Inadequate pasture management causes land degradation through reduction of grass, increased presence of invasive plants or pests, compaction, erosion, and nutrient deficiency. The recognition of pasture degradation is therefore essential. Remote sensing satellite systems allow us to do so at regional-to global scales. A struggle is in progress nowadays is to improve detection accuracy and implement high-resolution surveys at farm scales using low-cost unmanned aerial vehicles (UAVs). The pasture imagery can be translated into maps of degraded pasture using the popular NDVI as diagnostic parameter, but their generation using a UAV requires a high-cost NIR sensor, while the struggle is to use low-cost UAVs equipped with RGB cameras. The first step to recognize degraded pastures using RGB cameras is to define a suitable vegetation index. Thus, the purpose of this study was to present the total brightness quotient of red (TBQR), green (TBQG), and blue (TBQB) bands. The test to the index resorted to LANDSAT-8 satellite images captured over the environmental protection area of Uberaba River basin (Minas Gerais, Brazil) in the 2017–2019 period. The images were not captured by a UAV because the equipment was not then available. The results were promising given the large detection accuracy (88.63%) of the TBQG and the high (0.965) correlation between TBQG and NDVI. Besides, the TBQ-based areas of degraded pasture (17,486.3–25,180.1 hectares) were larger than the NDVI counterparts (12,066.9 hectares). This is an additional reason to oversight degraded pastures based on the TBQs, as they seek for improved environmental compliance and economic development.

中文翻译：

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基于可见光谱的改进植被指数在退化牧场诊断中的应用：对发展的影响

牧场管理不当会导致草地减少、入侵植物或害虫增加、压实、侵蚀和养分缺乏，从而导致土地退化。因此，对牧场退化的认识是必不可少的。遥感卫星系统使我们能够在区域到全球范围内做到这一点。目前正在进行的一项斗争是使用低成本无人机 (UAV) 提高检测精度并在农场规模实施高分辨率调查。牧场图像可以使用流行的 NDVI 作为诊断参数转换为退化牧场的地图，但使用无人机生成它们需要高成本的 NIR 传感器，而使用配备 RGB 摄像头的低成本无人机则是困难重重。使用 RGB 相机识别退化牧场的第一步是定义合适的植被指数。因此，本研究的目的是展示红色 (TBQR)、绿色 (TBQG) 和蓝色 (TBQB) 波段的总亮度商数。该指数的测试采用了 2017-2019 年期间在乌贝拉巴河流域（巴西米纳斯吉拉斯州）环境保护区上空捕获的 LANDSAT-8 卫星图像。这些图像不是由无人机拍摄的，因为当时设备不可用。考虑到 TBQG 的高检测精度 (88.63%) 和 TBQG 与 NDVI 之间的高 (0.965) 相关性，结果很有希望。此外，基于TBQ的退化牧场面积（17,486.3-25,180.1公顷）大于NDVI对应面积（12,066.9公顷）。这是根据 TBQ 监督退化牧场的另一个原因，因为它们寻求改善环境合规性和经济发展。