吕梁山地区植被物候变化及对气候的响应

吕梁山地区地形垂直差异明显,植被对气候变化反应敏感,研究吕梁山地区植被物候变化,探索植被物候变化与气候的响应关系,旨在为高海拔山区植被物候研究和生态治理提供借鉴。基于2000—2015年MODIS NDVI时间序列数据,通过动态阈值法提取吕梁山地区的植被物候,对气温、降水进行空间插值,并对植被2个关键物候期与气候因素进行偏相关分析。结果表明：（1）植被生长季开始日期(the start of the growing season,SOS)提前的区域约占85.7%,其中16.2%显著提前;植被生长季结束日期(the end of the growing season,EOS)推迟的区域约占90.6%,其中33.3%显著推迟。（2）区内74.8%、87.7%植被SOS分别与气温、降水呈负相关,气温升高或降水增加,植被SOS提前。植被SOS在高海拔山区受4月气温影响显著,而低海拔地区受4月降水影响显著。（3）区内72.6%、65.1%植被EOS分别与气温、降水呈正相关,气温升高或降水增加,植被EOS推迟。植被EOS在北部和西部地区受11月气温影响显著,而高海拔地区受9月降水影响显著。2000—2015年吕梁山地区植被物候发生显著变化,各地区对气温、降水的响应不同,研究结果可为区域物候、气候变化研究和陆地生态治理提供科学依据。     

Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau,China

Soil erosion in the Three-River Headwaters Region (TRHR) of the Qinghai-Tibet Plateau in China has a significant impact on local economic development and ecological environment. Vegetation and precipitation are considered to be the main factors for the variation in soil erosion. However, it is a big challenge to analyze the impacts of precipitation and vegetation respectively as well as their combined effects on soil erosion from the pixel scale. To assess the influences of vegetation and precipitation on the variation of soil erosion from 2005 to 2015, we employed the Revised Universal Soil Loss Equation (RUSLE) model to evaluate soil erosion in the TRHR, and then developed a method using the Logarithmic Mean Divisia Index model (LMDI) which can exponentially decompose the influencing factors, to calculate the contribution values of the vegetation cover factor (C factor) and the rainfall erosivity factor (R factor) to the variation of soil erosion from the pixel scale. In general, soil erosion in the TRHR was alleviated from 2005 to 2015, of which about 54.95% of the area where soil erosion decreased was caused by the combined effects of the C factor and the R factor, and 41.31% was caused by the change in the R factor. There were relatively few areas with increased soil erosion modulus, of which 64.10% of the area where soil erosion increased was caused by the change in the C factor, and 23.88% was caused by the combined effects of the C factor and the R factor. Therefore, the combined effects of the C factor and the R factor were regarded as the main driving force for the decrease of soil erosion, while the C factor was the dominant factor for the increase of soil erosion. The area with decreased soil erosion caused by the C factor (12.10×10³ km²) was larger than the area with increased soil erosion caused by the C factor (8.30×10³ km²), which indicated that vegetation had a positive effect on soil erosion. This study generally put forward a new method for quantitative assessment of the impacts of the influencing factors on soil erosion, and also provided a scientific basis for the regional control of soil erosion.     

青藏高原地区积雪变化及特征分析

利用我国高原地区1963-2002年的逐月积雪日数资料,以及1972-2011年的格点积雪月频率资料,分析、对比了两种资料在该地区的时空演变特征。结果表明：同时段的(1972-2002)站点资料与格点资料相比,空间分布其高值区与积雪日数增值区均偏西北,偏北程度大致为3~4°,偏西程度大致为2~3°,且中心更为明显。在青藏高原西侧(85°E以西),积雪日数呈整体下降趋势。两种资料的积雪日数EOF分析存在一定的偏差,这与其对应的空间分布差异及气候趋势空间分布存在的偏差相吻合。     

Investigation of environmental and land use impacts in forested permafrost headwaters of the Selenga-Baikal river system,Mongolia - Effects on discharge,water quality and macroinvertebrate diversity

