Phenological Dataset for Ecological Forecasting
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We present a harmonized phenology dataset from multiple sources organized as follows: Phenology data from ground monitoring (ground_phenology_dataset_22062025.csv) Traditional ecological knowledge of species phenology (tek_phenology_dataset_25062025.csv) Phenocam derived phenology (rbg_index_phenocam_22062025.csv) Citizen-science label-a-thon (phenopulse_events_classification_22062025.csv) Climate data (climate_dataset_26062025.csv) Satellite images derived phenology (provided at https://data.4tu.nl/ using the same doi 10.5281/zenodo.15704554) Metadata that describes columns in each datset is presented below. 1. Phenology data from ground monitoring (ground_phenology_dataset_22062025.csv) Variable name Description Type Range 1 forest_id Name of forest site Categorical Bobiri – Bobiri forest reserve; BFMS – Boabeng Fiema Monkey Sanctuary 2 plot_id Plot number Categorical Plot 1 Plot 2 3 tag_number Unique number linked to each liana or tree individual monitored in the plots Numerical 1001-3518 4 species_name_worldflora Scientific names of species of tagged tree and lianas from worldfloraonline.org Categorical 5 family Name of higher order taxonomic family to which the plant belongs. Categorical 6 life_form Stem habit of the plant Categorical Tree Liana 7 flower_present Presence of flowers on plant individual. Binomial Yes No 8 flower_phase Phase of flower phenology observed. Categorical Closed buds First bloom (25% of flowers open) Mid bloom (50% of flowers open) Late bloom (75% of flowers open) End bloom (all flowers open) NA - no data 9 fruit_present Presence of fruits on plant individual. Binomial Yes No 10 fruit_phase Phase of fruit phenology observed. Categorical Fruit set (fruit formed) Fruit development (fruit growing) Fruit maturation (fruit mature) Fruit ripening (ripe fruit) Fruit aging (overripe or drying fruit) Fruit fall NA - no data 11 fruit_formed Fruit set Binomial No – 0 Yes – 1 NA - no data 12 fruit_growing Growing fruit but not of maturity yet. Binomial No – 0 Yes – 1 NA - no data 13 fruit_mature Matured fruits Binomial No – 0 Yes – 1 NA - no data 14 fruit_ripe Ripe fruit (often changing colouration or scent) Binomial No – 0 Yes – 1 NA - no data 15 fruit_aging Over ripe or drying fruit Binomial No – 0 Yes – 1 NA - no data 16 fruit_fall Fruits fall seen on forest floor. Binomial No – 0 Yes – 1 NA - no data 17 leaf_present Presence of leaves on plant individual. Binomial Yes No 18 leaf_phases Phase of leaf phenology observed. Categorical Bud swelling (closed bud) Leaf unfolding (bud opening) Leaf expansion (new leaf) Mature leaf Leaf coloured Leaf fully coloured Leaf fall NA - no data 19 closed_leaf_bud Bud swelling (closed bud) Binomial No – 0 Yes – 1 NA - no data 20 open_leaf_bud Leaf bud unfolding (bud opening) Binomial No – 0 Yes – 1 NA - no data 21 new_leaf Leaf expansion (new leaf) Binomial No – 0 Yes – 1 NA - no data 22 mature_leaf Mature leaf Binomial No – 0 Yes – 1 NA - no data 23 leaf_coloured Leaf colouration onset (browning, yellowing or other signs of senescence onset) Binomial No – 0 Yes – 1 NA - no data 24 leaf_fully_coloured Leaf fully coloured (fully brownish or yellowish or othe colours of leaf senescence) Binomial No – 0 Yes – 1 NA - no data 25 leaf_fall Leaf fall on forest floor (leaf shedding) Binomial No – 0 Yes – 1 NA - no data 26 tree_crown_visible Visibility of tree crown from forest floor. Categorical Fully visible Partially visible Not visible NA - no data 27 date Week in which data was collected (DD/MM/YYYY) date 17-07-2024 to 16-06-2025 (48 weeks) 28 parent_index Unique code that links observation to original record on koboform Numeric 1485-1649 2. Traditional ecological knowledge (tek) of species phenology (tek_phenology_dataset_25062025.csv) Variable Description Type Range 1 forest Name of forest near respondent Categorical Boabeng Fiema Monkey Santuary Bobiri Forest Reserve 2 community Respondent’s community of residence Categorical Boabeng Bonte Tankor Kokrompe Fiema Bomini Dwabenema Kubease Krofofrom Duapompo NA - no community selected 3. Respondent_age Age of respondent interviewed Continuous Above 60 51 - 60 18 - 30 41 - 50 31 - 40 NA - no age selected 4 Gender Respondent’s gender identity Categorical Male Female 5 Community_stay Years lived in the community Categorical 1-2 years, 3-5 years, 6-10 years, 11-20 years, above 20 years 6 Primary profession/occupation Respondent's main livelihood or occupation Farmer Other Artisan Trader NA - no profession selected 7 Respondents Unique respondent number Categorical 8 Plant_list Plants respondent knows from the list provided. Local name provided in parenthesis. Nominal 9 month Month and associated phenophase (e.g. jan_nl means occurrence of new leaf in January) Categorical New leaves - nl; Leaf shedding - ls; Flowering - fl; Fruiting - fr 10 count Response whether or not the phenophase for the species occurs the month specified. Categorical 0 - No, 1 - Yes 3. Phenocam derived phenology (rbg_index_phenocam_22062025.csv) Variable name Description Type Range/Format 1 file File address and file name. Filename is an id made of site name, plot number, camera number, date and time image was captured. Nominal siteid_YYYY_MM_DD_HHMMSS.JPG 2 time Time on the filename Date DD/MM/YYYY 3 red Mean values from red colour channel Numeric 4 green Mean values from green colour channel Numeric 5 blue Mean values from blue colour channel Numeric 6 rcc Red Chromatic Coordinates (RCC) = RDN/(RDN+GDN+BDN), where DN are average digital numbers within ROI. Numeric 7 gcc Green Chromatic Coordinates (GCC) = GDN/(RDN+GDN+BDN), where DN are average digital numbers within ROI. Numeric 8 bcc Blue Chromatic Coordinates (BCC) = BDN/(RDN+GDN+BDN), where DN are average digital numbers within ROI. Numeric 9 rcc.std Standard deviation for rcc in ROI. Numeric 10 gcc.std Standard deviation for gcc in ROI. Numeric 11 bcc.std Standard deviation for bcc in ROI. Numeric 12 rcc05, rcc10, rcc25, rcc50, rcc75, rcc90, rcc95 5, 10, 25, 50, 75, 90 and 95 percentiles derived for each red chromatic coordinate across the entire ROI Numeric 13 gcc05, gcc10, gcc25, gcc50, gcc75, gcc90, gcc95 5, 10, 25, 75, 90 and 95 percentiles derived for each green chromatic coordinate across the entire ROI Numeric 14 