One of the major causes of poverty globally is land degradation and poor natural resource conservation, leading to reduced agricultural productivity. This degradation is often caused by a mismatch between land use and land potential, specifically using marginal lands for agriculture. For over 50 years the Land Capability Classification (LCC) system has been used globally for land evaluation to support soil and natural resource conservation. The LCC system classifies the land into eight classes; however, its use is currently limited by two factors: the lack of digital platforms for data input, storage, and management, and an insufficient technical capacity in many regions necessary to generate the required inputs. This paper describes the development of a system to facilitate rapid, flexible, and transparent determinations of LCC by non-soil scientists using a newly developed function of the Land-Potential Knowledge System (LandPKS) mobile app. Inputs include soil texture and rock fragment volume by depth, slope, and site observations of soil limiting factors. A standardized system for evaluating inputs and calculated indicators was developed based on US and international implementations of LCC. The system was evaluated using USDA Natural Resources Conservation Service soil survey data in eight US counties. Results show that the standardized system predictions were within one class for 73.8% of the 1,312 soils tested, despite a high level of variability in how LCC was determined within the US database. The LandPKS LCC system was further tested in Tanzania and Ethiopia to examine site-specific applications, usability, and usefulness of the system for national land use planning efforts. It was concluded that the LandPKS app automates a globally applied system (LCC) for supporting natural resource conservation and sustainable land management and can serve as a foundation for crop-specific land suitability evaluations. More generally, improved land evaluation efforts can contribute to better soil and natural resource conservation, more sustainable agricultural systems, and increased food security.

中文翻译：

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基于手机技术的土地评价标准化土地能力分类系统

全球贫困的主要原因之一是土地退化和自然资源保护不力，导致农业生产力下降。这种退化通常是由土地利用和土地潜力之间的不匹配造成的，特别是将边际土地用于农业。50 多年来，土地能力分类 (LCC) 系统已在全球范围内用于土地评估，以支持土壤和自然资源保护。LCC 系统将土地分为八类；然而，它的使用目前受到两个因素的限制：缺乏用于数据输入、存储和管理的数字平台，以及许多地区生成所需输入所需的技术能力不足。本文描述了一个系统的开发，以促进快速、灵活、非土壤科学家使用土地潜力知识系统 (LandPKS) 移动应用程序的新开发功能透明地确定 LCC。输入包括土壤质地和岩石碎片体积（按深度、坡度和土壤限制因素的现场观察）。基于美国和国际 LCC 的实施，开发了用于评估输入和计算指标的标准化系统。该系统使用美国农业部自然资源保护局土壤调查数据在美国八个县进行评估。结果表明，尽管在美国数据库中确定 LCC 的方式存在很大差异，但在测试的 1,312 种土壤中，73.8% 的标准化系统预测属于一类。LandPKS LCC 系统在坦桑尼亚和埃塞俄比亚进行了进一步测试，以检查特定地点的应用程序、可用性、该系统对国家土地利用规划工作的有用性。得出的结论是，LandPKS 应用程序使支持自然资源保护和可持续土地管理的全球应用系统 (LCC) 自动化，并可作为特定作物土地适宜性评估的基础。更一般地说，改进土地评估工作有助于更好地保护土壤和自然资源、更可持续的农业系统和提高粮食安全。