Headwater streams play a major role for provision of ecosystem services, e.g. drinking water. We investigated a high-altitude headwater catchment of the Kharaa River (including 41 1st-order rivers) to understand the impact of land cover (especially forest cover), environment and human usage on runoff, chemical water quality and macroinvertebrate fauna in a river basin under discontinuous permafrost conditions in an arid, sparsely populated region of Mongolia. To verify our hypotheses that different landuses and environmental impacts in permafrost headwaters influence water quality, we investigated 105 sampling sites, 37 of them at intermittent stream sections without water flow. Discharge was positively impacted by land cover types steppe, grassland and forest and negatively by shrubland, forest burnt by wild fires (indicating a reduction of permafrost) and slope. Water quality was affected by altitude, longitude and latitude, shrub growth and water temperature. Shannon diversity of macroinvertebrates was driven by water temperature, iron content of the water, flow velocity, and subbasin size (adjusted R² = 0.54). Sample plots clustered in three groups that differed in water chemistry, macroinvertebrate diversity, species composition and bio-indicators. Our study confirms that steppes and grasslands have a higher contribution to runoff than forests, forest cover has a positive impact on water quality, and diversity of macroinvertebrates is higher in sites with less nutrients and pollutants. The excellent ecological status of the upper reaches of the Kharaa is severely threatened by forest fires and human-induced climate change and urgently needs to be conserved.     

基于温度植被干旱指数的兖州煤田煤炭开采影响边界遥感提取

为识别植被覆盖区煤炭开采的生态影响边界,该文以兖州煤田为研究区域,应用温度植被干旱指数TVDI(temperature vegetation drought index)反演沉陷积水区外围的土壤湿度空间分布特征,利用MATLAB拟合TVDI变化趋势并依据其趋于稳定的渐近线,反解煤炭开采活动对矿区生态的影响边界,将其与采用MSCS(mining subsidence prediction system,MSCS)软件预计获得的下沉10 mm沉陷边界进行对比。结果表明:不同距离的TVDI中位数随距积水区边缘距离的变化表现为先增加后趋于平稳、呈指数变化特征;基于TVDI分析得到的煤炭开采的非积水影响范围,仅相当于沉陷积水面积的2.07倍,预计沉陷非积水面积与预计沉陷积水面积之比为4.63倍。通过模型拟合遥感指数随距离的变化特征,能够获得煤炭开采的影响边界;兖州煤田基于TVDI获取的煤炭开采影响面积,相对小于预计的开采沉陷面积。该研究可为确定煤炭开采对生态影响的边界提供参考。     

基于Lab颜色空间的棉花覆盖度提取方法研究

基于手持高清可见光图像和无人机可见光遥感影像中植被与非植被像元在不同颜色空间单通道上分布的差异性,以苗期和蕾期的棉花为对象,进行了棉花覆盖度的提取方法研究。基于不同天气状况和不同采集时刻等光照条件下采集的29幅具有不同覆盖度的棉花地面可见光图像,分别对比分析了Lab颜色空间a通道、RGB颜色空间2G-R-B指数和HIS颜色空间H通道对棉花的识别能力,以及使用动态阈值和固定阈值两种情况下的棉花覆盖度提取精度。其中动态阈值通过植被与非植被像元的高斯分布交点确定,固定阈值在3种颜色空间分别设置为动态阈值的均值。结果表明,植被像元与非植被像元在a通道、2G-R-B指数和H通道上呈现高斯分布,可以采用非线性最小二乘算法实现高斯分布拟合。通过高斯分布拟合求解交点得到的动态分类阈值分布范围较为集中,将其均值-3.78、0.06、0.13设定为固定分类阈值。相比于2G-R-B指数和H通道,a通道对绿色植被的识别能力最好,更适合提取棉花植被覆盖度;相比于动态阈值,固定阈值的提取精度更好,平均提取误差为0.009 4。将该方法应用到无人机尺度时,同样可以较好地提取不同天气状况和不同土壤干湿类型的棉花覆盖度,且总体平均提取误差为0.012。经过初步检验和分析认为,基于植被与非植被像元在Lab颜色空间a通道上分布的差异性,结合固定分类阈值,可以精确地提取不同光照条件下的苗期和蕾期棉花覆盖度。     

