Update README.md

README.md

@@ -48,7 +48,7 @@ dataset_summary: '
 
   # Note: other available arguments include ''max_samples'', etc
 
-  dataset = load_from_hub("harpreetsahota/Larch_Tree_Damage")
+  dataset = load_from_hub("Voxel51/Larch_Tree_Damage")
 
 
   # Launch the App
@@ -60,12 +60,8 @@ dataset_summary: '
   '
 ---
 
-# Dataset Card for larch_casebearer
-
-<!-- Provide a quick summary of the dataset. -->
-
-
-
+# Dataset Card for Forest Damages - Larch Casebearer
+![image/png](larch_casebarer.gif)
 
 
 This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 1536 samples.
@@ -86,141 +82,132 @@ from fiftyone.utils.huggingface import load_from_hub
 
 # Load the dataset
 # Note: other available arguments include 'max_samples', etc
-dataset = load_from_hub("harpreetsahota/Larch_Tree_Damage")
+dataset = load_from_hub("Voxel51/Larch_Tree_Damage")
 
 # Launch the App
 session = fo.launch_app(dataset)
 ```
 
 
+# Forest Damages - Larch Casebearer
+
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
+The Forest Damages - Larch Casebearer dataset contains aerial drone imagery of forests in Västergötland, Sweden, captured to support AI-based detection and monitoring of tree damage caused by the larch casebearer moth (*Coleophora laricella*). The dataset was created as part of a project to help forest caretakers quickly identify pest threats and respond to prevent further forest damage.
 
+The dataset consists of 1,543 high-resolution RGB images collected during two drone flight campaigns over five affected forest areas. Images are organized into 10 batches and contain approximately 101,878 bounding box annotations identifying individual trees. Trees are categorized by species (Larch or Other), and batches 1-5 additionally include damage severity annotations across four categories: Healthy (H), Light Damage (LD), High Damage (HD), and Other.
 
+- **Curated by:** Swedish Forest Agency (Skogsstyrelsen)
+- **Funded by:** Microsoft AI for Earth program (supporting partner)
+- **Shared by:** National Forest Data Lab (Skogsdatalabbet), LILA BC
+- **Language(s) (NLP):** N/A (image dataset)
+- **License:** Community Data License Agreement - Permissive (CDLA-Permissive)
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** en
-- **License:** [More Information Needed]
+### Dataset Sources
 
-### Dataset Sources [optional]
+- **Repository:** [LILA BC](https://lila.science/datasets/forest-damages-larch-casebearer/)
+- **Download:** [Google Cloud Storage](https://storage.googleapis.com/public-datasets-lila/larch-casebearer/Data_Set_Larch_Casebearer.zip)
+- **Paper:** N/A
+- **Demo:** N/A
 
-<!-- Provide the basic links for the dataset. -->
+## Uses
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+### Direct Use
 
-## Uses
+This dataset is suitable for:
+- Training and evaluating object detection models for individual tree detection from aerial/drone imagery
+- Developing tree species classification systems (Larch vs. Other)
+- Building damage assessment models to classify tree health status from aerial imagery
+- Research on automated forest health monitoring and pest damage detection
+- Benchmarking remote sensing approaches for forestry applications
 
-<!-- Address questions around how the dataset is intended to be used. -->
+### Out-of-Scope Use
 
-### Direct Use
+This dataset may not be suitable for:
+- Detection of forest damages from pests other than larch casebearer, as damage patterns may differ significantly
+- Application to forest types or geographic regions substantially different from Swedish larch stands
+- High-altitude satellite imagery analysis (dataset uses low-altitude drone imagery)
+- Real-time operational deployment without additional validation on local forest conditions
 
-<!-- This section describes suitable use cases for the dataset. -->
+## Dataset Structure
 
-[More Information Needed]
+### Original Format
 
-### Out-of-Scope Use
+The original dataset is structured into 10 batches with images and annotations in Pascal VOC XML format. All batches contain tree species labels (Larch, Other), while batches 1-5 also include damage severity labels (H, LD, HD, Other).
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+### FiftyOne Format
 
-[More Information Needed]
+The dataset has been parsed into FiftyOne format with the following structure:
 
-## Dataset Structure
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | ObjectIdField | Unique sample identifier |
+| `filepath` | StringField | Path to the image file |
+| `tags` | ListField(StringField) | Sample-level tags |
+| `metadata` | ImageMetadata | Image dimensions, format, etc. |
+| `created_at` | DateTimeField | Sample creation timestamp |
+| `last_modified_at` | DateTimeField | Last modification timestamp |
+| `location` | Classification | Geographic location identifier |
+| `capture_date` | DateTimeField | Date the image was captured |
+| `ground_truth` | Detections | Original bounding box annotations with species and damage labels |
+| `visual_segmentation` | Detections | Instance segmentation masks (model-generated) |
+| `radio_embeddings` | VectorField | Dense image embeddings (model-generated) |
+| `radio_heatmap` | Heatmap | Spatial feature heatmaps (model-generated) |
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+**Statistics:**
+- Total samples: 1,536 images
+- Total tree annotations: ~101,878 bounding boxes
+- Annotations with damage labels: ~44,500 (batches 1-5)
 
-[More Information Needed]
+**Label Classes:**
+- Species: `Larch`, `Other`
+- Damage (batches 1-5 only): `Healthy (H)`, `Light Damage (LD)`, `High Damage (HD)`, `Other`
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
+The larch casebearer is an invasive moth species that has caused significant damage to larch stands in Västergötland, Sweden. The Swedish Forest Agency initiated this project to develop AI-powered tools for identifying, inventorying, mapping, and monitoring affected forest areas. The primary motivation was to enable forest caretakers to rapidly identify pest threats and take preventive action before damage spreads.
 
 ### Source Data
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
 #### Data Collection and Processing
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
+Images were captured using drones during two separate flight campaigns over five forest areas affected by larch casebearer in Västergötland, Sweden. The Swedish Forest Agency secured permits for dissemination of geographical data from Lantmäteriet (Swedish Land Survey).
 
 #### Who are the source data producers?
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
+The drone imagery was collected by the Swedish Forest Agency as part of their forest monitoring program.
 
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+### Annotations
 
 #### Annotation process
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
+Annotations were created manually, with each tree marked using a bounding box and labeled with tree type (Larch or Other). A subset of annotations (batches 1-5) also includes damage severity classifications. Annotations are provided in Pascal VOC XML format.
 
 #### Who are the annotators?
 
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
+Annotations were created by personnel at the Swedish Forest Agency.
 
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+## Citation
 
 **BibTeX:**
-
-[More Information Needed]
+```bibtex
+@dataset{swedish_forest_agency_2021,
+  author       = {{Swedish Forest Agency}},
+  title        = {{Forest Damages – Larch Casebearer 1.0}},
+  year         = {2021},
+  publisher    = {National Forest Data Lab},
+  url          = {https://lila.science/datasets/forest-damages-larch-casebearer/}
+}
+```
 
 **APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
+Swedish Forest Agency. (2021). *Forest Damages – Larch Casebearer 1.0* [Dataset]. National Forest Data Lab. https://lila.science/datasets/forest-damages-larch-casebearer/
 
 ## Dataset Card Contact
 
-[More Information Needed]
+- **Original Dataset Contact:** Halil Radogoshi, Swedish Forest Agency (halil.radogoshi@skogsstyrelsen.se)
+- **LILA BC:** https://lila.science/