bcc05, bcc10, bcc25, bcc50, bcc75, bcc90, bcc95 5, 10, 25, 75, 90 and 95 percentiles derived for each blue chromatic coordinate across the entire ROI Numeric 15 brightness The maximum pixel value for red, green and blue channels. Numeric 16 darkness The minimum pixel value for red, green and blue channels. Numeric 17 contrast The difference between brightness and darkness. Numeric 18 grR green/red ratio Numeric 19 rbR red/blue ratio Numeric 20 gbR green/blue ratio Numeric 21 GRVI green-red vegetation index (GRVI = G-R/G+R) Numeric 22 exG excess greenness (exG = 2G - R- B) Numeric 4. Citizen-science label-a-thon (phenopulse_events_classification_22062025.csv) Variable name Description Type Range/Format 1 user_id Unique number for each image labelling volunteer Numeric classification_id Unique number for each image label classification Numeric 2 workflow_name The name of labeling task on zooniverse Categorical Leafing events, Flowering events, Fruiting events created_at Date and time classification was created. date 3 annotations Labeling task executed on image file. String 4 subject_data Information on subject of task, e.g., time subject was created, time subject was retired. String 5 filename An id made of site name, plot number, camera number, date and time image was captured. Nominal siteid_YYYY_MM_DD_HHMMSS.JPG 6 event_values Label applied to subject by volunteer/labeler. May also includes coordinates for polygons drawn on the image by labeler. Categorical Leafing events: New leaves, Mature leaves, Dry leaves, Leaf shedding Flowering events: Yes, No, circle polygons Fruiting events: Yes, No, triangle polygons. NA - no data 5. Climate data (climate_dataset_26062025.csv) Variable Description Unit/format 1 Date Date the values of climate variables were logged. Day, month, year 2 Time Time of observation hour, minute, second 3 Wind_Speed Average horizontal wind speed measured at sensor height above the ground m/s 4 Gust_Speed Maximum wind speed (gust) detected during each measurement interval m/s 5 Wind_Direction Compass direction from which the wind originates ° 6 Prec Total accumulated precipitation recorded during the sampling interval mm 7 Temp Ambient air temperature measured at the sensor height °C 8 RH Percentage of water vapor present in the air relative to the maximum it can hold at a given temperature % 9 Dew_Point The temperature at which air becomes saturated and water vapor condenses into dew °C 10 Site Name of the location where the Automatic Weather Station (AWS) is installed. Text (BFMS - Boabeng Fiema Monkey Sanctuary; BFR - Bobiri Forest Reserve) 11 Month Calendar Month of the observation in number form Integer (1-12) 12 Year Calendar Year of the observation Integer (2024, 2025) 13 Season Climatic season classification, useful for ecological and phenological analysis Text (Dry, Wet) 14 CumRain Daily Cumulative Rainfall mm 15 Dry Binary indicator flag where 1 indicates a dry day with exactly 0 mm of precipitation (Prec == 0), and 0 indicates a wet day with rainfall greater than 0 mm Boolean (1 = dry, 0 = wet) 6. Satellite images derived phenology (provided at https://data.4tu.nl/ using the same doi 10.5281/zenodo.15704554)
