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China Forestry Science Academe (2007)

Mechanism and Methodology for Sandy Land Monitoring Using Remote Sensing

王晓慧;

Titre : Mechanism and Methodology for Sandy Land Monitoring Using Remote Sensing

Auteur : 王晓慧;

Grade : Doctoral Dissertation 2007

Université : China Forestry Science Academe

Résumé
China is one of the most serious countries in the world which is suffering from landsandification. The velocity of sandification now is slower than that in the 1990s, and the trend ofsandy land expansion in the whole country has been controlled, however, the areas of sandylands are still expanding in some regions and the whole situation of sandification is still serous.It is a long and arduous task to take the powerful measure for combating sandification.Since 1994 China has implemented three monitoring projects of the national sandificationto aware the types, degrees, areas, distributions and changes of sandy lands, analyze the reasonof dynamics, and provide reliable foundation for macroscopical decision making ofsandification combation. Remote sensing has played an active role in the national sandificationmonitoring. Based on the great information amount, large observation extent, high precisionand quick velocity of remote sensing, it will be more beneficial to successfully implementsandification monitoring to further disscuss the techniques, theories and methods ofsandification monitoring using remote sensing and strengthen the analyse and evaluation ofsandification monitoring results.The paper systematically analyzed the current research situation and trend of sandy landmonitoring using remote sensing at home and abroad, taking Dengkou County of InnerMogolia for example, and Minqin County of Gansu Province and Gonghe County of QinghaiProvince involved, disscussed the rules of spectral characteristics of sandy lands, establishedthe technical system of information extraction and change detection of sandy lands, andanalyzed the dynamic, landscape pattern and grain effect to reveal the process and rule ofsandy land evolvement. The paper deeply understood sandy land monitoring mechanisms usingremote sensing, solved the problems of the large extent, time and energy consuming, increasedthe efficiency of information collection, strengthened the acquaintance ability of sandy landevolvement, and provided the technical support for decision making of sandification combation.The paper has obtained several achievements as follows.(1) Spectral characteristics of sandy lands. Using the spectral instrument of ASD, the fieldspectra of main indicators of sandification process, various surface coverage types and various degrees of sandy lands were measured. The quantitative relationship of spectral characteristicsand sandification was established, the spectral variability rule was found, and the criteria wasprovided for classifying and quantitative analyzing sandy lands in the respect of spectrum. Itwas brought forward that two types of surface features including single surface features,namely various vegetation types and soil types, and compound surface features, namely sandyland with various vegetation coverages and salina with various degrees were measured bydifferent spectral sampling methods. The analyses of spectral characteristics showed thatspectral data of sandy lands changed with vegetation coverage, vegetation type, soil, landcover,etc. With the increasing vegetation coverage, the reflectances of sandy lands decreased.Affected by vegetation and soil moisture, the reflectances in the spectrum of 1300~2500nmwere lower than that in the spectrum of 750~1300nm, the reflectance diffence of sandy landswith different vegetation coverages increased.(2) Information extraction of sandy land. The multi-layer information extraction methodof sandy lands was developed. Sandy lands were first extracted, and then the degrees of sandylands were classified. Using multi-temporal Landsat ETM+images, overrating and underratingsandy lands were avoided. Based on image and spectral characteristic analyses, knowledgeswere introduced using multi-layer extraction method with different formats in different layersto simplify the relationship between various land types, clarify the layer relationship betweenvarious layers during classification process, and realize the separation of sandy lands and otherlands. The basic criteria of sandy land classification was vegetation coverage, detailedly that inclassification standard of the national desertification investigation. By regression models ofNDVI and vegetation coverage, sandification degrees were divided with the thresholds ofNDVI, and the method was an effective way to evaluate sandy land degrees.(3) Change detection of sandy land. To quickly detect the extension or reversion of sandylands, the hybrid method of principal component analysis and supervised classification wasadopted to detect sandy land changes in ten years using two dates of Landsat ETM+/TMimages with principal component analysis producing change areas and supervised classificationproviding detailed change types. It could identify the extension or reversion of sandy lands andprovide scientifica basis for adopting control measures. It also benefited to sandy land mapupdating. Based on the current baseline classification map, the change area was classified to avoid a great lot of labours of field investigation and validation, reduce workload, and increasethe work efficiency. Combination method of multi-time and multi-band in principal componentanalysis was adopted.

Mots clés : Sandy land; remote sensing monitoring; spectral analysis; information extraction; change detection; dynamics; landscape analysis; grain effect;

Présentation (CNKI)

Page publiée le 8 janvier 2018