Fixed README and weather coordinate columns

README.md

@@ -3,7 +3,8 @@ license: cc-by-4.0
 language:
   - en
 pretty_name: PUUM_passive_recordings
-task_categories: [audio-classification] # ex: image-classification, see key list at https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/pipelines.ts
+description: Unlabelled passive acoustic recordings of Hawaiian birds from Pu'u Maka'ala Natural Area Reserve (PUUM), intended for unsupervised audio analysis and machine learning research.
+task_categories: [audio-classification]
 modalities: [Audio]
 tags:
   - biology
@@ -25,11 +26,11 @@ size_categories: 1K<n<10K
 
 
 ### Dataset Description
-This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the [Pu'u Maka'ala Natural Area Reserve](https://www.neonscience.org/field-sites/puum) (PUUM) in Hawaii. This dataset is intended for use in unsupervised audio analysis methods, classification using existing models, and other machine learning and ecology research purposes. Additionally, this dataset contains dataframes with the weather and bird detections.
+This is a dataset containing unlabelled, unprocessed passive acoustic recordings of Hawaiian birds in the [Pu'u Maka'ala Natural Area Reserve](https://www.neonscience.org/field-sites/puum) (PUUM) in Hawaii. It is intended for use in unsupervised audio analysis methods, classification using existing models, and other machine learning and ecology research purposes. Additionally, this dataset contains dataframes with the weather and bird detections.
 
 - **Curated by:** Kate Nepovinnykh, Fedor Zolotarev, Maksim Kholiavchenko
 <!-- Provide the basic links for the dataset. These will show up on the sidebar to the right of your dataset card ("Curated by" too). -->
-- **Repository:** [https://github.com/Imageomics/amakiki-project/tree/phenology]
+- **Repository:** <https://github.com/Imageomics/amakiki-project/tree/phenology>
 
 
 <!-- Provide a longer summary of what this dataset is. -->
@@ -179,14 +180,15 @@ Bird detections from phenology study recordings processed with sound separation,
 Same as phenology_birds_single_species.csv with the addition of a `Probability` column specifying the probability assigned by Perch.
 
 **weather.csv**
-Daily environmental measurements including temperature, rainfall, humidity, and vegetation indices for correlation with bird activity.
+Daily environmental measurements including temperature, rainfall, humidity, and vegetation indices for correlation with bird activity. Weather data were obtained from the [Hawai'i Climate Data Portal](https://www.hawaii.edu/climate-data-portal) for the PUUM site coordinates.
 
-  - `date`: Date of environmental measurements
+  - `date`: Date of environmental measurements in Mon-DD format (e.g., Jan-22). All dates are in 2025.
   - `rainfall_mm`: Daily rainfall measurement in millimeters
   - `humidity_percent`: Relative humidity percentage
   - `mean_temp_c`: Mean temperature in degrees Celsius
   - `ndvi`: Normalized Difference Vegetation Index (measure of vegetation health/density)
-  - `coordinates`: Geographic coordinates (latitude/longitude)
+  - `latitude`: Latitude coordinate (decimal degrees)
+  - `longitude`: Longitude coordinate (decimal degrees)
   - `min_temp`: Minimum temperature (°C)
   - `max_temp`: Maximum temperature (°C)
 
@@ -229,12 +231,12 @@ This dataset was created in order to study correlation Hawaiian birds and phenol
 <!-- Motivation for the creation of this dataset. For instance, what you intended to study and why that required curation of a new dataset (or if it's newly collected data and why the data was collected (intended use)), etc. -->
 
 ### Source Data
-These data were collected at the Pu'u Maka'ala Natural Area Reserve (PUUM), a NEON field site located on the windward slope of Mauna Loa volcano at approximately 1700m elevation on Hawai'i Island. The site includes diverse habitats ranging from grasslands to tropical rainforest, with active koa-dominated forest restoration.
+These data were collected at the [Pu'u Maka'ala Natural Area Reserve (PUUM)](https://www.neonscience.org/field-sites/puum), a NEON field site located on the windward slope of Mauna Loa volcano at approximately 1700m elevation on Hawai'i Island. The site includes diverse habitats ranging from grasslands to tropical rainforest, with active koa-dominated forest restoration.
 
