本数据为2019年咸海植被调查数据集。包括：植被照片、植被调查表。植被调查表中包含样点编号、样方编号、样方大小、航点、地理位置信息、物种名称、种群数量、长轴、短轴、高度、冠幅、分盖度和总盖度。22个采样点，40幅植被照片，以植物近景和景观远景照片为主，反映咸海周边植被覆盖情况。
", "ds_source": "2019年咸海野外调查数据。
", "ds_process_way": "首先，在野外调查阶段，根据预设的样点布设方案，使用GPS定位样点位置，记录样点编号和航点信息，并在每个样点内设置标准大小的样方（如3m×3m、10m×10m或20m×20m），详细记录样方编号和样方大小；在样方内，逐一识别并记录物种名称，测量种群数量、植株的长轴、短轴、高度和冠幅，计算分盖度和总盖度，确保数据采集的准确性和完整性；同时，拍摄植被近景和景观远景照片，记录植被覆盖情况和样方环境特征。野外调查结束后，将所有纸质记录数据统一整理，核对样点编号、样方编号和测量数据，确保无遗漏或错误；将物种名称与标准植物名录进行比对，确保命名准确；将测量数据录入电子表格，进行标准化处理，如统一单位、填补缺失值和处理异常值；对照片进行分类整理，按样点编号和拍摄内容命名，便于后续分析。最后，将整理后的数据与地理位置信息进行匹配，生成完整的植被调查数据集，并备份保存，确保数据安全和可追溯性。整个加工过程严谨规范，确保了数据的准确性和可用性，为后续分析和研究提供了可靠基础。
", "ds_quality": "数据采集过程规范，信息完整且无缺失，样方大小和测量指标符合标准，物种名称准确，种群数量、长轴、短轴、高度和冠幅等测量数据经过多次核对，确保精度可靠；照片拍摄角度和光线条件适宜，能够直观展示植被特征，与调查表数据相互印证；所有数据均经过统一整理和标准化处理，样点编号和航点信息与地理位置信息一一对应，数据格式规范，便于后续分析和应用；综合来看，本数据集质量可靠，信息全面，能够为咸海周边植被研究提供科学依据。
", "ds_acq_start_time": "2019-01-01 00:00:00", "ds_acq_end_time": "2019-12-31 00:00:00", "ds_acq_place": "咸海", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 124473995, "ds_files_count": 2, "ds_format": ".jpg格式和 .xlsx格式", "ds_space_res": "无", "ds_time_res": "无", "ds_coordinate": "无", "ds_projection": "无", "ds_thumbnail": "4bb2ba77-59a7-41fd-a0c3-daf05eff416b.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "180.51" ], "quality_level": 1, "publish_time": "2025-05-06 13:48:55", "first_publish_time": null, "last_updated": "2025-05-27 18:59:48", "protected": false, "protected_to": null, "lang": "zh", "cstr": "33110.11.ariddc.00153", "license": null, "extra": null, "files_shape": [ { "name": "南咸海植被调查2019.xlsx", "size": 95586, "is_dir": false }, { "name": "植被调查照片.rar", "size": 124378409, "is_dir": false } ], "features": null, "data_level": 0, "i18n": { "en": { "title": "2019 Aral Sea vegetation survey data", "ds_abstract": "This data is the 2019 Aral Sea vegetation survey dataset. Including: vegetation photos, vegetation questionnaires. The vegetation questionnaire includes sample point number, sample number, sample size, navigation point, geographical location information, species name, population number, long axis, short axis, height, crown width, coverage and total coverage. There were 40 vegetation photos at 22 sampling points, mainly close-up plant and long-term landscape photos, reflecting the vegetation coverage around the Aral Sea.
", "ds_source": "2019 Aral Sea field survey data.
", "ds_process_way": "First, during the field investigation stage, according to the preset sample point layout plan, GPS is used to locate the sample point locations, record the sample point numbers and waypoint information, and set a standard size sample square within each sample point (such as 3m×3m, 10m×10m or 20m×20m), record the plot number and plot size in detail; within the plot, identify and record the species names one by one, measure the population number, plant long axis, short axis, height and crown width, calculate the coverage and total coverage to ensure the accuracy and integrity of data collection; At the same time, take close-up vegetation and long-term landscape photos to record the vegetation coverage and the environmental characteristics of the plot. After the field investigation, all paper record data will be organized uniformly, and the sample point numbers, sample square numbers and measurement data will be checked to ensure that there are no omissions or errors; the species names will be compared with the standard plant list to ensure accurate naming; The measurement data will be entered into spreadsheets for standardization, such as unifying units, filling in missing values and handling abnormal values; the photos will be sorted out and named according to the sample point numbers and shooting content to facilitate subsequent analysis. Finally, the compiled data is matched with geographical location information to generate a complete vegetation survey data set, and backup it and save it to ensure data security and traceability. The entire processing process is rigorous and standardized, ensuring the accuracy and availability of data and providing a reliable basis for subsequent analysis and research.
", "ds_quality": "The data collection process is standardized, the information is complete and without missing, the sample size and measurement indicators meet the standards, the species name is accurate, and the measurement data such as population number, long axis, short axis, height and crown width have been checked many times to ensure reliable accuracy; The photo shooting angle and light conditions are suitable, which can visually display the vegetation characteristics and verify each other with the questionnaire data; All data has been uniformly organized and standardized. The sample point numbers and waypoint information correspond one-to-one to geographical location information. The data format is standardized to facilitate subsequent analysis and application. Overall, this dataset is of reliable quality and comprehensive information, which can provide scientific basis for research on vegetation around the Aral Sea.
", "ds_acq_place": "Aral Sea", "ds_format": ".jpg format and.xlsx format", "ds_projection": "no", "ds_space_res": "no", "ds_time_res": "no" } }, "license_type": null, "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "高度", "盖度", "种群", "植被" ], "ds_subject_tags": [ "植物学" ], "ds_class_tags": [], "ds_locus_tags": [ "咸海" ], "ds_time_tags": [ 2019 ], "ds_contributors": [ "郑新军", "刘铁" ], "ds_meta_authors": [ "李锦", "郑新军" ], "ds_managers": [ "刘铁" ], "category": "生态环境" }