基于无人机遥感影像的冬小麦氮素监测

精准氮素管理是一项提高作物氮肥利用效率的有效策略,利用无人机遥感技术精确估测小麦氮素状况是必要的。试验在山东省乐陵市科技小院实验基地进行,利用八旋翼无人机搭载Mini-MCA多光谱相机于2016年获取冬小麦4个关键生育时期(返青期、拔节期、孕穗期、扬花期)冠层多光谱数据,同步获取地上部植株样品并测定其生物量、吸氮量、氮营养指数,及成熟期籽粒产量,根据各关键生育期与全生育期分别构建植被指数与农学参数回归分析模型,评估基于无人机遥感影像的冬小麦氮素营养诊断潜力。结果表明:基于无人机遥感影像能够较好地估测冬小麦氮素指标(R2为0.45~0.96),决定系数随着生育期推移而逐渐增大。拔节期、孕穗期和扬花期估产效果接近且具有很好的估测能力,扬花期DATT幂函数模型对小麦氮营养指数的解释能力最强(R2=0.95)。因此,以多旋翼无人机为平台同步搭载多光谱相机对冬小麦有较好的氮素诊断潜力,可利用估测结果指导精准氮肥管理。     

1979—2020年杭州市富阳区土地利用对耕层土壤有机碳储量变化的影响

土地利用变化对陆地生态系统碳储量变化影响显著,在制定土地政策时,必须考虑土地利用变化对土壤碳储量的动态影响。以杭州市富阳区为研究对象,探讨了1979—2006年间土地利用变化对碳储量的影响,并预测评价了县区级土地利用规划政策对土壤碳库的影响。结果显示:研究区1979—2006年间土地利用变化导致全区植被碳总量损失为273.4 Gg,表层土壤(0—20 cm)有机碳总量损失为771.0 Gg,建设占用耕地和林地是导致土壤碳储量下降的主要原因。预测2006—2020年间研究区植被碳损失的年均速率将减至25.93 kg·hm^-2,土壤有机碳损失的年均速率将减至27.48 kg·hm^-2。制定合理政策和有效措施来保护林地,抑制建设用地增长,扭转土壤碳损失趋势势在必行。     

基于时序NDVI图谱库提高土地覆盖分类精度的方法

为提高MODIS土地覆盖产品的分类精度,该文以河南省为试验区,首先将MODIS土地覆盖产品(MCD12Q1)分为高精度区域和低精度区域,然后通过构建时序NDVI图谱库并利用图谱曲线相似性测定方法,改进MCD12Q1低精度区域的分类精度。结果表明:1)时序NDVI是土地覆盖的重要分类特征,二者之间具有较强的关联性。2)利用时序NDVI图谱库能够明显提高MODIS土地覆盖产品的分类精度,改进后的MCD12Q1的总体分类精度分别由72.76%(比较评价)、64.52%(样本评价)提高到83.05%和81.72%。3)不同土地覆盖类别精度提高的程度不同,林地、草地、耕地、人工地表以及水体的生产者精度分别提高35.36%、29.51%、2.98%、6.96%和6.11%。4)对于判定时序NDVI曲线相似度的2种具体方法而言,最小距离法(minimum distance,MD)总体上优于光谱角度匹配法(spectral angle mapper,SAM)。综上,保留现有土地覆盖产品中分类精度较高的部分,基于时序NDVI图谱库改进分类精度较低的部分,是提高现有土地覆盖产品分类精度的有效方法。     

饲草作物对土壤健康与农业可持续发展的作用

饲草作物是指为增加土壤肥力,防止土壤侵蚀,累积和保护土层,增加土壤养分和含水率以及提高土壤质量而种植的植物。饲草作物为农田土壤提供了诸多益处,其还有助于增加和维持土壤中的微生物多样性。本文对多种饲草作物对土壤特性的作用,如土壤含水量、土壤微生物的活动、土壤碳固存、土壤硝态氮淋失、土壤水分和土壤健康等进行综述。饲草作物的选择通常取决于其自身对土壤的作用,其他考虑因素还包括天气条件,播种时间,是否为豆科植物以及杀灭饲草作物的时间和方法。研究表明,饲草作物也可用于减缓气候变化,抑制作物中的杂草,增加可交换的营养物质如Mg2+和K+,具有一定的经济性。另外,覆盖作物也会存在一些问题,包括杀灭覆盖作物的方法,其可能成为病原体的寄主,饲草作物的再生性以及短期收益不明显。尽管有一些局限,饲草作物仍被认为可以明显改善土壤整体健康状况,为主栽作物提供可持续的生态环境。