AUTHOREA
Log in Sign Up Browse Preprints

loading page

Optimal deployment of cultivated land quality monitoring points based on satellite-driven cultivated land quality and improved spatial simulated annealing
  • +5
  • Wenhao Yang,
  • Yiping Peng,
  • Chenjie Lin,
  • Hao Yang,
  • Xinrong Cheng,
  • Xiaofang Wu,
  • Ya Wen,
  • Zhenhua Liu
Wenhao Yang
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Yiping Peng
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Chenjie Lin
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Hao Yang
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Xinrong Cheng
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Xiaofang Wu
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Ya Wen
South China Agricultural University College of Natural Resources and the Environment
Author Profile
Zhenhua Liu
South China Agricultural University College of Natural Resources and the Environment

Corresponding Author:zhenhua@scau.edu.cn

Author Profile

Abstract

科学合理布设耕地质量（CLQ）监测点，可以及时准确地提供耕地质量现状和变化信息，对保障国家粮食安全具有重要意义。传统的 CLQ 监测点选择方法是基于土地利用斑块的 CLQ。由于大补丁可能有不同等级，被选为监控点会降低监控CLQ的可靠性。此外，传统的监测点部署方法主要只考虑CLQ，而忽略了道路可达性和地形等因素，导致部分监测点无法进入。因此，为了提高 CLQ 监测的可靠性，本研究提出了一种部署 CLQ 监测点的新方法。第一的，像素尺度的 CLQ 是使用遗传算法 - 反向传播神经网络 (GA-BPNN) 模型基于具有 30 m 空间分辨率的 Landstat8 数据估计的。其次，采用分层抽样模型确定最佳样本点。最后，应用改进的空间模拟退火算法（ISSA），同时考虑坡度和道路可达性，以优化监测点的位置。本研究在中国广东省广州市从化区进行。结果突出表明 (1) 与测量的 CLQ 的准确度相比，准确度 (R 应用改进的空间模拟退火算法（ISSA），同时考虑坡度和道路可达性，以优化监测点的位置。本研究在中国广东省广州市从化区进行。结果突出表明 (1) 与测量的 CLQ 的准确度相比，准确度 (R 应用改进的空间模拟退火算法（ISSA），同时考虑坡度和道路可达性，以优化监测点的位置。本研究在中国广东省广州市从化区进行。结果突出表明 (1) 与测量的 CLQ 的准确度相比，准确度 (R2  =   0.63, RMSE = 79.32, NRMSE = 13.77%) 用遥感技术估计的 CLQ 是可靠的，不同等级的像素级 CLQ 数据比斑块级 CLQ 数据更合理。(2)基于分层抽样模型，最终在研究区确定了132个监测点。（3）与空间模拟退火算法（SSA）和标准网格法相比，本研究提出的方法总分更高（F=94.61）。此外，获得的样本点主要位于道路和平坦地形附近。这样可以有效避开人迹罕至的地方。因此，基于本研究提出的新方法的结果为获得最佳CLQ监测点提供了科学依据和技术支持。

Peer review status:ACCEPTED

29 Aug 2022Submitted to Land Degradation & Development
Show details
Hide details
30 Aug 2022Submission Checks Completed
30 Aug 2022Assigned to Editor
02 Sep 2022Reviewer(s) Assigned
13 Sep 2022Review(s) Completed, Editorial Evaluation Pending
17 Sep 2022Editorial Decision: Revise Major
17 Oct 20221st Revision Received
18 Oct 2022Review(s) Completed, Editorial Evaluation Pending
18 Oct 2022Submission Checks Completed
18 Oct 2022Assigned to Editor
22 Oct 2022Reviewer(s) Assigned
14 Nov 2022Editorial Decision: Revise Minor
17 Nov 20222nd Revision Received
17 Nov 2022Assigned to Editor
17 Nov 2022Review(s) Completed, Editorial Evaluation Pending
17 Nov 2022Submission Checks Completed
19 Nov 2022Reviewer(s) Assigned
27 Nov 2022Editorial Decision: Revise Minor
21 Dec 20223rd Revision Received
21 Dec 2022Review(s) Completed, Editorial Evaluation Pending
21 Dec 2022Submission Checks Completed
21 Dec 2022Assigned to Editor
25 Dec 2022Reviewer(s) Assigned
09 Jan 2023Editorial Decision: Revise Minor
11 Jan 20234th Revision Received
12 Jan 2023Submission Checks Completed
12 Jan 2023Assigned to Editor
12 Jan 2023Review(s) Completed, Editorial Evaluation Pending
13 Jan 2023Editorial Decision: Accept