantations. We used MODIS EVI and SWIR time-series from 2001–2014 to classify tree-cover changes across MSEA and performed a supervised change detection using an upscaling approach by deriving samples from existing Landsat classifications. We used the random forest classifier and distinguished 24 classes (16 representing boom-crops) with an accuracy of 82.2%. Boom-crops occupy about 18% of the landscape (8% of which is rubber). Since 2003 74,960 km² of rubber have been planted; 70% of rubber is planted on former forest land, and 30% on low vegetation area (mainly former croplands). Timing, patterns of change, and deforestation rates, however, differ among the MSEA countries and the high spatial and temporal detail of our classification allowed us to quantify dynamics and discuss political and socio-economic drivers of change.     

利用遥感影像软件ENVI提取植被指数

在遥感影像处理中，植被指数提取广泛应用于定性和定量评价植被覆盖及其生长活力。主要介绍了在ENVI遥感图像处理软件对遥感影像进行植被指数。对植被指数提取的关键部分进行分析，并给出植被指数提取的技术关键。     

Quantification of net primary production of Chinese forest ecosystems with spatial statistical approaches

Net primary production (NPP) of terrestrial ecosystems provides food, fiber, construction materials, and energy to humans. Its demand is likely to increase substantially in this century due to rising population and biofuel uses. Assessing national forest NPP is of importance to best use forest resources in China. To date, most estimates of NPP are based on process-based ecosystem modeling, forestry inventory, and satellite observations. There are little efforts in using spatial statistical approaches while large datasets of in-situ observed NPP are available for Chinese forest ecosystems. Here we use the surveyed forest NPP and ecological data at 1,266 sites, the data of satellite forest coverage, and the information of climate and topography to estimate Chinese forest NPP and their associated uncertainties with two geospatial statistical approaches. We estimate that the Chinese forest and woodland ecosystems have total NPP of 1,325 ± 102 and 1,258 ± 186 Tg C year⁻¹ in 1.57 million km² forests with a regression method and a kriging method, respectively. These estimates are higher than the satellite-based estimate of 1,034 Tg C year⁻¹ and almost double the estimate of 778 Tg C year⁻¹ using a process-based terrestrial ecosystem model. Cross-validation suggests that the estimates with the kriging method are more accurate. Our developed geospatial statistical models could be alternative tools to provide national-level NPP estimates to better use Chinese forest resources.     

鄱阳湖区粮食供给功能的空间格局分析

在种植制度复杂、地块破碎及多阴雨天气的南方地区,应用卫星遥感植被指数时间序列数据提取复种指数受到中低空间分辨率的限制。使用较高空间分辨率影像是提取该区域复种信息有效的数据源。论文以鄱阳湖区为研究区,通过遥感解译提取水田空间信息;在界定单/双季稻生长期物候历的前提下,根据水稻不同生长期内归一化植被指数(NDVI)的明显差异,选择合理时间窗口的TM影像获取水田NDVI数据,采用非监督分类法提取单/双季稻的空间分布信息;结合湖区乡镇不同熟制水稻单产数据估算出基于栅格的水稻产量。研究表明,4月下旬到6月下旬是判别双季早稻与单季稻空间分布的合理时间窗口;7月上旬到8月上旬及9月中旬到10上旬是判别单季稻与双季晚稻空间分布的合理时间窗口。2005年,单季稻播种面积为3 081.58 km²,晚稻/早稻播种面积为3 602.97 km²,水稻复种指数为153.9%。单季稻普遍分布在市县建成区周边,双季稻主要分布在河口三角洲等地。全年水稻总产量约1 650×10⁴ t,单季稻占30.5%,双季稻占69.5%。赣江下游地区两种熟制水稻产量均较高,而湖汊及湖区外围丘陵地区产量较低。     

MODIS 3 km气溶胶光学厚度产品检验及其环境空气质量指示

分析了MODIS C006 3 km卫星遥感气溶胶产品的算法流程,并与AERONET观测数据进行对比验证,综合新疆阿克苏地区地面空气子站1年的颗粒物质量浓度(PM10)、环境气象资料(能见度、湿度等),评估了该高分辨率气溶胶产品的精度和稳定性.分析表明,MODIS 3 km AOD与AERONET地基AOD(Issyk-Kul)的相关系数(r)达到0.8836,满足期望误差要求,但存在高估;研究区AOD和PM10存在同步变化趋势,新疆阿克苏市区2个空气子站PM10质量浓度与AOD的相关系数(r)均大于0.55,直接对比的相关性好于类似研究;经高度订正和湿度订正后AOD-PM10的相关系数和拟合优度均有所提高,标准误差和变异系数均下降,但提升并不明显.这一相关性结果与研究区本底气象环境条件有关.MODIS 3 km AOD的季平均结果表明,阿克苏地区AOD存在显著的季节性变化,春季明显高于其他季节,主要城市春季平均AOD在1.5以上,夏季和秋季AOD均值基本介于0.6~0.7之间,阿克苏市主城区夏秋季AOD季均值仍在1.0以上,反映人口集聚、城市交通工业发展等大气人为污染的增加导致AOD的增高.结果表明,MODIS C006 3 km AOD产品质量稳定,其月、季平均等长时间尺度结果有更好的空间覆盖,可满足区域环境空气质量评估的需要.     

