基于遥感光谱的干旱区土地退化评价体系构建

干旱区土地退化(荒漠化)作为全球面临生态环境挑战之一,对粮食安全、环境质量和区域自然资源管理至关重要。土地退化本质是人与自然因素协同作用下土地利用/覆被类型、数量、结构以及功能的改变而引起的生态服务价值降低,核心是土壤和植被的退化。一方面,人与自然共同作用下的土地利用覆被可以表征土地退化状态,另一方面植被-土壤生境时间序列相互作用过程进一步辅助土地退化过程诊断。因此,该文首先从覆被结构、退化类型和退化程度3个层次建立干旱区土地退化状态评价体系。其次,采用GF-1/WFV时间序列遥感影像,基于多端元光谱混合分解模型建立土地利用/覆被精细分类量化表征下垫面质量属性,并进一步利用植被-生境组分互动特征参数进行功能量化,综合评价民勤2015年退化类型和退化程度。最后,结合地面立地景观照片以及采样点实测数据,对土地退化状态评价结果进行绝对定标和交叉验证。结果表明:遥感评价识别土地退化类型和程度的能力分别为87.5%和78.7%。对于民勤旱地系统,沙化过程、沙-盐化过程是主要的土地退化过程,轻度沙化、中度沙化为主导退化程度。该方法为宽波段遥感国产高分1号卫星在旱地系统土地退化状态信息提取和深入应用提供科学依据和实证研究。

Establishment of land degradation assessment system in arid region based on remote sensing spectrum

Land degradation (desertification) in arid region, as one of the global ecological challenges, is crucial to food security, environmental quality and regional natural resource management. Fortunately, the development of remote sensing technology greatly improves the ability of land degradation information extraction and assessment, which can effectively reveal conditions of land degradation in arid region and provide the scientific basis for land degradation trend prediction and formulating the corresponding preventing measures. In fact, the essence of land degradation is the decrease of ecological service following the change of type, quantity, structure and function of land use/cover which emerges from interactions of the coupled human-environment (H-E) factors at multiple spatio-temporal scales, leading the difficulty of classification and assessment. This prompts an attempt to reduce the complexity of the assessment by identifying a limited suite number of processes and variables which makes the problem tractable at particular scale like the interaction process of soil and vegetation, the core of the degradation. Based the standard spectral endmember space of GF-1 satellite, this paper innovatively established three levels evaluation system of land degradation state in arid areas, including land use/cover structure, degradation type and degradation degree. Secondly, we realized dryland multi-temporary linear spectral mixture analysis. The remote sensing images of GF-1/WFV endmember fractions time series were applied to characterize the quality attributes of the underlying surface and organize the classification knowledge, and then to complete the fine land cover/use classification of Minqin county in 2015. Based on land use/cover mapping in arid region, the time series EMs including vegetation (GV), sand land (SL), saline land (SA), dark surface (DA) were combined to obtain and express the variables reflecting the ecosystem function, and then, were organized with decision tree (DT) for degradation state mapping. Finally, the results of land degradation state were assessed using photos of the site landscape and the measured data of the sampling sites. The results showed that: 1) The MESMA method could decompose four stable EMs types, which were consistent with the physical components of the surface cover in study area. The model could effectively simulate the spectral information of study area. More importantly, it solved the problem that the bands number of GF-1 WFV was few and the information mining was insufficient. And which provides a basis for establishing knowledge for decision tree classification and assessment. 2) The time series EMs in standard spectral endmember space could perfectly highlight the temporal interaction characteristics details between vegetation types and habitat and the ability of remote sensing to identify land degradation types and degree, with corresponding accuracy of 87.5% and 78.7%, respectively. 3) For Minqin, a typical dryland system, the sandification process and the sand-salinization process were the dominant land degradation processes. Light sandification and moderate sandification were the dominant degradation degrees. Through the relative evaluation results of land degradation types and degree, it helps divide the key control areas, ecological conservation areas and the use of decompression areas. The research result contributes to the sustainable development of regional management and control of ecological fragile areas, land space development and ecological environment protection. General remote-sensing technical framework for land degradation assessment was confirmed that it have the potential to be applied to the study of land degradation assessment in arid regions across time and regions.