基于遥感技术的矿山生态修复调查研究——以冀东铁矿为例

为科学推进矿山生态修复,依托高分辨率遥感数据精度优势,融合传统地质调查工作特点,厘清现有技术方法适用范围,提出基于遥感技术的矿山生态修复调查方法协作方式。以河北省唐山市冀东铁矿为例,实现矿山生态修复调查典型案例示范。研究表明:以"人机交互解译技术""面向对象信息提取技术""三维景观模拟技术"等方法手段为主体、以野外调查验证为辅助的矿山生态修复调查工作协作方式,可实现对矿山露天采场内独立地物与关键要素的精准识别、快速提取,辅之野外调查验证,进而完成对矿山地质安全隐患、土地损毁、生态退化等现状摸底。调查结果既可作为生产矿山"边开采、边治理"的工作依据,也可作为闭坑矿山生态修复的重要参考。

东西伯利亚地区植被对气温和降水交互作用的定量化响应

Significant changes to the world’s climate over the past few decades have had an impact on the development of plants.Vegetation in high latitude regions,where the ecosystems are fragile,is susceptible to climate change.It is possible to better understand vegetation’s phenological response to climate change by examining these areas.Traditional studies have mainly investigated how a single meteorological factor affects changes in vegetation phenology through linear correlation analysis,which is insufficient for quantitatively revealing the effects of various climate factor interactions on changes in vegetation phenology.We used the asymmetric Gaussian method to fit the normalized difference vegetation index(NDVI)curve and then used the dynamic threshold method to extract the phenological parameters,including the start of the season(SOS),end of the season(EOS),and length of the season(LOS),of the vegetation in this study area in the Tundra-Tagar transitional zone in eastern and western Siberia from 2000 to 2017.The monthly temperature and precipitation data used in this study were obtained from the climate research unit(CRU)meteorological dataset.The degrees to which the changes in temperature and precipitation in the various months and their interactions affected the changes in the three phenological parameters were determined using the GeoDetector,and the results were explicable.The findings demonstrate that the EOS was more susceptible to climate change than the SOS.The vegetation phenology shift was best explained by the climate in March,April,and September,and the combined effect of the temperature and precipitation had a greater impact on the change in the vegetation phenology compared with the effects of the individual climate conditions.The results quantitatively show the degree of interaction between the variations in temperature and precipitation and their effects on the changes in the different phenological parameters in the various months.Understanding how various climatic variations effect phenology changes in plants at different times may be more intuitive.This research provides as a foundation for research on how global climate change affects ecosystems and the global carbon cycle.

东西伯利亚苔原-泰加林过渡带植被遥感物候时空特征及其对气温变化的响应

Phenology is an important indicator of climate change.Studying spatiotemporal variations in remote sensing phenology of vegetation can provide a basis for further analysis of global climate change.Based on time series data of MODIS-NDVI from 2000 to 2017,we extracted and analyzed four remote sensing phenological parameters of vegetation,including the Start of Season(SOS),the End of Season(EOS),the Middle of Season(MOS)and the Length of Season(LOS),in tundra-taiga transitional zone in the East Siberia,using asymmetric Gaussian function and dynamic threshold methods.Meanwhile,we analyzed the responses of the four phenological parameters to the temperature change based on the temperature change data from Climate Research Unit(CRU).The results show that:in regions south of 64°N,with the rise of temperature in April and May,the SOS in the corresponding area was 5-15 days ahead of schedule;in the area between 64°N and 72°N,with the rise of temperature in May and June,the SOS in the corresponding area was 10-25 days ahead of schedule;in the northernmost of the study area on the coast of the Arctic Ocean,with the drop of temperature in May and June,the SOS in the corresponding area was 15-25 days behind schedule;in the northwest of the study area in August and the southwest in September,with the drop of temperature,the EOS in the corresponding areas was 15-30 days ahead of schedule;in regions south of 67°N,with the rise of temperature in September and October,the EOS in the corresponding area was 5-30 days behind schedule;the change of the EOS in autumn was more sensitive to the change of the SOS in spring,because the smaller temperature fluctuation can cause the larger change of the EOS;the growth season of vegetation in the study area was generally moving forward,and the LOS in the northwest was shortened,while the LOS in the middle and south of the study area was prolonged.

MODISEVI时序数据重建方法及拟合分析

植被遥感监测中长时间序列数据择优的重建方法,已成为当今一个研究热点。本文以东北地区5种主要植被覆盖类型为例,在定性分析TIMESAT提供的3种常用重建方法对EVI(Enhanced Vegetation Index)时序曲线重建效果的基础上,定量对比研究了各方法,对原始高质量EVI点真实值的保真性,及对原始曲线整体特征的保持度。结果表明:S-G(Savitzky-Golay)滤波对原始曲线生长季的峰值及宽度重建效果较好,但容易因过度拟合保留过多噪声,特别是草地和灌丛类型;非对称性高斯函数(AG)和双Logistic曲线(DL)方法相似,对草地、灌丛和耕地的重建结果更接近真实值,但AG拟合对波峰处异常值的处理结果较差,重建后波峰表现低平。3种算法对原始EVI时序数据的保真性和对原始时序数据曲线特征的保持度,都表现出与植被类型分布相关的空间分布格局。分析结果表明,在东北地区,AG算法对草原和灌丛的重建效果最好,DL算法对耕地重建效果最优,S-G算法最适合对落叶阔叶林和落叶针叶林进行重建处理。

东西伯利亚苔原—泰加林过渡带植被遥感物候时空特征及其对气温变化的响应

物候变化是气候变化的重要指示器,通过对植被物候时空变化的研究可以为进一步分析全球气候变化提供依据。基于2000—2017年MODIS-NDVI时间序列数据,利用不对称高斯函数和动态阈值法,提取、分析了东西伯利亚苔原—泰加林过渡带植被生长季起始期(SOS)、结束期(EOS)、中期(MOS)和长度(LOS)4种植被遥感物候参数的时空变化格局。同时结合同期CRU(Climate Research Unit)气温观测数据,分析了4种物候参数对气温变化的响应关系。结果表明:遥感物候参数可以直接、有效地反映气温的变化:研究区64°N以南区域4—5月气温升高,对应区域SOS提前5~15 d;64°N~72°N之间5—6月气温升高,对应区域SOS提前10~25 d;最北端北冰洋沿岸6月气温升高幅度较小且7月气温降低,对应区域SOS推后15~25 d;西北部8月、西南部9月气温降低,对应地区EOS提前15~30 d;67°N以南区域9—10月气温升高,对应区域EOS推后5~30 d;EOS的变化对气温变化较SOS更为敏感,较小的气温波动即引起EOS较大的变动;研究区内植被生长季整体呈前移趋势,且西北部LOS缩短,中部、南部LOS延长。