 #### Data Collection and Processing
-Nine SongMeter Micro 2 audio recorders (Wildlife Acoustics) were deployed between January 23 and April 3, 2025. Six recorders were arranged along an 800-meter phenology transect in a forested area, while three additional recorders were installed at separate koa tree (\textit{Acacia koa}) restoration sites representing different maturity stages (Open Grassland, Park Land, and Closed Canopy).
+Nine [SongMeter Micro 2](https://www.wildlifeacoustics.com/products/song-meter-micro) audio recorders (Wildlife Acoustics) were deployed between January 23 and April 3, 2025. Six recorders were arranged along an 800-meter phenology transect in a forested area, while three additional recorders were installed at separate koa tree (*Acacia koa*) restoration sites representing different maturity stages (Open Grassland, Park Land, and Closed Canopy).
 
-Each recorder was programmed to collect acoustic data daily: 30 minutes during the dawn chorus (6:00-7:00) and 15 minutes every hour from 7:00 to 19:00. Raw audio files were processed using Bird-MixIT, an unsupervised sound source separation model based on Mixture Invariant Training, to isolate individual bird vocalizations from overlapping environmental sounds. Separated sources were then classified using the Perch bird sound recognition model, retaining all Hawaiian species detections with probability >0.01. 
+Each recorder was programmed to collect acoustic data daily: 30 minutes during the dawn chorus (6:00-7:00) and 15 minutes every hour from 7:00 to 19:00. Raw audio files were processed using [Bird-MixIT](https://github.com/google-research/sound-separation/tree/master/models/bird_mixit), an unsupervised sound source separation model based on Mixture Invariant Training, to isolate individual bird vocalizations from overlapping environmental sounds. Separated sources were then classified using the [Perch](https://github.com/google-research/perch) bird sound recognition model (v2.0), retaining all Hawaiian species detections with probability >0.01. 
 
