中亚五国土地开发利用潜力空间数据集（V1.0）

中亚作为典型干旱半干旱区，其土地和农业的可持续发展受到了不同的程度的水热限制和环境限制。分析和预测土地利用的潜力，对保障区域粮食安全和减少气候变化的不利影响至关重要。本数据集面向中亚五国农业可持续发展，以旱作农业、灌溉农业、林业、草牧业为土地利用目标，从土地资源开发利用潜力角度开展了土地利用和农业生态的潜力评价。多目标土地资源开发利用评价因子包括：气候（热量、水资源）、地形、灌溉及取水条件、土壤条件等多个方面，它们分别是大于10℃积温，一月平均温度，七月平均温度，降水，降水变差系数，高程，坡度，取水距离，地下水位，土壤有机质，土壤质地，土壤酸碱度，其中降水变差系数基于降水转换而得，坡度信息从高程数据中提取。可变的气候要素包括未来月尺度的降水、平均温度、最大和最小气温、湿度，均来源于经过偏差校正和降尺度的CMIP6的ACCESS-CM2, BCC-CSM2-MR, CanESM5, CAS-ESM2–0, CESM2-WACCM, EC-Earth3, GFDL-ESM4, KACE-1–0-G多模式集合平均数据，其实验均为r1i1p1f1。该数据可为中亚五国未来土地资源开发利用和农业发展等提供基础数据支撑。

Central Asia, a typical arid and semi-arid region, faces varying degrees of water-heat and environmental constraints on its sustainable land and agricultural development. Analyzing and predicting land use potential is critical to ensuring regional food security and mitigating the adverse effects of climate change. This dataset targets the sustainable agricultural development of the five Central Asian countries, taking rainfed agriculture, irrigated agriculture, forestry, and grass-livestock husbandry as land use objectives, and conducts land use and agro-ecological potential evaluations from the perspective of land resource development and utilization potential. Multi-objective land resource development and utilization evaluation factors cover multiple aspects: climate (heat and water resources), topography, irrigation and water intake conditions, soil conditions, etc. Specifically, these factors include ≥10℃ accumulated temperature, January average temperature, July average temperature, precipitation, precipitation variation coefficient, elevation, slope, water intake distance, groundwater level, soil organic matter, soil texture, and soil pH. Among them, the precipitation variation coefficient is derived from precipitation conversion, and slope information is extracted from elevation data. Variable climatic factors include future monthly-scale precipitation, average temperature, maximum and minimum temperatures, and humidity, all sourced from the multi-model ensemble mean data of CMIP6 models including ACCESS-CM2, BCC-CSM2-MR, CanESM5, CAS-ESM2–0, CESM2-WACCM, EC-Earth3, GFDL-ESM4, and KACE-1–0-G, which have undergone bias correction and downscaling. All their experiments adopt the r1i1p1f1 experimental scheme. This dataset can provide basic data support for future land resource development and utilization, agricultural development, and other related work of the five Central Asian countries.

搜集汇总

背景与挑战

背景概述

中亚五国土地开发利用潜力空间数据集（V1.0）提供了2000年至2050年中亚地区土地资源开发利用潜力的空间分布数据，空间分辨率为0.05º - 0.1º，数据格式为GeoTiff。该数据集基于多目标土地资源开发利用评价因子，包括气候、地形、土壤条件等，旨在为中亚五国未来土地资源开发利用和农业发展提供基础数据支撑。