Caracterización Ecológica De Bofedales, Hábitat De Vicuñas Aplicando Metodologías De Teledeteccion Y Sig Estudio De Caso: Reserva De Producción De Fauna Chimborazo
Bibliographic record
Abstract
This article presents a methodology based on classification of images from Landsat 7 ETM + to classify Andean wetlands known as ¨Bofedal¨ (wetland) located in the Fauna Production Reserve Chimborazo. Five of the seven in-situ geo-referenced bofedales belong to this category and two belong to the altiplano. These georeferenced reservoirs are the principal habitat of the vicuñas that are located within the RPFCH in the jurisdictions of the province of Tungurahua: Río Blanco, ¨Mocha¨ Valley area, 472.26 ha, 4400 m.; Chimborazo Province: Bofedal Quebrada Toni, Urbina area, 16.74 ha, 4301 m, bofedal El Refugio (Hermanos Carrel) at the Nevado Chimborazo, 1.44 ha, 4800msnm, and Curi bofedal Pogyo, Chorrera Mirador, 0.34 ha., 4523 m. and in the Bolivar Province: the wetlands Chag Pogyo, Pulinguí San Pablo, 19.36 ha, 4064 meters above sea level. Bofedal Sinche1, the sector ¨antennas¨, 8.53 ha. 4167 m., And Sinche2, ¨Puente Ayora¨ area, 9.39 ha., 3981 meters, the latter being Chag Pogyo highland bofedales. The seven bofedales represent 0.93% (527.87 ha) of the total area of the RPFCH (56653, 27 ha.). Two images of the satellite Landsat 7 ETM +, from the years 2001 - EarthSat, 2004 - USGS and an orthophoto 2013-2014 - GIS land were used. Georeferenced and rectified to capture the spatial and temporal variability of these ecosystems and define the characterization of bofedales in the reserve. For each image two classification methods were used, the supervised classification being the most efficient when representing the four representative classes in the RPFCH: snow, rock, pajonal and bofedal. Since this classification is oriented to objects that takes into account aspects such as shape and texture and not just the spectral information of each pixel. Allowing to obtain information on the characteristics and spatial distribution of the bofedales which was verified and validated later in the field. This process allows the generation of digital cartography with the identification, delimited and distributed bofedales along the RPFCH, representing a total of approximately 1483.94 ha in the RPFCH. In addition, the Normalized Difference Vegetation Index (NDVI) was applied, which made it possible to differentiate water bodies from other coverages, as well as specifically to know the extent of the reservoirs present in the Reserve, in order to better infer Distribution of vicuñas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".