Land Suitability Analysis as a Tool for Evaluating Soil-Improving Cropping Systems

Abstract

Agricultural land use planning is based on the capacity of the soil to support different types of crops and is a prerequisite for better use of cultivated land. Land Suitability Analysis (LSA) is used to measure the level of suitability of growing a specific crop in the area and can also be used to evaluate future scenarios as a means for sustainable agriculture. LSA was employed to calculate current land suitability, as well as four scenarios of Soil-Improving Cropping Systems (SICS): (a) Conservation Tillage (CT), (b) Cover Crop (CC), (c) Crop Residue Management (CRM), and (d) Manure Application (MA). The scenarios of SICS were derived by increasing soil organic matter and cation exchange capacity values depending on the SICS hypothetically applied for a period of 100 years in the future. LSA was evaluated for maize in three sites: (a) Flanders (BE), (b) Somogy (HU), and (c) Hengshui (CH). LSA was performed using the Agricultural Land Use Evaluation System (ALUES) considering soil and climatic and topographic parameters. Weighing factors of input parameters were assigned using the Analytical Hierarchy Process (AHP). The results show that in Flanders, the highly suitable (S2) class covered 3.3% of the total area, and the best scenario for improving current LS was CRM, in which S2 expanded to 9.1%. In Somogy, the S2 class covered 18.3% of the total area, and the best scenarios for improving current land suitability were CT and CC, in both of which the S2 class expanded to 70.5% of the total area. In Hengshui, the S2 class covered 64.7% of the total area, and all SICS scenarios performed extremely well, converting almost all moderately suitable (S3) areas to S2. The main limiting factor that was recognized from a limiting factor analysis in all cases was the climatic conditions. This work proves that LSA can evaluate scenarios of management practices and recognize limiting factors. The proposed methodology is a novel approach that can provide land suitability maps to efficiently evaluate SICS scenarios by projecting soil characteristics and LSA in the future, thus facilitating management decisions of regional policy makers.

Analisis Kesesuaian Lahan Pertanian Di Kota Kupang Dengan Menggunakan Geographic Information System

“…Sebuah pendekatan yang berfokus pada potensi lahan dapat mendukung pembangunan yang Vol. 16, No. 1, Mei 2024 berkelanjutan dan berdaya guna dalam jangka panjang, pertumbuhan ekonomi yang lebih baik, serta memberikan hasil yang lebih optimal bagi perkembangan wilayah tersebut [6].…”

“…[ Kemiringan lereng merupakan salah satu faktor yang mempengaruhi kesesuaian lahan untuk pertanian. Kemiringan lereng dapat berhubungan dengan ketersediaan air, suhu, dan radiasi matahari yang mempengaruhi pertumbuhan tanaman [16]. Oleh karena itu, analisis kemiringan lereng perlu dilakukan untuk menentukan kelas-kelas kesesuaian lahan berdasarkan derajat kemiringannya.…”

Analysis of Land Suitability for Maize Production under Climate Change and Its Mitigation Potential through Crop Residue Management

“…The current LSA was carried out to evaluate land suitability for sustainable maize production and identify the key limiting factors that compromise maize cultivation based on the criteria of soil, climate, and topography. Based on the LSA in the same region [33], expert knowledge from local information sources was incorporated through AHP, utilizing weighting schemes to express the relative importance of each parameter or category in the final assessment of land suitability. The FAO framework for LSA [8] was employed to assess current land suitability for maize production, classifying suitable land into three categories: highly suitable (S1); moderately suitable (S2), with additional inputs required; and marginally suitable (S3), with significant inputs needed.…”

“…The FAO framework for LSA [8] was employed to assess current land suitability for maize production, classifying suitable land into three categories: highly suitable (S1); moderately suitable (S2), with additional inputs required; and marginally suitable (S3), with significant inputs needed. Threshold values for input parameters related to maize suitability were adopted from previous work in the region [33] for the selected soil properties from SoilGrids, namely CEC, SOC, pH, texture, and coarse fragments (see supplementary material). Soil textural classes were based on the USDA classification scheme.…”

“…This potential is investigated by applying the Crop Residue Management (CRM) scenario from the available SICS for a period of 80 years and examining the resulting differences in suitability. To take the SICS scenario into consideration, based on the previous results in the same study area [33,53,54] and published reviews on the effect of CRM in long-term experiments [55,56], the impact of applying 80 years (2020-2099) of CRM practices was calculated as an increase in SOC at a rate of 200 kg/ha per year. This perspective was incorporated into the LSA procedures by calculating new values for SOC and CEC.…”