本研究发布了一套多源整合的物候（Phenology）数据集，结构如下： 1. 地面监测物候数据（ground_phenology_dataset_22062025.csv） 以下为各数据集的列元数据说明： ### 地面监测物候数据（ground_phenology_dataset_22062025.csv） | 序号 | 变量名 | 描述 | 类型 | 取值范围 | |------|--------|------|------|----------| | 1 | forest_id | 森林站点名称 | 分类变量 | Bobiri – 博比里森林保护区（Bobiri Forest Reserve）；BFMS – 博阿本格·菲玛猴子保护区（Boabeng Fiema Monkey Sanctuary） | | 2 | plot_id | 样地编号 | 分类变量 | Plot 1、Plot 2 | | 3 | tag_number | 样地内监测的藤本或树木个体的唯一编号 | 数值型 | 1001-3518 | | 4 | species_name_worldflora | 来自worldfloraonline.org的标记树木与藤本的物种学名 | 分类变量 | - | | 5 | family | 植物所属的高级分类科名称 | 分类变量 | - | | 6 | life_form | 植物的茎生长型 | 分类变量 | 乔木（Tree）、藤本（Liana） | | 7 | flower_present | 植株是否具花 | 二项分类 | 是、否 | | 8 | flower_phase | 观测到的花物候阶段 | 分类变量 | 闭合花苞、初花（25%花朵开放）、盛花中期（50%花朵开放）、晚花（75%花朵开放）、终花（全部花朵开放）、NA - 无数据 | | 9 | fruit_present | 植株是否具果 | 二项分类 | 是、否 | | 10 | fruit_phase | 观测到的果物候阶段 | 分类变量 | 坐果（果实形成）、果实发育（果实生长）、果实成熟、果实完熟、果实衰老（过熟或干枯）、落果、NA - 无数据 | | 11 | fruit_formed | 坐果情况 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 12 | fruit_growing | 果实正在生长但未成熟 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 13 | fruit_mature | 果实已成熟 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 14 | fruit_ripe | 果实已完熟（通常伴随颜色或气味变化） | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 15 | fruit_aging | 果实过熟或干枯 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 16 | fruit_fall | 林地表层可见落果 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 17 | leaf_present | 植株是否具叶 | 二项分类 | 是、否 | | 18 | leaf_phases | 观测到的叶物候阶段 | 分类变量 | 花苞膨大（闭合叶芽）、叶片展开（芽体开放）、叶片扩展（新叶）、成熟叶、叶色变化、叶色完全转变、落叶、NA - 无数据 | | 19 | closed_leaf_bud | 叶芽闭合（花苞膨大阶段） | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 20 | open_leaf_bud | 叶芽展开（芽体开放阶段） | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 21 | new_leaf | 叶片扩展（新叶阶段） | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 22 | mature_leaf | 成熟叶 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 23 | leaf_coloured | 叶色变化启动（褐变、黄化或其他衰老起始迹象） | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 24 | leaf_fully_coloured | 叶色完全转变（完全褐变、黄化或其他叶片衰老色） | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 25 | leaf_fall | 林地表层可见落叶 | 二项分类 | 否 – 0、是 – 1、NA - 无数据 | | 26 | tree_crown_visible | 从林地表层可见的树冠情况 | 分类变量 | 完全可见、部分可见、不可见、NA - 无数据 | | 27 | date | 数据采集周（格式为DD/MM/YYYY） | 日期型 | 2024-07-17至2025-06-16，共48周 | | 28 | parent_index | 将观测链接至koboform原始记录的唯一代码 | 数值型 | 1485-1649 | 2. 传统生态知识（Traditional Ecological Knowledge, TEK）物种物候数据（tek_phenology_dataset_25062025.csv） | 序号 | 变量名 | 描述 | 类型 | 取值范围 | |------|--------|------|------|----------| | 1 | forest | 受访者附近的森林名称 | 分类变量 | 博阿本格·菲玛猴子保护区、博比里森林保护区 | | 2 | community | 受访者的居住社区 | 分类变量 | Boabeng、Bonte、Tankor、Kokrompe、Fiema、Bomini、Dwabenema、Kubease、Krofofrom、Duapompo、NA - 未选择社区 | | 3 | Respondent_age | 受访受访者的年龄 | 连续型 | 60岁以上、51-60岁、18-30岁、41-50岁、31-40岁、NA - 未提供年龄 | | 4 | Gender | 受访者的性别认同 | 分类变量 | 男性、女性 | | 5 | Community_stay | 在当前社区居住的年限 | 分类变量 | 1-2年、3-5年、6-10年、11-20年、20年以上 | | 6 | Primary profession/occupation | 受访者的主要生计或职业 | 分类变量 | 农民、其他、手工业者、商人、NA - 未选择职业 | | 7 | Respondents | 唯一的受访者编号 | 分类变量 | - | | 8 | Plant_list | 受访者知晓的提供清单中的植物，本地名称标注于括号内 | 名义变量 | - | | 9 | month | 月份与相关物候期（例如jan_nl表示1月出现新叶） | 