{"title":"A new algorithm to determine the spatial coverage of carob (Neltuma piurensis) by ecological floor: Chira-Piura River Basin case","authors":"Cristhian Aldana , Jaime Lloret , Wilmer Moncada , Joel Rojas Acuña , Yesenia Saavedra , Vicente Amirpasha Tirado-Kulieva","doi":"10.1016/j.rsase.2024.101363","DOIUrl":null,"url":null,"abstract":"<div><div>The carob tree (<em>Neltuma piurensis</em>) is characteristic of the forests of northern Peru, withstand extreme climatic events such as “El Niño” and droughts, in addition to the influence of climate change, affecting its distribution of coverage at different altitudes. The objective of this article is to propose an algorithm to determine the Spatial Coverage of Carob by Ecological Floor (SCCEF) in the Chira-Piura River Basin, Peru. The method used consisted of measuring the spectral signature of the carob tree with the FieldSpec4 spectroradiometer at three sampling points corresponding to the localities of Cardal, Lancones and Macacará, located on different ecological floors. The comparison of the spectral signatures for Cardal and Lancones gives an R<sup>2</sup> = 0.9459, for Cardal and Macacará an R<sup>2</sup> = 0.9866 and for Lancones with Macacará an R<sup>2</sup> = 0.9469, which allows an accurate identification of the carob tree in the satellite images. The Mann-Whitney-Wilcoxon <em>U</em> test validates the spectral signatures extracted from the satellite images with the spectral signatures measured with the spectroradiometer at Lancones (p-value = 0.9705 >α = 0.05), Cardal (p-value = 0.9819 > 0.05) and Macacará (p-value = 0.7959 > 0.05). The results show that the SCCEF in the Tropical (T) ecological floor represents 1.55 % of the T area, in the Tropical Pre-Montane (TPM) ecological floor it is 1.47 % of the TPM area, in the Low Tropical Montane (LTM) ecological floor it is 0.78 % of the LTM area, in the Montane (M) ecological floor it is 0.69 % of the M area and in the Paramo (P) ecological floor it is 0.35 % of the P area. Therefore, the SCCEF decreases in each ecological floor as its altitude increases.</div></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101363"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938524002271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The carob tree (Neltuma piurensis) is characteristic of the forests of northern Peru, withstand extreme climatic events such as “El Niño” and droughts, in addition to the influence of climate change, affecting its distribution of coverage at different altitudes. The objective of this article is to propose an algorithm to determine the Spatial Coverage of Carob by Ecological Floor (SCCEF) in the Chira-Piura River Basin, Peru. The method used consisted of measuring the spectral signature of the carob tree with the FieldSpec4 spectroradiometer at three sampling points corresponding to the localities of Cardal, Lancones and Macacará, located on different ecological floors. The comparison of the spectral signatures for Cardal and Lancones gives an R2 = 0.9459, for Cardal and Macacará an R2 = 0.9866 and for Lancones with Macacará an R2 = 0.9469, which allows an accurate identification of the carob tree in the satellite images. The Mann-Whitney-Wilcoxon U test validates the spectral signatures extracted from the satellite images with the spectral signatures measured with the spectroradiometer at Lancones (p-value = 0.9705 >α = 0.05), Cardal (p-value = 0.9819 > 0.05) and Macacará (p-value = 0.7959 > 0.05). The results show that the SCCEF in the Tropical (T) ecological floor represents 1.55 % of the T area, in the Tropical Pre-Montane (TPM) ecological floor it is 1.47 % of the TPM area, in the Low Tropical Montane (LTM) ecological floor it is 0.78 % of the LTM area, in the Montane (M) ecological floor it is 0.69 % of the M area and in the Paramo (P) ecological floor it is 0.35 % of the P area. Therefore, the SCCEF decreases in each ecological floor as its altitude increases.
期刊介绍:
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems