Detection of an experimental mass grave over time and at different spatial scales in a temperate environment
Notice bibliographique
Résumé
In the past decades, the detection of clandestine mass graves has become a topic of high interest for the international forensic community. Hyperspectral remote sensing may provide complementary and novel techniques to detect mass graves in regions with human conflict by detecting changes in site surface reflectance, which can potentially be different from a non-grave area. In this research study, I assessed differences in spectral reflectance between an experimental mass grave and a non-grave in a temperate environment at three different spatial scales: leaf level and plot level using field spectroscopy and airborne hyperspectral imagery. To test the application of hyperspectral remote sensing as a tool in the detection of mass graves, three experimental study sites were established in Ottawa, Ontario, Canada: an experimental mass grave containing pig carcasses (Sus Scrofa domesticus) at one meter depth, a reference site containing only disturbed soil, and an undisturbed control site. Soil and vegetation samples and spectral data using field spectrometry and airborne hyperspectral imagery were collected in the first 15 months post-disturbance. The main findings of this research show that differences in spectral reflectance depend on spatial scale, disturbance stage and time in the growing season. Overall differences were found between the grave and control in soil chemistry, vegetation pigmentation and spectral reflectance throughout the study period. In the first 13 months post-disturbance, differences in soil chemistry (e.g. calcium and manganese), vegetation pigmentation (i.e. chlorophyll and carotenoids), and spectral reflectance between the mass grave and reference can be attributed to the overall site disturbance and not as a result of the decomposition process. In contrast, 13 months after burial there are differences in soil chemistry (i.e. ammonium, nitrate, and available phosphorus) and vegetation pigmentation between the mass grave and reference. In terms of spectral reflectance, differences were found along the 400 – 700 nm wavelength range between mass grave and reference during this period. It was also found that the combination of different vegetation indices on airborne imagery increases the spectral separation between mass grave, reference and control depending on time since disturbance. Given that spectral differences emerge towards the end of the data collection, detectable differences between the mass grave and the reference may be delayed due to (1) a slow cadaver decomposition rate and/or (2) the depth of burial that provides a greater barrier to nutrient uptake in surficial plants as previously shown in others studies for deep and shallow graves.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».