基于RUSLE模型的延河流域2001-2010年土壤侵蚀动态变化

以黄土高原典型丘陵沟壑区--延河流域为研究区, 基于GIS和RS技术, 利用2001-2010年延河流域水文站月降雨量数据、MODIS NDVI数据、DEM数据、土壤类型数据和土地利用数据,率定了修正的通用土壤流失方程(RUSLE)的相关参数,计算了研究区2001-2010年逐年的土壤侵蚀模数, 利用杏河水文站实测的泥沙数据, 验证了模型的有效性,分析了延河流域土壤侵蚀强度的时空变化特征。结果表明,2001年到2010年延河流域土壤侵蚀模数呈减小趋势,2001年土壤侵蚀模数最大,为6 596.72 t/(km²·a),2008年土壤侵蚀模数最小,减小到2 485.46 t/(km²·a),降低62.32%;2009年由于暴雨冲刷,土壤侵蚀模数显著增大;2010年土壤侵蚀模数和2006、2007年相差不多;土壤侵蚀强度分布比例变化明显,土壤侵蚀强度为强度、极强、剧烈的面积比分别由16.21%、21.93%和12.36%降低为10.85%、4.58%和0.39%。土壤侵蚀强度等级转移矩阵表明大部分地区的土壤侵蚀强度向低一级转移,2001-2005年31.68%的面积土壤侵蚀强度降低一级,2005-2010年42.13%的面积土壤侵蚀强度降低一级。     

基于MODIS的湖南省农业干旱监测模型

诸多遥感干旱监测指数已被成功应用于中国北方地区,但在南方湿润地区的应用则相对较少。以湖南省为研究区,结合遥感(RS)、地理信息系统(GIS)技术,利用MODIS增强植被状态指数(EVCI)和温度状态指数(TCI)的复合信息,并根据EVCI和TCI对干旱信息的敏感程度不同,赋予不同的权重值,建立干旱状态指数(DCI)遥感监测模型,并将该模型应用于湖南省农作物的旱情监测,得到了湖南省耕地旱情等级的空间分布图。通过与该省97个气象台站同期获取的综合气象干旱指数(CI)的相关分析与验证,表明DCI与CI指数的线性相关显著,EVCI和TCI的权重分别取值0.4和0.6时为最佳组合,并论证了该模型适宜南方地区的干旱监测。     

Validation of MODIS aerosol retrievals and evaluation of potential cloud contamination in East Asia

MODIS aerosol retrievals onboard Terra/Aqua and ground truth data obtained from AERONET(Aerosol Robtic Network) solar direct radiance measurements are collocated to evaluate the quality of the former in East Asia. AERONET stations in East Asia are separated into two groups according to their locations and the preliminary validation results for each station. The validation results showed that the accuracy of MODIS aerosol retrievals in East Asia is a little worse than that obtained in other regions such as Eastern U.S., Western Europe, Brazil and so on. The primary reason is due to the improper aerosol model used in MODIS aerosol retrieval algorithm, so it is of significance to characterize aerosol properties properly according to long term ground-based remote sensing or other relevant in situ observations in order to improve MODIS retrievals in East Asia. Cloud contamination is proved to be one of large errors, which is demonstrated by the significant relation between MODIS aerosol retrievals versus cloud fraction, as well as notable improvement of linear relation between satellite and ground aerosol data after potential cloud contamination screened. Hence, it is suggested that more stringent clear sky condition be set in use of MODIS aerosol data. It should be pointed out that the improvement might be offset by other error sources in some cases because of complex relation between different errors. Large seasonal variation of surface reflection and uncertainties associated with it result in large intercepts and random error in MODIS aerosol retrievals in northern inland of East Asia. It remains to be a big problem to retrieve aerosols accurately in inland characterized by relatively larger surface reflection than the requirement in MODIS aerosol retrieval algorithm.     

基于MODIS数据的重庆市地表热环境效应研究

利用2000—2006年EOS/MODIS卫星资料反演的地表温度(LST)和植被指数(NDVI)资料,分析了重庆市夏季地表热场分布状况,并对重庆市夏季地表热场变化规律及成因进行了研究. 结果表明:①重庆市夏季LST分布区域特征明显,东北部LST最低,西部LST最高;2000—2003年重庆市除了中部地区LST升高外,其他地区降温明显;2003—2006年重庆市中部和西部地区LST明显升高. ②2000年以来,重庆市热岛效应明显增强,重庆市中心强热岛区(城郊温差大于8 ℃)面积由2000年的53 km2增至2006年的313 km2;城郊最高温差由2000年的10.8 ℃增至2006年的14.5 ℃. ③重庆市的LST和NDVI具有显著的负相关关系,相关系数均在-0.7以上;在植被长势较好的2000和2003年,重庆市NDVI每升高0.1,LST降低约4 ℃;而在植被长势较差的2006年,NDVI每升高0.1,LST降低约5 ℃. ④在2006年大气环流异常背景下,NDVI的急剧降低和城市热岛效应的显著增强进一步促进了重庆市高温伏旱天气的形成.      

基于多时相NDVI数据的复种指数提取方法研究

多熟种植是中国重要的种植制度,在农业生产中具有重要的地位。复种指数反映了耕地实际利用强度,及时获取其空间分布信息是国家农业决策的基础。论文在重新理解和定义复种指数的基础上,提出了一种基于NDVI曲线迭代修正的复种指数遥感提取方法,并以SPOT/VGT多时相NDVI数据为基础,提取了1999~2004年中国北方17省市区农用地的复种指数。结果表明:提取的复种指数空间分布符合我国耕作制度区划,基于目视解译的样点检验总体精度为95.24%,Kappa系数为0.9057,与根据统计数据得出的复种指数结果的线性回归斜率为0.9288（R2=0.9159,P<0.001）,表明该方法能够准确快捷地提取复种指数,及时地为农业和土地管理部门提供耕作制度的空间信息。