 #### Who are the source data producers?
 These data were produced through a collaborative effort involving members of the AI and Biodiversity Change (ABC) Global Center, the Imageomics Institute, participants in the Experiential Introduction to AI and Ecology Course, and the National Ecological Observatory Network (NEON) team. NEON team members provided crucial support for recorder deployment and field logistics at the Pu'u Maka'ala Natural Area Reserve.
@@ -303,18 +305,20 @@ If you use this dataset in your research, please cite it as:
 }
 ```
 
--for an associated paper:
+<!--
+For an associated paper:
+
 **Paper**
-```​
+```
 @article{<ref_code>,
   title    = {<title>},
   author   = {<author1 and author2>},
   journal  = {<journal_name>},
-  year     =  <year>,
+  year     = <year>,
   url      = {<DOI_URL>},
   doi      = {<DOI>}
 }
-```​
+```
 -->
 
 <!---

csv/weather.csv

@@ -1,73 +1,73 @@
-date,rainfall_mm,humidity_percent,mean_temp_c,ndvi,coordinates,min_temp,max_temp
-Jan-22,0.1,64.97,11.8,0.63,"Lat: 19.5618, Lon: -155.3148",6.1,17.6
-Jan-23,0.0,74.57,12.5,-,"Lat: 19.5618, Lon: -155.3148",6.8,18.2
-Jan-24,2.05,76.3,12.5,-,"Lat: 19.5618, Lon: -155.3148",7.3,17.7
-Jan-25,4.27,78.81,13.8,-,"Lat: 19.5618, Lon: -155.3148",9.5,18.1
-Jan-26,3.07,81.46,13.6,0.62,"Lat: 19.5618, Lon: -155.3148",9.5,17.6
-Jan-27,1.16,86.06,12.4,-,"Lat: 19.5618, Lon: -155.3148",8.7,16.1
-Jan-28,0.88,85.63,11.6,0.59,"Lat: 19.5618, Lon: -155.3148",7.5,15.8
-Jan-29,1.7,79.67,13.4,0.6,"Lat: 19.5618, Lon: -155.3148",8.7,18.1
-Jan-30,19.27,69.93,17.4,0.59,"Lat: 19.5618, Lon: -155.3148",12.8,22.1
-Jan-31,18.62,81.03,14.9,-,"Lat: 19.5618, Lon: -155.3148",12.6,17.2
-Feb-01,1.65,72.96,15.0,-,"Lat: 19.5618, Lon: -155.3148",10.9,19.0
-Feb-02,0.89,77.09,12.9,0.49,"Lat: 19.5618, Lon: -155.3148",8.0,17.8
-Feb-03,0.01,64.72,11.4,0.53,"Lat: 19.5618, Lon: -155.3148",6.0,16.9
-Feb-04,1.12,74.27,10.8,0.53,"Lat: 19.5618, Lon: -155.3148",5.2,16.4
-Feb-05,1.33,68.34,11.7,-,"Lat: 19.5618, Lon: -155.3148",5.1,18.2
-Feb-06,11.47,77.29,11.5,0.41,"Lat: 19.5618, Lon: -155.3148",6.3,16.8
-Feb-07,3.32,77.9,12.2,0.45,"Lat: 19.5618, Lon: -155.3148",7.5,17.0
-Feb-08,0.08,70.28,12.9,0.33,"Lat: 19.5618, Lon: -155.3148",7.0,18.8
-Feb-09,0.28,75.1,13.0,-,"Lat: 19.5618, Lon: -155.3148",7.8,18.1
-Feb-10,0.02,72.5,12.7,-,"Lat: 19.5618, Lon: -155.3148",7.1,18.3
-Feb-11,0.0,73.5,13.0,0.28,"Lat: 19.5618, Lon: -155.3148",7.6,18.4
-Feb-12,0.1,75.08,13.0,0.39,"Lat: 19.5618, Lon: -155.3148",7.4,18.6
-Feb-13,0.17,71.08,13.1,-,"Lat: 19.5618, Lon: -155.3148",7.2,18.9
-Feb-14,0.05,70.03,13.2,0.57,"Lat: 19.5618, Lon: -155.3148",6.8,19.5
-Feb-15,9.96,73.32,15.6,-,"Lat: 19.5618, Lon: -155.3148",10.6,20.5
-Feb-16,1.45,76.79,15.2,-,"Lat: 19.5618, Lon: -155.3148",10.2,20.1
-Feb-17,0.05,76.03,14.3,0.67,"Lat: 19.5618, Lon: -155.3148",9.3,19.3
-Feb-18,4.18,71.36,14.7,0.67,"Lat: 19.5618, Lon: -155.3148",9.3,20.1
-Feb-19,1.07,74.65,14.0,0.69,"Lat: 19.5618, Lon: -155.3148",8.8,19.1
-Feb-20,0.0,76.59,13.5,0.67,"Lat: 19.5618, Lon: -155.3148",8.2,18.8
-Feb-21,0.0,78.07,12.5,0.67,"Lat: 19.5618, Lon: -155.3148",7.3,17.8
-Feb-22,0.05,71.12,13.6,-,"Lat: 19.5618, Lon: -155.3148",7.5,19.6
-Feb-23,0.01,72.3,13.2,0.67,"Lat: 19.5618, Lon: -155.3148",7.5,19.0
-Feb-24,0.34,72.3,13.6,0.67,"Lat: 19.5618, Lon: -155.3148",7.6,19.7
-Feb-25,0.07,67.61,13.2,0.68,"Lat: 19.5618, Lon: -155.3148",7.2,19.3
-Feb-26,0.02,69.26,14.3,0.68,"Lat: 19.5618, Lon: -155.3148",8.4,20.2
-Feb-27,0.05,71.32,13.7,0.66,"Lat: 19.5618, Lon: -155.3148",8.0,19.4
-Feb-28,0.0,71.42,14.4,0.66,"Lat: 19.5618, Lon: -155.3148",9.0,19.7
-Mar-01,0.0,69.19,13.4,0.66,"Lat: 19.5618, Lon: -155.3148",7.6,19.2
-Mar-02,0.1,73.81,13.7,0.68,"Lat: 19.5618, Lon: -155.3148",8.4,19.0
-Mar-03,0.31,72.0,13.8,0.67,"Lat: 19.5618, Lon: -155.3148",8.8,18.8
-Mar-04,5.25,73.85,13.9,0.66,"Lat: 19.5618, Lon: -155.3148",9.6,18.2
-Mar-05,0.86,63.18,14.0,-,"Lat: 19.5618, Lon: -155.3148",9.1,18.8
-Mar-06,3.53,70.93,13.0,-,"Lat: 19.5618, Lon: -155.3148",8.6,17.5
-Mar-07,8.05,77.0,11.7,0.64,"Lat: 19.5618, Lon: -155.3148",7.7,15.7
-Mar-08,1.09,68.88,12.2,0.64,"Lat: 19.5618, Lon: -155.3148",7.3,17.1
-Mar-09,2.11,73.4,12.5,0.64,"Lat: 19.5618, Lon: -155.3148",8.2,16.8
-Mar-10,74.5,92.94,12.4,0.62,"Lat: 19.5618, Lon: -155.3148",9.2,15.5
-Mar-11,10.2,74.22,13.0,-,"Lat: 19.5618, Lon: -155.3148",8.6,17.4
-Mar-12,6.94,67.99,12.9,0.63,"Lat: 19.5618, Lon: -155.3148",7.9,17.9
-Mar-13,17.4,66.41,13.4,0.63,"Lat: 19.5618, Lon: -155.3148",8.7,18.0
-Mar-14,0.47,75.34,12.0,0.6,"Lat: 19.5618, Lon: -155.3148",7.0,17.1
-Mar-15,8.76,75.63,12.5,0.57,"Lat: 19.5618, Lon: -155.3148",6.7,18.2
-Mar-16,26.24,77.74,13.8,0.49,"Lat: 19.5618, Lon: -155.3148",9.4,18.3
-Mar-17,4.37,74.94,14.7,-,"Lat: 19.5618, Lon: -155.3148",9.9,19.5
-Mar-18,0.9,75.1,13.6,0.38,"Lat: 19.5618, Lon: -155.3148",9.1,18.1
-Mar-19,10.29,85.33,13.0,-,"Lat: 19.5618, Lon: -155.3148",9.8,16.3
-Mar-20,0.92,75.73,13.8,0.38,"Lat: 19.5618, Lon: -155.3148",9.7,17.9