分类变量 | 新叶（nl）、落叶（ls）、开花（fl）、结果（fr） | | 10 | count | 表征该物候期是否在对应月份出现的响应值 | 分类变量 | 0 - 否、1 - 是 | 3. Phenocam衍生物候数据（rbg_index_phenocam_22062025.csv） | 序号 | 变量名 | 描述 | 类型 | 取值范围/格式 | |------|--------|------|------|--------------| | 1 | file | 文件地址与文件名，文件名由站点名称、样地编号、相机编号、图像捕获日期和时间组成 | 名义变量 | siteid_YYYY_MM_DD_HHMMSS.JPG | | 2 | time | 文件名中包含的时间 | 日期型 | DD/MM/YYYY | | 3 | red | 红色通道的平均像素值 | 数值型 | - | | 4 | green | 绿色通道的平均像素值 | 数值型 | - | | 5 | blue | 蓝色通道的平均像素值 | 数值型 | - | | 6 | rcc | 红色色度坐标（Red Chromatic Coordinates, RCC）= RDN/(RDN+GDN+BDN)，其中DN为感兴趣区域（Region of Interest, ROI）内的平均数字值 | 数值型 | - | | 7 | gcc | 绿色色度坐标（Green Chromatic Coordinates, GCC）= GDN/(RDN+GDN+BDN)，其中DN为感兴趣区域内的平均数字值 | 数值型 | - | | 8 | bcc | 蓝色色度坐标（Blue Chromatic Coordinates, BCC）= BDN/(RDN+GDN+BDN)，其中DN为感兴趣区域内的平均数字值 | 数值型 | - | | 9 | rcc.std | 感兴趣区域内rcc的标准差 | 数值型 | - | | 10 | gcc.std | 感兴趣区域内gcc的标准差 | 数值型 | - | | 11 | bcc.std | 感兴趣区域内bcc的标准差 | 数值型 | - | | 12 | rcc05, rcc10, rcc25, rcc50, rcc75, rcc90, rcc95 | 针对整个感兴趣区域内红色色度坐标计算得到的5%、10%、25%、50%、75%、90%、95%分位数 | 数值型 | - | | 13 | gcc05, gcc10, gcc25, gcc50, gcc75, gcc90, gcc95 | 针对整个感兴趣区域内绿色色度坐标计算得到的5%、10%、25%、50%、75%、90%、95%分位数 | 数值型 | - | | 14 | bcc05, bcc10, bcc25, bcc50, bcc75, bcc90, bcc95 | 针对整个感兴趣区域内蓝色色度坐标计算得到的5%、10%、25%、50%、75%、90%、95%分位数 | 数值型 | - | | 15 | brightness | 红、绿、蓝三通道的最大像素值 | 数值型 | - | | 16 | darkness | 红、绿、蓝三通道的最小像素值 | 数值型 | - | | 17 | contrast | 最大与最小像素值的差值（对比度） | 数值型 | - | | 18 | grR | 绿红比 | 数值型 | - | | 19 | rbR | 红蓝比 | 数值型 | - | | 20 | gbR | 绿蓝比 | 数值型 | - | | 21 | GRVI | 绿红植被指数（Green-Red Vegetation Index, GRVI）= (G-R)/(G+R) | 数值型 | - | | 22 | exG | 过量绿度指数= 2G - R - B | 数值型 | - | 4. 公民科学标注马拉松数据（phenopulse_events_classification_22062025.csv） | 序号 | 变量名 | 描述 | 类型 | 取值范围/格式 | |------|--------|------|------|--------------| | 1 | user_id | 每位图像标注志愿者的唯一编号 | 数值型 | - | | | classification_id | 每个图像标注分类的唯一编号 | 数值型 | - | | 2 | workflow_name | Zooniverse平台上的标注任务名称 | 分类变量 | 抽叶事件、开花事件、结果事件 | | | created_at | 分类创建的日期与时间 | 日期型 | - | | 3 | annotations | 对图像文件执行的标注任务 | 字符串型 | - | | 4 | subject_data | 任务主题信息，例如主题创建时间、主题退役时间 | 字符串型 | - | | 5 | filename | 由站点名称、样地编号、相机编号、图像捕获日期和时间组成的图像ID | 名义变量 | siteid_YYYY_MM_DD_HHMMSS.JPG | | 6 | event_values | 志愿者/标注者为主题施加的标签，还可包含标注者在图像上绘制的多边形坐标 | 分类变量 | 抽叶事件：新叶、成熟叶、枯叶、落叶；开花事件：是、否、圆形多边形；结果事件：是、否、三角形多边形；NA - 无数据 | 5. 气候数据（climate_dataset_26062025.csv） | 序号 | 变量名 | 描述 | 单位/格式 | |------|--------|------|----------| | 1 | Date | 气候变量的记录日期 | 日/月/年 | | 2 | Time | 观测时间 | 时:分:秒 | | 3 | Wind_Speed | 传感器高度处测得的平均水平风速 | m/s | | 4 | Gust_Speed | 每个测量间隔内检测到的最大阵风风速 | m/s | | 5 | Wind_Direction | 风的来源方位（风向） | ° | | 6 | Prec | 采样间隔内记录的总累积降水量 | mm | | 7 | Temp | 传感器高度处测得的环境气温 | °C | | 8 | RH | 空气中水汽相对于特定温度下最大持水量的百分比（相对湿度） | % | | 9 | Dew_Point | 空气达到饱和、水汽凝结为露的温度（露点温度） | °C | | 10 | Site | 自动气象站（Automatic Weather Station, AWS）的安装位置名称 | 文本：BFMS - 博阿本格·菲玛猴子保护区；BFR - 博比里森林保护区 | | 11 | Month | 观测的公历月份（数字形式） | 整数型（1-12） | | 12 | Year | 观测的公历年 | 整数型（2024、2025） | | 13 | Season | 气候季节分类，用于生态与物候分析 | 文本：旱季、雨季 | | 14 | CumRain | 日累积降雨量 | mm | | 15 | Dry | 二元指示标志：1表示降水量恰好为0mm的干燥日（Prec == 0），0表示降水量大于0mm的湿润日 | 布尔型（1 = 干燥，0 = 湿润） | 6. 卫星影像衍生物候数据，数据可通过链接https://data.4tu.nl/获取，使用相同的DOI：10.5281/zenodo.15704554
