Evaluation of the potential of radar ENVISAT data for the updating of numerical thematic maps on the coastal fringe of French Guyana

Kouame, Jacob; Classeau, N.; Rudant, Jean Paul; Trebossen, H.

doi:10.1109/igarss.2003.1295248

Cited by 1 publication

(2 citation statements)

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“…Finally, in the early stages of the use of RS for soil mapping, RS was often used to delineate/identify soil types or soil classes (e.g., [61,[63][64][65][66][67][68][69][70][71][72][73]75,76,195]). At the initiative of French geographers, in particular E. de Martonne [196], these approaches were initially based on the visual interpretation of aerial photographs, most often in photogrammetric mode for a better identification of morphological units [26][27][28].…”

Section: Most Studied Soil Properties In French Remote Sensing Researchmentioning

confidence: 99%

“…Observation and hence, understanding the spectral behavior of soil as a function of its composition and structure has been the cornerstone for establishing relationships between the spatial distribution of soil properties at different scales, soil types, or soilscapes, and RS imagery products in the solar (e.g., [61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77]), as well as in the microwave (e.g., [65,70,71,73]) and the thermal infrared (e.g., [59,78,79]) domains. Several studies have also addressed the mapping of soil color (e.g., [46,51,80]) or soil moisture (e.g., [78,79,[81][82][83][84][85][86]).…”

Section: Introductionmentioning

confidence: 99%

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Remote Sensing Data for Digital Soil Mapping in French Research—A Review

et al. 2023

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Soils are at the crossroads of many existential issues that humanity is currently facing. Soils are a finite resource that is under threat, mainly due to human pressure. There is an urgent need to map and monitor them at field, regional, and global scales in order to improve their management and prevent their degradation. This remains a challenge due to the high and often complex spatial variability inherent to soils. Over the last four decades, major research efforts in the field of pedometrics have led to the development of methods allowing to capture the complex nature of soils. As a result, digital soil mapping (DSM) approaches have been developed for quantifying soils in space and time. DSM and monitoring have become operational thanks to the harmonization of soil databases, advances in spatial modeling and machine learning, and the increasing availability of spatiotemporal covariates, including the exponential increase in freely available remote sensing (RS) data. The latter boosted research in DSM, allowing the mapping of soils at high resolution and assessing the changes through time. We present a review of the main contributions and developments of French (inter)national research, which has a long history in both RS and DSM. Thanks to the French SPOT satellite constellation that started in the early 1980s, the French RS and soil research communities have pioneered DSM using remote sensing. This review describes the data, tools, and methods using RS imagery to support the spatial predictions of a wide range of soil properties and discusses their pros and cons. The review demonstrates that RS data are frequently used in soil mapping (i) by considering them as a substitute for analytical measurements, or (ii) by considering them as covariates related to the controlling factors of soil formation and evolution. It further highlights the great potential of RS imagery to improve DSM, and provides an overview of the main challenges and prospects related to digital soil mapping and future sensors. This opens up broad prospects for the use of RS for DSM and natural resource monitoring.

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