-Mar-21,1.84,78.33,14.1,-,"Lat: 19.5618, Lon: -155.3148",9.0,19.2
-Mar-22,1.61,77.45,13.0,0.3,"Lat: 19.5618, Lon: -155.3148",7.7,18.4
-Mar-23,2.27,75.55,12.6,0.46,"Lat: 19.5618, Lon: -155.3148",6.8,18.5
-Mar-24,0.33,77.97,12.2,-,"Lat: 19.5618, Lon: -155.3148",7.0,17.5
-Mar-25,0.28,75.4,12.5,0.41,"Lat: 19.5618, Lon: -155.3148",7.2,17.8
-Mar-26,1.72,75.4,13.0,-,"Lat: 19.5618, Lon: -155.3148",7.9,18.0
-Mar-27,2.29,76.0,13.2,0.44,"Lat: 19.5618, Lon: -155.3148",7.8,18.6
-Mar-28,1.77,79.03,12.8,0.47,"Lat: 19.5618, Lon: -155.3148",7.7,17.8
-Mar-29,2.17,80.7,12.8,0.46,"Lat: 19.5618, Lon: -155.3148",7.8,17.8
-Mar-30,0.42,77.34,13.0,0.44,"Lat: 19.5618, Lon: -155.3148",7.9,18.2
-Mar-31,0.64,75.12,13.4,-,"Lat: 19.5618, Lon: -155.3148",8.0,18.8
-Apr-01,0.01,72.46,13.8,0.44,"Lat: 19.5618, Lon: -155.3148",8.7,18.9
-Apr-02,0.33,74.82,13.0,-,"Lat: 19.5618, Lon: -155.3148",7.8,18.2
-Apr-03,0.26,67.04,14.0,0.45,"Lat: 19.5618, Lon: -155.3148",7.8,20.1
+date,rainfall_mm,humidity_percent,mean_temp_c,ndvi,latitude,longitude,min_temp,max_temp
+Jan-22,0.1,64.97,11.8,0.63,19.5618,-155.3148,6.1,17.6
+Jan-23,0.0,74.57,12.5,-,19.5618,-155.3148,6.8,18.2
+Jan-24,2.05,76.3,12.5,-,19.5618,-155.3148,7.3,17.7
+Jan-25,4.27,78.81,13.8,-,19.5618,-155.3148,9.5,18.1
+Jan-26,3.07,81.46,13.6,0.62,19.5618,-155.3148,9.5,17.6
+Jan-27,1.16,86.06,12.4,-,19.5618,-155.3148,8.7,16.1
+Jan-28,0.88,85.63,11.6,0.59,19.5618,-155.3148,7.5,15.8
+Jan-29,1.7,79.67,13.4,0.6,19.5618,-155.3148,8.7,18.1
+Jan-30,19.27,69.93,17.4,0.59,19.5618,-155.3148,12.8,22.1
+Jan-31,18.62,81.03,14.9,-,19.5618,-155.3148,12.6,17.2
+Feb-01,1.65,72.96,15.0,-,19.5618,-155.3148,10.9,19.0
+Feb-02,0.89,77.09,12.9,0.49,19.5618,-155.3148,8.0,17.8
+Feb-03,0.01,64.72,11.4,0.53,19.5618,-155.3148,6.0,16.9
+Feb-04,1.12,74.27,10.8,0.53,19.5618,-155.3148,5.2,16.4
+Feb-05,1.33,68.34,11.7,-,19.5618,-155.3148,5.1,18.2
+Feb-06,11.47,77.29,11.5,0.41,19.5618,-155.3148,6.3,16.8
+Feb-07,3.32,77.9,12.2,0.45,19.5618,-155.3148,7.5,17.0
+Feb-08,0.08,70.28,12.9,0.33,19.5618,-155.3148,7.0,18.8
+Feb-09,0.28,75.1,13.0,-,19.5618,-155.3148,7.8,18.1
+Feb-10,0.02,72.5,12.7,-,19.5618,-155.3148,7.1,18.3
+Feb-11,0.0,73.5,13.0,0.28,19.5618,-155.3148,7.6,18.4
+Feb-12,0.1,75.08,13.0,0.39,19.5618,-155.3148,7.4,18.6
+Feb-13,0.17,71.08,13.1,-,19.5618,-155.3148,7.2,18.9
+Feb-14,0.05,70.03,13.2,0.57,19.5618,-155.3148,6.8,19.5
+Feb-15,9.96,73.32,15.6,-,19.5618,-155.3148,10.6,20.5
+Feb-16,1.45,76.79,15.2,-,19.5618,-155.3148,10.2,20.1
+Feb-17,0.05,76.03,14.3,0.67,19.5618,-155.3148,9.3,19.3
