Monitoring and Mapping rangeland health using remote sensing and GIS methods: A case study in the foothill Artemisia-ephemeral rangeland region in Samarkand

This paper describes the use of NDVI analysis to assess the health condition of the rangeland in a specific study area. NDVI values were used to determine the vegetation cover and its condition by dividing the values into different classes based on field samples. The study found that the rangeland health condition could be classified into four classes based on the NDVI values ranging from -0.26 to 0.63. The results indicated the presence of both healthy and unhealthy vegetation cover in the study area. However, the study emphasizes that NDVI values can vary depending on different factors, such as season, weather conditions, and vegetation type, and therefore, these factors must be considered when interpreting the results. Overall, the study highlights the importance of using NDVI analysis as a valuable tool to assess the health condition of rangelands and to inform management practices. The paper presents the results of a study on rangeland health classification in a particular study area. The study utilized remote sensing and GIS technologies to classify the rangeland into healthy and degraded categories. The results showed that only 4.4% of the land area was classified as healthy rangeland, while most of the study area was classified as degraded. Specifically, 36.1% of the land area was classified as moderately degraded, 24.3% as low degraded, and 35.2% as highly degraded. These findings suggest that the health of rangelands in the study area is poor and requires effective management and restoration practices to improve productivity. The study demonstrates the usefulness of remote sensing and GIS technologies in monitoring rangeland health and supporting sustainable management practices.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-08-30
DOI
https://doi.org/10.1051/e3sconf/202456303070/pdf
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Monitoring and Mapping rangeland health using remote sensing and GIS methods: A case study in the foothill Artemisia-ephemeral rangeland region in Samarkand

Springer Link (Chiba Institute of Technology)
Remote Sensing in Agriculture
article

Monitoring and Mapping rangeland health using remote sensing and GIS methods: A case study in the foothill Artemisia-ephemeral rangeland region in Samarkand

article en

Abstract

This paper describes the use of NDVI analysis to assess the health condition of the rangeland in a specific study area. NDVI values were used to determine the vegetation cover and its condition by dividing the values into different classes based on field samples. The study found that the rangeland health condition could be classified into four classes based on the NDVI values ranging from -0.26 to 0.63. The results indicated the presence of both healthy and unhealthy vegetation cover in the study area. However, the study emphasizes that NDVI values can vary depending on different factors, such as season, weather conditions, and vegetation type, and therefore, these factors must be considered when interpreting the results. Overall, the study highlights the importance of using NDVI analysis as a valuable tool to assess the health condition of rangelands and to inform management practices. The paper presents the results of a study on rangeland health classification in a particular study area. The study utilized remote sensing and GIS technologies to classify the rangeland into healthy and degraded categories. The results showed that only 4.4% of the land area was classified as healthy rangeland, while most of the study area was classified as degraded. Specifically, 36.1% of the land area was classified as moderately degraded, 24.3% as low degraded, and 35.2% as highly degraded. These findings suggest that the health of rangelands in the study area is poor and requires effective management and restoration practices to improve productivity. The study demonstrates the usefulness of remote sensing and GIS technologies in monitoring rangeland health and supporting sustainable management practices.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 68%
Remote Sensing in Agriculture
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