+Feb-18,4.18,71.36,14.7,0.67,19.5618,-155.3148,9.3,20.1
+Feb-19,1.07,74.65,14.0,0.69,19.5618,-155.3148,8.8,19.1
+Feb-20,0.0,76.59,13.5,0.67,19.5618,-155.3148,8.2,18.8
+Feb-21,0.0,78.07,12.5,0.67,19.5618,-155.3148,7.3,17.8
+Feb-22,0.05,71.12,13.6,-,19.5618,-155.3148,7.5,19.6
+Feb-23,0.01,72.3,13.2,0.67,19.5618,-155.3148,7.5,19.0
+Feb-24,0.34,72.3,13.6,0.67,19.5618,-155.3148,7.6,19.7
+Feb-25,0.07,67.61,13.2,0.68,19.5618,-155.3148,7.2,19.3
+Feb-26,0.02,69.26,14.3,0.68,19.5618,-155.3148,8.4,20.2
+Feb-27,0.05,71.32,13.7,0.66,19.5618,-155.3148,8.0,19.4
+Feb-28,0.0,71.42,14.4,0.66,19.5618,-155.3148,9.0,19.7
+Mar-01,0.0,69.19,13.4,0.66,19.5618,-155.3148,7.6,19.2
+Mar-02,0.1,73.81,13.7,0.68,19.5618,-155.3148,8.4,19.0
+Mar-03,0.31,72.0,13.8,0.67,19.5618,-155.3148,8.8,18.8
+Mar-04,5.25,73.85,13.9,0.66,19.5618,-155.3148,9.6,18.2
+Mar-05,0.86,63.18,14.0,-,19.5618,-155.3148,9.1,18.8
+Mar-06,3.53,70.93,13.0,-,19.5618,-155.3148,8.6,17.5
+Mar-07,8.05,77.0,11.7,0.64,19.5618,-155.3148,7.7,15.7
+Mar-08,1.09,68.88,12.2,0.64,19.5618,-155.3148,7.3,17.1
+Mar-09,2.11,73.4,12.5,0.64,19.5618,-155.3148,8.2,16.8
+Mar-10,74.5,92.94,12.4,0.62,19.5618,-155.3148,9.2,15.5
+Mar-11,10.2,74.22,13.0,-,19.5618,-155.3148,8.6,17.4
+Mar-12,6.94,67.99,12.9,0.63,19.5618,-155.3148,7.9,17.9
+Mar-13,17.4,66.41,13.4,0.63,19.5618,-155.3148,8.7,18.0
+Mar-14,0.47,75.34,12.0,0.6,19.5618,-155.3148,7.0,17.1
+Mar-15,8.76,75.63,12.5,0.57,19.5618,-155.3148,6.7,18.2
+Mar-16,26.24,77.74,13.8,0.49,19.5618,-155.3148,9.4,18.3
+Mar-17,4.37,74.94,14.7,-,19.5618,-155.3148,9.9,19.5
+Mar-18,0.9,75.1,13.6,0.38,19.5618,-155.3148,9.1,18.1
+Mar-19,10.29,85.33,13.0,-,19.5618,-155.3148,9.8,16.3
+Mar-20,0.92,75.73,13.8,0.38,19.5618,-155.3148,9.7,17.9
+Mar-21,1.84,78.33,14.1,-,19.5618,-155.3148,9.0,19.2
+Mar-22,1.61,77.45,13.0,0.3,19.5618,-155.3148,7.7,18.4
+Mar-23,2.27,75.55,12.6,0.46,19.5618,-155.3148,6.8,18.5
+Mar-24,0.33,77.97,12.2,-,19.5618,-155.3148,7.0,17.5
+Mar-25,0.28,75.4,12.5,0.41,19.5618,-155.3148,7.2,17.8
+Mar-26,1.72,75.4,13.0,-,19.5618,-155.3148,7.9,18.0
+Mar-27,2.29,76.0,13.2,0.44,19.5618,-155.3148,7.8,18.6
+Mar-28,1.77,79.03,12.8,0.47,19.5618,-155.3148,7.7,17.8
+Mar-29,2.17,80.7,12.8,0.46,19.5618,-155.3148,7.8,17.8
+Mar-30,0.42,77.34,13.0,0.44,19.5618,-155.3148,7.9,18.2
+Mar-31,0.64,75.12,13.4,-,19.5618,-155.3148,8.0,18.8
+Apr-01,0.01,72.46,13.8,0.44,19.5618,-155.3148,8.7,18.9
+Apr-02,0.33,74.82,13.0,-,19.5618,-155.3148,7.8,18.2
+Apr-03,0.26,67.04,14.0,0.45,19.5618,-155.3148,7.8,20.1